Objective: To develop a prediction model for mild cognitive impairment (MCI) risk among the elderly, so as to provide a tool for MCI early screening. Methods : From July 2022 to September 2024, a multi-stage stratified random cluster sampling method was used to recruit permanent residents aged ≥65 years from the Xinjiang Uygur Autonomous Region as study participants. Data on sociodemographic characteristics, nutritional status, body composition indices, bone mineral density, and handgrip strength were collected through questionnaires and physical examinations. Sarcopenia was defined based on appendicular skeletal muscle index and handgrip strength. MCI was assessed using the Mini-Mental State Examination, with adjustments for educational level. Participants were randomly divided into a training set and a validation set in a 7∶3 ratio. LASSO regression and multivariable logistic regression models were employed to screen for predictors and construct an MCI risk prediction model. The predictive performance of the model was evaluated using receiver operating characteristic (ROC) curve and decision curve analysis (DCA). Results: A total of 1 641 participants were surveyed, including 755 males (46.01%) and 886 females (53.99%). The majority of participants were aged 65-<75 years, comprising 1 154 individuals (70.32%). MCI was detected in 517 participants, corresponding to a detection rate of 31.51%. Resultsfrom LASSO regression and multivariate logistic regression analysis showed that residence (rural, OR = 2.323, 95% CI: 1.682-3.210), age (75-<85 years, OR = 1.405, 95% CI: 1.019-1.937; ≥85 years, OR = 3.655, 95% CI: 1.696-7.875), educational level (primary school, OR = 0.341, 95% CI: 0.247-0.472; junior high school, OR = 0.255, 95% CI: 0.160-0.408; high school, OR = 0.286, 95% CI: 0.154-0.531; bachelor's degree or above, OR = 0.120, 95% CI: 0.041-0.351), history of alcohol consumption (yes, OR = 3.216, 95% CI: 2.164-4.779), risk of malnutrition (yes, OR = 1.464, 95% CI: 1.064-2.014), sarcopenia (yes, OR = 3.197, 95% CI: 2.332-4.385), and waist-to-hip ratio (abnormal, OR = 1.540, 95% CI: 1.159-2.048) were identified as predictive factors for MCI among the elderly. In the training set, the area under the ROC curve, sensitivity, and specificity were 0.788, 0.719, and 0.712, respectively. In the validation set, the corresponding values were 0.784, 0.913, and 0.542, respectively. DCA demonstrated that the model provided a higher clinical net benefit for predicting MCI risk when the risk threshold probability ranged from 0.124 to 0.764. Conclusion The prediction model developed in this study demonstrates good discriminative ability and clinical utility, indicating its substantial value for predicting the MCI risk among the elderly.

Colorectal cancer (CRC) is the third most commonly diagnosed malignancy and the second leading cause of cancer-related mortality worldwide. Despite therapeutic advancements over recent decades, the prognosis for patients with metastatic CRC (mCRC) remains poor. Approximately 2%-4% of mCRC cases exhibit human epidermal growth factor receptor 2 (HER2) amplification or overexpression, defining a distinct molecular subtype. This HER2-positive status is strongly associated with primary resistance to anti-epidermal growth factor receptor (EGFR) therapies, which are the standard of care for patients with RAS wild-type tumors. Beyond its well-established role in breast and gastric cancers, HER2 has emerged as a pivotal biomarker and actionable therapeutic target in mCRC. However, selecting appropriate treatment strategies remains challenging due to patient heterogeneity and diverse molecular subtypes. This review systematically summarizes the molecular biology, diagnostic strategies, and