guo, na · pan, jiachen · li, tiantian · et al.

14 files · 100 MB · csv, rar, tsv

ADM_LSIR is a physics-inspired laparoscopic aerosol degradation dataset for aerosol-aware surgical image analysis and image restoration. The v1.0.0 release contains: - 21,916 clean clinical laparoscopic frames (clean/) - 9,562 real intraoperative aerosol-degraded frames (degraded/) - 36,052 simulated aerosol masks, including 19,701 smoke-like masks and 16,351 trajectory masks (mask/) - Blender simulation/cache materials (ADM_LSIR_Blender_simulation_files_v1.0.rar) - metadata_quality_report_v1.0.csv - recommended_splits_v1.0.csv - video_mapping_v1.0.csv - parts_manifest.txt - checksums_v1.0.tsv - release_manifest_v1.0.json All released clinical frames are de-identified and stored as lossless PNG files. Filenames use anonymized video identifiers, e.g., C-V##-####.png for clean frames and D-V##-####.png for degraded frames. The recommended split is defined at the source_video_id/public_video_label level to reduce leakage across frames from the same source video. The public video labels in video_mapping_v1.0.csv provide privacy-safe source-video identifiers (video1-video19). The Blender archive documents the smoke and trajectory mask simulation setup and supports reuse, but it is not a guaranteed exact per-mask reproduction package. The released pre-rendered mask library is the primary reusable dataset component. Source code for synthesis and quality screening is available at: https://github.com/SweetDeathh/ADM_LSIR

Winter, Henry · Severino, MaryKay · Volunteer Scientist

16 files · 100 MB · csv, pdf, zip

These are audio recordings taken by an Eclipse Soundscapes (ES) Data Collector during the week of the April 08, 2024 Total Solar Eclipse. It was decided to include only raw, unprocessed audio data files in each site-specific ZIP archive and in each Zenodo record. This decision was so that any researcher can independently verify, reproduce, and extend the analysis performed. As a result, some sites have WAV files with 0 bytes of data or timestamps outside the range of probable recording times. Procedures used by the Eclipse Soundscapes team to process audio data for its purposes are outlined in the Data Management reports located in the Eclipse Soundscapes Zenodo community. Data with 0 bytes of data were included for completeness. Data Site location information: Latitude: 44.46311 Longitude: -71.68203 Local Eclipse Type: Total Solar Eclipse Solar Eclipse Eclipse Percent (%): 100 WAV files Time & Date Settings: Set with Automated AudioMoth Time Chime (More information on TimeStamp Setting below) Data Collector Start Time Notes: N/A Included Data: Audio files in WAV format with the date and time in UTC within the file name: YYYYMMDD_HHMMSS meaning YearMonthDay_HourMinuteSecond For example, 20240411_141600.WAV means that this audio file starts on April 11, 2024 at 14:16:00 Coordinated Universal Time (UTC) CONFIG Text file: Includes AudioMoth device setting information, such as sample rate in Hertz (Hz), gain, firmware, etc. README.md: Markdown formatted file with information about the recording and recording site. file_list.csv: A machine and human file that gives the following information on each file in the record: File Name, File Type, Description, File Size in kilobytes, Name of Associated Data Dictionary with the file, calculated SHA-512 Hash of the file as a unique identifier to insure data integrity during transfer and compression. total_eclipse_data.csv: A machine and human readable file that gives the following information about the site where the audio data recording was taken: ESID#, Latitude, Longitude, Eclipse_type, CoveragePercent, Eclipse Start UTC (1st contact), Totality Start UTC (2nd contact), Totality End UTC (3rd Contact), Eclipse End UTC (4th Contact), Max Eclipse Time UTC License.txt: A human readable file that explains the terms and conditions under which the data can be used. AudioMoth_Operation_Manual.pdf: A human readable document that explains the use of an AudioMoth device. The document is current up to the time of the AudioMoth's use in the Eclipse Soundscapes project. file_list_data_dict.csv: A machine and human data dictionary file that gives information on the variables contained within the file_list.csv file. CONFIG_data_dict.csv: A machine and human data dictionary file that gives information on the variables contained within the CONFIG.TXT file. eclipse_data_data_dict.csv: A machine and human data dictionary file that gives information on the variables contained within the total_eclipse_data.csv file. WAV_data_dict.csv: A machine and human data dictionary file that gives information on the variables contained within the *.WAV files. ES_Data_Management_Pre-Eclipse_Data_Infrastructure_Stage_0.pdf: PDF document that describes Stage 0 (Pre-Eclipse Infrastructure and Data Stewardship Planning) of the Eclipse Soundscapes (ES) data lifecycle. ES_Data_Management_Receipt_Sorting_and_Metadata_Organization_Stage_1.pdf: PDF document that describes Stage 1 (Receipt, Sorting, and Metadata Organization) of the Eclipse Soundscapes (ES) data lifecycle. ES_Data_Management_Data_Processing_Stage_2.pdf: PDF document that describes Stage 2 (Data Processing) of the Eclipse Soundscapes (ES) data Volunteer Scientists. 2023 and 2024 solar eclipse soundscapes audio datalifecycle. ES_Data_Management_Data_Sharing_Stage_3.pdf: PDF document that describes Stage 3 (Public Data Sharing) of the Eclipse Soundscapes (ES) data lifecycle. Eclipse Information for this location: Eclipse Date: April 08, 2024 Eclipse Start Time (UTC) (1st Contact): 18:16:15 Totality Start Time (UTC) (2nd Contact): [N/A if partial eclipse] 19:28:56 Eclipse Maximum Time [when the most possible amount of the Sun in blocked] (UTC): 19:29:25 Totality End Time (UTC) (3rd Contact): [N/A if partial eclipse] 19:29:53 Eclipse End Time (UTC) (4th Contact): [N/A if partial eclipse] 20:38:30 Audio Data Collection During Eclipse Week ES Data Collectors used AudioMoth devices to record audio data, known as soundscapes, over a 5-day period during the eclipse week: 2 days before the eclipse, the day of the eclipse, and 2 days after. The complete raw audio data collected by the Data Collector at the location mentioned above is provided here. This data may or may not cover the entire requested timeframe due to factors such as availability, technical issues, or other unforeseen circumstances. ES ID# Information: Each AudioMoth recording device was assigned a unique Eclipse Soundscapes Identification Number (ES ID#). This identifier connects the audio data, submitted via a MicroSD card, with the latitude and longitude information provided by the data collector through an online form. The ES team used the ES ID# to link the audio data with its corresponding location information and then uploaded this raw audio data and location details to Zenodo. This process ensures the anonymity of the ES Data Collectors while allowing them to easily search for and access their audio data on Zenodo. TimeStamp Information: The ES team and the Data Collectors took care to set the date and time on the AudioMoth recording devices using an AudioMoth time chime before deployment, ensuring that the recordings would have an automatic timestamp. However, participants also manually noted the date and start time as a backup in case the time chime setup failed. The notes above indicate whether the WAV audio files for this site were timestamped manually or with the automated AudioMoth time chime. Common Timestamp Error: Some AudioMoth devices experienced a malfunction where the timestamp on audio files reverted to a date in 1970 or before, even after initially recording correctly. Despite this issue, the affected data was still included in this ES site's collected raw audio dataset. Latitude & Longitude Information: The latitude and longitude for each site was taken manually by data collectors and submitted to the ES team, either via a web form or on paper. It is shared in Decimal Degrees format. General Project Information: The Eclipse Soundscapes Project is a NASA Volunteer Science project funded by NASA Science Activation that is studying how eclipses affect life on Earth during the October 14, 2023 annular solar eclipse and the April 8, 2024 total solar eclipse. Eclipse Soundscapes revisits an eclipse study from almost 100 years ago that showed that animals and insects are affected by solar eclipses! Like this study from 100 years ago, ES asked for the public's help. ES uses modern technology to continue to study how solar eclipses affect life on Earth! Eclipse Soundscapes is an enterprise of ARISA Lab, LLC and is supported by NASA award No. 80NSSC21M0008. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Aeronautics and Space Administration. Eclipse map/figure/table/predictions courtesy of Fred Espenak, NASA/Goddard Space Flight Center, from eclipse.gsfc.nasa.gov . Eclipse Data Version Definitions {1st digit = year, 2nd digit = Eclipse type (1=Total Solar Eclipse, 9=Annular Solar Eclipse, 0=Partial Solar Eclipse), 3rd digit is unused and in place for future use} 2023.9.0 = Week of October 14, 2023 Annular Eclipse Audio Data, Path of Annularity (Annular Eclipse) 2023.0.0 = Week of October 14, 2023 Annular Eclipse Audio Data, OFF the Path of Annularity (Partial Eclipse) 2024.1.0 = Week of April 8, 2024 Total Solar Eclipse Audio Data, Path of Totality (Total Solar Eclipse) 2024.0.0 = Week of April 8, 2024 Total Solar Eclipse Audio Data , OFF the Path of Totality (Partial Solar Eclipse) *Please note that this dataset's version number is listed below. Eclipse Soundscapes Data Collector Role Training and Implementation Resources Manual (2023-2024) (Archival Copy) This site-level record includes the Eclipse Soundscapes Data Collector Role Training and Implementation Resources Manual (2023-2024) . The manual documents the participant training, device setup procedures, metadata submission requirements, ES ID system, timestamp protocols, data return workflow, and public archiving processes used during the October 14, 2023 annular solar eclipse and the April 8, 2024 total solar eclipse. The manual is preserved for transparency and reproducibility and reflects the procedures under which this dataset was collected and processed. (DOI 10.5281/zenodo.18623442) Data Receipt, Processing, and Analysis Methods All programs supporting Stages 1–3 are openly available in the: Eclipse Soundscapes GitHub repository: https://github.com/ARISA-Lab-LLC/ESCSP Data Management Lifecycle The following section documents the relationship of this record to the full Eclipse Soundscapes (ES) data lifecycle, a multi-stage workflow designed to support large-scale participatory science, long-term data stewardship, open science, and scientific reuse. Each stage addressed a different operational need, beginning before eclipse deployment and continuing through validation, public archiving, and scientific analysis. Together, these stages transformed distributed volunteer-submitted audio recordings into structured, documented, publicly accessible NASA-funded research assets. Stage 0: Pre-Eclipse Infrastructure and Deployment Preparation Severino, M., & Winter, H. (2026). Eclipse Soundscapes Data Management: Pre-Eclipse Infrastructure and Deployment Preparation (Stage 0). Zenodo. https://doi.org/10.5281/zenodo.20413370 Stage 0 focused on building the operational foundation required to support geographically distributed eclipse data collection at national scale. This stage included AudioMoth device preparation, accessibility modifications, ES ID # assignment systems, metadata collection workflows, participant training materials, deployment logistics, and planning for downstream data stewardship and archival workflows. The 2023 annular eclipse served as both a scientific investigation and a large-scale operational beta test that informed improvements for the 2024 total solar eclipse campaign. Related Citations and Resources: Severino, M., & Kline, T. (2025, November 24). Eclipse Soundscapes Apprentice Role Curriculum: Solar Eclipses and Multi-Sensory Observing (Informal Education). Zenodo. https://doi.org/10.5281/zenodo.17703003 Severino, M., & Bauer, D. J. (2026). Eclipse Soundscapes Observer Role Training and Resources Manual (2023–2024). Zenodo. https://doi.org/10.5281/zenodo.18633602< /li> Severino, M., Winter, H., & Bauer, D. J. (2026). Eclipse Soundscapes Data Collector Role Training and Implementation Manual (2023–2024). Zenodo. https://doi.org/10.5281/zenodo.18623443 Stage 1: Receipt, Sorting, and Metadata Organization Severino, M., & Winter, H. (2026). Eclipse Soundscapes Data Management: Receipt, Sorting, and Metadata Organization (Stage 1). Zenodo. https://doi.org/10.5281/zenodo.19471425 Stage 1 transformed returned participant materials into organized, traceable site-level records. This included receiving mailed microSD cards, consolidating participant-submitted metadata, reconciling handwritten and online records, organizing physical audio media by ES ID #, and deriving eclipse timing and coverage information using NASA eclipse prediction datasets. The outputs of Stage 1 established the structured metadata relationships required for downstream validation, processing, archiving, and analysis workflows. Related Citations and Resources: Winter, H., & Goncalves, J. (2026). EPTT (Eclipse Phase Timing Tool) [Computer software]. GitHub. https://github.com/ARISA-Lab-LLC/ESCSP-Eclipse-Phase-Timing-Tool /li> Espenak, F. (n.d.). Eclipse predictions by Fred Espenak, NASA's GSFC Eclipse Web Site. NASA Goddard Space Flight Center. http://eclipse.gsfc.nasa.gov/eclipse.html Stage 2: Data Processing and Validation Severino, M., & Winter, H. (2026). Eclipse Soundscapes Data Management: Data Processing (Stage 2). Zenodo. https://doi.org/10.5281/zenodo.18683402 Stage 2 focused on centralized audio ingestion, validation, timestamp verification, metadata reconciliation, and preparation of datasets for analysis and public sharing. During this stage, returned audio recordings were processed using custom open-source tools developed by the ES team, including ES WAVES and ES AMES. The project implemented scalable infrastructure capable of processing large volumes of participant-submitted microSD cards while preserving all raw audio data without modification. Stage 2 established the validated dataset structure required for long-term preservation and scientific analysis. Related Citations and Resources: Winter, H., & Goncalves, J. (2026). ES WAVES (Eclipse Soundscapes WAV Audio Validation & Extraction Suite) [Computer software]. GitHub. https://github.com/ARISA-Lab-LLC/ESCSP-ES-WAV-Audio-Validation-Extraction-Suite Winter, H., & Goncalves, J. (2026). ES AMES (Eclipse Soundscapes AudioMoth Metadata Extractor Suite) [Computer software]. GitHub. https://github.com/ARISA-Lab-LLC/ESCSP-ES-AMES-AudioMoth-Metadata-Extractor-Suite Stage 3: Public Data Sharing and Open Archiving Severino, M., & Winter, H. (2026). Eclipse Soundscapes Data Management: Public Audio Data Sharing (Stage 3). Zenodo. https://doi.org/10.5281/zenodo.18683437 Stage 3 transformed validated site-level datasets into publicly archived, DOI-assigned research records published through the Eclipse Soundscapes Zenodo Community. This stage included dataset packaging, metadata standardization, README generation, integrity verification, DOI assignment, and automated repository upload workflows using the Automated Zenodo Upload Software (AZUS). These workflows established the project's long-term open-science infrastructure and ensured that datasets remained findable, accessible, interoperable, reusable, and citable for future scientific and educational use. Related Citations and Resources: Winter, H., & Goncalves, J. (2026). AZUS (Automated Zenodo Upload Software) [Computer software]. GitHub. https://github.com/ARISA-Lab-LLC/AZUS-Automated-Zenodo-Upload-Software Stage 4: Scientific Analysis and Research Use Stage 4 involves the scientific analysis and interpretation of validated eclipse soundscape datasets. Analysis workflows utilized datasets verified during earlier stages to investigate eclipse-related environmental and animal vocalization changes across hundreds of recording sites. This stage also includes broader scientific interpretation, publication development, and continued reuse of Eclipse Soundscapes datasets and infrastructure for future research, education, and open-science applications. Related Citations and Resources: Pease, B., Gilbert, N., & Severino, M. (2026). Eclipse Soundscapes Preliminary Findings – How Eclipses Affect Nature as determined by Sound (Recorded Webinar). Zenodo. https://doi.org/10.5281/zenodo.18613979 Gilbert, N. A., Pease, B. S., Severino, M., & Winter, H. III. (2026). Photic niche explains avian behavioral responses to solar eclipses. Ecology and Evolution, 16(2), e73090. https://doi.org/10.1002/ece3.73090 Analysis code repository: https://github.com/BrentPease1/eclipse-traits Companion Zenodo record archiving structured analysis scripts and derived outputs: https://doi.org/10.5281/zenodo.15790879[r] Public Archiving, Privacy, and Data Transparency The Eclipse Soundscapes Data Collector Role Training and Implementation Manual (2023-2024) includes a detailed explanation of how Eclipse Soundscapes audio data are publicly archived on Zenodo, how participant privacy is protected through the ES ID system, and how transparency and traceability are maintained. It also outlines the criteria for determining which recordings are included in the public archive, as well as the distinction between publicly shared archival data and datasets used for ES-led scientific analyses. Participants and data users can consult this section for full documentation of the project's open science and privacy practices. Severino, M., & Winter, H. (2026). Eclipse Soundscapes Data Collector Role Training and Implementation Manual (2023–2024). Zenodo. https://doi.org/10.5281/zenodo.18623443 Citations Individual Site Citation: APA Citation (7th edition) Winter, H., Severino, M., & Volunteer Scientist. (2026). 2024 solar eclipse soundscapes audio data [Audio dataset, ES ID# 292]. Zenodo.{Insert DOI} Collected by volunteer scientists as part of the Eclipse Soundscapes Project. This project is supported by NASA award No. 80NSSC21M0008. Eclipse Community Citation Winter, H., Severino, M., & Volunteer Scientists. 2023 and 2024 solar eclipse soundscapes audio data [Collection of audio datasets]. Eclipse Soundscapes Community, Zenodo. https://zenodo.org/communities/eclipsesoundscapes/ Collected by volunteer scientists as part of the Eclipse Soundscapes Project This project is supported by NASA award No. 80NSSC21M0008.

