Studies on specific transient receptor potential melastatin 2 (TRPM2) channel inhibitors can deepen our understanding of the pathological mechanism of related diseases, and allow discovery of novel, effective targets and drugs for therapy. The development of TRPM2 channel inhibitors can be broadly classified into four categories with distinct characteristics: reutilization and structural modification of homologous ion channel modulators to produce a diverse array of TRPM2 channel inhibitors with strong inhibitory effects; TRPM2 channel inhibitors based on channel gating mechanism with high specificity; inhibitors identified through high-throughput screening with novel chemical structures; inhibitors developed from natural antioxidants with higher safety. In recent years, the application of computer-aided drug design has significantly accelerated the development of TRPM2 channel inhibitors. Several promising compounds such as ZA18, A1 and D9 have been discovered, and it is expected that more potent and selective TRPM2 channel inhibitor scaffolds will be discovered in the future. This article reviews the advances on the studies of TRPM2 channel inhibitors, aiming to provide insights for further research and clinical application of TRPM2 channel inhibitors.
TRPM Cation Channels/antagonists & inhibitors* ; Humans ; Drug Design

The development and application of processing technology is closely related to the quality of Chinese medicine. Currently， Chinese medicine processing is still in the mechanization stage with limited processing equipment， low levels of automation and intelligence. As a result， the imprecise control of parameters during processing leads to unstable quality of Chinese herbal pieces. However， with the arrival of the big data era and the continuous development of "Internet+"， Chinese medicine processing technology and equipment have been continuously improved and updated， and gradually shifted to the development direction of automation and intelligence. The linkage production technology of Chinese herbal pieces optimizes the separate processing equipment coupling into the production line for continuous manufacture of Chinese herbal pieces， intending to improve production efficiency. The large-scale industrialized production of Chinese herbal pieces tends towards digital technology of processing experience and online inspection technology based on machine vision， electronic nose， and electronic tongue. These technologies are crucial prerequisites for standardizing the parameters of Chinese medicine processing. And further by docking the processing process and equipment with the internet， realizing the intelligent control of the production process is an important process for the transformation and upgrading of Chinese herbal piece industry in the future. In this paper， we summarized the development characteristics of different stages of Chinese medicine processing technology， combed application and development of processing theory， the evolution of processing equipment， and problems in the current industrial development stage of Chinese medicine processing， in order to provide ideas and methods for achieving digital and intelligent innovation of processing technology as well as high-efficient and high-quality production of Chinese herbal pieces.

Objective:To describe the detail sampling design,weighting,instruments,filed procedures and quality control methods of the epidemiological survey on dementia among community residents in Tongliao City.Methods:A three-stage disproportionate probability sampling design was used to investigate the inhabitants aged 65 years and over in Tongliao City,Inner Mongolia Autonomous Region.The 10/66 Dementia Research Group(10/66 DRG)assessment instruments were used to diagnose dementia,using computer-assisted personal interview mode in the selected older people.Comprehensive quality control methods were implemented throughout the field-work.Results:A total of 166 villages or communities were sampled from nine counties or districts in Tongliao Cit-y.Totally 4 345 older people were interviewed with 96.2％response rate.By calculating sampling design weights,non-response adjustment weights and post-stratification adjustment weights,these weights were multiplied and per-formed trimming adjustment and standardization adjustment to generate final weights.The 171 interviewers were well-trained and qualified to carry out filed interview.Quality control methods included computer data check,audio record check,and telephone check in order to ensure the quality of the survey.Conclusion:This survey is imple-mented using a rigorous sampling design and timely quality control methods,and uses the 10/66 DRG assessment instruments with satisfactory international validity and reliability as survey instruments,which has international cross-cultural comparability.It provides a valid and feasible methodology of epidemiological survey on dementia for further studies in different regions in China.

