Objective·To develop a graph neural network(GNN)-based auxiliary diagnostic model for gallbladder cancer on CT images,and validate its accuracy and feasibility.Methods·From January 2010 to November 2023,1 774 contrast-enhanced CT arterial-phase images were acquired from 887 patients with normal gallbladder,benign gallbladder disease,or gallbladder cancer at Xinhua Hospital and Renji Hospital,Shanghai Jiao Tong University School of Medicine.These images were randomly divided into training and testing sets at a 4∶1 ratio to develop a hybrid GNN-convolutional neural network(CNN)model,named VJK-GIN.The model constructed a pixel-level graph in which each pixel served as a node,and spatial adjacency defined the edges,enabling extraction of local texture features.In the model architecture design,VJK-GIN integrated a three-layer graph isomorphism network,augmented with virtual nodes and jump-knowledge connections;global pooling compressed node features into a graph-level representation,which was classified by a multi-layer perceptron head.Five-fold cross-validation was used to compare VJK-GIN with GNN baselines(GCN,GraphSAGE,GAT,and GIN)and CNN baselines(ViT,EfficientNetV2,and ConvNeXt)in terms of accuracy,precision,recall,F1-score,and area under the receiver operating characteristic curve(AUC).Results·The results of five-fold cross-validation showed that VJK-GIN achieved an F1-score of 0.799(95%CI 0.775?0.823),recall of 0.795(95%CI 0.773?0.817),precision of 0.799(95%CI 0.775?0.823),AUC of 0.812(95%CI 0.792?0.832),and accuracy of 0.773(95%CI 0.748?0.798),surpassing all competing models across every metric.Conclusion·The VJK-GIN model exhibits high stability and accuracy in identifying contrast-enhanced CT images of normal,benign,and malignant gallbladder conditions.

Cholesterol(CH)plays a crucial role in enhancing the membrane stability of drug delivery systems(DDS).However,its association with conditions such as hyperlipidemia often leads to criticism,overshadowing its influence on the biological effects of formulations.In this study,we reevaluated the delivery effect of CH using widely applied lipid microspheres(LM)as a model DDS.We conducted comprehensive in-vestigations into the impact of CH on the distribution,cell uptake,and protein corona(PC)of LM at sites of cardiovascular inflammatory injury.The results demonstrated that moderate CH promoted the accumulation of LM at inflamed cardiac and vascular sites without exacerbating damage while partially mitigating pathological damage.Then,the slow cellular uptake rate observed for CH@LM contributed to a prolonged duration of drug efficacy.Network pharmacology and molecular docking analyses revealed that CH depended on LM and exerted its biological effects by modulating peroxisome proliferator-activated receptor gamma(PPAR-γ)expression in vascular endothelial cells and estrogen receptor alpha(ERα)protein levels in myocardial cells,thereby enhancing LM uptake at cardiovascular inflam-mation sites.Proteomics analysis unveiled a serum adsorption pattern for CH@LM under inflammatory conditions showing significant adsorption with CH metabolism-related apolipoprotein family members such as apolipoprotein A-V(Apoa5);this may be a major contributing factor to their prolonged circu-lation in vivo and explains why CH enhances the distribution of LM at cardiovascular inflammatory injury sites.It should be noted that changes in cell types and physiological environments can also influence the biological behavior of formulations.The findings enhance the conceptualization of CH and LM delivery,providing novel strategies for investigating prescription factors' bioactivity.

