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.

Aim To study the therapeutic effect of al-licin on senna-induced diarrhea in mice and to explore the underlying mechanism.Methods Forty-eight C57BL/6J mice were randomly divided into six groups:control,model,loperamide positive control group(2 mg·kg-1),allicin low-dose group(6 mg·kg-1),allicin medium-dose group(12 mg·kg-1)and allicin high-dose group(18 mg·kg-1).Except for the con-trol group,the diarrhea model was induced in the other groups by intragastric administration of senna leaf ex-tract.After drug administration,several diarrhea indi-ces were measured:the rate of loose stools,diarrhea index,accumulated frequency of loose stools at differ-ent time points within 5 hours,and small intestine pro-pelling rate.Serum levels of TNF-α and IL-6 were de-tected by ELISA.Serum NO content was determined u-sing the Griess method.The activities of SOD and CAT,as well as MDA content in the ileum and colon,were measured.The pathological changes and the ex-pression of mRNA related to intestinal barrier proteins in the ileum and colon were evaluated using HE stai-ning and RT-qPCR.Results Allicin improved diar-rhea symptoms in mice induced by senna leaf.It re-duced the rate of loose stools,diarrhea index,cumula-tive number of loose stools in five hours,and the intes-tinal propulsion rate.Allicin also protected the intesti-nal mucosa,decreased serum TNF-α and IL-6 levels,and lowered MDA content in the intestines.It in-creased serum NO levels and enhanced SOD and CAT activities in the intestines.Additionally,allicin upreg-ulated the mRNA expression of AQP1,AQP4,and ZO-1 in intestinal tissues.Conclusions Allicin has a significant therapeutic effect on senna-induced diarrhea in mice.The underlying molecular mechanisms may involve anti-inflammatory and antioxidant effects,in-creased NO content,and upregulation of mRNA ex-pression of aquaporins and tight-junction proteins.

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 compare the therapeutic effect of ureteroscopy(RIRS)combined with fine needle ultra fine channel percutaneous nephrolithotomy(SMP)and microchannel percutaneous nephrolithotomy(MPCNL)in the treatment of complex kidney stones.Methods:100 patients with complex kidney stones who were admitted to our hospital from March 2022 to May 2024 were divided into control group of 50 cases and study group of 50 cases by using random number table method.The control group patients received MPCNL treatment,while the study group patients received fine needle SMP combined with RIRS treatment.The clinical indicators,pain status,inflammatory stress indicators,renal function indicators,and incidence of complications between the two groups were compared.Results:Surgical time in the study group was longer than that in the control group,the intraoperative blood loss was less than that of the control group,the postoperative hospitalization time and time to get out of bed after surgery were shorter than those in the control group(P＜0.05).There was no statistically significant difference in the success rate of stone removal between the two groups(P＞0.05).The visual analog pain scale(VAS)scores in the study group were lower than those in the control group at 6 h,24 h,and 48 h after surgery(P＜0.05).Serum procalcitonin(PCT),high-sensitivity C-reactive protein(hs-CRP),cortisol(Cor),norepinephrine(NE),urea nitrogen(BUN),serum creatinine(Scr),and cystatin C(Cys C)in the study group were lower than those in the control group at 3 d after surgery(P＜0.05).There was no statistically significant difference in the incidence of complications between the two groups(P＞0.05).Conclusion:Compared with MPCNL treatment for complex kidney stones,fine needle SMP combined with RIRS can reduce intraoperative bleeding,shorten time to get out of bed and hospitalization time,alleviate inflammatory stress response,and reduce damage to kidney function and postoperative pain without increasing the incidence of complications.