Objective This study aimed to investigate the factors influencing the personal burden rate incerebral ische-mic patients,compare the difference in the burden rate among the patients with varying degrees of cerebral ischemia,provide a reference for establishing a personal burden rate evaluation,and propose suggestions for control its increase.Methods The medi-cal insurance data were collected from 8164 discharged patients in a tertiary hospital in Tianjin between January and December 2022.With the data,the Generalized Linear Model was utilized to analyze the factors affecting the personal burden rate across different Diagnosis Related Groups(DRGs).Results Statistically significant differences were observed in the cost structure a-mong different DRGs.Age,length of hospital stays,total hospitalization cost,hospital admission mode,number of hospitaliza-tions,and type of medical insurance significantly impacted the personal burden rate.The personal burden rate was inversely cor-related with age and length of hospital stays,but directly correlated with the total hospitalization cost.The patients admitted from emergency,first-time hospitalization,and those covered by the basic medical insurance program for urban employees had a lower personal burden rate.Conclusion Hospitals should establish diverse personal burden rate performance evaluation standards for patients with different types of medical insurance,incorporating factors such as average length of hospital stays and average hospi-talization cost.A more equitable hospital internal assessment plan should be developed by considering patients admitted to differ-ent departments and aligning with the characteristics of clinical pathways.Medical institutions should minimize self-funded pro-jects under declared medical insurance,increase the enrollment of cases in DRGs,and promote tiered diagnosis and treatment to reduce the personal burden rate for patients.

Objective To analyze the research hotspots and trends of early mobilization in ICU patients with mechanical ventilation. Methods The literature on early mobilization of ICU patients with mechanical ventilation included in the China National Knowledge Infrastructure (CNKI) and Web of Science databases from 2000 to 2023 was searched. CiteSpace visualization software was used for literature analysis, and the publication volume and keywords of the literature were displayed in the form of maps. The research hotspots and problems in this field were analyzed. Results A total of 116 Chinese articles and 145 English articles related to early mobilization in ICU patients with mechanical ventilation were retrieved. The number of English articles increased with fluctuations, while the number of Chinese articles showed a steady growth trend overall, both of which fell slightly in 2020. The research focused on early mobilization, mechanical ventilation, ICU-acquired weakness and delirium. Chinese articles formed 11 clusters such as early mobilization, mechanical ventilation, nursing, review and muscle strength; English articles formed 10 clusters such as critical care, delirium and pilot study. The high-frequency keyword in 2023 was goal-directed. Conclusion Domestic and foreign scholars pay high attention to the early mobilization of ICU patients with mechanical ventilation, focusing on the impact of early mobilization on diseases and the evaluation of its effects. The research content in this field is rich, but there are few evidence-based practical studies.

Immune Checkpoint Inhibitors ; Transcriptome ; Immunotherapy ; Biomarkers, Tumor

Pathological dry skin is a disturbing and intractable healthcare burden,characterized by epithelial hy-perplasia and severe itch.Atopic dermatitis(AD)and psoriasis models with complications of dry skin have been studied using single-cell RNA sequencing(scRNA-seq).However,scRNA-seq analysis of the dry skin mouse model(acetone/ether/water(AEW)-treated model)is still lacking.Here,we used scRNA-seq and in situ hybridization to identify a novel proliferative basal cell(PBC)state that exclusively expresses transcription factor CUT-like homeobox 1(Cux1).Further in vitro study demonstrated that Cux1 is vital for keratinocyte proliferation by regulating a series of cyclin-dependent kinases(CDKs)and cyclins.Clinically,Cux1+PBCs were increased in patients with psoriasis,suggesting that Cux1+ PBCs play an important part in epidermal hyperplasia.This study presents a systematic knowledge of the tran-scriptomic changes in a chronic dry skin mouse model,as well as a potential therapeutic target against dry skin-related dermatoses.