Aim To investigate the effect of triptolide(TP)on corticosterone(CORT)-induced depression-like behaviors in mice and explore the antidepressant mechanism of TP based on the CREB/BDNF/TrkB sig-naling pathway.Methods Sixty 8-week-old male C57BL/6J mice were randomly divided into five groups:control group,CORT group,TP groups of low and high doses(10,30 μg·kg-1),and fluoxetine(FLU)group(10 mg·kg-1).Except for the control group,the other groups received subcutaneous injec-tions of CORT for three consecutive weeks to establish the model of depression.During the last two weeks of modeling,normal saline,TP and FLU were adminis-tered via intraperitoneal injection respectively.After the administration,depression-like behaviors in mice were assessed using forced swimming test,tail suspen-sion test,and sucrose preference test.Biochemical methods were used to measure the levels of SOD and MDA in the hippocampus and prefrontal cortex(PFC).Cell apoptosis was detected by TUNEL meth-od.Immunohistochemistry,immunofluorescence,and Western blotting were employed to detect the expres-sion of apoptosis/autophagy-related proteins,synaptic structure markers,and proteins related to the CREB/BDNF/TrkB signaling pathway.Results TP signifi-cantly ameliorated CORT-induced depression-like be-haviors in mice,mainly manifested by reduced immo-bility time in the tail suspension test and forced swim-ming test,and increased sucrose preference rate.TP alleviated CORT-induced oxidative stress by increasing SOD levels and reducing MDA production in brain tis-sue.Additionally,TP also inhibited apoptosis and ex-cessive autophagy of neurons in the hippocampus and prefrontal cortex,maintained synaptic plasticity,and significantly upregulated the expression of p-CREB,BDNF,and TrkB.Conclusions TP exhibits potential antidepressant effect in mice by upregulating the CREB/BDNF/TrkB signaling pathway,reducing oxida-tive stress,inhibiting excessive neuronal apoptosis and autophagy,and improving synaptic plasticity.

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 a graph neural network(GNN)-based auxiliary diagnostic model for gallbladder cancer on CT images,and validate its accuracy and feasibility.Methods·From January 2010 to November 2023,1 774 contrast-enhanced CT arterial-phase images were acquired from 887 patients with normal gallbladder,benign gallbladder disease,or gallbladder cancer at Xinhua Hospital and Renji Hospital,Shanghai Jiao Tong University School of Medicine.These images were randomly divided into training and testing sets at a 4∶1 ratio to develop a hybrid GNN-convolutional neural network(CNN)model,named VJK-GIN.The model constructed a pixel-level graph in which each pixel served as a node,and spatial adjacency defined the edges,enabling extraction of local texture features.In the model architecture design,VJK-GIN integrated a three-layer graph isomorphism network,augmented with virtual nodes and jump-knowledge connections;global pooling compressed node features into a graph-level representation,which was classified by a multi-layer perceptron head.Five-fold cross-validation was used to compare VJK-GIN with GNN baselines(GCN,GraphSAGE,GAT,and GIN)and CNN baselines(ViT,EfficientNetV2,and ConvNeXt)in terms of accuracy,precision,recall,F1-score,and area under the receiver operating characteristic curve(AUC).Results·The results of five-fold cross-validation showed that VJK-GIN achieved an F1-score of 0.799(95%CI 0.775?0.823),recall of 0.795(95%CI 0.773?0.817),precision of 0.799(95%CI 0.775?0.823),AUC of 0.812(95%CI 0.792?0.832),and accuracy of 0.773(95%CI 0.748?0.798),surpassing all competing models across every metric.Conclusion·The VJK-GIN model exhibits high stability and accuracy in identifying contrast-enhanced CT images of normal,benign,and malignant gallbladder conditions.

Heat stroke is a heat-related illness caused by an imbalance between the body's heat production and heat dissipation,which could lead to multiple organ dysfunction syndrome with a high mortality rate.Rapid and effective reduction of core body temperature is key to successful treatment.This article reviews recent progress in the treatment of heat stroke,including new understandings of organ injury mechanisms,the timing,velocity and goals of cooling treatment,evaluation and selection of traditional cooling techniques(such as cold water immersion),and scientific evaluation of new cooling technologies(such as blood purification technology and intravascular heat exchange cooling technology),aiming to promote understanding and treatment of heat stroke.

