ObjectiveTo explore the effects of hypoxia on the migration ability of human oligodendrocyte precursor cells （hOPCs） and its regulatory mechanisms. MethodsBased on the variations in oxygen concentration within the culture system， three experimental groups were set up： the 21%O₂ group （normoxic control group）， the 5%O₂ group， and the 2%O₂ group. The migration ability of hOPCs under normoxia （21%O₂）， 5%O₂， and 2%O₂ conditions was detected through the Transwell migration assay. RT-qPCR， transcriptome sequencing， and flow cytometry were used to detect the expression changes of genes and proteins such as hypoxia-inducible factor 1 alpha （HIF-1α） and chemokine （C-X-C Motif） receptor 4 （CXCR4）. Bioinformatics analysis was combined to analyze the KEGG pathways related to migration， so as to explore the effects of different oxygen concentrations on the migration ability of hOPCs and their possible mechanisms. ResultsHypoxia treatments at concentrations of 5%O₂ and 2%O₂ could both promote the in vitro migration of hOPCs， and the promoting effect of migration was more significant at the 2%O₂ concentration （P<0.001）. After hypoxia treatment， the mRNA expression levels of HIF-1α， CXCR4， etc. in hOPCs significantly increased （P<0.001）. Compared with the 5%O₂ concentration， the expression of CXCR4 in cells was higher at the 2%O₂ concentration （P<0.000 1）. Flow cytometry analysis detection showed that the expression of CXCR4 increased significantly after hypoxia treatment （P<0.01）， and with the decrease of oxygen concentration， its expression level further increased （P<0.000 1）. Ordinary transcriptome sequencing analysis indicated that hypoxia treatment could activate the PI3K-Akt signaling pathway and the Axon guidance pathway. ConclusionHypoxia treatment can enhance the in vitro migration ability of hOPCs， and this effect is negatively correlated with the oxygen concentration. Its mechanism may be related to the up-regulation of the expression of genes such as HIF-1α and CXCR4， and the activation of the migration related signaling pathway including PI3K-Akt signaling pathway and axon guidance pathway.

Background/Aims: Lenvatinib resistance remains a critical barrier in advanced hepatocellular carcinoma (HCC) therapy. However, the underlying mechanisms and strategies for reversing resistance remain incompletely understood. Methods: Integrated transcriptomics of lenvatinib-resistant patient tumors and an acquired-resistance murine model identified a novel macrophage subpopulation. Functional validation employed CRISPR-SAM screening, conditioned medium (CM) assays, subcutaneous/orthotopic xenografts, patient-derived organoids (PDOs), and patient-derived xenografts (PDXs). Mechanistic studies included ChIP-qPCR, co-immunoprecipitation, and pharmacologic targeting. Clinical relevance was assessed in a retrospective cohort. Results: Resistant HCC exhibited significant enrichment of a COLEC12high TAM subset , which correlated with poor survival and treatment response. These TAMs secreted neuregulin-1 (NRG1) , activating HER2/HER3-AKT signaling in tumor cells to drive cancer stemness and lenvatinib resistance. Mechanistically, in TAMs COLEC12 sequestered STAT1 in the cytoplasm, preventing its phosphorylation, and thereby derepressing STAT3-mediated NRG1 transcription. Depletion of NRG1 reversed the stemness phenotypes and resensitized tumors to lenvatinib both in vitro and in vivo. Clinically, high NRG1 expression predicted an inferior lenvatinib response and shorter survival. Crucially, the bispecific anti-HER2/HER3 antibody zenocutuzumab restored lenvatinib efficacy in PDOs, PDXs, and murine models. Conclusions Our work establishes the COLEC12high TAM/NRG1 axis as a master regulator of therapeutic resistance and identifies NRG1 as a predictive biomarker, providing a clinically actionable strategy to overcome lenvatinib resistance in HCC.

