ObjectiveTo construct a standardized diagnostic scale for Qi-Yin deficiency with blood stasis syndrome in diabetic macrovascular disease. MethodsLiterature related to Qi-Yin deficiency with blood stasis syndrome in diabetic macrovascular disease was retrieved from CNKI， VIP， and Wanfang databases. Diagnostic information from four diagnostic methods was extracted and standardized， with items having a frequency of ≥15 included in the item pool. A three-round Delphi expert consultation was conducted， screening items using support degree， mean score， rank sum， and coefficient of variation. Item weights were determined using analytic hierarchy process （AHP）， gactor analysis （FA）， and combined weighting method （CWM）. The optimal weighting method was selected by comparing the area under the receiver operating characteristic （ROC） curve （AUC）. The Youden index was calculated to establish the diagnostic cutoff value， which was proportionally scaled. ResultsA total of 102 studies were included. Thirty-five items were incorporated into the item pool. The authority coefficients for the three Delphi rounds were 0.82， 0.85， and 0.86， with coordination coefficients of 0.648， 0.538， and 0.506， respectively. Fifteen items were retained after screening. ROC curve analysis showed the AUC ranking as FA > CWM > AHP. The maximum Youden index was 0.814， corresponding to a diagnostic cutoff of 8.361 （scaled to 40 points）. The final scale adopted a structured diagnostic framework： the symptom dimension requires at least 2 items， and the tongue or pulse dimension requires at least 1 category. ConclusionThis study developed a standardized diagnostic scale for Qi-Yin deficiency with blood stasis syndrome in diabetic macrovascular disease. Core items were screened via the Delphi method， with factor analysis identified as the optimal weighting method through AUC comparison. The diagnostic threshold （40 points） and structured diagnostic framework provide a quantitatively clear， clinically practical tool.

Imaging examination is a crucial part in diagnosis and treatment of central nervous system infection(CNSI),involving complex imaging sequences and parameters.This consensus was jointly written by multiple CNSI imaging experts in China,aimed to standardize imaging examination of CNSI.

OBJECTIVE To formulate an expert consensus on the prevention and control of respiratory infectious diseases in railway stations and trains in China,and to standardize the prevention and control of respiratory infec-tious diseases in railway stations and trains scientifically.METHODS The government authorities organized multi-ple prevention and control experts from transportation,medical care and prevention fields to conduct in-depth re-search through methods such as meetings and on-site investigations,and combined with their practical experi-ence in this field to formulate this expert consensus.RESULTS In-depth studies were conducted on the prevention and control strategies,measures and emergency response system construction of respiratory infectious diseases in railway stations and trains,and this expert consensus was formed.CONCLUSION This expert consensus supple-ments improves the existing prevention and control system for respiratory infectious diseases in railway stations and trains,and provides an important reference basis for the prevention and control of respiratory infectious disea-ses in railway stations and trains.

Objective To screen the predictors of early initiation of continuous renal replacement therapy(CRRT)in children with sepsis and construct a linear model,based on LASSO regression analysis.Methods A total of 55 children diagnosed with sepsis at Jiangmen Maternity and Child Health Care Hospital from April 2023 to February 2025.They were divided into CRRT group(n=17)and non-CRRT group(n=38)based on CRRT treatment usage.Using LASSO regression screening,predictive factors were identified and a Logistic regression model was established.The model's performance was evaluated using receiver operating characteristic(ROC)curve and calibration curve.Results There were significant differences in age,respiratory rate,body temperature,and mechanical ventilation between two groups(P＜0.05).Through LASSO regression analysis,four independent predictors of respiratory rate,body temperature,blood glucose,and C-reactive protein were identified.The constructed model demonstrated an area under the ROC curve of 0.94(95％CI:0.87-1.00),indicating good calibration accuracy.Conclusion The column line model based on body temperature,respiratory rate,blood glucose and C-reactive protein can effectively predict the need for early initiation of CRRT in sepsis children.

Cilia,as cellular sensory organelles,actively partici-pate in and regulate cellular processes such as autophagy and metabolic breakdown during their generation and transportation.Autophagy,on the other hand,is a cell self-protection mecha-nism that maintains cellular homeostasis by clearing aggregates and damaged organelles.Combining recent research findings,this review comprehensively elucidates the bidirectional crosstalk between primary cilia and autophagy.Specifically,it highlights the crucial role of cilia-dependent signaling pathways in activa-ting cellular autophagy and how autophagy regulates cilia genera-tion and length by degrading specific ciliary proteins.Moreover,the dysregulation of primary cilia and autophagy is closely asso-ciated with the clinical manifestations and pathogenesis of vari-ous ciliopathy-related diseases such as polycystic kidney disease and tuberous sclerosis.In terms of pharmacotherapy,this review provides a comprehensive and in-depth overview of small mole-cule inhibitors targeting ciliogenesis,including cytoskeletal drugs and Hedgehog signaling pathway inhibitors.Despite the current limitations in clinical use,these drugs lay the groundw-ork for developing highly specific targeted small molecule inhibi-tors of ciliogenesis and for the treatment of ciliopathies and canc-ers.By systematically discussing ciliogenesis,autophagy,disea-ses and drugs,this review offers new insights for further elucida-ting the crosstalk between ciliogenesis and autophagy,exploring their pathological mechanisms in disease development,and de-veloping therapeutic strategies in the future.