Aim To investigate the effect of triptolide(TP)on corticosterone(CORT)-induced depression-like behaviors in mice and explore the antidepressant mechanism of TP based on the CREB/BDNF/TrkB sig-naling pathway.Methods Sixty 8-week-old male C57BL/6J mice were randomly divided into five groups:control group,CORT group,TP groups of low and high doses(10,30 μg·kg-1),and fluoxetine(FLU)group(10 mg·kg-1).Except for the control group,the other groups received subcutaneous injec-tions of CORT for three consecutive weeks to establish the model of depression.During the last two weeks of modeling,normal saline,TP and FLU were adminis-tered via intraperitoneal injection respectively.After the administration,depression-like behaviors in mice were assessed using forced swimming test,tail suspen-sion test,and sucrose preference test.Biochemical methods were used to measure the levels of SOD and MDA in the hippocampus and prefrontal cortex(PFC).Cell apoptosis was detected by TUNEL meth-od.Immunohistochemistry,immunofluorescence,and Western blotting were employed to detect the expres-sion of apoptosis/autophagy-related proteins,synaptic structure markers,and proteins related to the CREB/BDNF/TrkB signaling pathway.Results TP signifi-cantly ameliorated CORT-induced depression-like be-haviors in mice,mainly manifested by reduced immo-bility time in the tail suspension test and forced swim-ming test,and increased sucrose preference rate.TP alleviated CORT-induced oxidative stress by increasing SOD levels and reducing MDA production in brain tis-sue.Additionally,TP also inhibited apoptosis and ex-cessive autophagy of neurons in the hippocampus and prefrontal cortex,maintained synaptic plasticity,and significantly upregulated the expression of p-CREB,BDNF,and TrkB.Conclusions TP exhibits potential antidepressant effect in mice by upregulating the CREB/BDNF/TrkB signaling pathway,reducing oxida-tive stress,inhibiting excessive neuronal apoptosis and autophagy,and improving synaptic plasticity.

Objective To propose a brain electrical phase prediction method based on long short-term memory network(LSTM)to improve the accuracy and robustness of phase synchronization prediction in transcranial magnetic stimulation(TMS).Methods First,an LSTM consisting of an input layer,an LSTM layer,an ReLU activation layer,a fully connected layer and a regression layer was constructed to capture the EEG signal features through the synergistic action of input gates,forgetting gates and output gates.Second,eye-open resting-state EEG data from 30 healthy subjects were trained using the LSTM to obtain a predictive model for EEG signal and EEG phase prediction.Finally,the LSTM method and the traditional autoregressive(AR)method were compared in terms of the phase prediction errors at the overall and individual levels and the prediction performance for peaks and troughs.A regression model was used to explore the relationships between instantaneous EEG amplitude,signal-to-noise ratio and phase prediction error with the LSTM method.Results The LSTM method achieved a total phase prediction error of 0.04°±5.69°,which was lower than that of the traditional AR method(-3.36°±51.13°).For each subject,the LSTM method demonstrated superior phase prediction accuracy compared to the traditional AR method(P＜0.001).The accuracy for predicting peaks(troughs)by the LSTM method(about 89％)was higher than that by the traditional AR method(about 10％).Unlike the traditional AR method,the LSTM method didnot result in linear relationships between instantaneous EEG amplitude,signal-to-noise ratio and phase prediction error,with Pvalues being 0.58 and 0.18,respectively.Conclusion The LSTM-based brain electrical phase prediction method shows high accuracy and robustness when used for EEG phase-synchronized TMS.[Chinese Medical Equipment Journal,2025,46(3):1-8]

