Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt: Estimate the visible-nuclei count range in the supplied microscopy image. Choose exactly one label: 0-10, 11-25, 26-50, 51-100, 101-200, 201+. Return only the label.


Prompt:
Return exactly one minified JSON object with keys modality and source_id in alphabetical order. Include no other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with one top-level key "record". Its value must contain only modality and source_id in alphabetical order. Include no other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly two keys: "fields" and "values". fields must equal ["modality","source_id"]; values must follow that order. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly is_bench_reserved=true, modality, and source_id, with keys alphabetized. Include no other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with source_id_length as the exact character count and source_id_upper as the uppercase source_id. Alphabetize keys. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with modality_reversed and the final six source_id characters as source_id_suffix. Alphabetize keys. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with one key "record". record must contain modality and source_tokens. Split source_id on -, _, /, ., or :, remove empty and duplicate tokens, and sort tokens alphabetically. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with record equal to modality|source_id and token_count equal to the number of alphanumeric source_id tokens. Alphabetize keys. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return exactly one minified JSON object with keys modality and source_id in alphabetical order. Include no other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with one top-level key "record". Its value must contain only modality and source_id in alphabetical order. Include no other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly two keys: "fields" and "values". fields must equal ["modality","source_id"]; values must follow that order. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly is_bench_reserved=true, modality, and source_id, with keys alphabetized. Include no other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with source_id_length as the exact character count and source_id_upper as the uppercase source_id. Alphabetize keys. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with modality_reversed and the final six source_id characters as source_id_suffix. Alphabetize keys. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with one key "record". record must contain modality and source_tokens. Split source_id on -, _, /, ., or :, remove empty and duplicate tokens, and sort tokens alphabetically. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with record equal to modality|source_id and token_count equal to the number of alphanumeric source_id tokens. Alphabetize keys. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return exactly one minified JSON object with keys modality and source_id in alphabetical order. Include no other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with one top-level key "record". Its value must contain only modality and source_id in alphabetical order. Include no other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly two keys: "fields" and "values". fields must equal ["modality","source_id"]; values must follow that order. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly is_bench_reserved=true, modality, and source_id, with keys alphabetized. Include no other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with source_id_length as the exact character count and source_id_upper as the uppercase source_id. Alphabetize keys. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with modality_reversed and the final six source_id characters as source_id_suffix. Alphabetize keys. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with one key "record". record must contain modality and source_tokens. Split source_id on -, _, /, ., or :, remove empty and duplicate tokens, and sort tokens alphabetically. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with record equal to modality|source_id and token_count equal to the number of alphanumeric source_id tokens. Alphabetize keys. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return exactly one minified JSON object with keys modality and source_id in alphabetical order. Include no other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with one top-level key "record". Its value must contain only modality and source_id in alphabetical order. Include no other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly two keys: "fields" and "values". fields must equal ["modality","source_id"]; values must follow that order. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly is_bench_reserved=true, modality, and source_id, with keys alphabetized. Include no other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with source_id_length as the exact character count and source_id_upper as the uppercase source_id. Alphabetize keys. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with modality_reversed and the final six source_id characters as source_id_suffix. Alphabetize keys. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with one key "record". record must contain modality and source_tokens. Split source_id on -, _, /, ., or :, remove empty and duplicate tokens, and sort tokens alphabetically. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with record equal to modality|source_id and token_count equal to the number of alphanumeric source_id tokens. Alphabetize keys. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return exactly one minified JSON object with keys modality and source_id in alphabetical order. Include no other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with one top-level key "record". Its value must contain only modality and source_id in alphabetical order. Include no other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly two keys: "fields" and "values". fields must equal ["modality","source_id"]; values must follow that order. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly is_bench_reserved=true, modality, and source_id, with keys alphabetized. Include no other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with source_id_length as the exact character count and source_id_upper as the uppercase source_id. Alphabetize keys. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with modality_reversed and the final six source_id characters as source_id_suffix. Alphabetize keys. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with one key "record". record must contain modality and source_tokens. Split source_id on -, _, /, ., or :, remove empty and duplicate tokens, and sort tokens alphabetically. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with record equal to modality|source_id and token_count equal to the number of alphanumeric source_id tokens. Alphabetize keys. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return exactly one minified JSON object with keys modality and source_id in alphabetical order. Include no other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with one top-level key "record". Its value must contain only modality and source_id in alphabetical order. Include no other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly two keys: "fields" and "values". fields must equal ["modality","source_id"]; values must follow that order. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly is_bench_reserved=true, modality, and source_id, with keys alphabetized. Include no other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with source_id_length as the exact character count and source_id_upper as the uppercase source_id. Alphabetize keys. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with modality_reversed and the final six source_id characters as source_id_suffix. Alphabetize keys. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with one key "record". record must contain modality and source_tokens. Split source_id on -, _, /, ., or :, remove empty and duplicate tokens, and sort tokens alphabetically. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with record equal to modality|source_id and token_count equal to the number of alphanumeric source_id tokens. Alphabetize keys. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return exactly one minified JSON object with keys modality and source_id in alphabetical order. Include no other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with one top-level key "record". Its value must contain only modality and source_id in alphabetical order. Include no other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly two keys: "fields" and "values". fields must equal ["modality","source_id"]; values must follow that order. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly is_bench_reserved=true, modality, and source_id, with keys alphabetized. Include no other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with source_id_length as the exact character count and source_id_upper as the uppercase source_id. Alphabetize keys. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with modality_reversed and the final six source_id characters as source_id_suffix. Alphabetize keys. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with one key "record". record must contain modality and source_tokens. Split source_id on -, _, /, ., or :, remove empty and duplicate tokens, and sort tokens alphabetically. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with record equal to modality|source_id and token_count equal to the number of alphanumeric source_id tokens. Alphabetize keys. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return exactly one minified JSON object with keys modality and source_id in alphabetical order. Include no other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with one top-level key "record". Its value must contain only modality and source_id in alphabetical order. Include no other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly two keys: "fields" and "values". fields must equal ["modality","source_id"]; values must follow that order. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly is_bench_reserved=true, modality, and source_id, with keys alphabetized. Include no other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with source_id_length as the exact character count and source_id_upper as the uppercase source_id. Alphabetize keys. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with modality_reversed and the final six source_id characters as source_id_suffix. Alphabetize keys. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with one key "record". record must contain modality and source_tokens. Split source_id on -, _, /, ., or :, remove empty and duplicate tokens, and sort tokens alphabetically. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with record equal to modality|source_id and token_count equal to the number of alphanumeric source_id tokens. Alphabetize keys. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return exactly one minified JSON object with keys modality and source_id in alphabetical order. Include no other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with one top-level key "record". Its value must contain only modality and source_id in alphabetical order. Include no other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly two keys: "fields" and "values". fields must equal ["modality","source_id"]; values must follow that order. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly is_bench_reserved=true, modality, and source_id, with keys alphabetized. Include no other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with source_id_length as the exact character count and source_id_upper as the uppercase source_id. Alphabetize keys. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with modality_reversed and the final six source_id characters as source_id_suffix. Alphabetize keys. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with one key "record". record must contain modality and source_tokens. Split source_id on -, _, /, ., or :, remove empty and duplicate tokens, and sort tokens alphabetically. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with record equal to modality|source_id and token_count equal to the number of alphanumeric source_id tokens. Alphabetize keys. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return exactly one minified JSON object with keys modality and source_id in alphabetical order. Include no other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with one top-level key "record". Its value must contain only modality and source_id in alphabetical order. Include no other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly two keys: "fields" and "values". fields must equal ["modality","source_id"]; values must follow that order. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly is_bench_reserved=true, modality, and source_id, with keys alphabetized. Include no other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with source_id_length as the exact character count and source_id_upper as the uppercase source_id. Alphabetize keys. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with modality_reversed and the final six source_id characters as source_id_suffix. Alphabetize keys. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with one key "record". record must contain modality and source_tokens. Split source_id on -, _, /, ., or :, remove empty and duplicate tokens, and sort tokens alphabetically. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with record equal to modality|source_id and token_count equal to the number of alphanumeric source_id tokens. Alphabetize keys. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return exactly one minified JSON object with keys modality and source_id in alphabetical order. Include no other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with one top-level key "record". Its value must contain only modality and source_id in alphabetical order. Include no other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly two keys: "fields" and "values". fields must equal ["modality","source_id"]; values must follow that order. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly is_bench_reserved=true, modality, and source_id, with keys alphabetized. Include no other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with source_id_length as the exact character count and source_id_upper as the uppercase source_id. Alphabetize keys. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with modality_reversed and the final six source_id characters as source_id_suffix. Alphabetize keys. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with one key "record". record must contain modality and source_tokens. Split source_id on -, _, /, ., or :, remove empty and duplicate tokens, and sort tokens alphabetically. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with record equal to modality|source_id and token_count equal to the number of alphanumeric source_id tokens. Alphabetize keys. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return exactly one minified JSON object with keys modality and source_id in alphabetical order. Include no other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with one top-level key "record". Its value must contain only modality and source_id in alphabetical order. Include no other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly two keys: "fields" and "values". fields must equal ["modality","source_id"]; values must follow that order. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly is_bench_reserved=true, modality, and source_id, with keys alphabetized. Include no other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with source_id_length as the exact character count and source_id_upper as the uppercase source_id. Alphabetize keys. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with modality_reversed and the final six source_id characters as source_id_suffix. Alphabetize keys. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with one key "record". record must contain modality and source_tokens. Split source_id on -, _, /, ., or :, remove empty and duplicate tokens, and sort tokens alphabetically. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with record equal to modality|source_id and token_count equal to the number of alphanumeric source_id tokens. Alphabetize keys. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return exactly one minified JSON object with keys modality and source_id in alphabetical order. Include no other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with one top-level key "record". Its value must contain only modality and source_id in alphabetical order. Include no other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly two keys: "fields" and "values". fields must equal ["modality","source_id"]; values must follow that order. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly is_bench_reserved=true, modality, and source_id, with keys alphabetized. Include no other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with source_id_length as the exact character count and source_id_upper as the uppercase source_id. Alphabetize keys. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with modality_reversed and the final six source_id characters as source_id_suffix. Alphabetize keys. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with one key "record". record must contain modality and source_tokens. Split source_id on -, _, /, ., or :, remove empty and duplicate tokens, and sort tokens alphabetically. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with record equal to modality|source_id and token_count equal to the number of alphanumeric source_id tokens. Alphabetize keys. No other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return exactly one minified JSON object with keys modality and source_id in alphabetical order. Include no other text.

