ObjectiveTo observe the influence and therapeutic effect of quercetin on cuproptosis in rheumatoid arthritis rats and to explore its possible mechanism based on the solute carrier family 31 member 1 （SLC31A1）/ferredoxin 1 （FDX1） pathway. MethodsSixty male SD rats were divided into six groups： A control group， a model group， high- and low-dose quercetin groups （150 and 50 mg·kg^-1）， a cuproptosis inhibitor （tetrathiomolybdate， TTM） group （10 mg·kg^-1）， and a methotrexate group （2 mg·kg^-1）， 10 rats in each group. Except for the control group， the model of rheumatoid arthritis （CIA） rats was established by type Ⅱ collagen induction method. After successful modeling， each drug group was intervened according to the corresponding dose of drugs， and the control group and the model group were given the same amount of normal saline by gavage， once a day， which lasted for 4 weeks. The swelling degree of rats' feet was observed， and the clinical arthritis scores were determined. The levels of serum rheumatoid factor （RF）， matrix metalloproteinase-3 （MMP-3）， tumor necrosis factor-α （TNF-α）， interleukin-1β （IL-1β）， interleukin-10 （IL-10）， and ceruloplasmin （Cp） were detected by enzyme-linked immunosorbent assay （ELISA）. The content of copper ion （Cu）， malondialdehyde （MDA）， superoxide dismutase （SOD）， and glutathione （GSH） in joint tissue was detected. Hematoxylin-eosin （HE） staining was used to observe the pathological changes of joint tissue. The levels of reactive oxygen species （ROS） and dihydrolipoic acid transacetylase （DLAT） were detected by immunofluorescence （IF）. The protein and mRNA expression of SLC31A1， FDX1， lipoic acid synthase （LIAS）， heat shock protein 70 （HSP70）， pyruvate dehydrogenase E1 subunit β （PDHB）， and copper transporting P-type ATPase β （ATP7B） was detected by immunohistochemistry （IHC） and real-time fluorescence quantitative polymerase chain reaction （Real-time PCR）. ResultsCompared to the control group， the model group exhibited joint swelling and deformity， significantly increased clinical arthritis scores， obvious bone destruction， synovial hyperplasia， and inflammatory cell infiltration in joint tissue. In addition， the serum levels of RF， MMP-3， TNF-α， IL-1β， and Cp showed significant elevation， while the level of IL-10 was significantly reduced. The levels of Cu， MDA， ROS， and DLAT in joint tissue were markedly increased， whereas SOD and GSH content was significantly decreased. The protein and mRNA expression of SLC31A1 and HSP70 was significantly up-regulated， while the protein and mRNA expression of FDX1， LIAS， PDHB， and ATP7B was significantly down-regulated （P<0.01）. Compared to the model group， each treatment group exhibited varying degrees of improvement in joint swelling and deformation as well as clinical arthritis scores in rats. Additionally， there was a reduction in joint bone destruction， inflammatory cell infiltration， and synovial hyperplasia in rats. Furthermore， the serum levels of RF， MMP-3， TNF-α， IL-1β， and Cp significantly decreased， while the level of IL-10 increased significantly. In joint tissue， the levels of Cu， MDA， ROS， and DLAT showed significant decreases， while SOD and GSH content exhibited significant increases. The protein and mRNA expression of SLC31A1 and HSP70 was down-regulated， while the protein and mRNA expression of FDX1， LIAS， PDHB， and ATP7B was up-regulated （P<0.05）. ConclusionQuercetin effectively reduces synovial hyperplasia and inflammatory infiltration in rats with rheumatoid arthritis， thereby alleviating pathological damage to joint tissue. This effect may be attributed to the blockade of the SLC31A1/FDX1 signaling pathway activation and inhibition of excessive cuproptosis.

[Objective]To investigate the value of radiomics based on contrast-enhanced computed tomography(CT)image in predicting the traditional Chinese medicine(TCM)differentiation typing of primary non-small cell lung cancer(NSCLC).[Methods]A total of 130 patients diagnosed as NSCLC by pathology from July 2018 to October 2023 in Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University were retrospectively analyzed.According to the diagnostic criteria of TCM,all the enrolled patients were divided into deficiency syndrome group(67 cases)and excess syndrome group(63 cases),and then assigned to training cohort(91 cases)and validation cohort(39 cases)in a ratio of 7:3.The largest diameter slice of lesion on cross-sectional images was selected and the regions of interest were contoured at unenhanced,arterial and venous phases respectively,and then the radiomics features were extracted.The linear correlation among features and L1 regularization were used for feature selection,and then logistic regression was used to construct the radiomics model based on radiomics features of each phase.The receiver operating characteristic(ROC)curve was used to evaluate the effectiveness of the model in predicting deficiency and excess syndromes of NSCLC.The Delong test was used for comparison of area under curve(AUC)between the two models.[Results]In the training cohort,a total of 7 radiomics models were constructed,including three single-phase radiomics models,three two-phase combination radiomics models and one three-phase combination radiomics model.The AUC of combination radiomics model was higher than that of the single-phase radiomics model.The AUC of three-phase combination radiomics model was the largest,which was 0.876[95%confidence interval(CI)(0.807～0.945)]and 0.755[95%CI(0.603～0.908)]in the training cohort and validation cohort respectively.[Conclusion]The radiomics model based on contrast-enhanced CT image has high efficacy in predicting the TCM differentiation typing of NSCLC,and the three-phase combination radiomics model demonstrates the best diagnostic efficacy.