Fischer, Fabian Jörg · Chave, Jerome · Zanne, Amy · et al.

45 cols · 8.0 MB · csv

31 categorical · 12 numeric · 2 text

The Global Wood Density Database v.2 The Global Wood Density Database v.2 (GWDD v.2) is a collection of 109,626 taxonomically standardized wood density records and 15,093 additional bark density records. Data include measurements at different levels of aggregation (individual, species) and both georeferenced records and values from the literature. For a full description of the database, please see the corresponding manuscript. ( Fischer et al. 2026. Beyond species means - the intraspecific contribution to global wood density variation. New Phytol. https://doi.org/10.1111/nph.70860 ). It includes and supersedes the GWDD v.1 ( Zanne et al. 2009 , https://doi.org/10.5061/dryad.234 ). When using the GWDD v.2 in your work, please cite Fischer et al. 2026 as well as this repository using the corresponding DOI (10.5281/zenodo.16919509). If you would like to report an issue or suggest improvements for future updates of the GWDD, please do so on github: https://github.com/fischer-fjd/GWDD/issues Aggregated wood density data We provide pre-aggregated wood density data, with wood density estimates at species, binomial species and genus level. Wood density estimates are derived from hierarchical (random effects) models and provided both as simple species mean values ( wsg_est ) and as species mean values for trunks ( wsg_est_trunk ) and branches ( wsg_est_branch ) separately. In addition, we provide raw wood density means ( wsg_raw ), but we do not recommend using them for practical purposes due to outliers for poorly sampled species. gwddagg_v2.x_species: pre-aggregated wood density values for 17,261 species, including infraspecific epithets; comprises 16,828 taxonomically resolved species well as 433 values with uncertain taxonomic status gwddagg_v2.x_binomial: pre-aggregated wood density values for 16,905 binomial species gwddagg_v2.x_genus: pre-aggregated wood density values for 3,198 genera Raw wood density data In addition, we also provide the underlying raw wood density database. This collection contains one metadata file and raw data files in .csv format. Since special characters (e.g., in the references) can be distorted by operating systems when reading in .csv files, we also provide all data in .RData format, which can be loaded into R with the load() function. columns_gwdd_v2.x : metadata for all the columns included in the GWDD v.2 gwdd_v2.x : the GWDD v.2, including all 109,626 wood density records gwdd_v2.x_withbark : the GWDD v.2, including all 109,626 wood density records and 15,093 additional bark density records

