ObjectiveTo screen suitable packaging and storage conditions for small packaged Alismatis Rhizoma decoction pieces， laying the foundation for developing standardized storage， maintenance techniques and determining shelf life. MethodsUsing the accelerated stability test method， the small packaged decoction pieces of Alismatis Rhizoma were placed in polyethylene plastic bags， aluminum foil polyethylene composite bags， and cowhide coated paper bags under temperature of （40±2） ℃ and relative humidity of （75±5）% conditions， the quality testing was conducted at the end of the 0^th， 1^st， 2^nd， 3^rd， and 6^th month， respectively. Using long-term stability test method， an orthogonal experiment was designed to investigate storage conditions， packaging materials， and packaging methods. At the end of the 0^th， 1^st， 3^rd， 6^th， 9^th， 12^th， 18^th， and 24^th month， the quality of small packaged Alismatis Rhizoma decoction pieces was tested under different packaging and storage conditions（including 2 packaging methods：vacuum packaging and sealed packaging， 3 storage conditions：room temperature， cool， and modified atmosphere， 3 packaging materials：cowhide coated paper bag， aluminum foil polyethylene composite bag， and polyethylene plastic bag）. Then， the G1-entropy weight method combined with orthogonal experiment was used to analyze the quality changes of the decoction pieces under different packaging and storage conditions to identify optimal packaging and storage conditions. The quality testing indicators for Alismatis Rhizoma decoction pieces were expanded beyond those specified in the 2020 edition of the Pharmacopoeia of the People's Republic of China. In addition to the existing indicators（characteristics， moisture content， extractives， and the total content of 23-acetyl alisol B and 23-acetyl alisol C）， new indicators including color value， water activity， total triterpenoid content， and alisol B content have been added. ResultsThe accelerated stability test results indicated that the quality of small packaged Alismatis Rhizoma decoction pieces was more stable when packaged in aluminum foil-polyethylene composite materials compared to cowhide-coated paper bags and polyethylene plastic bags. Analysis of the long-term stability test results using the G1-entropy weight method combined with orthogonal experiment revealed that storage conditions had the greatest impact on both raw and salt-processed products， followed by packaging materials， while the packaging method had the least influence. For both types of small packaged Alismatis Rhizoma decoction pieces， modified atmosphere storage demonstrated superior efficacy compared to cool storage or room temperature storage. Storage in aluminum foil-polyethylene composite bags was superior to polyethylene plastic bags or cowhide-coated paper bags. However， the stability of sealed raw products was better than vacuum-packed ones， whereas vacuum-packed salt-processed products exhibited greater stability than their sealed counterparts. ConclusionBased on the results of the quality changes of small packaged Alismatis Rhizoma decoction pieces under different storage conditions， it is recommended that the suitable storage packaging conditions for small packaged raw products are sealed packaging with aluminum foil polyethylene composite bags and controlled atmosphere storage， and the suitable storage and packaging conditions for small packaged salt-processed products are vacuum packaging with aluminum foil polyethylene composite bags and controlled atmosphere storage.

