OBJECTIVE: Patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection frequently develop central nervous system damage, yet the mechanisms driving this pathology remain unclear. This study investigated the primary pathways and key factors underlying brain tissue damage induced by the SARS-CoV-2 beta variant (lineage B.1.351). METHODS: K18-hACE2 and C57BL/6 mice were intranasally infected with the SARS-CoV-2 beta variant. Viral replication, pathological phenotypes, and brain transcriptomes were analyzed. Gene Ontology (GO) analysis was performed to identify altered pathways. Expression changes of host genes were verified using reverse transcription-quantitative polymerase chain reaction and Western blot. RESULTS: Pathological alterations were observed in the lungs of both mouse strains. However, only K18-hACE2 mice exhibited elevated viral RNA loads and infectious titers in the brain at 3 days post-infection, accompanied by neuropathological injury and weight loss. GO analysis of infected K18-hACE2 brain tissue revealed significant dysregulation of genes associated with innate immunity and antiviral defense responses, including type I interferons, pro-inflammatory cytokines, Toll-like receptor signaling components, and interferon-stimulated genes. Neuroinflammation was evident, alongside activation of apoptotic and pyroptotic pathways. Furthermore, altered neural cell marker expression suggested viral-induced neuroglial activation, resulting in caspase 4 and lipocalin 2 release and disruption of neuronal molecular networks. CONCLUSION These findings elucidate mechanisms of neuropathogenicity associated with the SARS-CoV-2 beta variant and highlight therapeutic targets to mitigate COVID-19-related neurological dysfunction.
Animals ; COVID-19/genetics* ; Mice ; Brain/metabolism* ; Apoptosis ; Mice, Inbred C57BL ; SARS-CoV-2/physiology* ; Pyroptosis ; Gene Expression Profiling ; Transcriptome ; Male ; Female

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Stent entrapment is a rare complication of percutaneous coronary intervention.In recent years,with the development of distal radial artery puncture technology,the rare complications related to distal radial artery have been gradually understood.This article describes a patient who underwent coronary intervention through a distal radial approach,and the stent was dislodged and trapped in the far radial artery.The patient came to our hospital for stent implantation because of acute extensive anterolateral myocardial infarction.During the intervention,the balloon could not be filled when the stent was released from the left anterior descending artery,and the retracting stent could not be used to remove the guide catheter.The stent was dislodged and embedded in the distal vessel.The sheath was inserted through the proximal radial reverse puncture,and the stent was captured with a snare and removed.

Objective To predict the risk of coronary atherosclerosis using cerebral small vessel disease and cerebral artery stenosis in order to assist early identification of coronary artery disease(CHD).Methods A retrospective analysis was conducted on 130 patients(aged≥65 years)who underwent cerebral MRI,magnetic resonance angiography(MRA),and coronary computed tomo-graphy angiography in the Chinese PLA General Hospital between January 2019 and December 2024.Based on coronary computed tomography angiography results,the patients were categorized into an asymptomatic CHD group(56 cases)and a non-CHD group(74 cases).Cerebral MRI and MRA were used to assess white matter hyperintensity,enlarged perivascular spaces,lacunar infarcts,cerebral microbleeds(CMB)scores,total score of cerebral small vessel disease and degree of cerebral artery stenosis.Multivariate logistic regression analysis was employed to identify the clinical and radiological indicators related to CHD.Then a predictive model was constructed,and then its performance in early predicting CHD was evaluated.Results Blood glucose,low-density lipoprotein cholesterol,CMB score≥ 1,and≥50％stenosis of the posterior cerebral artery were independent risk factors for CHD(P＜0.05).The combined predictive model integrating clinical indicators,cerebral small vessel disease,and cerebral artery stenosis demonstrated the best performance,with an AUC value of 0.867(95％CI:0.807-0.927),outperforming the clinical model and the clinical-cerebral small vessel disease model.Conclusion cerebral small vessel dis-ease and cerebral artery stenosis are closely related to coronary atherosclerosis.The predictive model integrating clinical features and cerebrovascular disease imaging markers provides impor-tant reference for early screening of CHD.

