Sepsis is a systemic inflammatory response caused by severe infection or trauma, and is one of the common causes of acute lung injury(ALI) and acute respiratory distress syndrome(ARDS). Sepsis-acute lung injury(SALI) is a critical clinical condition with high morbidity and mortality. Its pathogenesis is complex and not yet fully understood, and there is currently a lack of targeted and effective treatment options. Pyroptosis, a novel form of programmed cell death, plays a key role in the pathological process of SALI by activating inflammasomes and releasing inflammatory factors, making it a potential therapeutic target. In recent years, the role of traditional Chinese medicine(TCM) in regulating signaling pathways related to pyroptosis through multi-components and multi-targets has attracted increasing attention. TCM may intervene in pyroptosis by inhibiting the activation of NLRP3 inflammasomes and regulating the expression of Caspase family proteins, thus alleviating inflammatory damage in lung tissues. This paper systematically reviews the molecular regulatory network of pyroptosis in SALI and explores the potential mechanisms and research progress on TCM intervention in cellular pyroptosis. The aim is to provide new ideas and theoretical support for basic research and clinical treatment strategies of TCM in SALI.
Pyroptosis/drug effects* ; Humans ; Sepsis/genetics* ; Acute Lung Injury/physiopathology* ; Animals ; Drugs, Chinese Herbal/therapeutic use* ; Medicine, Chinese Traditional ; Inflammasomes/metabolism* ; NLR Family, Pyrin Domain-Containing 3 Protein/genetics*

Recent studies have shown that shorter periods of ejaculatory abstinence may enhance certain sperm parameters, but the molecular mechanisms underlying these improvements are still unclear. This study explored whether reduced abstinence periods could improve semen quality, particularly for use in assisted reproductive technologies (ART). We analyzed semen samples from men with normal sperm counts ( n = 101) and those with low sperm motility or concentration ( n = 53) after 3-7 days of abstinence and then after 1-3 h of abstinence, obtained from the Reproductive & Genetic Hospital of CITIC-Xiangya (Changsha, China). Physiological and biochemical sperm parameters were evaluated, and the dynamics of transfer RNA (tRNA)-derived fragments (tRFs) were analyzed using deep RNA sequencing in five consecutive samples from men with normal sperm counts. Our results revealed significant improvement in sperm motility and a decrease in the DNA fragmentation index after the 1- to 3-h abstinence period. Additionally, we identified 245 differentially expressed tRFs, and the mitogen-activated protein kinase (MAPK) signaling pathway was the most enriched. Further investigations showed significant changes in tRF-Lys-TTT and its target gene mitogen-activated protein kinase kinase 2 ( MAP2K2 ), which indicates a role of tRFs in improving sperm function. These findings provide new insights into how shorter abstinence periods influence sperm quality and suggest that tRFs may serve as biomarkers for male fertility. This research highlights the potential for optimizing ART protocols and improving reproductive outcomes through molecular approaches that target sperm function.
Male ; Humans ; Spermatozoa/metabolism* ; RNA, Transfer/genetics* ; Sperm Motility/genetics* ; Adult ; Semen Analysis ; Sexual Abstinence/physiology* ; Sperm Count ; DNA Fragmentation

Objective To explore the medication rules of Professor HUANG Li for the treatment of recurrent angina pectoris after percutaneous coronary intervention(PCI)for coronary heart disease by data mining method.Methods The prescriptions for effective cases of recurrent angina pectoris after PCI for coronary heart disease treated by Professor HUANG Li in the outpatient department of China-Japan Friendship Hospital were collected.SPSS Statistics 26.0 software and SPSS Modeler 18.0 software were used for frequency statistics,analysis of the therapeutic actions,properties,flavors and meridian tropism of the prescribed herbs as well as association rule analysis,cluster analysis and factor analysis of the herbs.Results A total of 344 Chinese medicine prescriptions were obtained,involving 209 herbs,with a cumulative frequency of 5 874 times.The top 30 Chinese medicinals were named as the high-frequency Chinese medicines,and the herbs with the frequency over 100 times in descending order were Astragali Radix,Chuanxiong Rhizoma,Puerariae Lobatae Radix,Rhodiolae Crenulatae Radix et Rhizoma,Notoginseng Radix et Rhizoma,Poria,Dalbergiae Odoriferae Lignum,Atractylodis Macrocephalae Rhizoma,Curcumae Rhizoma,Sparganii Rhizoma,Dioscoreae Rhizoma,Citri Reticulatae Pericarpium,Pinelliae Rhizoma Praeparatum,Codonopsis Radix,and Glycyrrhizae Radix et Rhizoma.The high-frequency Chinese medicinals were mostly classified as blood-activating and stasis-resolving drugs and qi-replenishing drugs.The medicinal properties of the drugs were characterized by being warm,mild,or cold,the flavors were predominated by being sweet,pungent or bitter,and the medicinals usually had the meridian tropism of the spleen,lung and liver meridians.A total of 30 association rules were mined out,cluster analysis yielded 5 herbal groups,and factor analysis yielded 11 groups of common factors.Conclusion For the treatment of cardiovascular diseases,Professor HUANG Li follows the theory of qi,blood and water,and especially pays more attention to the ascending and descending of qi movement.For qi deficiency and blood stasis contribute to the basic pathogenesis of recurrent angina pectoris after PCI,the therapy of benefiting qi,activating blood and removing stasis is recommended.Moreover,the simultaneous regulation of five zang-organs and simultaneous use of the cold and warm herbs are performed,and the herbs of benefiting qi and invigorating spleen,resolving phlegm and inducing diuresis,tranquilizing mind,promoting qi and dissipating masses,and activating blood to eliminate stasis are used for adjuvant therapy.