Objective To develop a predictive model for postoperative mortality risk in patients with acute aortic dissection(AAD)using the Extreme Gradient Boosting(XGBoost)algorithm combined with Shapley Additive Explanation(SHAP),and to establish a prediction website to serve as a diagnostic and therapeutic support platform for clinicians and patients.Methods A retrospective cohort study design was adopted.Data from 782 AAD patients who underwent surgical treatment at the Fourth Hospital of Hebei Medical University from January 2013 to December 2023 were collected,including basic information and initial serum biomarker test results.Patients were randomly divided into training and test sets at a 7:3 ratio.An external validation set consisting of 313 AAD patients admitted to the Second Hospital of Hebei Medical University from January 2020 to December 2023 was also established for further model validation.Variables were screened using LASSO regression,and an XGBoost machine learning model was constructed and interpreted using SHAP.The predictive performance of the model was evaluated using receiver operating characteristic(ROC)curve analysis.Using the Shiny package,the XGBoost model was deployed to shinyapps.io to create a prediction website for postoperative mortality risk in AAD patients.One patient was selected by simple random sampling from the test set and the external validation set respectively for the prediction example on the Shiny webpage.Results The XGBoost model demonstrated high predictive performance for postoperative mortality in AAD patients,with area under the ROC curve(AUC)values of 0.928(95%CI 0.901-0.956)in the training set,0.919(95%CI 0.891-0.949)in the test set,and 0.941(95%CI 0.915-0.967)in the external validation set.SHAP values indicated the following order of variable importance in the model(from highest to lowest):"lactate dehydrogenase""blood chlorine""multiple organ injury""carbon dioxide combining power""prothrombin time""α-hydroxybutyric acid""creatine kinase isoenzyme""Stanford classification""combined use of bedside blood purification""gender""acute kidney injury""gastrointestinal bleeding""brain injury"and"shock".A risk prediction website for adverse postoperative outcomes in AAD patients was developed using XGBoost-SHAP method(https://dun-dunxiaolu.shinyapps.io/document/)and validated with examples.One randomly selected patient from each of the test and external validation sets was applied:the predicted mortality risk value for patient 1(who died postoperatively)was 0.9539,and that for patient 2(who survived postoperatively)was 0.0206.Conclusions The XGBoost-SHAP model demonstrates high accuracy in predicting postoperative mortality risk for AAD patients.The online prediction tool established based on this model enhances the identification efficiency of high-risk postoperative mortality patients.

Objective To analyze the basic conditions and pathological characteristics of the samples in the Human Brain Bank of Hebei Medical University,which were pathologically diagnosed as cerebral amyloid angiopathy,and to provide reference for the research of related diseases.Methods The basic data of gender,age,apolipoprotein E genotype,pathological classification of cerebral amyloid angiopathy,Alzheimer's disease-related pathological change score,comorbidities and other pathological information were analyzed.Results Up to October 2024,twenty samples were confirmed by pathological diagnosis,with a male to female ratio of 3:1 and an average age of(80.90±8.08)years.Involve three kinds of apolipoprotein E subtype,5 kinds of genotypes(ε2/ε3 xε2/ε4、ε3/ε3 xε3/ε4、ε4/ε4);There were 2 pathologic types,including 6 cases of type 1 and 14 cases of type 2.The pathological grade included 3 grades.The severity grade and subtype classification of cerebral amyloid vascular disease were correlated with the degree of pathological changes of Alzheimer's disease.Cerebral amyloid angiopathy samples could coexist with other degenerative diseases with high comorbidity.Conclusion The incidence of cerebral amyloid angiopathy is higher in the aged samples collected based on Brain Bank,which coexists with conditions such as Alzheimer's disease and microbleeds,etc.It provides more detailed pathological diagnosis basis for further scientific research sharing of samples.

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.

Aim To investigate the role of corylin in angiotensin Ⅱ(Ang Ⅱ)-induced cardiomyocyte hy-pertrophy and its underlying mechanisms.Methods An Ang Ⅱ-induced cardiomyocyte hypertrophy model was established and treated with corylin.Real-time PCR was employed to assess hypertrophic gene mRNA expression,and immunofluorescence was used to meas-ure cardiomyocyte surface area.Western blot and en-zyme activity assay kits were used to evaluate SIRT1 expression and activity.Results Corylin markedly mitigated Ang Ⅱ-induced hypertrophic gene expression and cardiomyocyte surface area enlargement.Moreo-ver,it prevented the Ang Ⅱ-mediated decline in SIRT1 protein levels and deacetylase activity.Further investi-gation indicated that corylin inhibited Ang Ⅱ-driven NF-κB transcriptional activity and the expression of its downstream target genes,such as TNF-α,IL-6,and IL-1β.Notably,SIRT1 silencing abolished the protective effects of corylin against cardiomyocyte hypertrophy,as well as its regulation of the SIRT1/NF-κB signaling pathway.Conclusion Corylin suppresses cardiomyo-cyte hypertrophy by modulating the SIRT1-dependent NF-κB signaling pathway.