Aalborg, Trine

7 files · 8.0 MB · csv, gzip

README - Data for "Genomic constraint and hypervariability in tetraploid potatoes" Trine Aalborg, May 2026 The data applied in the study includes phenotypic and genotypic information on the MASPOT panel (768 F1 progeny of an 18-parent diallel cross - property of Danespo A/S). The genotypic data was generated using genotyping-by-sequencing technology as described in the paper. Following genotype calling and filtration (5-60x read depth, < 50 % missing rate, > 1 % MAF), the total SNP set includes 151,164 biallelic SNPs. Coordinates of these SNPs relative to the DMv6.1 potato reference genome are provided. In addition to genotypes across the clones, the estimated GERP score of that SNP from (Wu et al., 2023) is reported. The manuscript analyses only consider markers with reliable GERP scores (MSA alignment depth > 50, and neutral score > 2), which corresponded to 97,815 of the total 151,164 biallelic SNPs. SNPeff annotations of the markers (based on the DMv6.1 reference genome) are also appended. The phenotypes were collected across 1-2 field trials, depending on the traits, and includes a minimum of two replicates per clone from a randomized block design. There are phenotypes for eight traits: dry matter content [%], yield (hkg/ha), senescence [1-9], flesh color [1-9], tubers/plant, tuber length [mm], tuber diameter [mm], and tuber size [mm^3]. Metadata includes phenotyping year and block location of the plot as well as pedigree of the diallel offspring. File descriptions: gt_MASPOT.csv - .csv file of the non-imputed genotypic data of 151,164 SNPs for the 768 F1 clones (those with GERP scores). Columns 1-3 are SNP coordinates and SNP IDs. Column names from column 4 and onwards are clone IDs. gt_MASPOT_imputed.csv - .csv file holding the imputed (random forest, missRanger algorithm) genotypic data of 151,164 SNPs for the 768 F1 clones. gt_MASPOT_recoded.csv - .csv file of the recoded, imputed genotypic data of 151,164 SNPs for the 768 F1 clones. The SNPs are recoded from original MASPOT ref/alt allele (based on AF in the MASPOT panel) to the alternative allele = the derived allele in the 100-Solanaceae panel. pt_MASPOT.csv - .csv file holding the phenotypic data (eight traits) of the 768 F1 clones (Clone_ID). The number of observations varies across traits. Also including metadata: year of phenotyping (Year), block number (Block, Line_in_block), clone parents (Mother, Father, Family). GERP_MASPOT.csv - .csv file holding the GERP scores (including alignment depth, neutral scores, and a marker annotation based on GERP score thresholds (deleterious, neutral, hypervariable, or low quality)), SNPeff annotations, and the derived allele in the 100-Solanaceae panel from (Wu et al., 2023) [MASPOT_Alt_Allele_Is_Sol_Derived_Allele - used for recoding of the genotypes] of the MASPOT SNPs with GERP scores. snps.MASPOT_F1.vcf.gz - zipped .vcf file of the GBS MASPOT genotypic data (both discrete genotype calls and allele frequencies) called to the DMv6.1 potato reference genome. Filtered to read depth 5x, MQ > 30. A total of 160,920 biallelic SNPs. Includes the 768 F1 progeny analyzed. Literature: Wu, Y., Li, D., Hu, Y., Li, H., Ramstein, G. P., Zhou, S., et al. (2023). Phylogenomic discovery of deleterious mutations facilitates hybrid potato breeding. Cell 186, 2313-2328.e15. doi: 10.1016/j.cell.2023.04.008

Yang, Qingliu

6 files · 8.0 MB · bzip2

Dataset Description This dataset contains 3D lightning location results, DALMA and FALMA waveform for two Energetic Compact Stroke (ECS) events. location results are included: HF3D_1732785151.dat - 3D lightning locations for the ECS leader A flash. HF3D_1734785454.dat - 3D lightning locations for the ECS leader B flash. The timestamp 1734785454 and 1732785151 corresponds to the occurrence time of the lightning flash in Japan Standard Time. File format and parameters The first row contains the lightning occurrence time. Column descriptions: Time (ms) - time relative to the lightning source. X, Y, Z (m) - 3D spatial coordinates relative to ground level. The origin (0, 0, 0) corresponds to latitude 36.76°N and longitude 136.76°E. FALMA and DALMA waveform ECSLeaderA_DALMA_waveform.bz2 is DALMA waveform of Leader A. ECSLeaderA_FALMA_waveform.bz2 is FALMA waveform of Leader A. ECSLeaderB_DALMA_waveform.bz2 is DALMA waveform of Leader B. ECSLeaderB_FALMA_waveform.bz2 is FALMA waveform of Leader B. This dataset allows analysis of the spatial and temporal development of these two ECS flashes.

Kovaliov, Michael

1 files · 100 MB · parquet

Omukuti, Rodney

1 files · 8.0 MB · vcf

Tsui, Claire · Briga, Michael · Komdeur, Jan · et al.

56 files · 8.9 MB · csvdeclared

Data and code for analysis in manuscript titled "Asynchrony of ageing among traits in a wild bird population" Dataframes ending with"_28_5.csv" and "survival_model.csv" are used in scripts model1-13, of which the output is plotted using "new model outputs.R" Code for Figures 1 and 2 are in script "new model outputs.R" asymmetry bivar ver3.R runs the bivariate models used to estimate the degree of synchrony of ageing. scripts starting with "aic.." are used in the analysis for age by lifespan interaction

inquantio

3 files · 2.0 MB · jpeg, pdfdeclared

A study published on bioRxiv demonstrates the first hybrid quantum computing framework combining classical Hamming distance filtering with the Grover quantum search algorithm to overcome bottlenecks in massive genomic data analysis. Utilizing the IBM Qiskit 27-qubit simulator, researchers rapidly and flawlessly identified a 50-nucleotide target sequence of a Cas9-like nuclease within a Brazilian biome metagenome database, even under conditions allowing up to a 30% mismatch. The study lays a revolutionary foundation for synthetic genome design by completing simulations that precisely insert a "BioBloQu" (quantum biological block)—composed of a promoter, an RBS, an enzyme, and a terminator—into the explored scar regions of the minimal genome M. mycoides JCVI-Syn3B. [Quantum Biology Society] Modern life sciences are pouring out genomic sequencing data at an exponential rate. However, due to the immense complexity of biological data, existing classical computing methods are facing severe computational bottlenecks in analyzing and manipulating it. To break through these limitations, a disruptive study recently published on the preprint repository bioRxiv, titled "Genetic Engineering with Quantum Circuits: creating codes and studying BioBloQu genetic elements," has brought quantum computers to the forefront of genetic engineering. A joint research team led by Professor Elibio Rech from the Brazilian Agricultural Research Corporation (Embrapa) Genetic Resources and Biotechnology and the Federal University of Rio Grande do Sul (UFRGS) presented this innovative research. ■ Scanning Massive Genomic Databases with Qubits Using the core quantum mechanical principles of superposition and entanglement as the foundation for information processing, the research team developed a hybrid quantum framework that combines classical Hamming distance filtering with the Grover quantum search algorithm. Powered by IBM's Qiskit 27-qubit simulator, this algorithm was used to search for a 50-nucleotide target sequence of a Cas9-like nuclease within a Brazilian biome metagenome database. As a result, the team successfully and swiftly identified the massive genetic data through amplitude amplification, filtering out the sequence perfectly even under conditions allowing up to a 30% mismatch rate. This proves that vast amounts of genetic data, which are unmanageable for classical computers, can be analyzed in a flash through quantum parallel processing. ■ The Era of Synthetic Genome Design Opened by BioBloQu Furthermore, the researchers successfully completed a quantum circuit simulation that accurately inserts a synthetic genetic construct called "BioBloQu" (quantum biological block) into the identified target regions. In the genome of M. mycoides JCVI-Syn3B, an artificially synthesized minimal genome model, the quantum algorithm first identified two 20-nucleotide "scar" regions—which are traces of gene editing. Then, it precisely integrated a tandem genetic block (BioBloQu) composed of a promoter, a ribosome binding site (RBS), an enzyme sequence, and a terminator into that location. This innovative approach goes beyond simply cutting and pasting existing genes physicochemically; it opens up the possibility of designing and assembling novel synthetic genomes from the ground up under the control of quantum algorithms equipped with overwhelming computational power. By directly applying the computational power of quantum mechanics to biotechnology, this research is expected to serve as the starting point for a massive revolution in next-generation quantum-bio data manipulation, customized gene therapy, and synthetic biology. #QuantumComputing #GeneticRecombination #BioBloQu #QuantumAlgorithm #GroverAlgorithm #Metagenome #SyntheticBiology #GenomeDesign #QuantumBiology #KoreanQuantumBiologySociety https://www.biorxiv.org/content/10.1101/2025.05.02.651535v2