advances in targeted therapies for HER2-positive mCRC. On the diagnostic front, we discuss the applications of immunohistochemistry (IHC), fluorescence in situ hybridization (FISH), next-generation sequencing (NGS), and circulating tumor DNA (ctDNA) detection technologies. We highlight discrepancies in diagnostic criteria across key clinical trials—such as HERACLES, DESTINY, and MOUNTAINEER—underscoring the urgent need for standardized, CRC-specific definitions to ensure consistent patient selection and comparability of efficacy data across studies. Although NGS enables comprehensive genomic profiling, its cost-effectiveness relative to traditional methods must be carefully considered. Therapeutically, we summarize clinical trial data for HER2-directed agents, including tyrosine kinase inhibitors (TKIs) such as tucatinib and lapatinib, monoclonal antibodies like trastuzumab, bispecific antibodies, and antibody-drug conjugates (ADCs) such as trastuzumab deruxtecan. We review dual-targeting strategies and note recent FDA approvals that represent significant milestones in second-line treatment. Additionally, we explore the potential of combining immune checkpoint inhibitors with HER2-targeted therapies to enhance antitumor immunity through mechanisms including antibody-dependent cellular cytotoxicity (ADCC) and modulation of the tumor microenvironment. ADCs enable precise delivery of cytotoxic payloads, reducing off-target toxicity while effectively inhibiting oncogenic pathways. A substantial portion of this review is dedicated to dissecting the molecular mechanisms underlying primary and acquired resistance to HER2-targeted therapies—persistent challenges that limit clinical benefit. These mechanisms include reactivation of downstream signaling pathways such as PI3K/AKT/mTOR and MAPK, concurrent mutations in genes like KRAS or BRAF, and alterations in HER2 expression that compromise treatment efficacy. For instance, specific HER2 mutations (e.g., L755S) can reduce drug binding affinity, while ctDNA monitoring facilitates early detection of emerging resistance clones during disease progression, thereby enabling timely therapeutic adjustments. Tumor heterogeneity and dynamic interactions with the microenvironment further complicate resistance patterns observed in clinical practice. HER2-targeted therapy represents a new frontier in precision oncology for mCRC, offering renewed hope for improving patient outcomes. Realizing this potential will require continued optimization of diagnostic algorithms and treatment workflows. Future efforts must focus on overcoming resistance, validating liquid biopsy approaches for dynamic monitoring, and establishing unified clinical guidelines. HER2 has become an essential biomarker for stratifying mCRC patients beyond traditional RAS and BRAF status, underscoring the shift from empiric treatment to biomarker-driven precision medicine. International, multidisciplinary collaboration will be critical to validate emerging biomarkers and refine treatment algorithms globally.

ObjectiveTo investigate the mechanism by which activation of α7nicotinic acetylcholine receptors （α7nAChR） optimizes brown adipose tissue （BAT） thermogenesis in obese mice. MethodsObesity was induced in C57BL/6J mice via a high-fat diet. Fifty 8-week-old mice were randomly assigned to five groups： low-fat diet （Control）， high-fat diet （HFD）， high-fat diet plus a β3-adrenergic receptor agonist （HFD+β3）， high-fat diet plus a β3-adrenergic receptor agonist and an α7nAChR selective agonist （HFD+β3+GTS-21）， and high-fat diet plus a β3-adrenergic receptor agonist and an α7nAChR selective antagonist （HFD+β3+α-BGT）. Haematoxylin and eosin （HE） staining was used to evaluate BAT morphology. Transmission