Kv1.3,a voltage-gated potassium channel,is highly expressed in T lymphocytes,the nervous system,and vascular smooth muscle cells.It plays a critical role in membrane excitability and electrical signal transduction,serving as an important target for studying T-cell function and providing a promising direction for developing therapeutics against autoimmune and inflammatory diseases.Therefore,the de-velopment of specific inhibitors of Kv1.3 channel has emerged as a novel therapeutic strategy for these disorders.In this study,we isolated and purified a novel Kv1.3-inhibitory peptide toxin,LmKTx13,from the venom of the scorpion Lychas mucronatus using reversed-phase high-performance liquid chroma-tography(RP-HPLC).LmKTx13 consists of 38 amino acid residues,including six cysteines that form three disulfide bonds.Whole-cell patch-clamp recordings revealed that LmKTx13 potently inhibited Kv1.3 with an IC50 of 7.92±3.0 nmol/L.Selectivity analysis showed that 2 μmol/L LmKTx13 also in-hibited Kv1.2 and Kv1.7,but exhibited no significant effects on other potassium channel subtypes or voltage-gated sodium channels.Further investigation into the mechanism demonstrated that LmKTx13 acts as a pore-blocking inhibitor of Kv1.3.By analyzing the effects of LmKTx13 on Kv1.3 channel gating ki-netics and performing sequence alignment of the pore regions of Kv1.3 and Kv1.5,we constructed site-directed mutants and identified the pore region of Kv1.3 as the critical binding site for LmKTx13.Key residues involved in the interaction included T425,G427,and H451.In summary,we discovered a no-vel pore-blocking Kv1.3 inhibitor,LmKTx13,from L.mucronatus venom,which exhibits high affinity and selectivity for Kv1.3.These findings highlight its potential as a potential lead molecule for developing Kv1.3-targeted therapeutics.

Testicular descent occurs in two consecutive stages: the transabdominal stage and the inguinoscrotal stage. Androgens play a crucial role in the second stage by influencing the development of the gubernaculum, a structure that pulls the testis into the scrotum. However, the mechanisms of androgen actions underlying many of the processes associated with gubernaculum development have not been fully elucidated. To identify the androgen-regulated genes, we conducted large-scale gene expression analyses on the gubernaculum harvested from luteinizing hormone/choriogonadotropin receptor knockout ( Lhcgr KO) mice, an animal model of inguinoscrotal testis maldescent resulting from androgen deficiency. We found that the expression of secreted protein acidic and rich in cysteine (SPARC)-related modular calcium binding 1 ( Smoc1 ) was the most severely suppressed at both the transcript and protein levels, while its expression was the most dramatically induced by testosterone administration in the gubernacula of Lhcgr KO mice. The upregulation of Smoc1 expression by testosterone was curtailed by the addition of an androgen receptor antagonist, flutamide. In addition, in vitro studies demonstrated that SMOC1 modestly but significantly promoted the proliferation of gubernacular cells. In the cultures of myogenic differentiation medium, both testosterone and SMOC1 enhanced the expression of myogenic regulatory factors such as paired box 7 ( Pax7 ) and myogenic factor 5 ( Myf5 ). After short-interfering RNA-mediated knocking down of Smoc1 , the expression of Pax7 and Myf5 diminished, and testosterone alone did not recover, but additional SMOC1 did. These observations indicate that SMOC1 is pivotal in mediating androgen action to regulate gubernaculum development during inguinoscrotal testicular descent.
Animals ; Male ; Mice ; Testis/growth & development* ; Mice, Knockout ; Androgens/pharmacology* ; Testosterone/pharmacology* ; Receptors, LH/metabolism* ; Calcium-Binding Proteins/metabolism*

