Clinical Applications and Potential Mechanism of Cold Acclimation Therapy
Bibliographic record
Abstract
Yongxing Wang,1,* Yajun Wang,1,* Dezhi Han,2 Weijing Sun,2 Yaqun Qiao,1 Conghui Wang,3 Xu Zhang,1 Jinlong Xu2 1Department of General Surgery, The 969th Hospital of the Chinese People’s Liberation Army Joint Logistics Support Force, Hohhot, Inner Mongolia, 010051, People’s Republic of China; 2Department of Burn and Plastic Surgery, The 969th Hospital of the Chinese People’s Liberation Army Joint Logistics Support Force, Hohhot, Inner Mongolia, 010051, People’s Republic of China; 3Clinical Lab, The 969th Hospital of the Chinese People’s Liberation Army Joint Logistics Support Force, Hohhot, Inner Mongolia, 010051, People’s Republic of China*These authors contributed equally to this workCorrespondence: Jinlong Xu, Department of Burn and Plastic Surgery, The 969th Hospital of the Chinese People’s Liberation Army Joint Logistics Support Force, No. 111 Aimin Road, Hohhot, 010051, People’s Republic of China, Tel +8618548164089, Email xujinlong1986228@163.comAbstract: Cold acclimation therapy has emerged as a notable therapeutic approach with physical therapy and clinical medicine. Driven by the rising demand for effective pain management, sports recovery, and inflammation control, several studies have examined the physiological mechanisms and diverse applications of cold acclimation therapy. Current research shows that cold acclimation therapy can effectively alleviate both acute and chronic pain, promote post-exercise recovery, and mitigate inflammatory responses. Despite its potential, challenges persist in its clinical application, including the determination of precise clinical indications, optimal timing of intervention, and potential adverse effects. This review summarizes the fundamental principles, clinical applications, current research progress, and future potential of cold acclimation therapy, aiming to provide a reference for clinical practice. Furthermore, the future applications of cold acclimation therapy in medical practice is discussed, emphasizing its importance and development prospects in modern healthcare.Keywords: cold acclimation therapy, inflammation control, pain management, physical therapy, sports recovery
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".