electron microscopy was performed to assess mitochondrial number and lipid droplet morphology in adipocytes. ELISA was used to measure levels of tumour necrosis factor-α （TNF-α）， interleukin（IL）-1β，IL-10， transforming growth factor-β （TGF-β）， cyclic adenosine monophosphate （cAMP）， and norepinephrine （NE）. RT-qPCR was conducted to determine mRNA expression levels of vascular endothelial growth factor A （VEGF-A）， nitric oxide synthase 2 （NOS2）， arginase 1 （Arg1）， uncoupling protein 1 （UCP1）， PR domain-containing protein 16 （PRDM16）， and peroxisome proliferator-activated receptor γ coactivator-1α （PGC-1α） in BAT. Immunohistochemistry was used to detect macrophage markers （CD31， CD86， and CD206）. Protein expression levels of UCP1， α7nAChR， nuclear factor-κB p65（NF-κB p65）， phosphorylated Janus kinase 2 （p-JAK2）， and phosphorylated signal transducer and activator of transcription 3 （p-STAT3） were analyzed by Western blot. ResultsCompared with the Control group， the HFD group showed enlarged lipid droplets and reduced mitochondrial numbers in adipocytes， accompanied by increased TNF-α and IL-1β and decreased IL-10， TGF-β， Arg1， and VEGF-A （all P<0.01）. Compared with the HFD+β3 group， the HFD+β3+GTS-21 group showed a smaller lipid droplet area and a higher mitochondrial number， along with reduced levels of pro-inflammatory factors， NOS2， and NF-κB p65， and increased levels of anti-inflammatory factors， Arg1， and phosphorylation of JAK2 and STAT3 （all P<0.01）. ConclusionActivation of α7nAChR in combination with a β3-adrenergic receptor agonist effectively enhances thermogenesis， alleviates local adipose tissue hypoxia， and shifts the local inflammatory phenotype toward an M2-like state， thereby reducing inflammation in brown adipose tissue and improving its thermogenic capacity.

Objective To analyze the differences in clinical indicators between malignant insulinoma and benign in-sulinoma,in order to provide diagnostic and therapeutic insights for the early detection and diagnosis of malignant insulinoma.Methods A retrospective analysis was conducted in patients diagnosed and treated for insulinoma at Peking Union Medical College Hospital from January 2018 to June 2022.Among them,10 cases were diagnosed as malignant insulinoma.Twenty cases of benign insulinoma patients matched for age,sex,and body mass index(BMI),were randomly selected.Statistical analysis was performed to compare the differences between malignant and benign insulinomas.Results 1)Compared to benign insulinoma,malignant insulinoma showed significantly ele-vated C-peptide(CP)and C-peptide to glucose ratio(CPGlu)during hypoglycemia(blood glucose＜3.0 mmol/L)[6.04(3.40,6.76)vs 1.68(1.39,2.47)ng/mL,P＜0.05),2.25(1.12,3.58)vs 0.74(0.54,1.54),P＜0.05].The tumor diameter(DIA)was larger(1.9±0.6 vs 1.4±0.3 cm,P＜0.05),and the insulin level at 300 minutes(INS300)during the 5-hour oral glucose tolerance test(5 h OGTT)was significantly elevated(30.47±5.67 vs 9.67±3.32)μIU/mL,P＜0.01).Levels of blood tumor markers AFP,CEA,and CA724 were also increased(P＜0.05).2)Correlation analysis indicated that CP,CPGlu,DIA,INS300,AFP,CEA,and CA724 were positively correlated with malignant insulinoma during hypoglycemia.3)The ROC curve analysis suggested that the optimal cut-off points for distinguishing malignant from benign insulinomas were CP 2.49 ng/mL,CPGlu 1.31,DIA 1.85 cm,and INS300 20.22 μIU/mL,respectively.Conclusions In clinical practice,if an insulinoma patient has a CP level higher than 2.49 ng/mL and a tumor diameter larger than 1.9 cm during hypoglycemia,the possibility of malignant insulinoma should be considered,warranting further examinations and enhanced follow-up.Persistent elevation of AFP,CEA,and CA724 may indicate malignant insulinoma.