Objective To develop the value of machine learning(ML)models based on contrast-transthoracic echocardiography(cTTE)and transesophageal echocardiography(TEE)combined with clinical and laboratory indicators for predicting patent foramen ovale-associated stroke(PFO-AS).Methods Totally 313 patients with PFO diagnosed with cTTE and TEE were retrospectively enrolled.Among them,65 cases were found complicated with ischemic stroke and confirmed as PFO-AS(PFO-AS group),and the rest 248 cases without ischemic stroke were classified as non-PFO-AS group.The patients were divided into training set(n=219,including 48 cases of PFO-AS and 171 cases of non-PFO-AS)and test set(n=94,including 17 cases of PFO-AS and 77 cases of non-PFO-AS)at the ratio of 7∶3.Univariable and multivariable logistic regression(LR)were used to analyze clinical and laboratory indicators as well as cTTE and TEE parameters in training set to screen independent predictive factors of PFO-AS.ML models,including LR,K-nearest neighbor(KNN),support vector machine(SVM),random forest(RF),decision tree(DT),back propagation neural network(BPNN)and gradient boosting machine(GBM)were constructed,and the predictive efficacy of the models for predicting PFO-AS was evaluated,then the optimal model was selected.Results Patient's age＞49-69 years,with smoking history,plasma albumin≥43.8 g/L,significant right-to-left shunt at rest shown on cTTE and complicated atrial septal aneurysm shown on TEE were all independent predictors of PFO-AS,which were used to construct ML models.The area under the curve(AUC)of LR,KNN,SVM,RF,DT,BPNN and GBM models in training set was 0.779-0.853,while in test set was 0.730-0.877.RF model had relatively high and comparable sensitivity,specificity and AUC in both training and test sets,also higher precision and smaller Brier score in test set,hence was regarded as the optimal ML model.Conclusion RF model based on cTTE and TEE combined with clinical and laboratory indicators could be used to effectively predict PFO-AS.

Poly(lactic-co-glycolide)(PLGA)is a key excipient in long-acting sustained-release preparations,and its degradation properties directly affect the drug release behavior.In this study,PLGA microspheres were prepared by microfluidic techniques,and the morphology changes of the microspheres were observed by scanning electron microscopy(SEM).In alkaline environment,due to the accelerated hydrolysis of ester bonds,the surface of the microspheres was rapidly dissolved and eroded,and the degradation rate was significantly higher than that in acidic environment.High temperature accelerated the degradation of PLGA microspheres.Under neutral and alkaline conditions,the microspheres showed aggregation and adhesion.Under acidic conditions,the microspheres gradually decomposed into irregular fragments.The high ionic strength further promoted the surface corrosion of the microspheres,especially under extreme pH conditions.Simultaneously,PLGA microspheres encapsulating coumarin were prepared to simulate the microsphere formulation.The release rate of coumarin after degradation of the microspheres under different conditions was observed by measuring the absorbance with ultraviolet-visible spectrophotometry.The results were consistent with those of the blank microspheres.This study revealed that the degradation of PLGA microspheres was significantly pH-dependent,temperature sensitive and ion strength responsive.These findings not only helped to understand and optimize the long-term stability and controlled release performance of drug-carrying microspheres,but also provided a theoretical basis for further improvement of PLGA-based drug carrier design.

The aging trend is intensifying currently,but there is still a lack of standardized diagnosis and treat-ment schemes for severe infections in elderly people.This paper focuses on the recommendations for immune-related clinical diagnosis and treatment routes as well as the idea of risk stratified diagnosis and treatment for elderly peo-ple,aiming to effectively prevent infectious diseases in elderly people and perform stratified management through systematic and scientific means of immune function monitoring and regulation,so as to enhance the standardized level of diagnosis and treatment as well as clinical treatment effect of infection in elderly people.