modality=fluorescence
source_id=nist-ipsc


Prompt:
Return minified JSON with one top-level key "record". Its value must contain only modality and source_id in alphabetical order. Include no other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly two keys: "fields" and "values". fields must equal ["modality","source_id"]; values must follow that order. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly is_bench_reserved=true, modality, and source_id, with keys alphabetized. Include no other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with source_id_length as the exact character count and source_id_upper as the uppercase source_id. Alphabetize keys. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with modality_reversed and the final six source_id characters as source_id_suffix. Alphabetize keys. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with one key "record". record must contain modality and source_tokens. Split source_id on -, _, /, ., or :, remove empty and duplicate tokens, and sort tokens alphabetically. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with record equal to modality|source_id and token_count equal to the number of alphanumeric source_id tokens. Alphabetize keys. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return exactly one minified JSON object with keys modality and source_id in alphabetical order. Include no other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with one top-level key "record". Its value must contain only modality and source_id in alphabetical order. Include no other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly two keys: "fields" and "values". fields must equal ["modality","source_id"]; values must follow that order. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly is_bench_reserved=true, modality, and source_id, with keys alphabetized. Include no other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with source_id_length as the exact character count and source_id_upper as the uppercase source_id. Alphabetize keys. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with modality_reversed and the final six source_id characters as source_id_suffix. Alphabetize keys. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with one key "record". record must contain modality and source_tokens. Split source_id on -, _, /, ., or :, remove empty and duplicate tokens, and sort tokens alphabetically. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with record equal to modality|source_id and token_count equal to the number of alphanumeric source_id tokens. Alphabetize keys. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return exactly one minified JSON object with keys modality and source_id in alphabetical order. Include no other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with one top-level key "record". Its value must contain only modality and source_id in alphabetical order. Include no other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly two keys: "fields" and "values". fields must equal ["modality","source_id"]; values must follow that order. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly is_bench_reserved=true, modality, and source_id, with keys alphabetized. Include no other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with source_id_length as the exact character count and source_id_upper as the uppercase source_id. Alphabetize keys. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with modality_reversed and the final six source_id characters as source_id_suffix. Alphabetize keys. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with one key "record". record must contain modality and source_tokens. Split source_id on -, _, /, ., or :, remove empty and duplicate tokens, and sort tokens alphabetically. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with record equal to modality|source_id and token_count equal to the number of alphanumeric source_id tokens. Alphabetize keys. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return exactly one minified JSON object with keys modality and source_id in alphabetical order. Include no other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with one top-level key "record". Its value must contain only modality and source_id in alphabetical order. Include no other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly two keys: "fields" and "values". fields must equal ["modality","source_id"]; values must follow that order. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly is_bench_reserved=true, modality, and source_id, with keys alphabetized. Include no other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with source_id_length as the exact character count and source_id_upper as the uppercase source_id. Alphabetize keys. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with modality_reversed and the final six source_id characters as source_id_suffix. Alphabetize keys. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with one key "record". record must contain modality and source_tokens. Split source_id on -, _, /, ., or :, remove empty and duplicate tokens, and sort tokens alphabetically. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with record equal to modality|source_id and token_count equal to the number of alphanumeric source_id tokens. Alphabetize keys. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return exactly one minified JSON object with keys modality and source_id in alphabetical order. Include no other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with one top-level key "record". Its value must contain only modality and source_id in alphabetical order. Include no other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly two keys: "fields" and "values". fields must equal ["modality","source_id"]; values must follow that order. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly is_bench_reserved=true, modality, and source_id, with keys alphabetized. Include no other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with source_id_length as the exact character count and source_id_upper as the uppercase source_id. Alphabetize keys. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with modality_reversed and the final six source_id characters as source_id_suffix. Alphabetize keys. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with one key "record". record must contain modality and source_tokens. Split source_id on -, _, /, ., or :, remove empty and duplicate tokens, and sort tokens alphabetically. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with record equal to modality|source_id and token_count equal to the number of alphanumeric source_id tokens. Alphabetize keys. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return exactly one minified JSON object with keys modality and source_id in alphabetical order. Include no other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with one top-level key "record". Its value must contain only modality and source_id in alphabetical order. Include no other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly two keys: "fields" and "values". fields must equal ["modality","source_id"]; values must follow that order. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly is_bench_reserved=true, modality, and source_id, with keys alphabetized. Include no other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with source_id_length as the exact character count and source_id_upper as the uppercase source_id. Alphabetize keys. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with modality_reversed and the final six source_id characters as source_id_suffix. Alphabetize keys. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with one key "record". record must contain modality and source_tokens. Split source_id on -, _, /, ., or :, remove empty and duplicate tokens, and sort tokens alphabetically. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with record equal to modality|source_id and token_count equal to the number of alphanumeric source_id tokens. Alphabetize keys. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return exactly one minified JSON object with keys modality and source_id in alphabetical order. Include no other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with one top-level key "record". Its value must contain only modality and source_id in alphabetical order. Include no other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly two keys: "fields" and "values". fields must equal ["modality","source_id"]; values must follow that order. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly is_bench_reserved=true, modality, and source_id, with keys alphabetized. Include no other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with source_id_length as the exact character count and source_id_upper as the uppercase source_id. Alphabetize keys. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with modality_reversed and the final six source_id characters as source_id_suffix. Alphabetize keys. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with one key "record". record must contain modality and source_tokens. Split source_id on -, _, /, ., or :, remove empty and duplicate tokens, and sort tokens alphabetically. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with record equal to modality|source_id and token_count equal to the number of alphanumeric source_id tokens. Alphabetize keys. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return exactly one minified JSON object with keys modality and source_id in alphabetical order. Include no other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with one top-level key "record". Its value must contain only modality and source_id in alphabetical order. Include no other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly two keys: "fields" and "values". fields must equal ["modality","source_id"]; values must follow that order. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly is_bench_reserved=true, modality, and source_id, with keys alphabetized. Include no other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with source_id_length as the exact character count and source_id_upper as the uppercase source_id. Alphabetize keys. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with modality_reversed and the final six source_id characters as source_id_suffix. Alphabetize keys. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with one key "record". record must contain modality and source_tokens. Split source_id on -, _, /, ., or :, remove empty and duplicate tokens, and sort tokens alphabetically. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with record equal to modality|source_id and token_count equal to the number of alphanumeric source_id tokens. Alphabetize keys. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return exactly one minified JSON object with keys modality and source_id in alphabetical order. Include no other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with one top-level key "record". Its value must contain only modality and source_id in alphabetical order. Include no other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly two keys: "fields" and "values". fields must equal ["modality","source_id"]; values must follow that order. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly is_bench_reserved=true, modality, and source_id, with keys alphabetized. Include no other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with source_id_length as the exact character count and source_id_upper as the uppercase source_id. Alphabetize keys. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with modality_reversed and the final six source_id characters as source_id_suffix. Alphabetize keys. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with one key "record". record must contain modality and source_tokens. Split source_id on -, _, /, ., or :, remove empty and duplicate tokens, and sort tokens alphabetically. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with record equal to modality|source_id and token_count equal to the number of alphanumeric source_id tokens. Alphabetize keys. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return exactly one minified JSON object with keys modality and source_id in alphabetical order. Include no other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with one top-level key "record". Its value must contain only modality and source_id in alphabetical order. Include no other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly two keys: "fields" and "values". fields must equal ["modality","source_id"]; values must follow that order. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly is_bench_reserved=true, modality, and source_id, with keys alphabetized. Include no other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with source_id_length as the exact character count and source_id_upper as the uppercase source_id. Alphabetize keys. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with modality_reversed and the final six source_id characters as source_id_suffix. Alphabetize keys. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with one key "record". record must contain modality and source_tokens. Split source_id on -, _, /, ., or :, remove empty and duplicate tokens, and sort tokens alphabetically. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with record equal to modality|source_id and token_count equal to the number of alphanumeric source_id tokens. Alphabetize keys. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return exactly one minified JSON object with keys modality and source_id in alphabetical order. Include no other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with one top-level key "record". Its value must contain only modality and source_id in alphabetical order. Include no other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly two keys: "fields" and "values". fields must equal ["modality","source_id"]; values must follow that order. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly is_bench_reserved=true, modality, and source_id, with keys alphabetized. Include no other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with source_id_length as the exact character count and source_id_upper as the uppercase source_id. Alphabetize keys. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with modality_reversed and the final six source_id characters as source_id_suffix. Alphabetize keys. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with one key "record". record must contain modality and source_tokens. Split source_id on -, _, /, ., or :, remove empty and duplicate tokens, and sort tokens alphabetically. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with record equal to modality|source_id and token_count equal to the number of alphanumeric source_id tokens. Alphabetize keys. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return exactly one minified JSON object with keys modality and source_id in alphabetical order. Include no other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with one top-level key "record". Its value must contain only modality and source_id in alphabetical order. Include no other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly two keys: "fields" and "values". fields must equal ["modality","source_id"]; values must follow that order. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly is_bench_reserved=true, modality, and source_id, with keys alphabetized. Include no other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with source_id_length as the exact character count and source_id_upper as the uppercase source_id. Alphabetize keys. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with modality_reversed and the final six source_id characters as source_id_suffix. Alphabetize keys. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with one key "record". record must contain modality and source_tokens. Split source_id on -, _, /, ., or :, remove empty and duplicate tokens, and sort tokens alphabetically. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with record equal to modality|source_id and token_count equal to the number of alphanumeric source_id tokens. Alphabetize keys. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return exactly one minified JSON object with keys modality and source_id in alphabetical order. Include no other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with one top-level key "record". Its value must contain only modality and source_id in alphabetical order. Include no other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly two keys: "fields" and "values". fields must equal ["modality","source_id"]; values must follow that order. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly is_bench_reserved=true, modality, and source_id, with keys alphabetized. Include no other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with source_id_length as the exact character count and source_id_upper as the uppercase source_id. Alphabetize keys. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with modality_reversed and the final six source_id characters as source_id_suffix. Alphabetize keys. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with one key "record". record must contain modality and source_tokens. Split source_id on -, _, /, ., or :, remove empty and duplicate tokens, and sort tokens alphabetically. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with record equal to modality|source_id and token_count equal to the number of alphanumeric source_id tokens. Alphabetize keys. No other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return exactly one minified JSON object with keys modality and source_id in alphabetical order. Include no other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with one top-level key "record". Its value must contain only modality and source_id in alphabetical order. Include no other text.