Objective To report the diagnosis,treatment,and verification process of a patient with sex development disorder whose chromosomal karyotype and genetic test results are inconsistent,and conduct a literature review to improve the understanding of the mosaic status of sexual development disorders.Methods A 14-year-old patient presented with primary amenorrhea on April 3,2020,at the First Affiliated Hospital of Hebei North University,exhibiting female sexual characteristics.The patient underwent ultrasonic/magnetic resonance imaging of gonads,assessment of gonadal axis function,chromosomal karyotype,and molecular genetic testing,as well as pelvic exploration,malignant gonads resection,and hormone replacement therapy,resulting in drug-induced menstruation.During the diagnosis and treatment,it was found that the patient's chromosomal karyotype analysis was inconsistent with the molecular genetic test results.Subsequently,samples from the three germ layer cells were taken,and fluorescence in situ hybridization(FISH)was used to detect the sex chromosomes in each germ layer cell.XY probes were used to label the gonadal pathological sections to explore the distribution differences of the Y chromosome in the gonads,and changes in anti-Müllerian hormone(AMH)levels before and after surgery were compared.Databases such as Wanfang and PubMed were searched to summarize relevant cohort study literature and understand the current status of research on this disease.Results The patient's body exhibited a significant differences between the 45,X and 46,XY cell lines in different germ layers and within the same layer tissues.The proportion of 45,X in buccal mucosal cells derived from the ectoderm was 30%(6/20),in peripheral blood lymphocytes derived from the mesoderm was 9.7%(11/114),and in bladder shed cells derived from endoderm was 20.4%(22/108).The gonadal pathological sections labeled with XY probes indicated a mosaic state with a reduced Y-chromosome;where the epididymal structure area had a 45,X cell line mosaic of 50.0%,and the malignant area had a normal"Y"content.After gonadal resection,AMH levels significantly dropped from 7.28 pmol/L to＜0.07 pmol/L.Literature review revealed that patients with 45,X/46,XY have a complex phenotype spectrum,most with features of Turner syndrome,and female phenotypes are at risk of gonadal tumors.Conclusions In the diagnosis of difficult cases of sex development disorders,when performing peripheral blood karyotype testing,the number of counted cells and analyzed cells should be increased as much as possible,and multi-germ layer cell sampling should be performed.Gonads with a high"Y"mosaic rate are more prone to malignancy in the abdominal cavity.Detecting AMH levels can distinguish cryptorchidism and anorchidism in sexual development disorders with Y chromosomes.

Objective To explore the predictive value of automated breast ultrasound(ABUS)features combined with Ki-67 in predicting pathological complete response(pCR)after neoadjuvant chemotherapy(NAC)in triple-negative breast cancer(TNBC).Methods A retrospective analysis was conducted on 127 female TNBC patients treated at Xijing Hospital,Air Force Medical University from March 2019 to December 2023.All patients underwent NAC and surgical treatment after ABUS examination.Based on postoperative pathological results,patients were divided into pCR group(n=60)and non-pathological complete response(npCR)group(n=67).Differences in various parameters before NAC were compared between the two groups.LASSO regression was used to identify independent factors influencing pCR after NAC in TNBC patients,and a predictive model was constructed using multivariate logistic regression.The prediction model was internally validated using the Bootstrap method(1000 resamples).The discriminative ability of the model was evaluated using receiver operating characteristic(ROC)curves,and the area under the curves(AUCs)of different prediction models were compared using De-long's test.The accuracy of the model was assessed using calibration curves,and the clinical benefit of the model was evaluated using clinical decision curve analysis(DCA).Results Significant differences were observed between two groups in terms of age,Ki-67,menopausal status,tumor type,posterior echo,coronal plane convergence sign,coronal plane skip sign,and coronal plane white wall sign before NAC(P<0.05).LASSO regression analysis showed that Ki-67,coronal plane convergence sign,and coronal plane white wall sign were independent influencing factors of pCR after NAC in TNBC patients(P<0.05).The AUC of the multivariate logistic regression model based on Ki-67 was 0.733(95%CI 0.646-0.819),the AUC of ABUS model was 0.777(95%CI 0.695-0.858),and the AUC of ABUS combined with Ki-67 model was 0.816(95%CI 0.741-0.890).De-long's test showed that the AUC of the combined model was higher than those of ABUS feature model and Ki-67 model,with statistically significant differences(P<0.05).There was no significant difference in the AUC between ABUS feature model and Ki-67 model(P=0.40).Hosmer-Lemeshow test indicated that the combined model had a good fit(P=0.304).Internal validation results showed that the combined model had a good stability with a consistency index(C-index)of 0.820(95%CI 0.726-0.879).The calibration curve demonstrated good consistency between the predicted and actual probabilities of the combined prediction model,and the DCA curve indicated that the model had favorable clinical benefit.Conclusion The combined ABUS feature and Ki-67 model can be used to predict the probability of pCR after NAC in TNBC patients,providing a reference for the formulation of clinical treatment plans in TNBC patients.