Objective To explore the application effect of dexmedetomidine combined with ropivacaine for quadratus lumborum block at the lateral supra-arcuate ligament(QLB-LSAL) in open hepatocellular carcinoma resection.Methods A prospective study was conducted in 60 patients who underwent elective open hepatocellular carcinoma resection at Jining First People's Hospital. The patients were randomly divided into the compound group and the control group,with 30 cases in each group. Patients in the compound group received QLB-LSAL combined general anesthesia,and patients in the control group received simple general anesthesia. All patients underwent patient controlled intravenous analgesia (PCIA)postoperatively. The mean arterial pressure (MAP),heart rate (HR) and visual analogue scale (VAS) scores during rest and coughing at different time points were observed and compared between the two groups. The number of postoperative PCIA compressions,the dosage of sufentanil,the first postoperative exhaust time,the first postoperative ambulation time,the hospital stay and the occurrence of adverse reactions of the two groups were recorded. Results In the compound group,the HR and MAP were significantly lower than those of the control group at the time of skin incision (T2) and at the end of surgery (T3);the VAS scores during rest and coughing were significantly lower than those of the control group at the time of exiting the anesthesia recovery room and 6 hours and 12 hours after surgery;and the PCIA compression times were significantly less than those of the control group;the dosage of sufentanil was significantly lower than that in the control group 0 to 24 hours after surgery,and the dosage of sufentanil was higher than that in the control group 25 to 48 hours after surgery;the first postoperative ambulation time and the first postoperative exhaust time were significantly earlier than those in the control group;and the above differences were statistically significant(P<0.05). There was no significant difference in the HR or MAP at 5 minutes into the operating room (T0) and 5 minutes before skin incision (T1),VAS scores during rest and coughing 24 hours and 48 hours after surgery,hospital stay and incidence of adverse reactions between the two groups (P>0.05).Conclusion For patients with open hepatocellular carcinoma resection,dexmedetomidine combined with ropivazine for QLB-LSAL can provide more ideal postoperative analgesia,reduce perioperative opioid consumption,and have less impact on circulatory system,which is conducive to rapid postoperative recovery.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Aim To explore the effect of astragalosideⅣ(AS-Ⅳ)on lipopolysaccharide(LPS)-induced po-larization and migration of RAW 264.7 macrophages and the underlying mechanism.Methods 1 mg·L-1 LPS was used to construct cell migration model.Scratch assay was utilized to determine cell migration rate.Immunofluorescence staining was utilized to de-tect the expression and location of F4/80,iNOS and Arg-1.CCK-8 assay was used to determine the viabili-ty of RAW 264.7 cells.Griess assay was used to measure NO content.Molecular docking was used to analyze the interaction between AS-Ⅳ and the core tar-gets such as cGAS and STING protein.Western blot was employed to detect the expression of iNOS,Arg-1,cGAS,STING,NF-κB p65 and p-NF-κB p65 protein.Results AS-Ⅳ significantly inhibited the migration and M1 polarization of RAW 264.7 cells induced by LPS.Moreover,AS-Ⅳ could interact with cGAS and STING protein,especially cGAS.Further Western blot assay showed that AS-Ⅳ significantly downregulated the expression of iNOS,cGAS,STING and p-NF-κB p65 protein.Conclusions AS-Ⅳ could promote mac-rophage M1 to M2 polarization,thereby inhibited mac-rophage migration through restraining the cGAS/STING/NF-κB signaling pathway,which provides a new therapeutic target for AS-Ⅳ to improve the early inflammatory response of AS.