AIM To study the chemical constituents from Commelina communis L.METHODS The 95％ethanol extract from C.Communis was isolated and purified by activated charcoal,silica gel,Sephadex LH-20,and HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.RESULTS Seventeen compounds were isolated and identified as p-hydroxyl ethyl cinnamate(1),p-hydroxybenzaldehyde(2),vanillin(3),4-hydroxy-2,3-dimethyl-2-nonen-4-olide(4),hemeratrol A(5),chakyunglupulin B(6),chakyunglupulin A(7),2-(2-hydroxyethyl)-3-methylfumaric acid(8),N-cis-feruloyl tyramine(9),N-trans-coumaroyltyramine(10),5,6,7,3',4',5'-hexamethoxyflavone(11),N-trans-sinapoyltyramine(12),dihydro-feruloyltyramine(13),N-trans-feruloyltyramine(14),2-phenylethanol-β-D-glucoside(15),quercetin-3-O-β-D-glucoside(16),and isorhamnetin-3-O-β-D-glucopyranoside(17).CONCLUSION Compounds 4-8,10 and 11 are isolated from Commelina genus for the first time,and 1,9,12-15 are first isolated from this plant.

Central nervous system(CNS)degenerative disorders refer to a spectrum of pathological alterations triggered by struc-tural damage to cerebral neural tissues,clinically manifested as diverse neurological dysfunction syndromes,including multiple sclerosis(MS),neurodegenerative diseases(NDs),and ische-mic stroke.The hallmark pathological features of these disorders involve irreversible neuronal damage and decompensation of functional neural networks,ultimately leading to progressive neurological deficits.Notably,with the accelerating global popu-lation aging,the incidence of these diseases has surged signifi-cantly.According to WHO statistics,they now rank among the top three global causes of disability and mortality.Current re-search has confirmed that the pathogenesis of CNS degenerative disorders exhibits high heterogeneity,encompassing multifaceted pathophysiological processes such as genetic predisposition,oxi-dative stress,protein misfolding,and metabolic dysregulation.This intricate pathogenic network not only complicates clinical differential diagnosis but also poses substantial challenges to the development of precision therapeutic strategies.Importantly,re-cent studies have revealed that mitochondrial homeostasis disrup-tion-induced inflammatory cascades(termed mitochondrial in-flammation)play a pivotal regulatory role in neurodegenerative progression.Key molecular mechanisms include impaired mito-phagy,aberrant mitochondrial DNA(mtDNA)release and NL-RP3 inflammasome activation.This review systematically deci-phers the molecular regulatory network of mitochondrial inflam-mation,with a focus on its biological effects in critical pathologi-cal events such as blood-brain barrier disruption,microglial hy-peractivation and neuronal apoptosis.The overarching aim is to provide a theoretical foundation for developing innovative thera-peutic strategies targeting mitochondrial homeostasis restoration.

Objective:To develop and validate machine learning models for predicting the cumulative live birth rate (CLBR) following in vitro fertilization (IVF) and to analyze key predictive features using SHAP values. Methods:This retrospective study included data from patients who underwent IVF-embryo transfer at the Department of Reproductive Medicine, Baoding Maternal and Child Health Hospital, between January 2017 and December 2022. Patients were categorized into two groups based on live birth outcome: the live birth group ( n=1 036) and the non-live birth group ( n=756). The dataset was randomly divided into a training set and a validation set in a ratio of 7∶3. Five algorithms were utilized for model development: logistic regression, random forest, extreme gradient boosting (XGBoost), support vector machine, and neural networks. Model performance was assessed using the area under the receiver operating characteristic (AUC) curve, F1 score, and calibration curves. Clinical decision curve analysis (DCA) was employed to evaluate the clinical utility of the models. SHAP values were used to interpret feature importance in the XGBoost model and enhance its explainability. Results:The XGBoost model demonstrated the best performance in predicting CLBR,with accuracy of 72.44%, AUC of 0.775, and F1 score of 0.654, accuracy and F1 score outperforming logistic regression (accuracy was 70.02%, F1 score was 0.585), random forest (accuracy was 71.69%, F1 score was 0.606), support vector machine (accuracy was 70.20%, F1 score was 0.607), and neural network (accuracy was 68.72%, F1 score was 0.560). The calibration curve of XGBoost closely aligned with the diagonal line, indicating that the predicted probabilities were very close to the actual outcomes, demonstrating good calibration. DCA indicated that the XGBoost model provided higher net benefits across a wide range of clinical decision thresholds. SHAP value analysis identified number of previous IVF failures, antral follicle count, anti-Müllerian hormone level, percentage of normal sperm morphology, and sperm DNA fragmentation index as key predictors of CLBR.Conclusion:The XGBoost model exhibits excellent predictive performance and calibration for CLBR, with SHAP values providing important insights into feature importance. This model has the potential to support the development of personalized treatment strategies in clinical practice. However, its generalizability needs to be validated using external datasets to ensure its applicability to diverse populations.