Objective To analyze the differences in bone serum protein between patients with osteoporosis accompanied by obstructive sleep apnea syndrome(OSAS)and those with osteoporosis only using proteomics.Methods A total of 80 osteoporosis patients who attended our hospital between June 2022 and June 2024 were enrolled.Based on their polysomnography results,the participants were divided into an OSAS and osteoporosis comorbidity(OSAS-osteoporosis)group(n=42)and an osteoporosis only group(n=38).Propensity score matching was applied to incorporate covariates in logistic regression so that the individual characteristics of the two groups of patients were generally balanced.Following the matching procedure,a final cohort of 20 matched pairs was obtained and subsequently utilized for further analysis.The mass spectrum was obtained using laser desorption ionization mass spectrometry.Principal component analysis(PCA)was performed to assess differences in metabolic patterns between groups.Partial least squares discriminant analysis(PLS-DA)and orthogonal PLS-DA(OPLS-DA)were employed for further data analysis.Variable importance in projection(VIP)scores of each substance were calculated with OPLS-DA to screen the metabolites showing inter-group differences.Heatmaps were generated to visualize metabolic profile differences between the OSAS-osteoporosis group and the osteoporosis group.Enrichment pathway analysis was conducted on the differential identified metabolites.Results After propensity score matching,individual characteristics between the groups were well balanced.Mass spectrometry revealed significant differences between the OSAS-osteoporosis and osteoporosis groups.In the PCA score plot,the separation trend of the two groups was not significant.The PLS-DA score plot showed a discernible separation trend,with R2 and Q2 lower than those of the corresponding results of the real model,confirming the reliability of the model.OPLS-DA showed that the total R2X of the model was 0.635,R2Y was 0.879,and O2Y was 0.728,showing obvious separation trends between the two groups.A total of 16 differential metabolites were identified,including stearyl-oleyl-glycerol phosphate choline,phosphate choline,L-histidine,erucamide,2'-deoxyuridine,1-palmitoyl glycerol,thymine,tyramine,L-pyroglutamic acid,L-glutamic acid,myristate,glycerol-3-phosphate,caprylic acid,pregnenolone,L-arginine,D-4-hydroxyphenylglycine,and isobutyric acid.Heatmaps showed significant differences in metabolic profiles between the OSAS-osteoporosis group and the osteoporosis group.Pathway enrichment analysis showed that 27 metabolic pathways were involved.27 metabolic pathways.Under the conditions of P<0.05 and pathway impact>0.2,the three most significant metabolic pathways identified included mainly alanine,aspartate,and glutamate metabolism,arginine biosynthesis,and histidine metabolism.Conclusion Significant differences were observed in the metabolic profiles between patients with both OSAS and osteoporosis and those with osteoporosis alone.

OBJECTIVE To standardize the main processes and related technical links of the clinical comprehensive evaluation of drugs， and provide guidance and reference for improving the quality of comprehensive evaluation evidence and its transformation and application value. METHODS The construction of Guideline for the Workflow of Clinical Comprehensive Evaluation of Drugs was based on the standard guideline formulation method of the World Health Organization （WHO）， strictly followed the latest definition of guidelines by the Institute of Medicine of the National Academy of Sciences of the United States， and conformed to the six major areas of the Guideline Research and Evaluation Tool Ⅱ. Delphi method was adopted to construct the research questions； research evidence was established by applying the research methods of evidence-based medicine. The evidence quality classification system of the Chinese Evidence-Based Medicine Center was adopted for evidence classification and evaluation. The recommendation strength was determined by the recommendation strength classification standard formulated by the Oxford University Evidence-Based Medicine Center， and the recommendation opinions were formed through the expert consensus method. RESULTS & CONCLUSIONS The Guideline for the Workflow of Clinical Comprehensive Evaluation of Drugs covers 4 major categories of research questions， including topic selection， evaluation implementation， evidence evaluation， and application and transformation of results. The formulation of this guideline has standardized the technical links of the entire process of clinical comprehensive evaluation of drugs， which can effectively guide the high-quality and high-efficient development of this work， enhance the standardized output and transformation application value of evaluation evidence， and provide high-quality evidence support for the scientific decision-making of health and the rationalization of clinical medication.

