Gastric cancer is one of the most common malignant tumors in the digestive system, characterized by high incidence and mortality rates. In recent years, with the rapid develop-ment of molecular immunology, the application of immune checkpoint inhibitors (ICIs) in neoadju-vant therapy has significantly improved pathological response rates and survival outcomes for patients with resectable locally advanced gastric cancer. The authors systematically review current research progress on combination strategies involving immune checkpoint inhibitors in neoadjuvant therapy for locally advanced gastric cancer, aiming to provide an evidence for optimizing individua-lized therapeutic regimens.

Gastric cancer is one of the most common malignant tumors in the digestive system, characterized by high incidence and mortality rates. In recent years, with the rapid develop-ment of molecular immunology, the application of immune checkpoint inhibitors (ICIs) in neoadju-vant therapy has significantly improved pathological response rates and survival outcomes for patients with resectable locally advanced gastric cancer. The authors systematically review current research progress on combination strategies involving immune checkpoint inhibitors in neoadjuvant therapy for locally advanced gastric cancer, aiming to provide an evidence for optimizing individua-lized therapeutic regimens.

Purpose To evaluate the value of preoperative MRI-based radiomic models for assessing tumor-infiltrating CD8+T-cell expression in glioblastoma patients,and to identify the most stable and efficient radiomic feature region for predicting prognosis following immunotherapy.Materials and Methods This retrospective study included 150 patients with histopathologically confirmed glioblastoma from Lanzhou University Second Hospital(January 2018 to April 2022).Tumor-infiltrating CD8+T-cell expression was quantitatively assessed using immunohistochemical staining,with patients stratified into CD8-high and CD8-low expression groups based on overall survival.A total of 1 185 radiomic features were extracted from each patient's contrast-enhanced T1C and T2WI images,covering the original tumor region and sequentially expanded peritumoral regions(2.5 mm,5.0 mm,7.5 mm,10.0 mm,12.5 mm,15.0 mm morphological dilation of tumor core+peritumoral area).Feature selection was performed using variance threshold,minimum redundancy maximum relevance,and least absolute shrinkage and selection operator methods.XGBoost classifier was employed to construct clinical,radiomic,and clinical-radiomic multimodal combined prediction models.Diagnostic performance was evaluated using receiver operating characteristic curve analysis.Results The radiomic model based on tumor expansion of 7.5 mm(tumor+peritumoral region)demonstrated optimal predictive performance.The clinical-radiomic multimodal combined model showed superior predictive capability compared to clinical and radiomic models alone,achieving an area under the curve of 0.991 and accuracy of 99.0%in the training set,and area under the curve of 0.840 with accuracy of 80.0%in the validation set.Conclusion MRI radiomics provides a feasible approach for evaluating tumor-infiltrating CD8+T-cell expression in glioblastoma patients,offering potential for preoperative prognosis prediction.

With the aggravation of population aging in our country,the prevalence of osteoporosis(OP)has surged dramatically.Currently,the diagnosis of OP primarily relies on bone mineral density(BMD),and the precise measurement of BMD is crucial in the diagnosis and treatment of spinal surgical diseases.In recent years,computed tomography(CT)has gained widespread attention in clinical diagnosis and treatment due to its unique advantages.Vertebral CT values not only enhance the diagnostic rate of OP but also effectively predict the occurrence of postoperative complications such as adjacent vertebral fractures,fusion device subsidence,and pedicle screw loosening.This article summarizes the research progress of vertebral CT value in the field of spine surgery,and discusses its feasibility in guiding spinal surgery and its correlation with postoperative complications of spine.Additionally,it elaborates on the progress of combining CT with artificial intelligence(AI)to assist in disease diagnosis and treatment,aiming to better promote the clinical application of vertebral CT values.

Purpose To evaluate the value of preoperative MRI-based radiomic models for assessing tumor-infiltrating CD8+T-cell expression in glioblastoma patients,and to identify the most stable and efficient radiomic feature region for predicting prognosis following immunotherapy.Materials and Methods This retrospective study included 150 patients with histopathologically confirmed glioblastoma from Lanzhou University Second Hospital(January 2018 to April 2022).Tumor-infiltrating CD8+T-cell expression was quantitatively assessed using immunohistochemical staining,with patients stratified into CD8-high and CD8-low expression groups based on overall survival.A total of 1 185 radiomic features were extracted from each patient's contrast-enhanced T1C and T2WI images,covering the original tumor region and sequentially expanded peritumoral regions(2.5 mm,5.0 mm,7.5 mm,10.0 mm,12.5 mm,15.0 mm morphological dilation of tumor core+peritumoral area).Feature selection was performed using variance threshold,minimum redundancy maximum relevance,and least absolute shrinkage and selection operator methods.XGBoost classifier was employed to construct clinical,radiomic,and clinical-radiomic multimodal combined prediction models.Diagnostic performance was evaluated using receiver operating characteristic curve analysis.Results The radiomic model based on tumor expansion of 7.5 mm(tumor+peritumoral region)demonstrated optimal predictive performance.The clinical-radiomic multimodal combined model showed superior predictive capability compared to clinical and radiomic models alone,achieving an area under the curve of 0.991 and accuracy of 99.0%in the training set,and area under the curve of 0.840 with accuracy of 80.0%in the validation set.Conclusion MRI radiomics provides a feasible approach for evaluating tumor-infiltrating CD8+T-cell expression in glioblastoma patients,offering potential for preoperative prognosis prediction.

