Database of opsin genotype-phenotype data and machine-learning models trained to predict opsin phenotypes. Database of all heterologously expressed opsin genes with λmax phenotypes.

Supporting materials for the GX Dataset.

The GX Dataset is a dataset of combined tES, EEG, physiological, and behavioral signals from human subjects.

Publication

A full data descriptor is published in Nature Scientific Data. Please cite this work as:

Gebodh, N., Esmaeilpour, Z., Datta, A. et al. Dataset of concurrent EEG, ECG, and behavior with multiple doses of transcranial electrical stimulation. Sci Data 8, 274 (2021). https://doi.org/10.1038/s41597-021-01046-y

Descriptions

A dataset combining high-density electroencephalography (EEG) with physiological and continuous behavioral metrics during transcranial electrical stimulation (tES; including tDCS and tACS). Data includes within subject application of nine High-Definition tES (HD-tES) types targeted three brain regions (frontal, motor, parietal) with three waveforms (DC, 5Hz, 30Hz), with more than 783 total stimulation trials over 62 sessions with EEG, physiological (ECG or EKG, EOG), and continuous behavioral vigilance/alertness metrics (CTT task).

Acknowledgments

Portions of this study were funded by X (formerly Google X), the Moonshot Factory. The funding source had no influence on study conduction or result evaluation. MB is further supported by grants from the National Institutes of Health: R01NS101362, R01NS095123, R01NS112996, R01MH111896, R01MH109289, and (to NG) NIH-G-RISE T32GM136499.

We would like to thank Yuxin Xu and Michaela Chum for all their technical assistance.

Extras

For downsampled data (1 kHz ) please see (in .mat format):

• Experiment 1 : https://doi.org/10.5281/zenodo.3840614
• Experiment 2 : https://doi.org/10.5281/zenodo.3840616

Code used to import, process, and plot this dataset can be found here:

• GitHub : https://github.com/ngebodh/GX_tES_EEG_Physio_Behavior

Additional figures for this project have been shared on Figshare. Trial-wise figures can be found here:

• PSD: https://doi.org/10.6084/m9.figshare.14810517.v1
• Topoplots During Stimulation: https://doi.org/10.6084/m9.figshare.14810478
• Voltage timeseries, spectrogram and behavior: https://doi.org/10.6084/m9.figshare.14810442.v1

The full dataset is also provided in BIDS format here:

• Data in BIDS format: https://doi.org/10.18112/openneuro.ds003670.v1.1.0

Data License
Creative Common 4.0 with attribution (CC BY 4.0)

NOTE

Please email ngebodh01@citymail.cuny.edu with any questions.

Feed costs and time to harvest are key factors affecting the economic viability of domestic sablefish (Anoplopoma fimbria) aquaculture. Use of fast growing all-female monosex stocks dramatically reduces time to harvest, but our research to date indicates that the commercial salmon feeds typically used by industry are not optimally formulated for sablefish and there is still a high degree of potential for improved growth and feed conversion. The effects of dietary balance of protein, fat, and carbohydrate on productive performance, growth and feed conversion at any post-juvenile stage of development are unknown, and there are no commercial diets specifically formulated for sablefish aquaculture in the marketplace. Dietary nutrient imbalances combined with inappropriate feeding schedules and strategies contribute to poor nutrient utilization and are unlikely to fully support the growth potential of this species, impeding continued efforts to improve performance during grow-out to harvest. Thus, research activity focuses on establishing performance optimized diets and feeding strategies that support maximum growth, efficient feed conversion and other economically important traits such as fillet yield. Informaion on tissues collected and physiological measures (e.g., plasma steroid levels) may be available.

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Preclinical Software for Physiology DA and AS Market Size 2025-2029

The preclinical software for physiology da and as market size is forecast to increase by USD 4.38 billion, at a CAGR of 6% between 2024 and 2029.

The Preclinical Software for Physiology market is witnessing significant growth, driven by the increasing role of bioinformatics tools and software in preclinical research. The digitalization of preclinical research is a key trend, with the adoption of advanced technologies such as machine learning and artificial intelligence increasing at a rapid pace. These technologies enable researchers to analyze large datasets more efficiently, leading to improved accuracy and productivity. However, the market faces challenges due to the stringent ethical framework governing the use of animals in preclinical research. Compliance with these regulations adds complexity and cost to research processes, necessitating the development of more humane and alternative testing methods.
Companies seeking to capitalize on market opportunities must invest in innovative solutions that address the need for ethical and efficient preclinical research while ensuring regulatory compliance. Additionally, collaboration and partnerships between industry players and regulatory bodies can help drive progress and innovation in the field.