Objective:To establish and optimize an autoverification system for thyroid function test reports of 5 items using historical test data.Methods:Based on the docoment' Autoverification of Clinical Laboratory Quantitative Test Results′, CLSI AUTO 10-A and AUTO 15 guidelines, an autoverification system for thyroid function test reports of 5 items was established combining with manual verification experience. A total of 193 860 thyroid function test reports of 5 items in 2021 were collected for the assessment of the original system. Totally 210 097 thyroid function test reports of 5 items in 2022 and 299 198 reports in 2023 were collected for the optimization of the autoverification system. There were 160 666 thyroid function test reports of 5 items from the first half of 2024 for the manual and autoverification comparison after optimization.Results:The pass rate of the autoverification system based on original thyroid function report in 2021 was 69.56%(134 849/193 860). The optimized system utilizing historical data from 2022 and 2023 covered 21 pattern rules and established verification for different patterns including range rules, delta check rules, and review rules. Taking manual verification as the standard for the data from the first half of 2024, the sensitivity and specificity of the optimized system were 100% (499/499) and 81.57% (130 646/160 167), respectively, with a false-negative rate of 0. The concordance rate between autoverification and manual verification was 81.63% (131 145/160 666), and the pass rate was 81.32% (130 646/160 666).Conclusion:Establishing and optimizing the autoverification system for thyroid function tests of 5 items using historical test data, and formulating verification rules for different patterns can be applied to clinical practise, which not only ensures the accuracy of test reports but also improves work efficiency, allowing continuously optimized and perfected of the system.

[Objective]To investigate the value of radiomics based on contrast-enhanced computed tomography(CT)image in predicting the traditional Chinese medicine(TCM)differentiation typing of primary non-small cell lung cancer(NSCLC).[Methods]A total of 130 patients diagnosed as NSCLC by pathology from July 2018 to October 2023 in Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University were retrospectively analyzed.According to the diagnostic criteria of TCM,all the enrolled patients were divided into deficiency syndrome group(67 cases)and excess syndrome group(63 cases),and then assigned to training cohort(91 cases)and validation cohort(39 cases)in a ratio of 7:3.The largest diameter slice of lesion on cross-sectional images was selected and the regions of interest were contoured at unenhanced,arterial and venous phases respectively,and then the radiomics features were extracted.The linear correlation among features and L1 regularization were used for feature selection,and then logistic regression was used to construct the radiomics model based on radiomics features of each phase.The receiver operating characteristic(ROC)curve was used to evaluate the effectiveness of the model in predicting deficiency and excess syndromes of NSCLC.The Delong test was used for comparison of area under curve(AUC)between the two models.[Results]In the training cohort,a total of 7 radiomics models were constructed,including three single-phase radiomics models,three two-phase combination radiomics models and one three-phase combination radiomics model.The AUC of combination radiomics model was higher than that of the single-phase radiomics model.The AUC of three-phase combination radiomics model was the largest,which was 0.876[95%confidence interval(CI)(0.807～0.945)]and 0.755[95%CI(0.603～0.908)]in the training cohort and validation cohort respectively.[Conclusion]The radiomics model based on contrast-enhanced CT image has high efficacy in predicting the TCM differentiation typing of NSCLC,and the three-phase combination radiomics model demonstrates the best diagnostic efficacy.

Objective:To establish and optimize an autoverification system for thyroid function test reports of 5 items using historical test data.Methods:Based on the docoment' Autoverification of Clinical Laboratory Quantitative Test Results′, CLSI AUTO 10-A and AUTO 15 guidelines, an autoverification system for thyroid function test reports of 5 items was established combining with manual verification experience. A total of 193 860 thyroid function test reports of 5 items in 2021 were collected for the assessment of the original system. Totally 210 097 thyroid function test reports of 5 items in 2022 and 299 198 reports in 2023 were collected for the optimization of the autoverification system. There were 160 666 thyroid function test reports of 5 items from the first half of 2024 for the manual and autoverification comparison after optimization.Results:The pass rate of the autoverification system based on original thyroid function report in 2021 was 69.56%(134 849/193 860). The optimized system utilizing historical data from 2022 and 2023 covered 21 pattern rules and established verification for different patterns including range rules, delta check rules, and review rules. Taking manual verification as the standard for the data from the first half of 2024, the sensitivity and specificity of the optimized system were 100% (499/499) and 81.57% (130 646/160 167), respectively, with a false-negative rate of 0. The concordance rate between autoverification and manual verification was 81.63% (131 145/160 666), and the pass rate was 81.32% (130 646/160 666).Conclusion:Establishing and optimizing the autoverification system for thyroid function tests of 5 items using historical test data, and formulating verification rules for different patterns can be applied to clinical practise, which not only ensures the accuracy of test reports but also improves work efficiency, allowing continuously optimized and perfected of the system.