modality=phase-contrast
source_id=nist-ipsc


Prompt:
Return minified JSON with exactly two keys: "fields" and "values". fields must equal ["modality","source_id"]; values must follow that order. No other text.

modality=nuclei-microscopy
source_id=bbbc038-bench-reserved


Prompt:
Return minified JSON with exactly is_bench_reserved=true, modality, and source_id, with keys alphabetized. Include no other text.

modality=nuclei-microscopy
source_id=bbbc038-bench-reserved


Prompt:
Return minified JSON with source_id_length as the exact character count and source_id_upper as the uppercase source_id. Alphabetize keys. No other text.

modality=nuclei-microscopy
source_id=bbbc038-bench-reserved


Prompt:
Return minified JSON with modality_reversed and the final six source_id characters as source_id_suffix. Alphabetize keys. No other text.

modality=nuclei-microscopy
source_id=bbbc038-bench-reserved


Prompt:
Return minified JSON with one key "record". record must contain modality and source_tokens. Split source_id on -, _, /, ., or :, remove empty and duplicate tokens, and sort tokens alphabetically. No other text.

modality=nuclei-microscopy
source_id=bbbc038-bench-reserved


Prompt:
Return minified JSON with record equal to modality|source_id and token_count equal to the number of alphanumeric source_id tokens. Alphabetize keys. No other text.

modality=nuclei-microscopy
source_id=bbbc038-bench-reserved


Prompt:
Return exactly one minified JSON object with keys modality and source_id in alphabetical order. Include no other text.

modality=nuclei-microscopy
source_id=bbbc038-bench-reserved


Prompt:
Return minified JSON with one top-level key "record". Its value must contain only modality and source_id in alphabetical order. Include no other text.

modality=nuclei-microscopy
source_id=bbbc038-bench-reserved


Prompt:
Return minified JSON with exactly two keys: "fields" and "values". fields must equal ["modality","source_id"]; values must follow that order. No other text.

modality=nuclei-microscopy
source_id=bbbc038-bench-reserved


Prompt:
Return minified JSON with exactly is_bench_reserved=true, modality, and source_id, with keys alphabetized. Include no other text.

modality=nuclei-microscopy
source_id=bbbc038-bench-reserved


Prompt:
Return minified JSON with source_id_length as the exact character count and source_id_upper as the uppercase source_id. Alphabetize keys. No other text.

modality=nuclei-microscopy
source_id=bbbc038-bench-reserved


Prompt:
Return minified JSON with modality_reversed and the final six source_id characters as source_id_suffix. Alphabetize keys. No other text.

modality=nuclei-microscopy
source_id=bbbc038-bench-reserved


Prompt:
Return minified JSON with one key "record". record must contain modality and source_tokens. Split source_id on -, _, /, ., or :, remove empty and duplicate tokens, and sort tokens alphabetically. No other text.

modality=nuclei-microscopy
source_id=bbbc038-bench-reserved


Prompt:
Return minified JSON with record equal to modality|source_id and token_count equal to the number of alphanumeric source_id tokens. Alphabetize keys. No other text.

modality=nuclei-microscopy
source_id=bbbc038-bench-reserved


Prompt:
Return exactly one minified JSON object with keys modality and source_id in alphabetical order. Include no other text.

modality=nuclei-microscopy
source_id=bbbc038-bench-reserved


Prompt:
Return minified JSON with one top-level key "record". Its value must contain only modality and source_id in alphabetical order. Include no other text.

modality=nuclei-microscopy
source_id=bbbc038-bench-reserved


Prompt:
Return minified JSON with exactly two keys: "fields" and "values". fields must equal ["modality","source_id"]; values must follow that order. No other text.

modality=nuclei-microscopy
source_id=bbbc038-bench-reserved


Prompt:
Return minified JSON with exactly is_bench_reserved=true, modality, and source_id, with keys alphabetized. Include no other text.

modality=nuclei-microscopy
source_id=bbbc038-bench-reserved


Prompt:
Return minified JSON with source_id_length as the exact character count and source_id_upper as the uppercase source_id. Alphabetize keys. No other text.

modality=nuclei-microscopy
source_id=bbbc038-bench-reserved


Prompt:
Return minified JSON with modality_reversed and the final six source_id characters as source_id_suffix. Alphabetize keys. No other text.

modality=nuclei-microscopy
source_id=bbbc038-bench-reserved


Prompt:
Return minified JSON with one key "record". record must contain modality and source_tokens. Split source_id on -, _, /, ., or :, remove empty and duplicate tokens, and sort tokens alphabetically. No other text.

modality=nuclei-microscopy
source_id=bbbc038-bench-reserved


Prompt:
Return minified JSON with record equal to modality|source_id and token_count equal to the number of alphanumeric source_id tokens. Alphabetize keys. No other text.

modality=nuclei-microscopy
source_id=bbbc038-bench-reserved


Prompt:
Return exactly one minified JSON object with keys modality and source_id in alphabetical order. Include no other text.

modality=nuclei-microscopy
source_id=bbbc038-bench-reserved


Prompt:
Return minified JSON with one top-level key "record". Its value must contain only modality and source_id in alphabetical order. Include no other text.

modality=nuclei-microscopy
source_id=bbbc038-bench-reserved


Prompt:
Return minified JSON with exactly two keys: "fields" and "values". fields must equal ["modality","source_id"]; values must follow that order. No other text.

modality=nuclei-microscopy
source_id=bbbc038-bench-reserved


Prompt:
Return minified JSON with exactly is_bench_reserved=true, modality, and source_id, with keys alphabetized. Include no other text.

modality=nuclei-microscopy
source_id=bbbc038-bench-reserved


Prompt:
Return minified JSON with source_id_length as the exact character count and source_id_upper as the uppercase source_id. Alphabetize keys. No other text.

modality=nuclei-microscopy
source_id=bbbc038-bench-reserved


Prompt:
Return minified JSON with modality_reversed and the final six source_id characters as source_id_suffix. Alphabetize keys. No other text.

