Trend in H2S Biology and Medicine Research—A Bibliometric Analysis
Bibliographic record
Abstract
The biological and medical importance of hydrogen sulfide (H2S) has been recognized for decades. The aim of this bibliometric study is to analyze the quantity and quality of publications in H2S biology and medicine (H2SBM) based on the databases of Web of Science and Google Scholar. A total of 5881 publications published between 1990 and 2016 were analyzed. The number of H2SBM papers published before 2004 was below 100 annually, but thereafter this number rapidly increased and peaked in 2015 with more than 7-fold increase. All publications related to H2SBM research achieved a total h-index of 136 and were cited 123,074 times. The most published disciplines in H2S biomedicine research were the cardiovascular system (8.5%), neuroscience (6.5%), and gastroenterology hepatology (4.7%). The country with the greatest number of publications in the H2SBM research field was the USA with 1765 (30.0%) publications, followed by China with 995 (16.9%) publications and Japan with 555 (9.4%) publications. The top 3 most published institutes were National University of Singapore, Peking University in China, and University of Groningen in Netherlands. Nitric Oxide Biology and Chemistry was the most exploited journal for H2SBM publications with 461 articles, followed by FASEB Journal with 200 publications and Antioxidants Redox Signaling with 116 publications. The most highly cited publications and researchers in H2SBM research were also unmasked from this bibliometric analysis. Collectively, H2SBM publications exhibit a continuous trend of increase, reflecting the increased H2SBM research intensity and diversity globally.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.064 | 0.033 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".