Hilar cholangiocarcinoma is insidious in onset and often causes obstructive jaundice due to bile stasis,leading to impaired liver function.For tumors with malignant obstructive jaundice,biliary drainage is often performed before surgery in clinical practice.Currently,the commonly used drainage methods are percutaneous transhepatic biliary drainage(PTBD)and endoscopic retrograde biliary drain-age(ERBD),but there are controversies over the advantages and disadvantages of the two drainage methods.PTBD drainage can often lead to tumor implantation metastasis,but the underlying mechanism remains unclear.We detected tumor cells in PTBD and ERBD bile samples from hilar cholangiocarcino-ma patients,subsequently explored their tumorigenicity and mechanisms through tumorsphere assay in vitro and xenograft tumor models in vivo.The experiments included benign gallstones group(30 cases)as a negative control,PTBD group(14 cases)and ERBD group(13 cases).Tumorsphere formation was i-dentified in 3 cases(23％)among the 13 cases of ERBD group,in 6 cases(42％)among the 14 cases of PTBD group,but there were no tumor cells or formed tumorspheres in the 30 cases of benign gallstone group.The tumor sphere formation ability of cells in the PTBD group was significantly higher than that in ERBD group.Subcutaneous xenograft tumor assays showed that tumor growth in the PTBD group was sig-nificantly higher than that in the ERBD group.Tumor cells in PTBD bile possessed stronger tumorigenici-ty compared with the ERBD group.Mechanically,stem cell transcription factor Nanog mRNA levels were significantly higher in the PTBD group compared to the ERBD group.Both tumorsphere formation and xenograft tumor growth were reduced by Nanog knockdown in three cases of the PTBD group,indicating the important roles of Nanog in tumorigenicity of PTBD group tumor cells.The half-life of Nanog mRNA was longer in PTBD group cells than in ERBD group cells,suggesting potential post-transcriptional regu-lation on Nanog mRNA.The Nanog m6A level was higher in PTBD group tumor cells compared to the ERBD group.Analysis of methyltransferases and demethylases,ALKBH5(α-ketoglutarate dependent dioxygenase alkb family homolog 5)mRNA levels were lower in the PTBD group than in the ERBD group and significantly correlated with the m6A level of Nanog.ALKBH5 knockdown led to an increase in the m6A level of Nanog,while ALKBH5 overexpression decreased the m6A level of Nanog.Dual-luciferase activity assays demonstrated that ALKBH5 knockdown significantly enhanced luciferase activity,whereas ALKBH5 overexpression reduced it.Further studies confirmed that ALKBH5 knockdown upregulated both the mRNA and protein levels of Nanog,whereas overexpressing ALKBH5 downregulated them.ALKBH5 mediated the demethylation modification of Nanog mRNA,and the lower levels of ALKBH5 expression in the PTBD group promoted Nanog's m6A modification.Overexpressing ALKBH5 decreased tumorsphere growth,while ALKBH5 knockdown increased it,which was subsequently reduced by the simultaneous Nanog knockdown again.In sum,tumor cells in PTBD and ERBD drainage bile from hilar cholangiocar-cinoma patients exhibited tumorigenicity.Compared to the ERBD group,tumor cells in PTBD bile with lower ALKBH5 expression levels enhanced Nanog's m6A modification to upregulate Nanog expression levels,resulting in stronger tumorigenicity.These findings are significant for elucidating propensity to tumor implantation metastasis from PTBD drainage.

Objective To propose a brain electrical phase prediction method based on long short-term memory network(LSTM)to improve the accuracy and robustness of phase synchronization prediction in transcranial magnetic stimulation(TMS).Methods First,an LSTM consisting of an input layer,an LSTM layer,an ReLU activation layer,a fully connected layer and a regression layer was constructed to capture the EEG signal features through the synergistic action of input gates,forgetting gates and output gates.Second,eye-open resting-state EEG data from 30 healthy subjects were trained using the LSTM to obtain a predictive model for EEG signal and EEG phase prediction.Finally,the LSTM method and the traditional autoregressive(AR)method were compared in terms of the phase prediction errors at the overall and individual levels and the prediction performance for peaks and troughs.A regression model was used to explore the relationships between instantaneous EEG amplitude,signal-to-noise ratio and phase prediction error with the LSTM method.Results The LSTM method achieved a total phase prediction error of 0.04°±5.69°,which was lower than that of the traditional AR method(-3.36°±51.13°).For each subject,the LSTM method demonstrated superior phase prediction accuracy compared to the traditional AR method(P＜0.001).The accuracy for predicting peaks(troughs)by the LSTM method(about 89％)was higher than that by the traditional AR method(about 10％).Unlike the traditional AR method,the LSTM method didnot result in linear relationships between instantaneous EEG amplitude,signal-to-noise ratio and phase prediction error,with Pvalues being 0.58 and 0.18,respectively.Conclusion The LSTM-based brain electrical phase prediction method shows high accuracy and robustness when used for EEG phase-synchronized TMS.[Chinese Medical Equipment Journal,2025,46(3):1-8]