Objective:To investigate the effects and its related mechanism of placenta-derived mesenchymal stem cells(PMSCs)on the lipopolysaccharides(LPS)damaged astrocytes.Methods:Primary astrocytes were isolated from the cerebral cortex of neonatal rats.The expression of glial fibrillary acidic protein(GFAP)was identified using immu-nofluorescence staining to evaluate the purity of the primary astrocytes.PMSCs were cocultured with LPS-treated astro-cytes.The expression levels of factors related to inflammation including interleukin-1β(IL-1β),inducible nitric oxide synthase(iNOS),tumor necrosis factor-α(TNF-α),interleukin-6(IL-6),arginase-1(Arg-1),S100 calcium-bind-ing protein A10(S100A10),and TGF-β/Smad signaling pathway-related proteins such as transforming growth factor beta 1(TGF-β1),transforming growth factor beta type I receptor(TβRⅠ),transforming growth factor beta type II re-ceptor(TβRⅡ),phospho-Smad2 and phospho-Smad3(p-Smad2,p-Smad3)in astrocytes from each group were detec-ted using real time RT-PCR or Western blot techniques.Results:Astrocytes at the third passage exhibited an 80%pos-itivity rate for GFAP.After treated with 10 μg/ml LPS,the astrocytes expression levels of pro-inflammatory factors IL-1β,iNOS,IL-6,and TNF-α were significantly increased(P<0.05),while their expression levels of the anti-inflam-matory factors of Arg-1 and S100A10 were significantly decreased(P<0.05).Meanwhile,their expression levels of TGF-β/Smad signaling pathway related proteins of TGF-β1,TβRⅠ,TβRⅡ,p-Smad2 and Smad3 were increased(P<0.05).After the LPS damaged astrocytes were cocultured with PMSCs,their expression levels of pro-inflammatory factors IL-1β,iNOS,IL-6,and TNF-α were significantly decreased(P<0.05),while their expression levels of the anti-inflammatory factors of Arg-1 and S100A10 were significantly increased(P<0.05).Also,their expression levels of TGF-β/Smad signaling pathway related proteins of TGF-β1,TβRⅠ,TβRⅡ,p-Smad2,and Smad3 were decreased(P<0.05).Conclusion:PMSCs may inhibit the activation of A1 astrocytes through the TGF-β/Smad signaling path-way,by which reducing the astrocytic activation.

AIM To investigate effects of petroleum ether fraction from Derris eriocarpa How on glucose and lipid metabolism in a mouse model of metabolic syndrome(MS).METHODS KM mice were fed a high-fat diet and administered streptozotocin intraperitoneally to establish MS models.The MS mice were then randomly assigned to the model group,the metformin hydrochloride group,the lovastatin group,the ursolic acid group,and the high-,medium-and low-dose D.eriocarpa petroleum ether fraction groups,with 10 mice in each group.Ten additional mice maitained on a normal diet served as the normal control group.After 4 weeks of intragastric administration,glucose and lipid metabolism indicators were measured.Hepatic pathological changes were assessed using HE staining and oil red O staining.Liver tissue mRNA expressions of ATF3,PEPCK,FXR,CYP7A1,HNF4ɑ,CYP8B1 and SRB1 were quantified by RT-qPCR.Hepatic protein expressions of ATF3,HNF4ɑ,PEPCK,FXR and CYP7A1 was analyzed by Western blot in MS mice.RESULTS Compared to the model group,the high-dose D.eriocarpa petroleum ether fraction group exhibited significant glucose tolerance improvement(reduced OGTT-AUC,P＜0.01);favorable serum lipid modulation in terms of increased HDL-C levels(P＜0.01)and decreased TG,TC,LDL-C(P＜0.01);reduced renal biomarkers(BUN,SCR)and hepatotoxic indicators of TBA,AST and ALT activities(P＜0.01);alleviated hepatic lipid accumulation and histopathological damage;downregulated mRNA and protein expressions of ATF3,HNF4ɑ and PEPCK,as well as CYP8B1 mRNA expression(P＜0.01);and upregulated mRNA and protein expressions of FXR and CYP7A1,along with SRB1 mRNA expression(P＜0.01).CONCLUSION D.eriocarpa petroleum ether fraction ameliorates glucose and lipid metabolism dysregulation in MS mice by modulating the ATF3/HNF4ɑ/CYP7A1 signaling pathway,consequently eliciting hypoglycemic,hypolipidemic,hepatoprotective and nephroprotective effects.