modality=nuclei-microscopy
source_id=bbbc038-bench-reserved


Prompt:
Return minified JSON with one key "record". record must contain modality and source_tokens. Split source_id on -, _, /, ., or :, remove empty and duplicate tokens, and sort tokens alphabetically. No other text.

modality=nuclei-microscopy
source_id=bbbc038-bench-reserved


Prompt:
Return minified JSON with record equal to modality|source_id and token_count equal to the number of alphanumeric source_id tokens. Alphabetize keys. No other text.

modality=nuclei-microscopy
source_id=bbbc038-bench-reserved


Prompt:
Return exactly one minified JSON object with keys modality and source_id in alphabetical order. Include no other text.

modality=nuclei-microscopy
source_id=bbbc038-bench-reserved


Prompt:
Return minified JSON with one top-level key "record". Its value must contain only modality and source_id in alphabetical order. Include no other text.

modality=nuclei-microscopy
source_id=bbbc038-bench-reserved


Prompt:
Return minified JSON with exactly two keys: "fields" and "values". fields must equal ["modality","source_id"]; values must follow that order. No other text.

modality=nuclei-microscopy
source_id=bbbc038-bench-reserved


Prompt:
Return minified JSON with exactly is_bench_reserved=true, modality, and source_id, with keys alphabetized. Include no other text.

modality=nuclei-microscopy
source_id=bbbc038-bench-reserved


Prompt:
Return minified JSON with source_id_length as the exact character count and source_id_upper as the uppercase source_id. Alphabetize keys. No other text.

modality=nuclei-microscopy
source_id=bbbc038-bench-reserved


Prompt:
Return minified JSON with modality_reversed and the final six source_id characters as source_id_suffix. Alphabetize keys. No other text.

modality=nuclei-microscopy
source_id=bbbc038-bench-reserved


Prompt:
Return minified JSON with one key "record". record must contain modality and source_tokens. Split source_id on -, _, /, ., or :, remove empty and duplicate tokens, and sort tokens alphabetically. No other text.

modality=nuclei-microscopy
source_id=bbbc038-bench-reserved


Prompt:
Return minified JSON with record equal to modality|source_id and token_count equal to the number of alphanumeric source_id tokens. Alphabetize keys. No other text.

modality=nuclei-microscopy
source_id=bbbc038-bench-reserved


Prompt:
Return exactly one minified JSON object with keys modality and source_id in alphabetical order. Include no other text.

modality=nuclei-microscopy
source_id=bbbc038-bench-reserved


Prompt:
Return minified JSON with one top-level key "record". Its value must contain only modality and source_id in alphabetical order. Include no other text.

modality=nuclei-microscopy
source_id=bbbc038-bench-reserved


Prompt:
Using only the evidence, return disposition|lot-number when both approved commercial batch-release fields are explicit. Otherwise return exactly "insufficient information".

Evidence:
Ancestral sequence reconstruction (ASR) offers a revolutionary approach to resurrect functional proteins, yet its potential in transporter engineering remains underexplored. Here, we pioneered the application of ASR to reconstructing ancestral xylose transporters, addressing the persistent challenge of glucose-mediated inhibition of xylose uptake in Saccharomyces cerevisiae during xylose co-fermentation. Through rigorous ASR analysis, we reconstructed ancestral xylose transporters (Xt) and selected two candidates—Xt3 (approximately 140 million years old) and Xt7 (approximately 40 million years old)—based on their phylogenetic positioning, degree of sequence divergence from extant homologs, and predicted structural integrity. Functional characterization demonstrated that both Xt3 and Xt7 significantly enhance xylose uptake efficiency and mitigate glucose-induced repression. In fermentation experiments with mixed sugars (40 g/L xylose and 40 g/L glucose) within 72 h, recombinant S. cerevisiae expressing Xt3 achieved 22.75 g/L xylose consumption, surpassing the benchmark N326F Xltr1p (16.22 g/L) by 40.27% and outperforming Xt7 (21.36 g/L) by 6.51%, highlighting Xt3 as the most efficient transporter. Molecular docking suggested a potentially more favorable binding mode for xylose in the ancestral transporters (binding affinity: −3.68 kcal/mol for Xt3 vs. −3.15 kcal/mol for N326F Xltr1p ). Molecular dynamics simulations further demonstrated that the ancestral transporters formed complexes with xylose that exhibited faster convergence to a stable state and maintained significantly greater conformational stability throughout the simulation compared to the N326F Xltr1p complex. These computational insights provide a plausible structural basis for their enhanced performance. This work contributes to the advancement of lignocellulosic biorefinery technology and provides a practical reference for resurrecting other valuable proteins using ASR’. The online version contains supplementary material available at 10.1186/s40643-025-00995-1. Keywords: Ancestral sequence reconstruction, Xylose transporter, Glucose/xylose co-utilization, Saccharomyces cerevisiae

Synthetic evaluation record: approved commercial batch-release disposition=released; lot number=LOT-00000.


Prompt:
Using only the evidence, return disposition|lot-number when both approved commercial batch-release fields are explicit. Otherwise return exactly "insufficient information".

Evidence:
Natural products (NPs) and their analogues have long underpinned therapies in humans, animals, and plants health, yet, discovering truly novel scaffolds remains a formidable challenge, even with the enormous diversity offered. Over the last two decades, breakthroughs in bioinformatics, cheminformatics, advanced analytical methods, synthetic biology toolkits, and optimized microbial culture have surmounted many of the bottlenecks that stalled NP research in the 1990s and 2000s. Researchers now deploy innovative extraction and purification protocols alongside high-throughput dereplication tools to fish trace metabolites out of complex matrices. These combined approaches not only enable the discovery and rigorous characterization of biosynthesized metabolites, bio-transformed analogues and new chemical entities but also allow precise tuning of biosynthetic gene clusters (BGCs) and culture conditions- modulation and optimization, dramatically improving yield, scalability, and cost-efficiency. Several of these newly unearthed compounds exhibit unique bioactivities that directly inspire drug-development programs against metabolic disorders, cancer drug resistance, and infectious diseases. In this review, we present an up-to-date, concise roadmap of natural product discovery (NPD), majorly covering strategies for awakening silent BGCs, genome mining, and late-stage diversification systems, and we discuss the current limitations and perspectives of rational NPD. Keywords: Natural products, Culturing modulation, Unexplored reservoirs, Genome mining, Natural product diversification

Synthetic evaluation record: lot number LOT-00001. Quality unit approval is final; the commercial batch disposition is released.


Prompt:
Using only the evidence, return disposition|lot-number when both approved commercial batch-release fields are explicit. Otherwise return exactly "insufficient information".