Objective To predict the risk of coronary atherosclerosis using cerebral small vessel disease and cerebral artery stenosis in order to assist early identification of coronary artery disease(CHD).Methods A retrospective analysis was conducted on 130 patients(aged≥65 years)who underwent cerebral MRI,magnetic resonance angiography(MRA),and coronary computed tomo-graphy angiography in the Chinese PLA General Hospital between January 2019 and December 2024.Based on coronary computed tomography angiography results,the patients were categorized into an asymptomatic CHD group(56 cases)and a non-CHD group(74 cases).Cerebral MRI and MRA were used to assess white matter hyperintensity,enlarged perivascular spaces,lacunar infarcts,cerebral microbleeds(CMB)scores,total score of cerebral small vessel disease and degree of cerebral artery stenosis.Multivariate logistic regression analysis was employed to identify the clinical and radiological indicators related to CHD.Then a predictive model was constructed,and then its performance in early predicting CHD was evaluated.Results Blood glucose,low-density lipoprotein cholesterol,CMB score≥ 1,and≥50％stenosis of the posterior cerebral artery were independent risk factors for CHD(P＜0.05).The combined predictive model integrating clinical indicators,cerebral small vessel disease,and cerebral artery stenosis demonstrated the best performance,with an AUC value of 0.867(95％CI:0.807-0.927),outperforming the clinical model and the clinical-cerebral small vessel disease model.Conclusion cerebral small vessel dis-ease and cerebral artery stenosis are closely related to coronary atherosclerosis.The predictive model integrating clinical features and cerebrovascular disease imaging markers provides impor-tant reference for early screening of CHD.

Abdominal war trauma is a common and high-risk type of injury in the modern battlefield,with rapid changes in condition and a high mortality rate.There is an urgent need for emerging medical technologies to improve the efficiency and success rate of first aid for military casualties.With the development of artificial intelligence(AI),5G,and other emerging technologies,the concept of intelligent medical treatment is gradually forming and can assist in the diagnosis and treatment of abdominal trauma.This paper reviews the characteristics of abdominal war trauma in modern wars,discusses the application of intelligent medical treatment for abdominal war trauma and its drawbacks to be solved,aiming to provide reference for research related to abdominal war trauma.

Objective To explore the correlation between gallbladder stones and small intestinal bacterial overgrowth(SIBO).Methods A retrospective analysis was conducted on the clinical data of 393 patients who attended the Department of Gastroenterology of the Sixth Medical Center of Chinese PLA General Hospital from January 2021 to September 2023.They were divided into gallbladder stones group(n=190)and control group(n=203)based on the presence of gallbladder stones.Their general clinical data,laboratory test results,and abdominal symptoms were compared.Multivariate logistic regression was used to analyze the risk factors for gallbladder stones.Additionally,the total population was divided into SIBO-positive group(n=239)and SIBO-negative group(n=154),and their clinical characteristics were analyzed by logistic regression to explore the risk factors for SIBO.Results Univariate analysis revealed that gallbladder stones group had a higher rate of age,body mass index(BMI),fasting plasma glucose(FPG),glutaminase levels,prevalence of hypertension,diabetes,coronary heart disease,non-alcoholic fatty liver disease,gallbladder polyps,and SIBO,as well as a higher prevalence of CH4-positive and H2-positive in SIBO group than control group(P＜0.05).In terms of abdominal symptoms,the incidence of bad breath(48.4%vs.35.5%),dyspepsia(38.4%vs.28.6%),abdominal pain(30.5%vs.14.8%),bloating(42.1%vs.28.6%),diarrhea(20.5%vs.7.4%),and more exhaustion(46.8%vs.34.5%)were significantly higher in gallbladder stones group than those in control group(P＜0.05).Multivariate logistic regression analysis showed that independent positive determinants for incident gallbladder stones were age,BMI,FPG,total bilirubin(TBIL),coronary heart disease,gallbladder polyps,and SIBO.Univariate analysis revealed that age,prevalence of gallbladder stones,proportion of single stones,triglycerides(TG),total cholesterol(TC),and low-density lipoprotein cholesterol(LDL-C)were significantly higher in SIBO-positive group than those in SIBO-negative group(P＜0.05).Multivariate logistic regression analysis showed that the risk factors for SIBO were age,coronary heart disease,and gallbladder stones,while the protective factor for SIBO was high-density lipoprotein cholesterol(HDL-C).Conclusion There is a significant correlation between gallbladder stones and small SIBO;interventions on related factors of gallbladder stones and small SIBO may help reduce their incidence.