Objective To compare the differences in radiation doses from CT scanning between children of different age groups and adult patients by using both traditional radiation dose assessment parameters and size-specific dose estimates (SSDE).Methods A total of 406 patients undergoing lung CT examination were studied.They were sampled retrospectively and continuously from the Union Hospital and divided into six groups by age distritution (0-2,3-6,7-10,11-14,15-18,＞18 years old).The CTDIvol and DLP values were randomly sampled using MATLAB platform-based dicom data software.The SSDE and water equivalent diameter were also calculated according to the AAPM 220 Report.The differences in radiation doses from lung CT scaning between children and adult patients were analysed.Results The CTDIvol values for all age groups were significantly lower than the SSDE values.The differences were statistically significant (t =-36.36,-32.83,-30.36,-28.74,-23.89,P＜0.05).The SSDE values were 137％,94％,79％,57％ and 42％ higher than the CTDIvol values,respectively.The CTDIvol values for the adult group were also lower than the SSDE values,and the difference was statistically significant (t=-21.92,P＜0.05),and the SSDE value was about 41％ higher than the CTDIvol value.With the increased age,CTDIvol value,DLP value,Dw value and SSDE value for children of all age groups gradually increased and were significantly smaller than those for the adult group.The difference was statistically significant (F=63.39,203.28,89.27,103.44,P＜0.05).The conversion coefficient f for all age groups decreased significantly with age,which was significantly higher than that for the adult group,and the difference was statistically significant (F =109.83,P ＜ 0.05).Conclusions In lung CT scanning,the CTDIvol value significantly underestimated the radiation doses to children as compared to adults.CTDIvol values are more easily underestimated for younger patients.The SSDE method allows for more accurate reflection of the radiation doses to different patients,taking into account differences in the examined patient size.

Objective: To explore the feasibility of constructing a machine learning classification model for unilateral sudden sensorineural hearing loss (SSHL) patients and normal controls based on diffusion tensor imaging. Methods: Prospective collection of 84 patients with untreated SSHL were recruited from the otolaryngology department of the Union Hospital of Tongji Medical College of Huazhong University of Science and Technology between June 2013 to May 2015 as the SSHL group. Meanwhile, a total of 63 healthy volunteers who were no any ear disease history, and the hearing function were confirmed with pure tone audiometry, were collected as the control group. All subjects underwent a brain DTI scan. The data were divided into the training set and validation set according to the ratio of 7 to 3, that was, the training set contained 58 cases of SSHL patients and 44 control groups, and the validation set included 26 cases of SSHL patients and 19 control groups. A vector which included the DTI parameters such as fractional anisotropy, mean diffusivity, axial diffusivity and radial diffusivity was constructed with the software R. The LASSO regression of machine learning method was used to perform feature dimensionality reduction and construct a classification model. The training set samples were used to map the nomogram based on the multivariate logistic analysis method, the validation set and the AUC were used to evaluate the prediction ability of the nomogram, and the calibration curve was used to evaluate the model. Results: From the 200 feature vectors including the fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) values of each brain region, after each dimension reduction process, a total of six features were retained, which were the MD of left superior corona radiate and right superior fronto-occipital fasciculus, the AD of the body of corpus callosum, and the RD of left inferior cerebellar peduncle, left superior corona radiate and right posterior limb of internal capsule. The six features of patients with unilateral SSHL were higher than the control group, and the difference was statistically significant (P<0.05). Based on this, a two-class model is constructed and a nomogram is drawn. The sensitivity, specificity, accuracy and AUC of the training set were 93.1% (54/58), 72.7% (32/44), 84.3% (86/102) and 0.854, respectively; the sensitivity, specificity, accuracy and AUC of validation set were 80.8% (21/26), 84.2% (16/19), 82.2% (37/45), 0.870, respectively. Nomogram could significantly improve the classification efficiency of the control group and patients, and the model with the LASSO method showed a higher prediction curve than other models. Conclusions The machine learning classification model based on DTI metrics can effectively distinguish patients with unilateral sudden sensorineural deafness from healthy control people.