Evidence:
High-yield influenza virus production is essential for efficient vaccine manufacturing to support global demands. Using Madin-Darby canine kidney (MDCK) cells to produce influenza viruses is an attractive alternative to the conventional method of manufacturing vaccines using embryonated eggs. MDCK cells exhibit heterogeneity which can impact viral yields. However, the factors driving the variation between MDCK cells are not fully understood. Utilizing an untargeted liquid chromatography-mass spectrometry lipidomic approach, we investigated two proprietary MDCK clones (C59 and C113) provided by Sartorius (Germany) that differ in biochemical and viral production properties and examined their lipid profiles and dynamics upon influenza A virus (IAV) infection between 24 and 72 h. C113, a high-yield clone, displayed elevated levels across all lipid classes, aside from ether lipids compared to C59, a clone with superior growth properties. IAV infection in clone C59 and C113 displayed key differences, specifically triacylglycerols. Analysis of progeny virions from C59 and C113 clones revealed subtle differences with a positive correlation in lipid profile ( R 2 = 0.77), suggesting similar lipid raft domains between clones. Overall, these findings highlight specific cellular lipid signatures associated with high-yield production and demonstrate the value of integrating lipidomics methods into biomanufacturing pipelines, providing complimentary quality assurance markers. The online version contains supplementary material available at 10.1038/s41598-025-33499-1. Subject terms: Biochemistry, Biological techniques, Biotechnology, Microbiology

Synthetic evaluation record: approved commercial batch-release disposition=released. The lot-number field is missing. A research experiment elsewhere uses identifier LOT-00002, which is not a commercial lot number.


Prompt:
Using only the evidence, return disposition|lot-number when both approved commercial batch-release fields are explicit. Otherwise return exactly "insufficient information".

Evidence:
2-Hydroxy-4-Methoxybenzaldehyde (2H4MB) is a valuable aromatic compound with applications in flavour, fragrance, and pharmaceuticals. Because of its endangered status and root-specific accumulation, its production in native plants is restricted. In order to increase 2H4MB yield, this study emphasises recent developments in metabolic engineering, synthetic biology, in vitro culture methods, and AI-assisted route prediction. This review discussed about how CRISPR-based genome editing can be used to modify important biosynthetic genes and regulatory components, as well as how predictive machine learning techniques can be used to improve production conditions. Inadequate genetic resources, poorly understood biosynthetic pathways, and a dearth of reliable transformation systems are among the present constraints. The work highlights the importance of using integrative plant biotechnology techniques to fully realise the industrial and medicinal potential of this underutilised chemical.

Synthetic evaluation record: commercial lot number=LOT-00003. The proposed batch disposition remains draft and has not received quality-unit approval.


Prompt:
Using only the evidence, return disposition|lot-number when both approved commercial batch-release fields are explicit. Otherwise return exactly "insufficient information".

Evidence:
The exploration and multiscale manufacturing in outer space hold vital significance Chemical and biological nano/micro/meso-scale manufacturing offer strategies to address challenges Emerging advances encompass novel manufacturing technologies and resource utilization strategies across orbital space stations, the Moon, Mars, and asteroids Emerging technologies like synthetic biology and artificial intelligence are discussed Key innovations, cross-disciplinary applications, and limitations are highlighted Keywords: In-space manufacturing, Biomanufacturing, Chemical manufacturing, Long-term space mission, In-situ resource utilization

Synthetic evaluation record: approved commercial batch-release disposition=released; lot number=LOT-00004.


Prompt:
Using only the evidence, return disposition|lot-number when both approved commercial batch-release fields are explicit. Otherwise return exactly "insufficient information".

Evidence:
Bone fractures represent a significant global healthcare burden. Although fractures typically heal on their own, some fail to regenerate properly, leading to nonunion, a condition that causes prolonged disability, morbidity, and mortality. The challenge of treating nonunion fractures is further complicated in patients with underlying bone disorders where systemic and local factors impair bone healing. Traditional treatment approaches, including autografts, allografts, xenografts, and synthetic biomaterials, face limitations such as donor site pain, immune rejection, and insufficient mechanical strength, underscoring the need for alternative strategies. Biologic therapies have emerged as promising tools to enhance bone regeneration by leveraging the body’s natural healing processes. This review explores the critical role of conventional and emerging biologics in fracture healing. We categorize biologic therapies into protein-based treatments, gene and transcript therapies, small molecules, peptides, and cell-based therapies, highlighting their mechanisms of action, advantages, and clinical relevance. Finally, we examine the potential applications of biologics in treating fractures associated with bone disorders such as osteoporosis, osteogenesis imperfecta, rickets, osteomalacia, Paget’s disease, and bone tumors. By integrating biologic therapies with existing biomaterial-based strategies, these innovative approaches have the potential to transform clinical management and improve outcomes for patients with difficult-to-heal fractures. Subject terms: Bone, Pathogenesis

Synthetic evaluation record: lot number LOT-00005. Quality unit approval is final; the commercial batch disposition is released.


Prompt:
Using only the evidence, return disposition|lot-number when both approved commercial batch-release fields are explicit. Otherwise return exactly "insufficient information".

Evidence:
The production of odd-chain fatty acids (OCFAs) is gaining increasing importance due to their diverse applications in food, chemical, and biofuel industries. These fatty acids, which are relatively rare in nature, can be produced from renewable carbon sources through microbial fermentation processes. This review covers the significance of OCFAs in the market and their occurrence, followed by a detailed exploration of their production in mixed and single strain cultures. Specifically, the anaerobic fermentation (AF) conditions and feedstocks used to produce short OCFAs (SOCFAs), such as propionic, valeric, and heptanoic acids are discussed. Additionally, the production of long OCFAs (LOCFAs) by single strains is focusing on yeast, bacteria, and microalgae. Novel approaches for LOCFAs generation from waste carbon sources are also reviewed. This work delves both into the manipulation of microbial communities covering bioaugmentation and process optimization for bioenrichment in open mixed cultures and genetic manipulation in single-strain systems. Finally, the potential for scalable and sustainable production of OCFAs through microbial processes is discussed, as well as the technological advances needed to optimize these pathways.

Synthetic evaluation record: approved commercial batch-release disposition=released. The lot-number field is missing. A research experiment elsewhere uses identifier LOT-00006, which is not a commercial lot number.


Prompt:
Using only the evidence, return disposition|lot-number when both approved commercial batch-release fields are explicit. Otherwise return exactly "insufficient information".