inquantio

3 files · 1.9 MB · jpeg, pdfdeclared

A study published on bioRxiv proposes quantum and classical graph neural networks that address the issues of parameter compression and temporal changes in protein-ligand geometry—factors previously overlooked by existing machine learning (ML) models for predicting drug dissociation kinetics (k_off). Demonstrated a significant improvement in predictive accuracy through temporal integration by introducing a 2-timestep GCN+GRU model that actively learns structural changes before and after a short molecular dynamics simulation. Proved that quantum structures act as a powerful lever for the advancement of kinetic ML models in drug design by using variational quantum circuits to compress the model head, eliminating 66% of parameters while perfectly maintaining expressive power. [Quantum Biology Society] In the field of drug design, dissociation kinetics ($k_{off}$)—the duration a drug remains bound to its target protein—is increasingly recognized as a much more critical indicator of in vivo efficacy than simple binding affinity. However, existing machine learning (ML) models have largely overlooked the dynamic, temporal changes in protein-ligand geometric structures and the fundamental computational requirement to represent complex spatial interactions with fewer parameters. A study recently published on the preprint repository bioRxiv, titled "Quantum and Classical Graph Convolutional Neural Networks for Protein Ligand Dissociation Constant Prediction," opens new horizons by extending state-of-the-art Spatial Graph Neural Networks (Spatial GNNs) in two innovative directions to break through these classical limitations. A research team at the University of Cincinnati—comprising Azamat Salamatov, Jun Bai, Gowtham Atluri, and Chaowen Guan—led this disruptive research. ■ Combining 2-Timestep Learning and Variational Quantum Circuits The first innovation introduced by the research team is the integration of temporal flow. By adopting a 2-timestep GCN+GRU model that actively learns structural changes before and after a short molecular dynamics simulation, they have elevated the accuracy of kinetic predictions to the next level. The second key innovation is groundbreaking parameter optimization utilizing quantum technology. By compressing the model head using variational quantum circuits, the researchers successfully eliminated 66% of unnecessary parameters while completely preserving the complex expressive power of the existing fully classical model. Results from the PDBbind-koff-2020 benchmark test revealed the remarkable achievement of this quantum compressed model: it perfectly matched the predictive accuracy of the heavy, fully classical model while exponentially reducing the model size. This study clearly proves that temporal kinetics and quantum neural network structures serve as a powerful, disruptive lever to break the massive computational bottlenecks that occur in future drug candidate screening processes, propelling kinetic ML models a significant leap forward. #DrugScreening #DissociationKinetics #QuantumMachineLearning #GraphNeuralNetworks #ProteinLigand #QuantumComputing #DrugDevelopment #MolecularDynamics #ArtificialIntelligence #KoreanQuantumBiologySociety https://www.biorxiv.org/content/10.1101/2025.11.20.689635v2.full

inquantio

3 files · 1.6 MB · jpeg, pdfdeclared

Published in the international journal PLOS Computational Biology, this study models for the first time the decrease in adult hippocampal neurogenesis in a hypomagnetic field using the 'Radical Pair Mechanism'. It establishes a theoretical mathematical model that explains the cognitive decline and reduction in reactive oxygen species (ROS) levels observed in previous mouse experiments through changes in the singlet-triplet spin dynamics of radical pairs consisting of flavin and superoxide. It demonstrates that the formation of neural networks and metabolic processes in the mammalian brain are not merely simple macroscopic biochemical reactions, but are directly governed by a microscopic quantum phenomenon: the spin dynamics of ROS electrons that depend on external magnetic fields. [Korean Society of Quantum Biology, Reporter Hak-Jin Kim] Could the radical pair mechanism—the principle by which birds sense the Earth's magnetic field to navigate—also be deeply involved in mammalian brain development and cognitive function? Recently, a theoretical study offering a clear physical answer to this remarkable quantum biological question has been published. The paper, titled "Radical pairs may explain reactive oxygen species-mediated effects of hypomagnetic field on neurogenesis," published in the international journal PLOS Computational Biology, uncovers that neurogenesis is intricately linked to a purely quantum mechanical process. The research team, led by Rishabh Rishabh and Professor Christoph Simon from the University of Calgary in Canada, spearheaded this innovative study. ■ Hypomagnetic Field Environment and the Decrease in ROS Levels According to recently published biological experimental results, mice exposed to a hypomagnetic field environment—where the geomagnetic field is largely shielded—showed significantly attenuated neurogenesis in the hippocampal region of the adult brain, resulting in a distinct decline in cognitive abilities. Surprisingly, the fundamental cause of this cognitive decline and suppressed neurogenesis was revealed to be a decrease in intracellular reactive oxygen species (ROS) levels. The University of Calgary research team mathematically analyzed the cause of this phenomenon through the lens of quantum mechanics. ■ Electron Spin Dynamics Governing Brain Development The research team constructed a radical pair model of 'flavin' and 'superoxide', which are responsible for intracellular ROS production, and simulated their spin dynamics. As a result, they found that when the external magnetic field decreases from the geomagnetic field level (approx. 50 μT) to a hypomagnetic field (approx. 0 μT), the yield of the singlet-triplet interconversion changes dramatically due to alterations in the internal hyperfine interactions of the radical pair. The mathematically calculated extent of the decrease in product yield was consistent with the reduction rate of ROS observed in actual experiments. In other words, the sophisticated formation of neural networks and metabolic processes in mammals are not simply macroscopic chemical reactions, but are directly governed by an extremely microscopic quantum phenomenon: the electron spin dynamics occurring within molecules. This research is a monumental achievement that mathematically proves the causal entanglement between the macroscopic geomagnetic environment of the Earth and the quantum spin states within living organisms. It is expected to provide a revolutionary paradigm for developing technologies that utilize magnetic fields to treat degenerative brain diseases and promote neurogenesis in the future. #QuantumBiology #RadicalPairMechanism #Magnetoreception #Neurogenesis #ReactiveOxygenSpecies #HypomagneticField #SpinDynamics #QuantumMechanics #BrainScience #KoreanSocietyOfQuantumBiology https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1010198

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A study published in the international journal PCCP (Physical Chemistry Chemical Physics) models the proton transfer pathways and quantum tunneling rates during Watson-Crick tautomerism in DNA A-T and G-C base pairs, utilizing Density Functional Theory (DFT) and a machine learning-based Nudged Elastic Band (ML-NEB) algorithm. The research physically demonstrates that proton transfer in A-T base pairs is highly unstable due to an extremely low reverse-reaction barrier, making the occurrence of mutations during the replication process highly improbable. In G-C base pairs, a high quantum tunneling correction value was observed, providing the first physical proof that the mutant form (G-C) possesses a biological lifespan sufficient to be misread as an error by the human DNA replication machinery (replisome). [Korean Society of Quantum Biology, Reporter Hak-Jin Kim] The phenomenon wherein protons shift positions within the hydrogen bonds of DNA—the carrier of an organism's genetic information—can induce transient but lethal point mutations. Known as tautomerism, this process has long been identified as a potential root cause of genetic variation and oncogenesis. A recent study published in Physical Chemistry Chemical Physics (PCCP) has combined pure quantum mechanical modeling (DFT) with machine learning techniques to precisely calculate the energy barriers of double proton transfer occurring within A-T and G-C base pairs. This significant physicochemical research was conducted by L. Slocombe, J. S. Al-Khalili, and M. Sacchi of the University of Surrey, UK. ■ Instantly Collapsing A-T Tautomers vs. Surviving G-C Tautomers The research team analyzed the energy landscape as the hydrogen bond structure shifts from the standard (amino-keto) to the mutant (imino-enol) form, using Density Functional Theory (DFT) and a machine learning-based Nudged Elastic Band (ML-NEB) algorithm. The results revealed that in A-T base pairs, although a quantum tunneling effect transitioning toward the mutant A*-T* state was observed, the reverse-reaction barrier was virtually nonexistent. Consequently, the state could not be maintained and immediately collapsed back into its original standard form. The situation was different for G-C base pairs. Beyond the classical reaction where protons cross the barrier using only thermal energy at room temperature, it was confirmed that wave-like movement via quantum tunneling contributes decisively to the formation of mutant populations. The team mathematically proved that the G-C mutant (G*-C*), which showed a significantly high tunneling correction value, possesses a lifespan long enough to reach the human replisome, suggesting a high probability of solidifying into a permanent point mutation. ■ Genetic Stability Governed by Physical Laws This study is a landmark achievement, demonstrating that complex DNA mutations occurring during the most critical replication processes of life are not merely the result of random thermal fluctuations, but are substantially controlled and shaped by the microscopic physical laws of quantum tunneling dynamics. By providing objective data on how the wave-like nature of protons physically threatens the fidelity of genetic information replication, this study underscores the importance of a quantum biological approach in future research regarding DNA damage and mutation-related diseases. #DNAPointMutation #ProtonTransfer #QuantumTunneling #WatsonCrickTautomerism #BasePair #QuantumBiology #Biophysics #GeneticMutation #MolecularDynamics #KoreanSocietyOfQuantumBiology https://pubs.rsc.org/en/content/articlehtml/2021/cp/d0cp05781a