Objective:To evaluate the short-term safety and efficacy of total laparoscopic, laparoscopy-assisted, and open total gastrectomy in patients with gastric cancer who have undergone neoadjuvant therapy.Methods:In this retrospective cohort study, relevant clinical data on 243 patients who had undergone radical total gastrectomy after receiving neoadjuvant therapy were collected. These patients had been admitted to the First Affiliated Hospital of Air Force Medical University, Yuncheng Central Hospital of Shanxi Province, and Heji Hospital Affiliated to Changzhi Medical College between January 2020 and April 2024. Among them, 202 were male (83.1%) and 41 were female (16.9%), and their average age was 61.3±8.1 years. The patients were allocated to three groups according to surgical procedure: total laparoscopic (68 cases), laparoscopic- assisted (79 cases), and open surgery (96 cases). We compared relevant baseline characteristics, neoadjuvant treatment, intraoperative and postoperative conditions, postoperative histopathological findings, and related complications between these three groups.Results:There were no statistically significant differences in baseline characteristics or neoadjuvant treatment between the three groups (all P>0.05). The operative time was longer in the total laparoscopic group than in the laparoscopic-assisted and open surgery groups (267.7±37.9 minutes vs. 243.9±38.3 minutes vs. 219.7±41.2 minutes, respectively; F=7,112.278; P<0.001). However, more lymph nodes were harvested in the total laparoscopic group than in the laparoscopic-assisted and open surgery groups (27.8±4.8 vs. 27.4±6.3 vs. 27.2±5.1, respectively; F=6.042; P=0.002). Additionally, the total laparoscopic group had shorter times to first postoperative flatus (2.3±0.7 days vs. 2.4±0.7 days vs. 2.6±0.6 days, respectively; F=5.094; P=0.006] and first postoperative bowel movement (2.9±0.5 days vs. 3.0±0.6 days vs. 3.0±0.6 days, respectively; F=3.929; P=0.020). There were no statistically significant differences in intraoperative blood loss, intraoperative transfusion rates, postoperative intensive care unit admission rates, maximum tumor diameter, number of positive lymph nodes dissected, TNM stage, time to first postoperative oral intake, time to drain removal, or length of hospital stay between the three groups (all P>0.05). Among the 243 patients, 22 developed postoperative complications, making the overall complication rate 9.1%. Six patients (8.8%) in the total laparoscopic group developed complications, comprising two (2.9%) Grade IIIa Clavien-Dindo complications. One of these patients (1.5%) was readmitted within 30 days due to complications. Seven patients (8.9%) in the laparoscopic-assisted group developed complications, comprising two (2.5%) Grade IIIa Clavien-Dindo complications. One of these patients was readmitted within 30 days and another was within 90 days due to complications. Nine patients (9.4%) in the open surgery group developed complications, comprising four (4.2%) Grade IIIa Clavien-Dindo complications. Two patients (2.1%) were readmitted within 30 days and another (1.0%) within 90 days due to complications. There were no statistically significant differences among the three surgical approaches in overall postoperative complication rates, Clavien-Dindo grades, or readmission rates 30 and 90 days postoperatively (all P>0.05). Conclusions:In patients with gastric cancer who have undergone neoadjuvant therapy, there are no significant differences in the overall safety and short-term effectiveness of the three surgical procedures. Although the operative time is longer for total laparoscopic total gastrectomy, this procedure offers the advantages of faster postoperative recovery and earlier resumption of feeding.

Aim To study the therapeutic effect of al-licin on senna-induced diarrhea in mice and to explore the underlying mechanism.Methods Forty-eight C57BL/6J mice were randomly divided into six groups:control,model,loperamide positive control group(2 mg·kg-1),allicin low-dose group(6 mg·kg-1),allicin medium-dose group(12 mg·kg-1)and allicin high-dose group(18 mg·kg-1).Except for the con-trol group,the diarrhea model was induced in the other groups by intragastric administration of senna leaf ex-tract.After drug administration,several diarrhea indi-ces were measured:the rate of loose stools,diarrhea index,accumulated frequency of loose stools at differ-ent time points within 5 hours,and small intestine pro-pelling rate.Serum levels of TNF-α and IL-6 were de-tected by ELISA.Serum NO content was determined u-sing the Griess method.The activities of SOD and CAT,as well as MDA content in the ileum and colon,were measured.The pathological changes and the ex-pression of mRNA related to intestinal barrier proteins in the ileum and colon were evaluated using HE stai-ning and RT-qPCR.Results Allicin improved diar-rhea symptoms in mice induced by senna leaf.It re-duced the rate of loose stools,diarrhea index,cumula-tive number of loose stools in five hours,and the intes-tinal propulsion rate.Allicin also protected the intesti-nal mucosa,decreased serum TNF-α and IL-6 levels,and lowered MDA content in the intestines.It in-creased serum NO levels and enhanced SOD and CAT activities in the intestines.Additionally,allicin upreg-ulated the mRNA expression of AQP1,AQP4,and ZO-1 in intestinal tissues.Conclusions Allicin has a significant therapeutic effect on senna-induced diarrhea in mice.The underlying molecular mechanisms may involve anti-inflammatory and antioxidant effects,in-creased NO content,and upregulation of mRNA ex-pression of aquaporins and tight-junction proteins.