What will be the Size of the Preclinical Software for Physiology DA and AS Market during the forecast period?

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Preclinical software for physiology DA (dynamic analysis) plays a pivotal role in the evolving landscape of high-throughput screening, research institutes, life sciences, computational biology, and various sectors within the broader context of drug discovery and development. The continuous unfolding of market dynamics in this domain is characterized by the integration of advanced technologies such as data management, data analysis, data visualization, machine learning, and artificial intelligence. Physiology DA software facilitates experimental design, enabling researchers to model and analyze complex physiological systems. This is crucial for target validation, pharmacokinetic (pk) and pharmacodynamic (pd) modeling, and safety pharmacology studies. Furthermore, it supports workflow automation, grant applications, and scientific publications, fostering collaboration and knowledge sharing within the research community.

Applications of preclinical software extend to disease modeling, in silico studies, drug interactions, and biomarker discovery. Regulatory compliance is ensured through robust statistical analysis and data management capabilities. In vivo studies, animal studies, and drug metabolism research also benefit from these advanced solutions. The integration of physiology DA software in the drug discovery process enables personalized medicine and Precision Medicine approaches, as well as biotech startups to streamline their research and development efforts. Systems biology and collaboration platforms further enhance the potential for innovation and knowledge transfer. The ongoing evolution of preclinical software in the physiology DA market reflects the dynamic nature of the life sciences sector, with continuous advancements in technology and applications shaping the future of drug discovery and development.

How is this Preclinical Software for Physiology DA and AS Industry segmented?

The preclinical software for physiology da and as industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

End-user

  Industrial labs and CROs
  Academic government and research labs


Deployment

  On-premises
  Cloud
  hybrid


Application

  Physiology Research
  Drug Development and Safety Testing
  Behavioral Studies
  Other Applications (e.g., Veterinary, Educational)


Type of Software

  Data Acquisition Software
  Data Analysis Software
  Integrated Platforms


Organization Size

  Small and Medium Enterprises (SMEs)
  Large Enterprises


Technology

  AI/ML-Integrated Software
  Traditional Software


Pricing Model

  Subscription-Based
  Perpetual License
  Freemium or Pay-per-Use


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    The Netherlands
    UK


  APAC

    China
    India
    Japan


  Rest of World (ROW)

By End-user Insights

The industrial labs and cros segment is estimated to witness significant growth during the forecast period.

Preclinical software plays a pivotal role in the drug discovery and development process, enabling advanced data analysis, pharmacokinetic (pk) and pharmacodynamic (pd) modeling, and workflow automation in areas such as high-throughput screening, target validation, and disease modeling. Cloud computing tec

The datasets stored in this folder summarize reproductive data for Brown Pelicans nesting on Gaillard and Cat Islands, Alabama, in 2017 and 2018. Data include nest and nestling survival, nest site characteristics, environmental covariates, and temperatures recorded inside nests. The datasets and FGDC-compliant metadata are available as .zip files. Dataset "Reproductive Physiology of Brown Pelican Along the Coast of Alabama, 2017-2018_Nest monitoring" provides data on the physiology of reproduction collected at Brown Pelican breeding colonies in coastal Alabama, 2017-2018, and includes nest and nestling survival, nest site characteristics, and environmental covariates. Dataset "Reproductive Physiology of Brown Pelican Along the Coast of Alabama, 2017-2018_Nest monitoring-temperature " provides data on the physiology of reproduction collected at Brown Pelican breeding colonies in coastal Alabama, 2017-2018, and includes nest and nestling survival, nest site characteristics, and environmental covariates (including temperature measured inside the nest).

Contact Information

If you would like further information about PeakAffectDS, to purchase a commercial license, or if you experience any issues downloading files, please contact us at peakaffectds@gmail.com.

Description

PeakAffectDS contains 663 files (total size: 1.84 GB), consisting of 612 physiology files, and 51 perceptual rating files. The dataset contains 51 untrained research participants (39 female, 12 male), who had their body physiology recorded while watching movie clips validated to induce strong emotional reactions. Emotional conditions included: calm, happy, sad, angry, fearful, and disgust; along with baseline a neutral condition. Four physiology channels were recorded with a Biopac MP36 system: two facial muscles with fEMG (zygomaticus major, corrugator supercilii) using Ag/AgCl electrodes, heart activity with ECG using a 1-Lead, Lead II configuration, and respiration with a wearable strain-gauge belt. While viewing movie clips, participants indicated in real-time when they experienced a "peak" emotional event, including: chills, tears, or the startle reflex. After each clip, participants further rated their felt emotional state using a forced-choice categorical response measure, along with their felt Arousal and Valence. All data are provided in plaintext (.csv) format.