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A study published on arXiv provides a structured narrative evidence map of the three complementary directions where quantum science and biology intersect: 'quantum in biology', 'quantum for biology', and 'biology for quantum'. It highlights hydrogen tunneling in enzymes and the radical-pair mechanism for magnetoreception as representative cases of quantum in biology. For quantum for biology, it analyzes how quantum sensing and imaging tools can improve biological inference. It also illuminates biology for quantum, which utilizes biomolecular self-assembly to enhance the performance of quantum devices, and presents a comprehensive benchmark to compare the current evidence and alternatives in each area. [Korean Society of Quantum Biology, Reporter Hak-Jin Kim] As we enter the 21st century, the convergence of quantum physics and the life sciences is moving beyond mere curiosity to establish itself as a substantial scientific paradigm. A recent paper published on the preprint repository arXiv, titled "Quantum in Biology, Quantum for Biology, and Biology for Quantum: Mapping the Evidence and the Road Ahead," clearly defines the three core areas where these two disciplines intersect. It provides a first-of-its-kind structured narrative evidence map that compiles the technological claims and experimental evidence of each field. A multinational collaborative research team led by Professor Travis J. A. Craddock of the University of Waterloo in Canada and Professor Francesco Petruccione of Stellenbosch University in South Africa published this extensive review. ■ Quantum in Nature and Quantum Tools Illuminating Biology The first pillar presented in this paper, 'Quantum in biology', deals with instances where quantum mechanics directly intervenes in the natural biological phenomena of living organisms. The most scientifically mature evidence highlighted includes the quantum tunneling of hydrogen in enzyme catalysis and the radical-pair spin chemistry mechanism that enables magnetoreception in birds. The second pillar, 'Quantum for biology', explores the application of cutting-edge quantum tools to the life sciences. The core question analyzed in this area is whether quantum technologies—such as quantum computing, quantum sensing, and quantum imaging—can provide significantly more precise biological inference and resolution beyond existing classical baselines, even under realistic biological constraints. ■ Living Organisms as the Foundation for Quantum Technology The final third pillar, 'Biology for quantum', is an innovative approach that utilizes biological systems in reverse to develop quantum technologies. The paper evaluates that the strongest claims in this field arise when the sophisticated structure or self-assembly capabilities unique to biomolecules are used to measurably improve the fabrication, integration, and robustness of artificial quantum devices. This monumental review paper holds great significance as it presents a macroscopic roadmap for the emerging interdisciplinary field of quantum biology. It establishes a powerful benchmark that allows for the at-a-glance comparison and verification of the current evidence levels and competitive alternative models in each specific subfield. #QuantumBiology #QuantumScience #LifeScience #InterdisciplinaryConvergence #EvidenceMap #QuantumSensing #QuantumLifeScience #QuantumTools #FutureScience #KoreanSocietyOfQuantumBiology https://arxiv.org/abs/2605.00205

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Published in the journal Frontiers in Photonics, this study designs an aptamer-based platform to detect the clinically relevant dengue NS1 protein, completely reinterpreting it from the perspective of a quantum-biological interface. Moving beyond classical approaches, the research demonstrates that electrochemical capacitance systems can be treated based on the quantum characteristics of electron transport, confirming that biomolecular interactions directly modulate quantum parameters such as the density of states (DOS) of the interface. By integrating quantum-scale concepts into bioelectrochemical sensing, the analytical capability is dramatically improved, achieving high sensitivity and a broad linear range of 0.01 to 1,000 ng/mL even in complex biological matrices like commercial human serum. [Reporter Hak-Jin Kim, Korean Society of Quantum Biology] Electrochemical biosensors are promising tools for clinical diagnostics, but technical challenges have remained in maximizing stability and sensitivity for target proteins within extremely complex biological matrices like human serum. Recently, an open-access study published in the international journal Frontiers in Photonics titled "Quantum-biological interface in biosensor design: detecting proteins with electrochemical aptasensor" , presented a groundbreaking paradigm to overcome these challenges by directly introducing quantum mechanics—the physical laws of the microscopic world—into sensor design. A research team led by Leonardo Peres Chiaradia Costa and Professor Marcelo Mulato from the University of São Paulo, Brazil, spearheaded this disruptive study. ■ Beyond Classical Accumulation: Quantum Capacitance The researchers constructed a self-assembled monolayer (SAM) composed of single-stranded DNA aptamers and a spacer molecule, 6-mercapto-1-hexanol (MCH), on a gold (Au) electrode surface, and measured the binding of the dengue NS1 protein using non-Faradaic electrochemical capacitance spectroscopy (ECS). The most prominent innovation lies in the shift in how this system is interpreted. While existing models described the sensor using the classical capacitance of an electric double layer where charge accumulates geometrically, this study reinterpreted the interaction between the molecular layer and the electrode as an intrinsic electron transport characteristic known as quantum capacitance ($C_q$). This means that the interaction between the protein molecule and the aptamer goes beyond simple physicochemical docking; it directly modulates the density of electronic states (DOS) of the sensor interface and the discrete energy levels of individual molecules, thereby controlling the quantum tunneling and transfer mechanisms of electrons. ■ Overwhelming Analytical Performance Driven by Quantum Control Based on this quantum-biological interface model, the research team precisely optimized the ratio of aptamer to MCH molecules on the sensor surface to 1:50. The optimized platform successfully maintained a broad linear response ranging from 0.01 ng/mL to 1,000 ng/mL, not only in simple laboratory buffers (PBS) but also in commercial human serum entangled with complex ions and proteins. In particular, this aptasensor recorded an outstanding limit of detection (LoD) of 25.8 ng/mL in a human serum environment, clearly demonstrating how an understanding of quantum characteristics can serve as powerful leverage to break through existing biochemical limitations and design highly sensitive diagnostic devices. This study will serve as a crucial starting point for completely restructuring future protein detection and disease diagnosis technologies from the perspective of microscopic quantum dynamics rather than macroscopic chemical reactions. #QuantumBiology #Biosensor #Aptasensor #ProteinDetection #ElectrochemicalSensor #QuantumCapacitance #UltrasensitiveDiagnostics #Nanotechnology #Biophysics #KoreanSocietyOfQuantumBiology https://www.frontiersin.org/journals/photonics/articles/10.3389/fphot.2026.1714572/full

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Posted on the international preprint server bioRxiv, the study provides the first direct demonstration—using multi-electrode array (MEA) electrophysiology—that the two stable lithium isotopes 6Li and 7Li exert giant and opposite effects on synaptic transmission in the rat hippocampus. 6Li rapidly strengthened synaptic transmission (amplitude +32%), whereas 7Li produced a slower but larger suppression (amplitude −58%). The difference in effect size between the two isotopes overwhelmingly exceeded the thresholds for both statistical and practical significance (Cohen's d > 300). The phenomenon is interpreted as arising from a difference in nuclear spin (7Li, spin 3/2; 6Li, spin 1) rather than mass, offering the first direct neurophysiological evidence in support of the brain's quantum cognition hypothesis. [Quantum Biology Society] Since Cade discovered lithium's dramatic neurological effects in the 1940s, the element has been studied intensively for more than seventy years, and since the mid-1970s it has served as a frontline medication for bipolar disorder. Its potential benefits are also being explored in other neurological disorders, including Alzheimer's disease. Yet despite this long clinical history and an enormous body of research, the precise mechanism by which lithium acts in the brain remains incompletely understood. It has long been known that the lithium salts prescribed in the clinic are a mixture of two stable isotopes—6Li (natural abundance 7.49%) and 7Li (92.51%)—but the question of what unique neurobiological effects each isotope produces has only recently begun to receive serious attention. A study titled "Giant and Opposite Lithium Isotope Effects on Rat Hippocampus Synaptic Activity Revealed by Multi-Electrode Array Electrophysiology" was recently posted on the international preprint server bioRxiv. Carried out by a collaborative team at the University of Waterloo in Canada spanning physics, nanotechnology, and public health—including Khadijeh Esmaeilpour, Irina Bukhteeva, Michel J.P. Gingras, Zoya Leonenko, and John G. Mielke—the work was supported by Canada's New Frontiers in Research Fund – Exploration (NFRF-E) program and the Quantum Brain Network led by Matthew Fisher (UCSB). By measuring in real time, in living brain slices, how the two lithium isotopes affect synaptic activity, the researchers demonstrated for the first time that 6Li and 7Li produce giant effects in diametrically opposite directions. ■ 6Li and 7Li: Giant and Opposite Effects on Synaptic Transmission The team prepared 350-micrometer-thick slices from the hippocampus of eight-week-old male rats, positioned the CA1 region over a 64-point multi-electrode array (MEA), and stimulated the Schaffer collateral pathway to record the evoked field excitatory postsynaptic potentials (fEPSPs). After recording a 20-minute baseline, they perfused the slices with a 20 mM lithium chloride solution for 20 minutes and then washed them out with artificial cerebrospinal fluid for a further 20 minutes. The results were dramatic. Perfusion with natural-abundance lithium (n-LiCl) reduced the fEPSP amplitude by 37%, and 7Li alone (7LiCl) produced an even stronger 58% decrease. In stark contrast, 6Li alone (6LiCl) did the opposite, driving a 32% increase in amplitude—the two isotopes pushing synaptic transmission in opposite directions. The difference between them overwhelmingly surpassed the thresholds for both statistical and practical significance (amplitude: t(8) = 481.9, p < .0001, Cohen's d = 305.7), an effect size rarely seen in neurophysiological experiments. The two isotopes also differed markedly in the speed of their response. The reaction to 6Li was very fast, reaching saturation within three minutes, whereas the responses to n-Li and 7Li were much slower, taking about ten minutes to reach their maximal change. The difference persisted even after washout: slices treated with 7Li remained 9% below baseline, while those treated with 6Li stayed 10% above it. Moreover, the chloride (LiCl) and carbonate (Li2CO3) salts yielded the same direction and a similar magnitude of effect, strongly confirming the reproducibility of the findings. ■ Why Nuclear Spin? A Quantum Biology Perspective 6Li and 7Li are chemically identical and differ only in the mass and spin of their nuclei: 7Li is a spin-3/2 nucleus and 6Li a spin-1 nucleus. The researchers argued that the very fast response to 6Li, together with the opposite effects of the two isotopes, points to a difference in nuclear spin—rather than mass-dependent factors such as slight differences in diffusion constants—as the origin of the phenomenon, since mass differences alone cannot readily account for a giant effect that reverses direction. This interpretation aligns with theoretical proposals from the expanding field of quantum biology. Matthew Fisher has advanced a quantum cognition hypothesis in which the brain could process quantum information through the nuclear spins of phosphorus atoms held within calcium phosphate clusters known as Posner molecules. Zadeh-Haghighi and Simon have separately proposed that an entangled radical-pair mechanism could explain lithium's effects on hyperactivity. Differences between the lithium isotopes have, in fact, already been observed experimentally in mitochondrial calcium cycling and in the in vitro formation of calcium phosphate clusters. The authors raised the possibility that the giant differences in synaptic activity observed here may stem from the two isotopes acting differently on the mitochondrial processes that govern synaptic activity. At the same time, they noted that a precise theoretical account of their observations is not yet available. ■ Distinct Roles Emerge in Short- and Long-Term Synaptic Plasticity The team also compared the two isotopes in synaptic plasticity, widely regarded as the basis of memory formation. In paired-pulse facilitation (PPF), a measure of short-term plasticity on the order of milliseconds, the two groups were nearly identical before lithium perfusion (127% and 130%, respectively) but diverged sharply afterward: 6Li markedly enhanced PPF to 169%, whereas 7Li suppressed it to 91%. The opposite-direction effects seen in synaptic transmission were thus reproduced in short-term plasticity as well. Long-term potentiation (LTP), which unfolds over tens of minutes, showed a somewhat different pattern. In the induction phase immediately following high-frequency stimulation (HFS), both isotopes produced potentiation, but of different magnitudes: 7Li drove a large 60% increase, while 6Li produced a much smaller 15% increase (p = .0003). In the later maintenance phase, by contrast, there was no significant difference between the two isotopes. Because both PPF and the induction phase of LTP are known to arise from rapid changes in presynaptic calcium (Ca2+) levels, the researchers focused on the possibility that the lithium isotopes act differently, primarily on presynaptic function. ■ The Significance and Outlook of the Study The central significance of this work lies in its directness. Previous studies of lithium isotope effects had remained either theoretical—such as the Posner molecule proposal—or confined to the cellular and biochemical level, as with mitochondrial calcium transport. This paper, by contrast, is the first empirical study to measure synaptic transmission in living brain slices in real time using electrophysiology, largely sidestepping the interpretive difficulties that have beset earlier behavioral experiments. The authors concluded that their findings could help clarify the presynaptic mechanisms underlying lithium's action as a mood stabilizer and, more broadly, pose new questions for quantum biology about how mass and/or nuclear spin might give rise to such effects. Above all, the study suggests that 6Li and 7Li may not be merely two forms of the same drug but pharmacologically distinct agents in their own right—a prospect that opens the door to precision therapeutic strategies that selectively harness a particular isotope. In doing so, the work lays a foundation for future research into quantum phenomena in neuronal activity. #QuantumBiology #Lithium #LithiumIsotopes #QuantumCognition #NuclearSpin #Neuroscience #Synapse #BipolarDisorder #Hippocampus #PosnerMolecule https://www.biorxiv.org/content/10.1101/2025.08.23.671929v1