Objectives:Recently,domestical developed left ventricular assist devices(LVAD)have been frequently introduced into clinical practice.This study aims to report the anesthesia protocol and perioperative outcomes in Chinese patients receiving LVAD implantation surgery.Methods:This retrospective analysis included patients who underwent LVAD implantation at our center from June 2017 to November 2024.During and after separation from cardiopulmonary bypass,we optimized right heart function through careful adjustments in heart rate,rhythm,preload,myocardial contractility,and afterload.Vasoactive agents were administered as needed,and mechanical ventilation parameters were optimized.We implemented blood conservation strategies and established strict transfusion criteria to minimize allogenic blood transfusions.Results:A total of 100 patients were included in the analysis,with 54.0%classified as Interagency Registry for Mechanically Assisted Circulatory Support(INTERMACS)I or II.Before leaving the operating room,the mean arterial pressure(MAP),mean pulmonary arterial pressure(mPAP),central venous pressure(CVP),lactic acid levels,and urinary output after cardiopulmonary bypass were recorded as(74±7)mmHg,(25±7)mmHg,(7±3)mmHg,(2.3±1.9)mmol/L,and(8.2±5.4)ml/(kg·h),respectively.The transfusion rates for red blood cells and fresh frozen plasma were 20.0%and 28.0%.The in-hospital mortality rate was 3.0%,with a low incidence of severe complications including right heart failure(12%).Left ventricular ejection fraction increased from(23.7±4.8)%preoperatively to(25.3±10.5)%prior to discharge.Conclusions:Patients who received LVAD at our center exhibited low rates of postoperative mortality and complications and significant improvement in left heart function before discharge.

This article reported a case of autosomal dominant intellectual developmental disorder type 22 caused by a heterozygous mutation in the ZBTB18 gene. At 24 +4 weeks of gestation, prenatal ultrasound indicated a short outer diameter of the fetal corpus callosum and bilateral ventricular dilatation. Whole-genome copy number variation analysis of the fetus showed no abnormalities. Whole exome sequencing (WES) and Sanger sequencing validation of the family revealed the fetus carried a c.1374_1383del(p.S459*) heterozygous mutation in the ZBTB18 gene (NM_205768.3), which was neither phenotypically present nor genotypically detected in the parents, suggesting a de novo mutation. Based on the clinical manifestations, the fetus was diagnosed with autosomal dominant intellectual developmental disorder type 22. After genetic counseling, the pregnant woman opted for termination of the pregnancy. This case highlights the correlation between prenatal ultrasonic detection of callosal dysgenesis and lateral ventricular enlargement and intellectual developmental disorders caused by gene mutations. Furthermore, it expands the mutation spectrum of the ZBTB18 gene, thereby facilitating prenatal diagnosis and genetic counseling.

Objectives:Recently,domestical developed left ventricular assist devices(LVAD)have been frequently introduced into clinical practice.This study aims to report the anesthesia protocol and perioperative outcomes in Chinese patients receiving LVAD implantation surgery.Methods:This retrospective analysis included patients who underwent LVAD implantation at our center from June 2017 to November 2024.During and after separation from cardiopulmonary bypass,we optimized right heart function through careful adjustments in heart rate,rhythm,preload,myocardial contractility,and afterload.Vasoactive agents were administered as needed,and mechanical ventilation parameters were optimized.We implemented blood conservation strategies and established strict transfusion criteria to minimize allogenic blood transfusions.Results:A total of 100 patients were included in the analysis,with 54.0%classified as Interagency Registry for Mechanically Assisted Circulatory Support(INTERMACS)I or II.Before leaving the operating room,the mean arterial pressure(MAP),mean pulmonary arterial pressure(mPAP),central venous pressure(CVP),lactic acid levels,and urinary output after cardiopulmonary bypass were recorded as(74±7)mmHg,(25±7)mmHg,(7±3)mmHg,(2.3±1.9)mmol/L,and(8.2±5.4)ml/(kg·h),respectively.The transfusion rates for red blood cells and fresh frozen plasma were 20.0%and 28.0%.The in-hospital mortality rate was 3.0%,with a low incidence of severe complications including right heart failure(12%).Left ventricular ejection fraction increased from(23.7±4.8)%preoperatively to(25.3±10.5)%prior to discharge.Conclusions:Patients who received LVAD at our center exhibited low rates of postoperative mortality and complications and significant improvement in left heart function before discharge.

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.