OBJECTIVES: To study the clinical characteristics of rashes induced by trimethoprim-sulfamethoxazole (TMP-SMZ) in children treated for pertussis and to inform safe medication practices. METHODS: A retrospective analysis was conducted on 238 children diagnosed with pertussis and treated with TMP-SMZ at Wuhu First People's Hospital from January to August 2024. The incidence and clinical features of rashes were summarized. RESULTS: Of 238 children, 34 (14.3%) developed rashes; 19 (55.9%) were boys, and the 5 to <10-year age group accounted for the highest proportion (70.6%, 24/34). A history of allergic disease was present in 50.0% (17/34). Rashes typically appeared on or after day 7 of therapy (82%, 28/34) and were predominantly erythematous or maculopapular eruptions (97%, 33/34); 71% (24/34) were pruritic. Fever occurred in 56% (19/34); among those who were tested for respiratory viruses, 77% (10/13) were positive for viruses such as rhinovirus and adenovirus. After discontinuation of TMP-SMZ, rashes resolved within 3 days in 97% (33/34) of patients (41% within 1 day; 56% within more than 1 but within 3 days). There was no significant difference in rash incidence between photoprotection and non-photoprotection groups (P>0.05). CONCLUSIONS TMP-SMZ for pertussis can induce rashes, particularly in children aged 5 to <10 years. The eruption is usually a pruritic erythematous or maculopapular rash, with over half of cases accompanied by fever and frequent concomitant viral infections. Most rashes resolve within 3 days after drug withdrawal. The potential association between the rash and sun exposure warrants further investigation.
Humans ; Male ; Child, Preschool ; Trimethoprim, Sulfamethoxazole Drug Combination/therapeutic use* ; Child ; Female ; Exanthema/chemically induced* ; Retrospective Studies ; Infant ; Whooping Cough/drug therapy* ; Adolescent

Objective To develop predictive models based on decision tree and logistic regression algo-rithms for pulmonary multidrug-resistant organism(MDRO)infection risk in intensive care unit(ICU)pa-tients,and compare their predictive performance to provide references for pulmonary MDRO infection preven-tion.Methods A total of 350 ICU patients admitted to the hospital from January 2021 to December 2023 were enrolled and divided into an infection group(n=52)and a non-infection group(n=298)based on the pres-ence of pulmonary MDRO infection.Clinical data from both groups were collected and analyzed to identify risk factors for pulmonary MDRO infection in ICU patients.Using the risk of pulmonary MDRO infection in ICU patients as the dependent variable and the indicators with statistically significant differences in univariate anal-ysis as the independent variables,predictive models for pulmonary MDRO infection risk were developed by u-sing decision tree algorithms and logistic regression analysis.The predictive performance of these two models was compared.Results There were statistically significant differences(P＜0.05)between the infection and non-infection groups in terms of age,history of diabetes,hospital stay≥2 weeks,indwelling urinary catheter,chlorine dioxide disinfection,prolonged bedridden status,and disturbance of consciousness.Logistic regression analysis with pulmonary MDRO infection risk in ICU patients as the dependent variable showed that age ≥60 years,indwelling catheter,hypoproteinemia,and disturbance of consciousness were risk factors for pulmonary MDRO infection in ICU patients,while chlorine dioxide disinfection was a protective factor.Based on these risk factors and regression coefficients,the original warning model was established as:logit(P 1)=0.856 × age+0.928 × indwelling catheter+0.916 × chlorine dioxide disinfection+0.866× hypoproteinemia+0.986 × disturbance of consciousness-4.371.The Hosmer-Lemeshow test indicated good model fit(coefficient of de-termination R2=0.579,P=0.531).The decision tree model for pulmonary MDRO infection risk in ICU pa-tients constructed using decision tree algorithm comprised 4 layers and 9 nodes,selecting four clinical features as nodes:presence of consciousness disturbance,indwelling catheter,hypoproteinemia,and age≥60 years,with consciousness disturbance being the most significant predictor.The decision tree model showed an area under the curve(AUC)of 0.892(95％CI:0.835-0.949)on receiver operating characteristic(ROC)analy-sis,compared to 0.862(95％CI:0.812-0.912)for the logistic regression model.Delong test revealed no sig-nificant difference in predictive performance between the two models(Z=1.148,P=0.095).Conclusion Both the decision tree model and logistic regression model established for predicting the risk of pulmonary MDRO infection in ICU patients demonstrate high predictive performance with comparable efficacy.