Objective To explore the correlation between the expression level of serum fibrinogen-like protein 1(FGL1)and the indexes of metabolism and renal function in patients with diabetic nephropathy(DN)and diabetes mellitus(DM),and provide reference for clinical diagnosis and treatment.Methods From January 2017 to April 2023,30 patients with DM and treated in Jiangsu Province Hospital of Chinese Medicine were selected as the DM group,68 patients with DN were selected as the DN group,and 36 healthy subjects were selected as the control group.The DN group was further divided into the early DN(DN-E)group(n=38)and the late DN(DN-A)group(n=30)according to whether there was a large amount of proteinuria and the severity.Clinical data such as serum albumin(ALB),estimated glomerular filtration rate(eGFR)and albumin-to-creatinine ratio(ACR)were collected.Serum FGL1 level was detected by enzyme-linked immunosorbent assay(ELISA).Pearson linear correlation was used for correlation,the diagnostic value was analyzed by ROC curve.Results Compared with the control group,the levels of ACR,FGL1 in patients with DM group increased,the levels of eGFR decreased,and the differences were statistically significant(t=5.686,4.336,-4.683,all P<0.05).Compated with the DM group,the levels of ACR,FGL1 in patients with DN-E group was increased,and the level of eGFR was decreased,and the differences were statistically significant(t=5.275,3.454,-4.969,all P<0.05).Compared with the DN-E group,the levels of ACR,FGL1 in the DN-A group were increased,the levels of eGFR were decreased,and the differences were statistically significant(t=7.881,7.051,-5.596,all P<0.05).Serum FGL1 level was negatively correlated with ALB and eGFR(r=-0.638,-0.547,all P<0.05),and positively correlated with ACR(r=0.691,P<0.05).The AUC(95%CI),specificity and sensitivity of serum FGL1 level in the diagnosis of DN were 0.947(0.908～0.987),100%and 82.4%,respectively.Conclusion The level of serum FGL1 in DN and DM patients is high,and the level of serum FGL1 is closely related to the common metabolic indexes such as ALB,eGFR and ACR in the diagnosis of DN,which may have certain clinical diagnostic value.

Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91％of the total clinical isolates and 4.07％of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89％were isolated from children and 33.11％were isolated from adults.More than 90％of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79％in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06％were isolated from children and 19.94％isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0％.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.

This paper explores the application and advancements of cross-cultural nursing concepts in the management of ICU patients. It identifies the core elements of humanistic care from a cross-cultural perspective, introduces relevant international research findings, and provides an in-depth analysis of existing challenges within the domestic healthcare context. Constructive suggestions are proposed to enhance the quality of life of ICU patients.

Menstrual migraine is a specific subtype of migraine unique to women,closely related to the menstrual cycle,characterized by periodic and intractable headaches,often accompanied by nausea,vomiting or photophobia and phonophobia,which seriously affects life and has a high degree of disability.Its pathogenesis is complex,involving multi-dimensional regulation such as estrogen fluctuations,neurovascular responses and genetic and environmental factors,but the specific mechanism has not been fully clarified.In recent years,with the increasing social attention to women's health,the clinical research demand for menstrual migraine has become increasingly urgent.Currently,modern medicine can alleviate symptoms through acute drug intervention(such as non-steroidal anti-inflammatory drugs,triptans)and preventive treatment(such as beta-blockers,CGRP antagonists),but there are problems such as drug dependence and insufficient individualization.Traditional Chinese medicine,based on the"holistic concept"and"syndrome differentiation and treatment"theory,regulates the balance of qi,blood,yin and yang through therapies such as traditional Chinese medicine and acupuncture,showing unique advantages in improving symptoms and preventing recurrence.The combination of traditional Chinese and Western medicine can optimize the therapeutic effect and reduce side effects through synergistic effects,but the full-cycle prevention and treatment strategy still needs further exploration.This article systematically reviews the pathogenesis and research progress of treatment of menstrual migraine in traditional Chinese and Western medicine,emphasizes the interaction between hormone fluctuations and neurovascular responses,and proposes an individualized intervention plan based on the menstrual cycle,providing new ideas for clinical practice and reference directions for future research.

Cytotoxicity, usually represented by cell viability, is a crucial parameter for evaluating drug safety in vitro. Accurate prediction of cell viability/cytotoxicity could accelerate drug development in the early stage. In this study, by integrating cellular transcriptome and cell viability data using four machine learning algorithms (support vector machine (SVM), random forest (RF), extreme gradient boosting (XGBoost), and light gradient boosting machine (LightGBM)) and two ensemble algorithms (voting and stacking), highly accurate prediction models of 50% and 80% cell viability were developed with area under the receiver operating characteristic curve (AUROC) of 0.90 and 0.84, respectively; these models also showed good performance when utilized for diverse cell lines. Concerning the characterization of the employed Feature Genes, the models were interpreted, and the mechanisms of bioactive compounds with a narrow therapeutic index (NTI) can also be analyzed. In summary, the models established in this research exhibit superior capacity to those of previous studies; these models enable accurate high-safety substance screening via cytotoxicity prediction across cell lines. Moreover, for the first time, Cytotoxicity Signature (CTS) genes were identified, which could provide additional clues for further study of mechanisms of action (MOA), especially for NTI compounds.