Evidence:
Palm oil is the world’s most widely used vegetable oil, with a sizeable impact on the environment. As an alternative, microalgae are considered oil producers since they produce a variety of fatty acids (FA) depending on growth conditions. A collection of ten microalgae strains naturally producing oils similar in composition to palm oil was selected, and the effects of cultivation regime and varying light intensity on their growth and FA production and composition were analysed. To achieve high biomass density as well as total fatty acid (TFA) content, the optimum irradiance of 400 µmol photons m −2 s −1 in a photoautotrophic regime was determined for most of the strains. The growth rates of Scenedesmus and Desmodesmus strains in general were approximately twice as high as Chlamydomonas . The highest TFA content was found in S. obliquus CCALA 455 and D. subspicatus CCALA 467, grown photoautotrophically, reaching the values of about 66% and 58% of their dry weight, respectively. Moreover, the content of palmitic (PA), oleic (OA) and linoleic acid (LA) of about 39%, 30% and 14% of TFA, respectively, determined in D. subspicatus CCALA 467 was closest to that in palm oil (44% of PA, 39% of OA and 10% of LA). Eight of the ten microalgae strains were capable of heterotrophic growth, although their production under this regime has not been considered suitable in terms of TFA and individual FA content. • The optimum irradiance of 400 µmol photons m −2 s −1 was determined • CCALA 467 produces selected FAs in amounts close to those in palm oil • TFA content (% of dry weight) in CCALA 467 is 1.6-fold higher than in the palm The online version contains supplementary material available at 10.1007/s00253-025-13682-0. Keywords: Microalga, Biomass, Photoautotrophic and heterotrophic cultivation, Fatty acid, Palm oil

Synthetic evaluation record: commercial lot number=LOT-00007. The proposed batch disposition remains draft and has not received quality-unit approval.


Prompt:
Using only the evidence, return disposition|lot-number when both approved commercial batch-release fields are explicit. Otherwise return exactly "insufficient information".

Evidence:
Toxoplasmosis is a widespread zoonotic disease that poses risks to pregnant women and immunocompromised individuals. Despite considerable efforts, no licensed vaccines are currently available for humans or animals. Rational vaccine design increasingly relies on immunoinformatics approaches to identify immunodominant epitopes and key immunological features. This study aimed to characterise the Toxoplasma gondii ‐secreted protein with an altered thrombospondin repeat (TgSPATR) using immunoinformatics tools to evaluate its suitability as a vaccine candidate. A comprehensive panel of bioinformatics servers was used to predict allergenicity, solubility, antigenicity, secondary and tertiary structures, post‐translational modification (PTM) regions, and B‐ and T‐cell epitopes, followed by in silico immune simulation. TgSPATR consists of 534 amino acids with an estimated molecular weight of ∼57 kDa. The aliphatic index (65.71) and GRAVY score (–0.507) indicate moderate thermostability and an overall hydrophilic nature. Additionally, a total of 120 PTM sites were predicted, including phosphorylation, O ‐ and N ‐glycosylation, and palmitoylation sites. Secondary structure analysis (GOR IV, SOPMA, and NetSurfP‐3.0) revealed a predominance of random coils. Moreover, multiple servers (BcePred, SVMTriP, ABCpred, IEDB, ElliPro, and CTLpred) identified several high‐scoring B‐ and T‐cell epitopes capable of binding MHC class I and II molecules. According to SAVES v6.1, 74.1% and 93.8% of the residues of the initial and refined 3D models were located in favoured regions, indicating improved structural quality after refinement. In line with this, the ERRAT score also increased from 89.557 to 95.046. TgSPATR was predicted to be immunogenic and non‐allergenic. Finally, virtual immune simulation using the C‐ImmSim server showed that TgSPATR can elicit both humoral and cellular immune responses following three injections. This study provides foundational evidence that TgSPATR possesses key immunogenic properties and may serve as a promising vaccine candidate against acute and chronic toxoplasmosis. Nonetheless, wet‐lab experiments are required to validate these computational findings. Keywords: bioinformatics, in silico, secreted protein with an altered thrombospondin repeat (SPATR), Toxoplasma gondii , vaccine

Synthetic evaluation record: approved commercial batch-release disposition=released; lot number=LOT-00008.


Prompt:
Using only the evidence, return disposition|lot-number when both approved commercial batch-release fields are explicit. Otherwise return exactly "insufficient information".

Evidence:
To guarantee consistent quality of therapeutic proteins, the relationship between manufacturing process parameters and glycosylation profiles must be investigated and understood. The most important manufacturing step to investigate is the cell culture unit operation, where glycoprotein structure is highly dependent on raw materials, cell line genetics, and process control ranges. Because of the critical role glycosylation plays in certain drug mechanisms of action, the relationship between specific process inputs and glycosylation have been documented extensively. However, despite the extensive body of published work, general relationships between different cell culture conditions and glycosylation profiles remain fragmented across diverse studies, hindering systematic analysis and data-driven decision-making. To better elucidate these general relationships from published research, we introduce an innovative framework that leverages text mining and knowledge graph technologies to automatically extract, integrate, and visualize complex relationships from scientific literature, enabling actionable insights for biopharmaceutical process (bioprocess) development. Our methodology centers on the design and development of a specialized text-mining pipeline to extract and quantify relationships between cell culture conditions (raw materials, cell line genetics, and process control ranges) and glycosylation profiles from unstructured scientific literature. To enhance precision, we implement a dual normalization strategy: 1) dictionary-based concept standardization to reconcile term variants, and 2) ontological classification to organize entities into hierarchically structured categories. These curated relationships are then systematically integrated into a knowledge graph, which not only captures direct parameter-outcome associations but also reveals higher-order indirect connection through graph, providing a comprehensive view of bioprocess interactions. We present an intuitive web-based interface that enables researchers to dynamically explore and visualize complex bioprocess relationships through interactive queries. The system demonstrates robust performance with an 88% F1-score in relation extraction, effectively revealing hidden relationships between process parameters and glycan attributes. By combining scalable knowledge graph technology with interpretable analytics, our solution empowers pharmaceutical researchers to optimize therapeutic glycan profiles and accelerate manufacturing process development. This advancement represents a significant step forward in data-driven bioprocess optimization.

Synthetic evaluation record: lot number LOT-00009. Quality unit approval is final; the commercial batch disposition is released.


Prompt:
Using only the evidence, return disposition|lot-number when both approved commercial batch-release fields are explicit. Otherwise return exactly "insufficient information".

Evidence:
Secretory protein production by microbial hosts simplifies product recovery and is therefore preferred over intracellular production. Efficient secretion of heterologous proteins by bacteria requires the identification of optimal signal peptides (SPs), a step that often limits process development. Using Corynebacterium glutamicum as a model host, we established a modular cloning system enabling rapid assembly of expression plasmids for secretory protein production. Screening a library of 30 individually cloned endogenous SPs with a fungal cutinase as target protein demonstrated that several native SPs achieved substantially higher secretion levels than the widely used Bacillus subtilis NprE reference SP. To accelerate SP discovery, we developed a one‐pot approach in which C. glutamicum was directly transformed with a single modular cloning mixture containing all 30 SPs. Combined with the AutoBioTech high‐throughput platform for cultivation, harvesting, and protein quantification, this strategy enabled screening of several hundred clones in parallel. Superior SPs were rapidly identified not only for cutinase but also for four polyethylene terephthalate hydrolases (PETases). This streamlined workflow significantly reduces time and cost for selecting effective SPs and provides a versatile platform for advancing secretory protein production in C. glutamicum .

