Exogenous harmful residues and endogenous toxic components are the main contents of safety analysis for animal traditional Chinese medicine. This review summarizes the inspection methods for exogenous harmful residues, as well as the research methods for the toxic effects and mechanisms of endogenous toxic components. The strategies for enhancing efficacy and reducing toxicity of toxic animal drugs and quality control, and prospects the development trend of safety analysis for animal drugs were also discussed. In the detection of exogenous harmful residues in animal drugs, traditional methods such as atomic absorption spectrometry and inductively coupled plasma mass spectrometry are widely used, and new methods such as high-resolution mass spectrometry and biochemical analysis are continuously developing. In the study of endogenous toxic components, the toxic components and mechanisms of some animal drugs including cantharidin and toad venom have been revealed through chemical composition analysis, toxicity tests and multiomics technologies, and some strategies for enhancing efficacy and reducing toxicity have been proposed based on this. In the future, it is necessary to strengthen multidisciplinary integration to innovate detection technologies, clarify toxic mechanisms to achieve efficacy enhancement and toxicity reduction, and improve the biosafety research system, so as to enhance the quality and safety of traditional Chinese medicine animal drugs and promote the internationalization process of traditional Chinese medicine.

Numerous studies have shown that depression is main-ly associated with the abnormal expression of connexin 43(Cx43)in astrocytes(Astro)and its mediated dysfunction of gap junction(GJ).However,the molecular mechanism of post-translational modifications targeting Cx43 to regulate neuroin-flammation-associated depression is still unclear.Post-transla-tional modifications of Cx43 mainly include phosphorylation of specific amino acid sites by PKC,PKA,PKG,MAPK and PTK,and protein degradation of Cx43 through the K48/K63 polyubiq-uitylation and deubiquitination pathways,which ultimately lead to protein degradation through K48/K63 polyubiquitination and deubiquitination.These modifications are ultimately involved in the regulation of neuroinflammatory responses through the associ-ation of GJ function.In this paper,we systematically review the role of Cx43 post-translational modifications in neuroinflamma-tion,with the aim of further exploring the potential application of targeting these modifications to modulate the inflammatory re-sponse mechanism in improving depressive symptoms.

Chronic kidney disease(CKD)is a chronic disease characterized by renal structural damage and dysfunction.At present,there is still a lack of effective therapeutic drugs and prevention and treatment methods for CKD in clinical practice.More and more studies have shown that necroptosis,as a new type of programmed cell death,plays a vital role in the onset and progression of CKD.Targeting key molecules in the necroptosis pathway,such as RIPK1,RIPK3 and MLKL,the development of small molecule inhibitors has become an emerging strategy for the treatment of CKD,and has shown significant potential to pro-tect the kidneys and alleviate renal fibrosis in a variety of in vitro and in vivo models.Therefore,this article summarizes the re-search progress of the mechanism of necroptosis in recent years,and focuses on the potential role of necroptosis in the pathogene-sis of CKD and the therapeutic potential of targeting this path-way,providing a new perspective and research direction for the prevention and treatment of CKD in the future.

Objective To detect the characteristics of whole-brain functional changes in patients with subjective tinnitus(ST)after"frontal-temporal"dual-site repetitive transcranial magnetic stimulation(rTMS)by resting-state functional magnetic resonance imaging(rs-fMRI).Methods A total of 45 ST patients were enrolled,and assessments of tinnitus severity and rs-fMRI scans were performed before and 2 weeks after treatment with"frontal-temporal"dual-site rTMS.Regional homogeneity(ReHo),fractional amplitude of low-frequency fluctuations(fALFF),degree centrality(DC)and seed-based functional connectivity(FC)were analyzed before and after treatment in ST patients.Results Tinnitus handicap inventory(THI)score of ST patients 2 weeks after treatment was significantly decreased compared with that before treatment(P<0.001).ReHo values of the right inferior parietal lobule decreased,fALFF values of the right temporal pole increased,fALFF values of the right superior temporal gyrus decreased,and DC(weighted)and DC(Binarized)values of the right medial temporal gyrus all decreased in ST patients 2 weeks after treatment compared with those before treatment(P<0.05,GRF correction).Using the above differential brain regions as seed points for FC analysis,FC values between right superior temporal gyrus(fALFF)and right middle temporal gyrus reduced,FC values between right middle temporal gyrus[(DC(weighted)]and right superior occipital gyrus reduced,and FC values between right middle temporal gyrus[DC(Binarized)]and right superior occipital gyrus reduced 2 weeks after treatment compared with those before treatment(P<0.05,GRF correction).Conclusion"Frontal-temporal"dual-site rTMS is initially effective for ST patients,and the auditory and non-auditory brain regions of ST patients showed different degrees of regional and interbrain function changes,mainly involving default mode network and visual-auditory network.