Objective To explore the spatiotemporal expression patterns of Patched 1(Ptch1)and insulin enhancer binding protein-1(Isl 1)in mouse embryonic foregut and their relationship with the early development of trachea-main bronchus.Methods The foregut of 60 mouse embryos at E9.5-12.5 was separated for the detection of Isl1 and sonic hedgehog(Shh)protein by Western blotting.Serial paraffin sections of 6 mouse embryos at E9.5-14.5 were taken for immunohistochemical staining and immunofluorescence double staining with Isl1,Ptch1,forkhead box protein A2(Foxa2),type Ⅱ collagen α1 chain(Col2a1)and α-smooth muscle actin(α-SMA),as well as HE staining and Masson staining.Results The expression trend of Isl1 and Shh in foregut endoderm at E9.5-12.5 was similar,and the peak of Shh expression was later than Isl1.The foregut developed into the trachea at E9.5-12.5,Ptch1 was expressed in the thickening and protrusion of the respiratory endoderm,the laryngal-tracheal groove and the solid cell cord,accompanied by the increase and aggregation of Isl1-positive mesenchymal cells,forming a characteristic pyramidal structure centered on the respiratory endoderm and the solid cell cord;The main bronchus appeared at E12.5-13.5,Ptch1 was only expressed in its lateral wall,accompanied by the accumulation of Isl1-positive mesenchymal cells;The trachea-main bronchial epithelium lost Ptch1 expression and the surrounding Isl 1-positive mesenchymal cells also decreased rapidly at E13.5-14.5.Co12a1-positive chondrocytes first appeared in the Isl1-positive mesenchymal area adjacent to the Ptch1-positive epithelium at E12.5;Col2a1-positive cartilage was nested within the Isl1-positive mesenchymic area in a"C"shape and expanded in a proximal-distal pattern at E12.5-13.5;Col2a1-positive cartilage extended to the dorsal trachea beyond the Isl1-positive mesenchyma and encircles α-SMA positive smooth muscle in a circular manner at E14.5.Conclusion The expression of Ptch1 in the foregut endoderm is involved in the development and morphogenesis of the trachea-main bronchus epithelium,and is closely related to the proliferation and aggregation of Isl1-positive mesenchyme in the trachea-main bronchial wall,Subsequently,they jointly determine the time,location and extent of airway cartilage.

Objective To investigate the potential mechanism of action of polygonatum odoratum in treating Alzheimer's disease through the utilization of network pharmacology and molecular docking techniques.Methods The methods employed include target screening,Gene Ontology(GO)function and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analysis,and molecular docking simulations to assess the binding interactions between the active compounds in polygonatum odoratum(POD)and the key target proteins associated with Alzheimer's disease.Subsequently,lipopolysaccharide(LPS)was used to induce an inflammatory cell model in BV2 microglial cells.After treating the cell model with POD extract for 24 hours,the cells were collected,and the expression of the target genes were detected by Real-time PCR.Results Eight active ingredients and 172 targets of POD were screened.The biological processes such as protein phosphorylation and signal transduction,protein binding and ATP binding were obtained by GO functional analysis.KEGG enrichment yielded PI3K/Akt,cAMP and other signaling pathways.The molecular docking result showed that the active ingredient of POD had well binding activity with epidermal growth factor receptor(EGFR),proto-oncogene tyrosine-protein kinase Src(SRC),tumor necrosis factor(TNF),STAT3.Through Real-time PCR experiments,the gene expressions of inducible nitric oxide synthase(iNOS),prostaglandin G/H synthase 2(PTGS2),interleukin(IL)-6,and IL-1β in the LPS-induced inflammatory cell model were significantly upregulated.After treating the inflammatory model with POD extract for 24 hours,the expression of TNF-α was significantly reduced,the expression of STAT3 was upregulated,there were no significant changes in the expressions of SRC and EGFR.Conclusion Network pharmacology suggests polygonatum odoratum's potential anti-Alzheimer's effects may be mediated through its interaction with targets such as EGFR,TNF,SRC,and STAT3.The experimental results suggest that polygonatum odoratum exerts an anti-inflammatory effect by acting on TNF-α,which may further alleviate the symptoms of Alzheimer's disease.