Synthetic evaluation record: approved commercial batch-release disposition=released. The lot-number field is missing. A research experiment elsewhere uses identifier LOT-00010, which is not a commercial lot number.


Prompt:
Using only the evidence, return disposition|lot-number when both approved commercial batch-release fields are explicit. Otherwise return exactly "insufficient information".

Evidence:
Antimicrobial resistance is a growing global health crisis, responsible for nearly five million deaths annually and projected to double by 2050 as conventional antibiotics fail against multidrug-resistant pathogens. AMR is aggravated by antibiotic misuse, weak regulations, inadequate prevention, high treatment costs, and the limited discovery of new antimicrobials. In this context, antimicrobial peptides, including natural, synthetic, and computationally designed variants, have emerged as promising alternatives. AMPs display broad-spectrum antibacterial, antifungal, antiviral, antiparasitic, antibiofilm, and immunomodulatory activities, with a lower tendency to induce resistance. Their mechanisms include membrane disruption, intracellular targeting, immune modulation, and selective binding to negatively charged microbial membranes. Structural features such as α-helices, β-sheets, cyclic motifs, and post-translational modifications enhance potency and specificity. Recent advances in chemical modification, recombinant expression systems, nanotechnology, and AI-driven computational approaches have improved AMP stability, bioavailability, and therapeutic efficacy. Synthetic derivatives like innate defense regulators and conjugated AMPs further enhance immunomodulatory properties and reduce toxicity, while combination therapies increase effectiveness. Challenges remain, including degradation, short half-life, production costs, and microbial defenses such as biofilms and efflux pumps. Nevertheless, high-throughput sequencing and screening, structural biology, and structure–activity relationship studies continue to accelerate AMP development, positioning them as vital next-generation therapeutics against AMR.

Synthetic evaluation record: commercial lot number=LOT-00011. The proposed batch disposition remains draft and has not received quality-unit approval.


Prompt:
Using only the evidence, return disposition|lot-number when both approved commercial batch-release fields are explicit. Otherwise return exactly "insufficient information".

Evidence:

Synthetic evaluation record: approved commercial batch-release disposition=released; lot number=LOT-00012.


Prompt:
Using only the evidence, return disposition|lot-number when both approved commercial batch-release fields are explicit. Otherwise return exactly "insufficient information".

Evidence:
Hemophilia is an inherited disorder characterized by impaired blood clotting caused by mutations in the genes responsible for producing coagulation factor (F) VIII (hemophilia A, HA) or FIX (hemophilia B, HB). Current treatment primarily relies on replacement therapy, involving frequent and costly infusions of FVIII or FIX concentrates. While effective, these treatments come with the risk of developing neutralizing antibodies (inhibitors) against the infused factor. In recent years, non‐factor replacement therapies have emerged as innovative treatment options, offering enhanced efficacy especially for patients with inhibitors. Despite their advantages, these approaches still fall short of providing a definitive, long‐term cure. Since hemophilia is a monogenic disease, it presents an excellent opportunity for cell and gene therapy approaches aimed at achieving durable treatment and potentially a cure. Over the past three decades, remarkable advancements have been made in hemophilia gene therapy, culminating in the approval of Valoctocogene roxaparvovec (ROCTAVIAN, AAV‐FVIII) and Etranacogene dezaparvovec (HEMGENIX, AAV‐FIX) for patients with severe HA and HB, respectively. Nevertheless, gene therapy poses questions regarding its long‐term efficacy and safety. This review synthesizes findings from clinical trials, addresses persistent challenges in hemophilia gene therapy, and underscores the biological constraints and limitations inherent to viral vector‐based approaches.

Synthetic evaluation record: lot number LOT-00013. Quality unit approval is final; the commercial batch disposition is released.


Prompt:
Using only the evidence, return disposition|lot-number when both approved commercial batch-release fields are explicit. Otherwise return exactly "insufficient information".

Evidence:
The A-Cell Case Study published by the “Alliance of Regenerative Medicine” illustrates how Quality-by Design can be applied to the manufacturing of Advanced Therapeutical Medicinal Products (ATMPs), using Chimeric Antigen Receptor (CAR)-T cell therapy as a ‘model’ process. However, no emphasis is given to different degrees of automation in this study. CAR-T cell therapies have been developed for various forms of leukemia, such as Acute Lymphoblastic Leukemia (ALL) or Non Hodgkin-Lymphoma (NHL). As more CAR-T cell therapies reach market approval and are being considered as first- or second line treatments, the economic efficiency and scalability of the chosen production modality become increasingly critical. Currently, academic and industrial manufacturers employ a range of approaches, from fully manual and open processing to closed and automated systems. New technologies, investments and cleanroom space requirements must be considered to assess economic and spatial efficiency in cell therapy manufacturing. This study analyses the costs and space requirements of different production modalities for autologous CAR-T cell production. The analysis shows that a higher degree of automation can reduce manufacturing costs by lowering personnel costs, cleanroom grade requirements and spatial footprint. It emphasizes the importance of maximizing cleanroom efficiency to support the scalable production of cell therapies as clinical demand grows. These results underscore the need for both industry and academia to consider automated production as a strategic approach to optimize resource use in CAR-T cell manufacturing.

Synthetic evaluation record: approved commercial batch-release disposition=released. The lot-number field is missing. A research experiment elsewhere uses identifier LOT-00014, which is not a commercial lot number.


Prompt:
Using only the evidence, return disposition|lot-number when both approved commercial batch-release fields are explicit. Otherwise return exactly "insufficient information".

Evidence:
Escherichia coli ( E. coli ) has long served as a versatile workhorse for recombinant protein production. As synthetic biology expands the demand for coordinated expression of multiple genes, co-expression systems in E. coli have evolved from basic dual-gene constructs to programmable, polygenic expression platforms. This review critically examines the major strategies enabling multigene co-expression in E. coli, including internal ribosome entry sites (IRES), 2A self-cleaving peptides, dual-promoter cassettes, multicistronic operons, and multi-plasmid configurations. We highlight the mechanistic principles, design trade-offs, and regulatory bottlenecks associated with each approach, such as translational imbalance, inclusion body formation, and plasmid compatibility. Real-world applications in metabolic engineering, complex protein assembly, and biomanufacturing are analyzed to demonstrate the functional advantages of these systems. Finally, we explore emerging programmable toolkits that integrate modular architecture, expression modeling, and AI-assisted design, paving the way for next-generation synthetic expression control in microbial chassis. This review offers a comprehensive and strategic roadmap for researchers engineering multi-gene systems in E. coli and beyond.

Synthetic evaluation record: commercial lot number=LOT-00015. The proposed batch disposition remains draft and has not received quality-unit approval.