Objectives:To investigate the association between the triglyceride-glucose(TyG)index and risk of non-alcoholic fatty liver disease(NAFLD)in young and middle-aged(<60 years)adults.Methods:From June 2006 to October 2007,47 675 employees of Kailuan Group with no liver disease were selected as the study objects.Based on the TyG index quartile,participants were divided into Q1 group(TyG index≤8.08,n=11 924),Q2 group(8.0836.46,n=11 919),the association between TyG index,cum-TyG and cumulative exposure time and the risk of NAFLD was analyzed.Results:The average age of the study population was(44.3±8.7)years,36 345 participants were males(76.23%).During a median follow-up period of 11.55(7.28,13.89)years,4 635(9.72%)participants developed new-onset NAFLD.After adjusting for confounders,cox regression analysis showed that compared with the Q1 group,the HR(95%CI)for NAFLD in the Q2 to Q4 groups were 1.328(1.191-1.480),1.591(1.430-1.770),and 2.106(1.861-2.384),respectively,Ptrend<0.001.Compared with the cum-Q1 group,the HR(95%CI)for NAFLD in the cum-Q2 to cum-Q4 groups were 1.571(1.426-1.730),2.123(1.935-2.330)and 2.593(2.367-2.840),respectively,Ptrend<0.001.Compared with the TyG index for 0 year,the HR(95%CI)of NAFLD for 2,4 and 6 years was 1.333(1.196-1.486),1.879(1.690-2.088)and 3.184(2.860-3.545),respectively,Ptrend<0.001.Conclusions:Increased TyG index is an independent risk factor for the new-onset NAFLD in young and middle-aged population.