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Published in the American Chemical Society journal ACS Omega, the study represents hemoglobin with the FePIm (iron–porphyrin–imidazole) model and uses spin-polarized density functional theory (DFT) to track, at the atomic level, how the spin state changes over the course of oxygen binding. It shows that O2 binding proceeds as a multi-step spin crossing running from the triplet, through the quintet, to the singlet. This spin crossing dramatically lowers the binding activation barrier from 0.82 eV to 0.02 eV, accelerating the reaction. It identifies the position of the iron (Fe) atom relative to the porphyrin plane as the key indicator governing oxygen affinity, and it raises the possibility of applying the system as an oxygen-reduction catalyst in fuel cells. [Quantum Biology Society] The oxygen molecule (O2) in the air we inhale is, in its ground state, a triplet carrying two unpaired electrons. The oxygen bound to hemoglobin—oxyhemoglobin—is, by contrast, a singlet with no unpaired electrons, a fact already established in 1936 when Linus Pauling observed the diamagnetism of oxyhemoglobin. Yet a fundamental principle of quantum mechanics poses a puzzle here. In a chemical reaction, a transition in which the total spin of the reactants and products differs is forbidden by the spin selection rule (spin-forbidden) and should therefore proceed only very slowly. The direct conversion of triplet oxygen into a singlet complex is exactly such a case. How, then, does our body carry out this forbidden reaction so quickly and reversibly with every breath? A 2018 study published in the ACS journal ACS Omega, "Spin-Dependent O2 Binding to Hemoglobin," answers this question through quantum-mechanical calculations. Daiichi Kurokawa, Jessiel Siaron Gueriba, and Wilson Agerico Diño of Osaka University in Japan simplified hemoglobin's active site to the FePIm model (iron Fe, porphyrin P, imidazole Im) and used spin-polarized DFT to trace, step by step, how the system's spin state changes along the oxygen-binding pathway. They showed that O2 binding is a spin-crossing process in which the system switches successively between several spin states—and that this very process is the key that unlocks the forbidden reaction. ■ As Oxygen Approaches, the Spin Shifts Step by Step The researchers narrowed the distance (R) between the iron atom and the oxygen molecule from 7.21 angstroms (Å) in the deoxy state down to 1.84 Å in the oxy state, calculating the system's total magnetization (spin multiplicity) at each point. In the deoxyhemoglobin state, with O2 not yet bound, the entire system (FePIm plus the separated O2 molecule) was a triplet (multiplicity 3), and the iron atom protruded 0.18 Å out of the porphyrin plane. As oxygen drew closer, the spin state did not change all at once but shifted in stages. At a point about 4 Å from the iron, the electrons in oxygen's antibonding (π*) orbital flipped their spin, raising the system to a septet (multiplicity 7)—a state nearly degenerate in energy with the triplet. Then, around R = 2.4 Å, it changed to a quintet (multiplicity 5), a shift accompanied by a lengthening of the bond between the two oxygen atoms within the O2 molecule. Finally, in the oxyhemoglobin state at R = 1.84 Å, oxygen formed a sigma (σ) bond between the iron's dz² orbital and its own π* orbital and stabilized as a singlet (multiplicity 1). In short, the system's total spin multiplicity traced a path from the triplet (degenerate with the septet), through the quintet, to the singlet. ■ The Key That Unlocks the Forbidden Reaction: Spin Crossing Why this multi-step spin transition matters becomes clear from the activation-barrier analysis. When the researchers fixed the system's spin state as a septet, the activation barrier for oxygen binding was a substantial 0.82 eV. But when the system was allowed to cross from the septet to the singlet—spin crossing—the binding barrier fell sharply to 0.02 eV. A single spin crossing lowered the barrier roughly fortyfold. The spin transition, in other words, is not an obstacle blocking oxygen binding but rather the passage that makes the forbidden reaction possible. Instead of directly connecting two states of different total spin (triplet oxygen and the singlet complex), the system detours through intermediate high-spin states, bypassing the spin selection rule and finding a low-energy path. For reference, a minimum-energy-path calculation with the atomic positions fully optimized (CINEB) yielded a binding barrier of 0.38 eV and an oxygen-release barrier of 0.92 eV. The researchers concluded that this spin crossing is the key factor governing the activation barrier. ■ The Switch for Oxygen Affinity: Iron Out of the Plane The researchers identified one more important indicator: how far the iron atom sits out of the porphyrin plane (d). In the oxygen-free deoxy state the iron protruded 0.18 Å out of the plane, but in the oxygen-bound oxy state it settled almost within the plane, at 0.01 Å. This agrees well with the crystal structure determined by experiment. Behind this movement lies an interaction between orbitals. In the deoxy state, the iron's dxy orbital interacts antibondingly with the nitrogen atoms of the porphyrin, pushing the iron out of the plane. But as oxygen binds and the electron in the dxy orbital flips its spin and moves to the dyz orbital, the dxy orbital empties and this antibonding interaction vanishes. As a result, the iron is drawn back into the porphyrin plane. The researchers concluded that, together with the iron–oxygen distance (R), this iron out-of-plane distance (d) is one of the two key reaction coordinates controlling oxygen affinity. ■ Significance and Outlook The greatest significance of this study lies in its concrete explanation, in the language of quantum mechanics, of breathing—the most basic activity of life. Life performs the oxygen-binding reaction, forbidden under the spin selection rule, quickly and reversibly by way of a spin crossing that switches successively through several spin states. In a sense, we harness a quantum-mechanical spin transition with every breath. The work also points to potential applications. The lengthening of the bond between the two oxygen atoms during an intermediate stage of binding suggests that the FePIm system could function as a catalyst that splits the oxygen molecule. The researchers noted the possibility of using the system as a cathode-electrode catalyst in polymer electrolyte fuel cells (PEFCs), where the oxygen reduction reaction takes place, while also pointing out that the challenge of overcoming the high activation barrier accompanying the reaction remains. By confronting head-on how life resolves the forbidden reaction of triplet oxygen binding to the heme iron, this study offers a solid starting point for further discussion from the standpoint of the quantum mechanics of respiration. #QuantumBiology #Hemoglobin #Respiration #OxygenBinding #SpinCrossing #QuantumMechanics #Porphyrin #DFT #FuelCellCatalyst #TripletOxygen https://pubs.acs.org/doi/10.1021/acsomega.8b00879