AIM: To study the correlation between meibomian gland dysfunction(MGD)patients and their sleep quality.METHODS: Retrospective case-control study. A total of 150 MGD patients treated in our hospital from January 2021 to October 2022 were selected and divided into sleep disorder group(75 cases, PSQI>10 points)and control group(75 cases, PSQI≤10 points)according to the Pittsburgh sleep quality index(PSQI). Both groups were scored using the ocular surface disease index(OSDI), underwent meibomian gland-related examinations(eyelid margin morphology, meibomian gland secretion ability, meibomian gland secretion quality score), corneal fluorescein staining(FL)score, Schirmer Ⅰ test(SⅠt), tear film break-up time(BUT)was measured, and sleep indicators(sleep quality, sleep latency, subjective sleep quality, sleep time)were evaluated.RESULTS: There were significant differences in OSDI score, FL score, SⅠt, BUT, eyelid margin morphology score, meibomian gland secretion ability score, and meibomian gland secretion quality score between the two groups(P<0.05). In the sleep disorder group, PSQI score, sleep latency score, subjective sleep quality score, and sleep time score were significantly positively correlated with OSDI score, FL score, meibomian gland secretion ability score, and meibomian gland secretion quality score(P<0.05); PSQI score, subjective sleep quality score, and sleep time score were significantly positively correlated with eyelid margin morphology score(P<0.05); PSQI score, sleep latency score, and subjective sleep quality score were significantly negatively correlated with BUT and SⅠt(P<0.05); sleep time score was significantly negatively correlated with BUT(P<0.05); sleep latency score was not significantly correlated with eyelid margin morphology score(P>0.05); sleep time score was not significantly correlated with SⅠt(P>0.05).CONCLUSION:The ocular surface condition of MGD patients is correlated with multiple sleep quality indicators, and a decline in sleep quality may increase the risk of MGD.

As an indicator that measures the degree of implementation of intervention measures during the implementation process, fidelity could be used for monitoring and quality evaluation of the completion degree of intervention measures, and plays an important role in improving the degree of intervention implementation and clarifying the factors that affect intervention implementation. This article aims to introduce the connotation and significance, measurement, control, and current application status of fidelity, as well as the current application status of fidelity in acupuncture-moxibustion clinical research and its inspiration for future research. Meanwhile, based on the existing evaluation tool development methods of fidelity and the characteristics of acupuncture-moxibustion clinical research, a preliminary fidelity evaluation framework is proposed. Introducing fidelity into acupuncture-moxibustion clinical research could improve the implementation quality and compliance of acupuncture-moxibustion in clinical research, increase the credibility and effectiveness of clinical research results, and promote the transformation of acupuncture-moxibustion experience into easily learnable and promotable treatment plans.
Moxibustion ; Acupuncture Therapy

Cancer is one of the major fatal diseases that seriously threaten human health， and its burden needs to be solved urgently. Health technology assessment （HTA） can provide scientific evidence-based basis for cancer diagnosis， treatment， prevention and related policy formulation. Cost-utility analysis is the gold standard for economic evaluation in HTA， and the accurate measurement of its health utility is one of the key elements to determine the accuracy of its results. This article focuses on systematic introduction of direct measures， multi-attribute health utility scales， and mapping methods in the field of cancer measurement and reviews their applications in cancer patients. Among them， direct measures are complex， costly， and require a high level of subject knowledge； multi-attribute health utility measures are currently the preferred method for measuring health utility in cancer patients； with the continuous development and refinement of disease-specific utility measures in multi-attribute health utility instruments， the mapping method may gradually decrease in future applications. This paper can provide a reference for the selection of health utility measurement tools for HTA in the field of cancer， and provide evidence-based basis for optimizing resource allocation and policy formulation in the field of cancer.