Pulmonary blast injury has become the main type of trauma in modern warfare, characterized by externally mild injuries but internally severe injuries, rapid disease progression, and a high rate of early death. The injury is complicated in clinical practice, often with multiple and compound injuries. Currently, there is a lack of effective protective materials, accurate injury detection instrument and portable monitoring and transportation equipment, standardized clinical treatment guidelines in various medical centers, and evidence-based guidelines at home and abroad, resulting in a high mortality in clinlcal practice. Therefore, the Trauma Branch of Chinese Medical Association and the Editorial Committee of Chinese Journal of Trauma organized military and civilian experts in related fields such as thoracic surgery and traumatic surgery to jointly develop the Clinical treatment guideline for pulmonary blast injury ( version 2023) by combining evidence for effectiveness and clinical first-line treatment experience. This guideline provided 16 recommended opinions surrounding definition, characteristics, pre-hospital diagnosis and treatment, and in-hospital treatment of pulmonary blast injury, hoping to provide a basis for the clinical treatment in hospitals at different levels.

Neoplasms immunotherapy has made a major breakthrough in the clinical practice of refractory tumor. However, there are still individual differences in treatment results and drug resistance in clinical application. Gastrointestinal microbiome is gradually recognized as an immunoregulatory factor in recent years, and more and more studies have focused on its influences on the efficacy of tumor immunotherapy. Targeting gastrointestinal microbiota to improve the response of tumor patients to immunotherapy has potential clinical application value.

Objective:To investigate the risk factors of severe chest trauma complicated by acute respiratory distress syndrome (ARDS).Methods:A case control study was conducted to analyze the clinical data of 120 patients with severe chest trauma admitted to 909th Hospital of Joint Logistics Support Force (Affiliated Dongnan Hospital of Xianmen University Medical College) from January 2018 to December 2020. There were 75 males and 45 females; aged 21-72 years [(42.2±4.8)years]. The causes of injury were traffic injury in 57 patients, crush injury in 21, fall injury in 21, smash injury in 11 and others in 10. There were 34 patients accompanied by fracture of the limb, spine and pelvis, 23 by abdominal organ injury and 8 by head trauma, with the exception of simple thoracic trauma in 55 patients. The patients were divided into ARDS group ( n=25) and non-ARDS group ( n=95) according to the condition of concurrent ARDS. The two groups were compared regarding the gender, age, causes of injury, respiratory rate, lung contusion, lung infection, flail chest, chest abbreviated injury scale (AIS), hemothorax, blood pressure, partial arterial oxygen pressure (PaO 2), initial central venous pressure (CVP) on admission, combined fracture of the limb, spine and pelvis, combined head injury and combined abdominal organ injury. The correlation between the above indexes and ARDS after severe chest trauma was analyzed by univariate analysis. Multivariate Logistic regression analysis was used to determine the independent risk factors for ARDS after severe chest trauma. Results:Univariate analysis showed a positive correlation of ARDS with age, respiratory rate, lung contusion, lung infection, flail chest, chest AIS, hemothorax, blood pressure, PaO 2, initial CVP on admission, combined fracture of the limb, spine and pelvis and combined abdominal organ injury ( P<0.05 or 0.01), but not with gender, causes of injury or combined head injury (all P>0.05). Multivariate Logistic regression analysis revealed that age ≥60 years ( OR=2.45, 95% CI 1.81-7.50, P<0.01), dyspnea (respiratory rate ≥28 times/minute or <10 times/minute) ( OR=9.55, 95% CI 2.26-9.38, P<0.01), lung contusion ( OR=6.78, 95% CI 1.84-6.96, P<0.01), lung infection ( OR=27.71, 95% CI 11.97-64.14, P<0.01), flail chest ( OR=8.97, 95% CI 2.29-14.97, P<0.01), chest AIS score ( OR=5.77, 95% CI 2.85-9.20, P<0.01), above medium amount of hemothorax ( OR=6.84, 95% CI 1.69-13.39, P<0.01), blood pressure <90 mmHg ( OR=7.93, 95% CI 1.64-11.84, P<0.01), PaO 2<60 mmHg ( OR=6.39, 95% CI 1.06-9.47, P<0.01) and absent initial CVP on admission ( OR=4.56, 95% CI 1.86-8.44, P<0.01) were significantly correlated with ARDS. Conclusion:Age ≥60 years, dyspnea (respiratory rate ≥28 times/minute or <10 times/minute), lung contusion, lung infection, flail chest, chest AIS, above medium l amount of hemothorax, blood pressure <90 mmHg, PaO 2<60 mmHg and absent initial CVP on admission are independent risk factors for ARDS in patients with severe chest trauma.