PeakAffectDS was created in the Affective Data Science Lab.

Physiology files

Each participant has 12 .CSV physiology files, consisting of 6 Emotional conditions, and 6 Neutral baseline conditions. All physiology channels were recorded at 2000 Hz. A 50Hz notch filter was then applied to fEMG and ECG channels to remove mains hum. Each .CSV file contains 6 columns, in order from left to right:

1. Sample timestamp (units: seconds)
2. EMG Zygomaticus (units: millivolts)
3. EMG Corrugator (units: millivolts)
4. ECG (units: millivolts)
5. Peak event makers: 0 = no event, 1 = chills, 2 = tears, 3 = startle

Perceptual files

There are 51 perceptual ratings files, one for each participant. Each .CSV file contains 4 columns, in order from left to right:

1. Filename of presented stimulus (see File naming Convention, below)
2. Felt emotional response: 1 = neutral, 2 = calm, 3 = happy, 4 = sad, 5 = angry, 6 = fearful, 7 = disgust
3. Felt Valence, ranging from: 1 = Very negative, to 7 = Very positive
4. Felt Arousal, ranging from: 1 = Very low, to 7 = Very high

File naming convention

Each of the 612 physiology files has a unique filename. The filename consists of a 3-part numerical identifier (e.g., 09-02-03.csv). The first identifier refers to the participant's ID (09), while the remaining two identifiers refer to the stimulus presented for that recording (02-03.mp4); these identifiers define the stimulus characteristics:

• Participant: 01 = participant 1, 02 = participant 2, ..., 51 = participant 51.
• Emotion: 01 = neutral, 02 = calm, 03 = happy, 04 = sad, 05 = angry, 06 = fearful, 07 = disgust.
• Stimulus set. For Emotional files: 01 = group 1, 02 = group 2, 03 = group 3. For Neutral files: 01 = instance 1, 02 = instance 2, ..., 06 = instance 6.

Filename example: 09-02-03.csv

• Participant 9 (09)
• Calm (02)
• Stimulus Set 3 (03)

Filename example: 09-01-05.csv

• Participant 9 (09)
• Neutral (01)
• Instance 5 (05)

Methods

A 1-way mixed-design was used, with a within-subjects factor Emotion (6 levels: Calm, Happy, Sad, Angry, Fearful, Disgust) and a between-subjects factor Stimulus Set (3 levels). Trials were blocked by Affect Condition (Baseline, Emotional), with each participant presented 6 blocked trials: Baseline (neutral), then Emotional (Calm, ..., Disgust). This design reduced potential contamination from preceeding emotional trials, by ensuring that participant's physiology began close to a resting baseline for emotional conditions.

Emotion was presented in pseudorandom order using a carryover balanced generalised Youden design, generated by the crossdes package in R. Eighteen emotional movie clips were used as stimuli, with three instances for each emotion category (6x3). Clips were then grouped into one of three Stimulus Sets, with participants assigned to a given Set using Block randomisation. For example, participants assigned to Stimulus Set 1 (PID: 1, 4, 7, ...) all saw the same movie clips, but these clips differed to those in Sets 2 and 3. Six Neutral baseline movie clips were used as stimuli, with all participants viewing the same neutral clips, with their order also generated with a Youden design.

Stimulus duration varied, with clips lasting several minutes. Lengthy clips without repetition were used to help ensure that participants became engaged, and experienced genuine, strong emotional responses. Participants were instructed to immediately indicate using the keyboard when experiencing a "peak" emotional event, including: chills, tears, or startle. Participants were permitted to indicate multiple events in a single trial, and identified the type of the evens at the trial feedback stage, along with ratings of emotional category, arousal, and valence. The concept of peak physiological events was explained at the beginning of the experiment, but the three states were not described as being associated with any particular emotion or valence.

License information

PeakAffectDS is released under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License, CC BY-NC-SA 4.0.

Citing PeakAffectDS

Greene, N., Livingstone, S. R., & Szymanski, L. (2022). PeakAffectDB [Data set]. Zenodo. https://doi.org/10.5281/zenodo.6403363

Table S1. (a) Life history trait and (b) physiology datasets. (c) Sample size for each treatment and sex. Correlation analysis between (d) the life-history traits (Spearman correlation) and (e) physiological (Pearson correlation) traits for each treatment separately.

This dataset is about books. It has 2 rows and is filtered where the book is Anatomy & physiology : with integrated study guide. It features 7 columns including author, publication date, language, and book publisher.