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Published in the Elsevier journal Plant Stress, this review synthesizes the field by extending the scope of plant quantum biology beyond the traditional territory of photosynthesis and magnetosensing to enzyme catalysis and stress responses (light, oxidative, temperature, and biotic stress). It offers a broad survey of how four quantum phenomena—quantum coherence, entanglement, the radical pair mechanism, and quantum tunneling—may be involved in light-harvesting efficiency, magnetic-field sensing, and enzyme reaction rates. It projects that understanding and controlling these quantum effects could be harnessed for sustainable agriculture, such as developing stress-tolerant crops, while also pointing to the challenges posed by biological complexity and experimental limitations. [Quantum Biology Society] Plant biology has traditionally explained stress responses in the language of classical physics and biochemistry. But as evidence accumulates that quantum phenomena once thought to be the exclusive province of the microscopic world are in fact involved in the activities of life, quantum biology—which explores what role quantum mechanics (QM) plays in core functions such as photosynthesis, light perception, and stress responses—is emerging as a new field. Concepts like superposition, entanglement, tunneling, and coherence are its central tools. A review recently published in the Elsevier journal Plant Stress, "Plant quantum biology: The quantum dimension of plant responses to stress," surveys this field broadly. Massimo E. Maffei of the University of Turin in Italy extends the scope of plant quantum biology—until now discussed largely in terms of photosynthesis and magnetosensing—to enzyme catalysis, stress responses, and, further still, agricultural applications. At the same time, the author is careful to note that the field is still young and that established evidence and theoretical hypotheses remain intermingled, drawing a cautious map of the terrain. ■ Photosynthesis: Quantum Coherence That Captures Light The area where the firmest evidence has accumulated in plant quantum biology is photosynthesis. Photosynthetic organisms convert the photons they absorb into chemical energy with almost no loss, achieving a quantum efficiency approaching 100%. The energy of a light-harvesting complex that has absorbed light is delivered to the reaction center within extraordinarily short times—femtoseconds to picoseconds—and this efficiency and speed are difficult to explain by classical physics alone. The phenomenon drawing attention here is quantum coherence. The excitation energy (exciton) generated by photon absorption is not trapped on a single pigment molecule but exists as a wave-like superposition spread across several pigments, so that it can explore multiple routes to the reaction center simultaneously. In the FMO complex of green sulfur bacteria, long-lived coherence persisting even at physiological temperatures has been observed by two-dimensional electronic spectroscopy (2DES), and the protein scaffold is thought to play a role in shielding this coherence from external disturbance. Quantum entanglement between pigments has also been proposed as a way to coordinate exciton movement and aid energy transfer, but direct evidence in photosynthetic systems is not yet as solid as that for coherence. Further, active debate continues over whether this coherence plays a functional role in genuinely improving energy-transfer efficiency or is merely an incidental byproduct of the structure, and over whether it is electronic coherence or vibronic (vibrational–electronic) coherence. On this point, the author presents both supportive and critical views in balance. ■ Magnetosensing: Radical Pairs That Read the Earth's Magnetic Field Plants respond even to fields as weak as the Earth's geomagnetic field, with effects on growth, development, circadian rhythms, and even the direction in which roots grow. The leading framework for explaining this magnetosensitivity is the radical pair mechanism (RPM). The central stage is cryptochrome, a blue-light photoreceptor. When the flavin (FAD) cofactor inside cryptochrome absorbs light and becomes reduced, it forms a radical pair with a neighboring tryptophan (a FAD radical and a tryptophan radical); the rate at which the spins of this radical pair oscillate between singlet and triplet states governs the outcome of the reaction and triggers downstream signaling. How can a magnetic field far weaker than thermal energy influence such a process? The answer lies in the fact that the interconversion between singlet and triplet is governed by electron spin, a purely quantum-mechanical property. Because of this, even a field as weak as the geomagnetic field can, through spin dynamics, alter the ratio of a chemical reaction's products. The author also discusses iron–sulfur (Fe–S) clusters as a potential magnetic-sensor candidate, while noting that direct experimental evidence supporting this in plants is still lacking. ■ Enzyme Catalysis: Quantum Tunneling Through the Barrier The third stage is the enzyme. In classical mechanics, a particle needs sufficient kinetic energy to surmount an energy barrier, but quantum tunneling allows a particle to pass through the barrier to the other side. Especially in reactions involving light particles such as hydrogen atoms, protons, or electrons, tunneling can substantially increase reaction rates. The clearest fingerprint of tunneling is the isotope effect. Because heavier isotopes tunnel less efficiently, reactions involving tunneling exhibit very large isotope effects, and their temperature dependence deviates from classical Arrhenius behavior. Enzymes are thought to raise the probability of tunneling by precisely arranging substrate and catalytic residues at the active site to lower and narrow the reaction's energy barrier. The author introduces attempts to boost, from a quantum standpoint, the efficiency of agriculturally important enzymes such as the carbon-fixation enzyme RuBisCO and nitrogenase, while making clear that such discussions confined to plants remain largely at the computational and theoretical level. ■ Stress Responses: The New Horizon This Review Opens The most original contribution of this paper is the way it connects the quantum phenomena above to plant stress responses. The author examines, in turn, the possibility of quantum effects intervening in four categories: light, oxidative, temperature, and biotic stress. For light stress, the key mechanisms are non-photochemical quenching (NPQ) and the xanthophyll cycle, which dissipate excess light energy as heat to prevent photodamage; here it is proposed that quantum coherence could help rapidly steer excess energy toward quenching sites, reducing the production of reactive oxygen species. For oxidative stress, given that scavenging reactive oxygen species (ROS) is a radical reaction involving unpaired electrons, the possibility is raised that the spin correlations of radical pairs could regulate the pathways and signaling of scavenging reactions. For temperature stress, the author offers the conjecture that quantum effects may be involved in protein folding and in the action of heat shock proteins and chaperones; for biotic stress, the hypothesis that tunneling could speed up the reactions of enzymes synthesizing defensive volatile organic compounds (VOCs) or phytoalexins. The author repeatedly emphasizes, however, that many of these links to stress are not yet established facts but promising hypotheses. Indeed, in the paper's summary schematic, the hypothetical connections to quantum effects are marked separately. ■ The Road to Agriculture, and the Challenges That Remain The author's interest in this field lies in its application potential. Possibilities raised include using magnetic-field treatments to regulate seed germination and growth; designing light-harvesting systems and enzymes on quantum principles to raise crops' photosynthetic efficiency and stress tolerance; and developing biological magnetic sensors that exploit cryptochromes. The author foresees particularly large potential for plant quantum biology as a strategy for creating resilient crops amid climate change. Yet the walls to be scaled are equally clear: the complexity of biological systems, the fleeting and fragile nature of quantum phenomena, and the experimental difficulty of directly observing and verifying these effects inside living cells. The author concludes that the field's next tasks are research that directly observes and manipulates quantum effects within living plants, and the development of robust theoretical models capable of predicting them. In synthesizing the whole of plant quantum biology—beyond isolated experimental cases—from the perspective of stress adaptation and sustainable agriculture, this review reads as a milestone bridging basic science and the agricultural field. #QuantumBiology #PlantScience #Photosynthesis #QuantumCoherence #RadicalPairMechanism #QuantumTunneling #Cryptochrome #Magnetosensing #SustainableAgriculture #StressTolerantCrops https://www.sciencedirect.com/science/article/pii/S2667064X25001988

inquantio

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Published in Scientific Reports (Nature Portfolio), this study extends inelastic electron tunneling spectroscopy (IETS)—originally proposed as a model for olfactory receptor activation—to the mammalian serotonin receptor (5-HT2A) through quantum-chemical modeling. It finds that several serotonin agonists, including LSD and DOI, share a common vibrational peak near 1500 cm⁻¹ whose intensity scales with the drug's potency, suggesting that the key to receptor activation may be not only a molecule's shape but its vibration. As a way to test this, it proposes deuterated versions of the LSD analogue DAM-57. The design—leaving the molecular shape almost untouched while altering only the vibration to check for a change in potency—could open a new path to computer-based potency prediction in drug discovery. [Quantum Biology Society] A large share of modern medicines target G protein-coupled receptors (GPCRs) on the cell surface. Yet how a drug (an agonist) switches such a receptor on—how it activates it—remains a fundamental question of pharmacology and drug design that is still not fully understood. The lock-and-key model, long used as the standard, explains a molecule's shape and binding but has been limited in predicting how strongly a drug acts (its potency). At the serotonin receptor, for instance, the two molecules DOI and DOB have almost the same binding affinity (docking) yet differ greatly in potency. Something beyond shape is clearly at work. A 2015 paper in the Nature Portfolio journal Scientific Reports, "Neuroreceptor Activation by Vibration-Assisted Tunneling," proposes a quantum-mechanical answer to this question. Ross D. Hoehn, David Nichols, and Sabre Kais of Purdue University, together with Hartmut Neven of Google, extended to the serotonin receptor a vibrational theory originally put forward to explain olfaction (the recognition of odorant molecules). The core idea is that a receptor is activated by reading not only the shape of the molecule it binds but also that molecule's characteristic vibration. ■ Beyond Shape: Vibration Opens a Channel for the Electron The roots of this theory lie in olfaction. The vibrational theory—that odor receptors sense the vibrations of odorant molecules—was once dismissed for lacking a clear mechanism, but it drew renewed attention when Luca Turin and others refined it into a physical mechanism resembling inelastic electron tunneling spectroscopy (IETS). Mapped onto a receptor, the mechanism runs as follows. The receptor's binding site is viewed as a single tunneling junction that an electron must cross, with specific amino acid residues forming the two walls of the junction as the electron donor and the electron acceptor. An electron cannot easily cross this gap on its own; but if it can hand off a packet of energy of exactly the right size to match a vibrational mode of the bound agonist, an inelastic channel opens through which the electron passes while exciting that vibration. The researchers propose that this very electron transfer is the trigger that switches the receptor on. The energy that drives the electron, they suggest, could be supplied by an ionic cofactor such as a calcium ion. The upshot is a picture in which each agonist's distinctive vibrational fingerprint, quite apart from its shape, takes part in receptor activation. ■ A Shared Peak at 1500 cm⁻¹, Marching in Step With Potency Using density functional theory (DFT) and normal-mode analysis, the researchers calculated the tunneling spectra of several 5-HT2A agonists. The subjects were hallucinogenic compounds including LSD and DOI, phenethylamines of the 2C-X class and amphetamines of the DOX class—many of them first characterized by the chemist Alexander Shulgin. The calculations showed that these agonists shared a common peak in one particular vibrational band, at 1500 cm⁻¹. More striking still, the intensity of this peak (the integral over the 1500 ± 35 cm⁻¹ range) tracked each drug's potency. Taking the most potent compound, LSD, as the reference, the peak intensity was roughly proportional to the inverse of the EC50—that is, to potency. The motions contributing to this band were stretching of the amide methyl hydrogens, stretching of the phenyl and indole hydrogens, and bending of the tertiary-amine methyl hydrogens. The potency difference between DOI and DOB—indistinguishable by shape alone—could, from this vibrational standpoint, finally begin to find an explanation. ■ Testing It With Deuterium: The Proposed DAM-57 Experiment To turn the theory into an experiment, the tool the researchers chose was deuterium. The target molecule was DAM-57 (lysergic acid dimethylamide), an analogue of LSD that carries a methyl group in place of LSD's flexible ethyl amide and is therefore far less potent. Deuterium is chemically almost identical to ordinary hydrogen, so it barely affects a molecule's shape or binding, but its mass is twice as great, which shifts vibrational frequencies. Substituting deuterium at specific positions therefore makes it possible to selectively lower the 1500 cm⁻¹ vibrational peak while leaving the shape intact. The researchers' prediction is clear: deuterating the amide side chain to deplete this peak should also reduce the compound's potency at the receptor. In the calculations, one substituted form (DAM-57-iv) showed its peak intensity cut to about one-third of the original and its tunneling probability density to roughly one-tenth, pointing to a steep drop in potency. Since binding and kinetic isotope effects alone rarely change potency by more than about 10%, a deuterium substitution that produces a much larger change would be strong evidence for the vibrational mechanism—a falsifiable prediction, in other words. ■ Significance, and a Note of Caution If this work is validated, it would not only supply a quantum-mechanical explanation for the biological phenomenon of receptor activation but could also become a new tool for predicting, by computer, the potency and activity of drugs that docking alone has struggled to capture. Its potential lies in broadening the perspective of drug design from shape-matching to vibration-reading. There are, however, clear reasons for caution. This is a computational and theoretical study, and the correlation between peak intensity and potency is a broad trend observed in a limited number of molecules. Above all, the olfactory vibrational theory at the root of this approach remains contested. In odor perception, shape-based explanations are the mainstream, and experiments on whether humans can distinguish deuterated molecules by smell have yielded conflicting results. The DAM-57 experiment the authors propose was, as of this paper, still an untested prediction. This study is therefore best read not as an established mechanism but as a provocative and testable hypothesis equipped with a clear path to verification. In treating the activation of neurotransmitter and drug receptors through quantum vibration-assisted tunneling—unlike the existing olfaction (odorant-vibration) entries—this paper adds a pharmacological perspective that the archive had not previously held. #QuantumBiology #QuantumTunneling #Neuroscience #SerotoninReceptor #DrugDiscovery #VibrationalTheory #Olfaction #GPCR #LSD #DeuteriumSubstitution https://www.nature.com/articles/srep09990