Objective To construct a predictive model for high-grade pathological components of early invasive lung adenocarcinoma(ILAC)based on radiomics.Methods Collecting information on total 495 patients who underwent radical operation and were pathologically diagnosed as stage Ⅰ in the cardiothoracic surgery of Zhoushan Hospital from January 2015 to December 2019,including gender,age,pathological findings,tumor markers and preoperative chest CT images.The micropapillary and solid components in postoperative pathology were defined as"high-grade pathological components",while those without high-grade pathological components were classified into the low-grade group and those with high-grade pathological components were classified into the high-grade group.And patients were randomly divided into the training set(343 cases)and the validation set(152 cases)with a ratio of 7∶3 using the simple randomization grouping method.The region of interest of nodules on CT images were delineated layer by layer by scientific research platform and 1950 radiomics features were extracted.And then those features were filtrated by F-test,Pearson correlation coefficient,and L1 based feature selection.A model was built by using Logistic regression machine learning classifier,named mod 2,and radscore was also obtained.Differences between general information and CT features were analyzed.Binary Logistic regression analysis was used to construct a model for statistically significant variables,named mod 1.At the same time,Radscore was added to build the mod and named comb mod.The area under the curve(AUC),sensitivity and specificity of the three models were calculated.A nomogram was also drawn.Results A total of 495 patients were divided into the training set(n=343)and the validation set(n=152).Gender,carcinoma embryonic antigen(CEA),nodule,and maximum diameter were screened out in clinical features and involved in constructing the mod 1.Twelve features were selected from the radiomics features to build mod 2.Comb mod performed best,training set AUC:0.887,validation set AUC:0.875,and had good clinical practicability.Conclusion The model composed of general feature,CT feature and radiomics features could accurately predict high-grade pathological components in early ILAC,and provide references for clinicians to choose surgical method for patients.

Facing of mounting resource constraints and rising demands for personalization in medical education,regional anatomy teaching urgently requires transformation.In this paper,we focus on the regional anatomy of the thoracic wall,in order to explore a novel AI-driven teaching paradigm.Anchored in the core principle of"virtual-real integration with cadaveric dissection as the cornerstone,"the paradigm redefines educational objective and constructs an intelligent,closed-loop teaching model integrating students,computers,and instructors.Leveraging the robust support of digital intelligence(e.g.,DeepSeek),this paradigm incorporates interactive method including group collaboration,branching instruction,and gamified assessments.It achieves a comprehensive intelligent transformation of the entire teaching process-from goal setting and plan customization to activity implementation,task completion,outcome exchange,multidimensional evaluation,and reflective iteration.This new paradigm centers on medical students and leverages digital intelligence to activate deep personalized learning potential.It seamlessly integrates fundamental anatomical knowledge with clinical scenarios(e.g.,key anatomy in breast cancer surgery,flap design in breast reconstruction),and significantly enhances clinical decision-making abilities,scientific research and innovative thinking,as well as medical humanistic literacy,paving a new path for intelligent medical education.