Analysis of Microcystis aeruginosa physiology by spectral flow cytometry: Impact of chemical and light exposure. new technique to observe photosynthesis to monitor the health or cyanobacteria and their reaction to hydrogen peroxide. This dataset is not publicly accessible because: The public would require specialized software in order to view and interpret files. It can be accessed through the following means: Email zucker.robert@epa.gov. Format: The data in the paper is acquired in proprietary format from the manufacturer of the equipment. This data presented in the paper can be read only by using the software from the manufacturer which is quite costly and not feasible to purchase unless the scientist owns the equipment. This dataset is associated with the following publication: Brentjens, E., E. Beall, and R. Zucker. Analysis of Microcystis aeruginosa physiology by spectral flow cytometry: Impact of chemical and light exposure. PLOS Water. Public Library of Science, San Francisco, CA, USA, 2(10): e0000177, (2023).

List of form and physiological medical specialty projects subsidized in the 103rd year.

This is the dataset that accompanies an article entitled "The use of insect life tables in optimizing invasive pest distributional models" that would be published in Ecography. The dataset include two R script that used to generate physical model and the physiology combined model respectively. Our paper shows that the physiology combined model show good performance when applying ecological niche model in risk assessment. We addressed this by determining whether incorporating physiological data from life table analyses of an invasive insect, Drosophila suzukii, improved predictions of ecological niche models. The dataset also include the physiology data D. suzukii that we assembled for running our physiology combined model.

*-All significance levels determined by Mann-Whitney rank sum test.

This dataset is about books. It has 1 row and is filtered where the book is Anatomy, physiology and pathology colouring and workbook for therapists and healthcare professionals. It features 7 columns including author, publication date, language, and book publisher.

This dataset is about book subjects, has 3 rows. and is filtered where the books is Physiology & anatomy : a homeostatic approach. It features 10 columns including book subject, number of authors, number of books, earliest publication date, and latest publication date. The preview is ordered by number of books (descending).

Natural and human-induced stressors elicit changes in energy metabolism and stress physiology in populations of a wide array of species. Cities are stressful environments that may lead to differential selection on stress-coping mechanisms. Given that city ponds are exposed to the urban heat island effect and receive polluted run-off, organisms inhabiting these ecosystems might show genetic differentiation for physiological traits enabling them to better cope with higher overall stress levels. A common garden study with 62 Daphnia magna genotypes from replicated urban and rural populations revealed that urban Daphnia have significantly higher concentrations of total body fat, proteins, and sugars. Baseline activity levels of the antioxidant defense enzymes superoxide dismutase (SOD) and glutathione-S-transferase (GST) were higher in rural compared to city populations, yet urban animals were equally well protected against lipid peroxidation. Our results add to the recent evidence of urbanisation-driven changes in stress physiology and energy metabolism in terrestrial organisms. Combining our results with data on urban life history evolution in Daphnia revealed that urban genotypes show a structured pace-of-life syndrome involving both life history and physiological traits, whereas this is absent in rural populations.

These data files contain the physiological muscle recordings in response to optical or electrical nerve stimulation. Files are labelled according to subject ID, as listed in Supplementary Table 3 in our eLife publication.The raw data files require AD Instruments LabChart software for viewing and analysis. Some example traces have been uploaded as image files.

This dataset is about book series, has 1 rows and is filtered where the books is Anatomy & physiology for dummies®. It features 10 columns including book series, number of authors, number of books, earliest publication date, and latest publication date. The preview is ordered by number of books (descending).

Physical function (K), emotional functioning (E), cognition (C), autonomy (Aut), social functioning family (Fam), social functioning friends (Fr) and body image (KB).

This dataset includes summary physiology and MRI data used in a publication identifying sex differences in insular organization to an autonomic challenge, the hand grip. The protocol consistent of healthy participants performing a series of four 16-second hand grip maneuvers one minute part, with baseline and recovery periods. Continues fMRI whole-brain scans were collected at 2 s intervals, and concurrent pulse oximetry data were acquired. The data include the SaO2 levels and continuous heart rate derived from the pleth waveform. The files include pdf and MATLAB figures, and tables and results from a SAS dataset with statistical results from RMANOVA (see10.12688/f1000research.8252.1 for method). The MRI data with summary T1 files after DARTEL normalization in SPM12 are published in a related dataset in this dataverse (Macey, Paul, 2017, "Summary fMRI and physiology data from Valsalva maneuver in female and male healthy subjects", doi:10.7910/DVN/QOHNFE, Harvard Dataverse, V1), and those fMRI data include the preprocessing whole-brain images (motion-corrected, coregistered to T1, spatially normalized using T1 DARTEL parameters, smoothed 8mm FWHM). Full details will be included in the publication.

This dataset is about books. It has 16 rows and is filtered where the book is Anatomy and physiology for nurses. It features 7 columns including author, publication date, language, and book publisher.