This study used machine learning techniques combined with routine blood cell analysis parameters to build preliminary prediction models, helping differentiate patients with depression from healthy controls, or patients with anxiety. A multicenter study was performed by collecting blood cell analysis data of Beijing Chaoyang Hospital and the First Hospital of Hebei Medical University from 2020 to 2021. Machine learning techniques, including support vector machine, decision tree, naïve Bayes, random forest and multi-layer perceptron were explored to establish a prediction model of depression. The results showed that based on the blood cell analysis results of healthy controls and depression group, the accuracy of prediction model reached as high as 0.99, F1 was 0.975. Receiver operating characteristic curve area and average accuracy were 0.985 and 0.967, respectively. Platelet parameters contributed mostly to depression prediction model. While, to random forest differential diagnosis model based on the data from depression and anxiety groups, prediction accuracy reached 0.68 and AUC 0.622. Age, platelet parameters, and average volume of red blood cells contributed the most to the model. In conclusion, the study researched on the prediction model of depression by exploring blood cell analysis parameters, revealing that machine learning models were more objective in the evaluation of mental illness.
Humans ; Depression ; Bayes Theorem ; Machine Learning ; Support Vector Machine ; Blood Cell Count

This study used machine learning techniques combined with routine blood cell analysis parameters to build preliminary prediction models, helping differentiate patients with depression from healthy controls, or patients with anxiety. A multicenter study was performed by collecting blood cell analysis data of Beijing Chaoyang Hospital and the First Hospital of Hebei Medical University from 2020 to 2021. Machine learning techniques, including support vector machine, decision tree, naïve Bayes, random forest and multi-layer perceptron were explored to establish a prediction model of depression. The results showed that based on the blood cell analysis results of healthy controls and depression group, the accuracy of prediction model reached as high as 0.99, F1 was 0.975. Receiver operating characteristic curve area and average accuracy were 0.985 and 0.967, respectively. Platelet parameters contributed mostly to depression prediction model. While, to random forest differential diagnosis model based on the data from depression and anxiety groups, prediction accuracy reached 0.68 and AUC 0.622. Age, platelet parameters, and average volume of red blood cells contributed the most to the model. In conclusion, the study researched on the prediction model of depression by exploring blood cell analysis parameters, revealing that machine learning models were more objective in the evaluation of mental illness.
Humans ; Depression ; Bayes Theorem ; Machine Learning ; Support Vector Machine ; Blood Cell Count

OBJECTIVES: To evaluate the report quality, methodological quality and evidence quality of the systematic reviews and meta-analyses (SRs/MAs) of acupuncture for in vitro fertilization-embryo transfer (IVF-ET). METHODS: The SRs/MAs of acupuncture for IVF-ET were searched electronically from databases of CNKI, Wanfang, VIP, SinoMed, PubMed, Embase, Cochrane Library, from inception of each database to September 27th, 2022. Two reviewers independently screened the literature and extracted the data. Using PRISMA statement, the AMSTAR 2 scale and the GRADE system, the report quality, methodological quality and evidence quality of the included SRs/MAs were assessed. RESULTS: A total of 28 SRs/MAs were included, with PRISMA scores ranging from 8.5 points to 27 points. The problems of report quality focused on protocol and registration, retrieval, risk of bias in studies, additional analysis, limitations and funding. The methodological quality of included studies was generally low, reflecting on items 2, 3, 7, 10, 12 and 16. A total of 85 outcome indexes were included in the GRADE system for evidence grade evaluation. Most of the evidences were low or very low in quality. The reasons for the downgrade were related to study limitations, inconsistency, imprecision and publication bias. CONCLUSIONS Acupuncture therapy improves the outcomes of IVF-ET, but the methodological quality and evidence quality of related SRs/MAs are low. It is recommended to conduct more high-quality studies in the future to provide more reliable evidences.
Acupuncture Therapy/methods* ; Databases, Factual ; Embryo Transfer ; Fertilization in Vitro ; Publication Bias ; Systematic Reviews as Topic

Uric acid (UA) is the final product of purine metabolism in human body,and its metabolic disorder will induce hyperuricemia (HUA).The occurrence and development of HUA are associated with a variety of pathological mechanisms such as oxidative stress injury,activation of inflammatory cytokines,and activation of renin-angiotensin-aldosterone system.These mechanisms directly or indirectly affect the bioavailability of endogenous nitric oxide (NO).The decrease in NO bioavailability is common in the diseases with high concentration of UA as an independent risk factor.In this review,we summarize the mechanisms by which high concentrations of UA affect the endogenous NO bioavailability,with a focus on the mechanisms of high-concentration UA in decreasing the synthesis and/or increasing the consumption of NO.This review aims to provide references for alleviating the multisystem symptoms and improving the prognosis of HUA,and lay a theoretical foundation for in-depth study of the correlations between HUA and other metabolic diseases.
Humans ; Nitric Oxide ; Uric Acid ; Hyperuricemia ; Biological Availability ; Cytokines