Objective To evaluate the transition rules of normal body mass index(BMI),overweight and metabolic syndrome(MetS)in patients with major depressive disorder(MDD).Methods Patients with MDD who had multiple admission records between Jan 2016 and Nov 2021 in Beijing Anding Hospital,Capital Medical University were included.Based on the overweight and metabolic syndrome status assessed at each admission,the patients were categorized into three states:normal BMI,overweight and metabolic syndrome.A multi-state Markov model was used to analyze the transition intensity and transition frequency between three states and the influence of covariates on transitions.Results A total of 892 records of 398 subjects were included,with a median age of 56 years old and 31.4% males.The median follow-up period was 40 months.The multi-state model showed that there were 494 transitions between the three states,of which 5.1% moved from normal BMI to overweight and 5.5% moved from overweight to MetS.The intensity of transition was the highest from overweight to MetS,9.52 times greater than overweight to normal BMI.After 48.53 months,MDD patients with normal BMI began to transition to MetS.For overweight MDD patients,the transition to MetS started after 8.77 months.MDD patients with normal BMI or overweight had 31.4% and 50.4% probabilities of developing Mets after 36 months.For MDD patients comorbid with MetS,the probability of staying at MetS was 51.2% after 36 months.Multivariate analysis showed that being unmarried was a risk factor against developing overweight in normal BMI MDD patients,while a higher level of education was a protective factor against developing MetS in overweight MDD patients.Conclusion MDD patients exhibited a higher intensity and risk of developing MetS,and it is not easy to reverse MetS,suggesting that BMI management and MetS intervention should be strengthened in MDD patients.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Objective To investigate the diagnostic value of our regression model based on quantitative parameters of dual-energy CT and clinical features for stages T2 and T3 colorectal cancer.Methods A cross-section study was performed on 91 patients with colorectal cancer confirmed by postoperative pathology in our hospital from January 2022 to November 2023.All of them underwent dual-energy CT examination.According to the pathological T staging criteria of Chinese Colorectal Cancer Diagnosis and Treatment Standard(2020 Edition),they were divided into T2 group(n=43)and T3 group(n=48).Univariate analysis was used to compare the differences in quantitative CT parameters and clinical features between the 2 groups,and the obtained significant variables were employed to construct diagnosis models by univariate or multivariate logistic regression analysis.The area under receiver operating characteristic curve(AUC)of the CT parametric model and the model combined with clinical features was compared to evaluate the efficacy of diagnosing T2 and T3 stages.Results Univariate analysis showed that carcinoembryonic antigen(CEA),N stage,tumor location,tumor longest diameter(LD),CT value of virtual noncontrast(CT-VNC),fat fraction,electron density(Rho)and dual energy index(DEI)were significantly different between the T2 and T3 groups(P＜0.05).Multivariate logistic regression analysis found that N stage,tumor location,LD,fat fraction and DEI were independent risk factors for the diagnosis of stage T3.The AUC value of the model of above CT parameters in diagnosing stage T3 colorectal cancer was 0.671(95％CI:0.558～0.783),and the AUC value of the combined model of above CT parameters and clinical features was 0.886(95％CI:0.815～0.957),and statistical difference was observed in the AUC value between the combined model and the CT parametric model(P＜0.01).Conclusion The regression model constructed with dual-energy CT quantitative parameters combined with clinical features has high value in the preoperative diagnosis of stages T2 and T3 colorectal cancer before surgery.

The fibrillization of α-synuclein(α-syn)is a key pathological hallmark of Parkinson's disease.Although biointerfaces play a crucial role in α-syn aggregation,the chiral regulation mechanisms remain insufficiently explored.In this work,chiral carbon dots(CD)were employed to construct nanoscale chiral interfaces,and surface-enhanced infrared absorption spectroscopy combined with nanoscale infrared spectroscopy was utilized to investigate the conformational transition ofα-syn at chiral interfaces.The results demonstrated that α-syn primarily adsorbed onto the chiral interfaces via electrostatic interactions,while spatial selectivity further modulated its conformational evolution.Notably,the D-CD interface exhibited high affinity,stabilizingα-syn in its helical conformation,whereas the L-CD and DL-CD interfaces,due to their weaker affinity,exposed aggregation-prone regions,thereby promotingβ-sheet formation and leading to the generation of oligomers and fibrils.This work elucidated the regulatory role of chiral interfaces inα-syn aggregation,providing theoretical insights for the design of protein aggregation inhibitors.

Objective:This study applies an integrated SWOT-CLPV framework combined with stakeholder analysis to systematically assess the strengths,weaknesses,opportunities,and threats of China's disease control inspector system,while identifying its control factors,leverage points,key problems,and vulnerabilities.Methods:Drawing on literature review,policy document analysis,and expert interviews with seven public health professionals,we extracted and categorized SWOT elements.A CLPV interaction analysis was conducted alongside stakeholder mapping to evaluate internal dynamics and systemic risks.Results:The inspector system demonstrates strengths in policy innovation and medical-public health integration,with external opportunities stemming from rising public health awareness and digital health advancements.However,the system faces weak endogenous momentum,limited leverage,and prominent control constraints and problem-prone areas,especially among grassroots institutions and inspectors themselves.Cross-sectoral coordination barriers and uneven local implementation contribute to significant institutional vulnerabilities.Conclusion:To enhance implementation and resilience,the system requires capacity building for key actors,improved governance structures,incentive and evaluation reforms,and strengthened coordination mechanisms to support the sustained and adaptive development of public health supervision.