inquantio

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Published in PNAS (Proceedings of the National Academy of Sciences), this study uses multiscale simulation to elucidate a key step in the long-range radical transport—spanning roughly 32 Å—in ribonucleotide reductase (RNR), the essential enzyme that produces DNA's raw materials. It shows that radical transfer from a tryptophan (W48) to a tyrosine (Y356) occurs through orthogonal PCET—in which the electron and proton move together but in different directions—and newly proposes that the proton acceptor is the glutamate residue E52. A conformational change in Y356 acts as a gatekeeper that opens the door to the reaction, and this motion shortens the distance so that the proton's hydrogen tunneling can occur efficiently—a case in which classical protein motion and quantum tunneling operate hand in hand. [Quantum Biology Society] Every cell in our body must be continuously supplied with deoxyribonucleotides—their raw materials—in order to build and repair DNA. The essential enzyme that produces these materials is ribonucleotide reductase (RNR), which is also an important target for antibiotic and anticancer drug development. Yet for this enzyme to begin its reaction, something remarkable must happen. The radical that serves as the reaction's trigger must travel a great distance—about 32 angstroms (Å)—across two subunits (α and β) to reach the active site where catalysis takes place. This long-range radical transport proceeds through a series of proton-coupled electron transfer (PCET) reactions, along a pathway of redox-active amino acid residues lined up like a chain. A study recently published in the Proceedings of the National Academy of Sciences (PNAS), "Conformationally Gated Multisite Proton-Coupled Electron Transfer in the Ribonucleotide Reductase β Subunit," has elucidated a key step in this pathway that had until now been poorly understood. Jiahua Deng of Princeton University and Sharon Hammes-Schiffer, an authority on PCET theory, used multiscale simulations combining several computational methods to track, at the atomic level, how the radical is passed from the tryptophan W48 to the tyrosine Y356 within the β subunit. At the heart of that process lay a conformational change in the protein and the quantum tunneling of a proton. ■ A Radical That Crosses 32 Å, and PCET PCET is a reaction in which the electron and proton move not separately but together, simultaneously, without forming a stable intermediate. In RNR, the radical starts from the tyrosine Y122 in the β subunit and is passed along a chain of residues—W48, Y356, and then Y731 and Y730 in the α subunit—to the cysteine C439 at the active site. This pathway has a different character in each segment. Within the α subunit, collinear PCET occurs, in which the electron and proton move in the same direction; this portion has been relatively well studied. Within the β subunit, by contrast, orthogonal PCET occurs, in which the electron and proton split off and move in different directions—a process that has remained poorly understood because the pathway is complex and theoretically difficult to treat. It is precisely this orthogonal PCET step, from W48 to Y356 in the β subunit, that the present study dug into. ■ The Orthogonal PCET Where Electron and Proton Split, With E52 as the Proton Acceptor The simulations showed that radical transfer from W48 to Y356 was thermodynamically favorable (reaction free energy of about −1.4 kcal/mol). The mechanism runs as follows. As the electron on Y356 moves to W48, which is in the cationic radical state, the proton released by Y356 moves to a glutamate residue, E52, located on an entirely different side. The electron and proton split off in different directions and move cooperatively. The spin densities before and after the reaction show the radical moving cleanly from W48 to Y356, matching this orthogonal PCET picture exactly. What is especially noteworthy here is the identity of the partner that receives the proton—the proton acceptor. Until now, experiments (the finding that replacing E52 with glutamine abolishes the enzyme's function) and structural information had been interpreted to mean that E52, as part of a water channel, indirectly regulates Y356's proton. But this simulation offers an alternative: that E52 is the direct partner that receives Y356's proton. The evidence is the change in distance. Before W48 was oxidized, the most stable distance between Y356 and E52 was about 6.6 Å, but once W48 was oxidized, the most stable distance narrowed sharply to about 2.6 Å—close enough for the proton to cross directly. ■ Conformational Change as Gatekeeper, and Hydrogen Tunneling Behind this change in distance lies a dramatic conformational change in Y356. Y356 sits on a flexible loop at the α/β interface. Before W48 is oxidized, it is held by an arginine residue, R236, and points in a particular direction; but when W48 is oxidized, a positive charge appears, water floods into the surroundings, and space opens up. As a result, Y356 is released from R236 and changes direction—first turning toward E52 to hand off its proton, then turning toward Y731 in the α subunit to prepare for the next radical transfer. In this way, Y356's motion serves as a gate that determines when, and in which direction, the reaction proceeds. And it is precisely here that quantum mechanics enters. In PCET, the proton does not classically climb over the barrier but moves by hydrogen tunneling, piercing through it. When the researchers analyzed the reaction with vibronically nonadiabatic PCET theory, they found that the reaction rate was extremely sensitive to the distance between the proton donor and the acceptor. The shorter the distance, the more strongly the proton's wavefunctions overlapped, and the more sharply tunneling occurred. The equilibrium donor–acceptor distance was about 2.61 Å, but the distance at which the reaction actually occurs most often was shorter still, about 2.52 Å. In other words, hydrogen tunneling occurs efficiently only when the protein's conformation, fluctuating from moment to moment, produces such short distances (estimated rate constant of about 1.6 × 10⁷ s⁻¹). Classical protein motion, so to speak, sets the stage for quantum tunneling. The researchers also confirmed that W48 could become a neutral radical by handing its proton to a nearby aspartate, D237; but weighing several considerations, they concluded that PCET to Y356 occurs mainly when W48 is in the cationic radical state. The cationic radical is a stronger oxidant and more readily produces a conformation favorable for radical transfer. ■ Significance and Outlook This study is meaningful on two levels. First, because RNR is a major target for anticancer and antibiotic drugs, understanding its radical-transport mechanism at the atomic level offers leads for drug design and protein engineering. More broadly, it demonstrates general principles for how an enzyme precisely coordinates the movement of electrons and protons across long distances—the local rearrangement of hydrogen bonds, hydration by water, conformational gating, and quantum hydrogen tunneling all interlocking to jointly control the reaction's reactivity and directionality. There are, of course, points to view with caution. This is a computational and simulation-based study, and the authors themselves note that current methods cannot accurately obtain the absolute energy values for RNR reactions, so the results should be regarded as qualitative insights. The proposal that E52 is the direct proton acceptor, as well as W48's involvement, has not yet been confirmed by direct experimental evidence, and these results concern forward radical transfer. Even so—unlike existing entries dealing with DNA-repair enzymes or electron transport—this paper, as a 2026 study, elucidates at the atomic level the long-range radical transport of an enzyme that builds DNA's raw materials, from the standpoint of quantum hydrogen tunneling, adding a new texture to the archive. #QuantumBiology #ProtonCoupledElectronTransfer #RibonucleotideReductase #HydrogenTunneling #EnzymeCatalysis #RadicalTransport #DNASynthesis #QuantumTunneling #MultiscaleSimulation #DrugTarget https://pmc.ncbi.nlm.nih.gov/articles/PMC12867644/