Objective:To compare the accuracy of two-dimensional (2D) ultrasound with three-dimensional (3D) reconstruction and conventional 2D ultrasound in measuring bladder volume in pelvic tumor patients, using computed tomography (CT) as the reference.Methods:A set of bladder phantoms were constructed to compare CT and ultrasound measurements with actual injected volumes. Clinical data of 104 pelvic tumor patients who received radiotherapy at the Cancer Hospital, Chinese Academy of Medical Sciences between August and December 2023 were retrospectively analyzed. Portable transabdominal ultrasound was used to obtain the largest bladder cross-section, and the maximum diameters in the left-right (LR), anterior-posterior (AP), and superior-inferior (SI) directions (D LR, D AP, D SI) were measured. The 2D ultrasound volume was calculated as V=0.523 × D LR × D AP × D SI. Full-bladder transverse videos were recorded and processed in Matlab R2016a through frame extraction(60 images), followed by contrast enhancement, edge detection segmentation, cubic spline interpolation, and image smoothing to achieve 3D reconstruction. Paired t-tests, intraclass correlation coefficients (ICC), and Bland-Altman analyses were performed to assess systematic bias and consistency between ultrasound methods and CT. Multivariate linear regression was applied to evaluate the effects of slice thickness, posture, age, and other factors on CT measurements. Results:In the phantom study, deviations of 2D ultrasound and CT from actual injected volumes were (0.73±3.05) ml ( t=-0.48, P=0.667) and (1.52±11.27) ml ( t=0.17, P=0.875), with ICC values>0.999. In the clinical study, mean bladder volumes measured by 3D-reconstructed ultrasound, conventional 2D ultrasound, and CT were (373.5±153.31), (314.89±135.28), (382.82±157.57) ml, respectively. The 3D-reconstructed method showed excellent agreement with CT (ICC=0.98; Bland-Altman mean bias=-9.32 ml, P=0.096), while 2D ultrasound also showed good consistency (ICC=0.91), but significantly underestimated bladder volume (mean bias=-67.93 ml, P<0.001). Subgroup analysis revealed that 2D ultrasound had the best agreement with CT in the medium-volume group (200-500 ml, ICC=0.902), whereas agreement decreased in the small-volume (<200 ml, ICC=0.884) and large-volume (>500 ml, ICC=0.840) groups (all P<0.001). The 3D-reconstructed ultrasound maintained excellent consistency with CT across all subgroups (all ICC>0.95), and the measured bladder volume was not statistically significant. Multivariate regression showed that slice thickness, posture, age, sex, and surgical status had no significant effects on CT measurements. Conclusions:Ultrasound with 3D reconstruction enables accurate bladder volume monitoring through true 3D contour reconstruction, while conventional 2D ultrasound systematically underestimates bladder volume and requires correction.

Objective:To investigate the mediating role of perceived stress between frailty and major adverse cardio-vascular events(MACE)after percutaneous coronary intervention(PCI)in elderly patients with coronary heart dis-ease(CHD).Methods:A convenience sampling method was employed to select 270 elderly patients who were first diagnosed as CHD and underwent PCI in Department of Cardiology,Cangzhou People's Hospital between October 2021 and February 2022.A comprehensive investigation was carried out using general demographic questionnaires,the Fried frailty phenotype scale,the Chinese version of perceived stress scale(CPSS),and follow-up question-naires.The association among frailty,CPSS score and MACE was analyzed using Logistic regression model.Bidi-rectional Spearman correlation analysis was used to explore the association of CPSS score with frailty and MACE.The R 4.2.2 software was employed to examine the mediating effects of perceived stress on frailty.Results:Within one year after PCI,the incidence rate of MACE was 13.70％.Multivariate Logistic regression analysis indicated that frailty(OR=3.554,95％CI 1.332～9.485,P=0.011)and CPSS score(OR=1.095,95％CI 1.038～1.154,P＜0.001)were independent risk factors for MACE in elderly CHD patients after PCI.Spearman correlation analy-sis indicated that CPSS score was positively correlated with frailty and MACE(r=0.506,0.346,P＜0.001 all).Perceived stress partially mediated the relationship between frailty and MACE after PCI,accounting for 38.03％of the total effect.Conclusion:Frailty may directly affect MACE in elderly CHD patients after PCI,and indirectly af-fect MACE through perceived stress.Clinically,the significant roles of both frailty and perceived stress in MACE should be fully considered,and early identification should be conducted for predictive interventions.

Objective To compile a comprehension assessment scale of double-conditional phrases for adults and to test its reliability and validity.Methods With reference to the compilation process of local and international word lists,a comprehension assessment scale of double-conditional phrases for adults was developed.The scale was used to assess 40 aphasia patients and 20 ordinary adults as subjects from four hospitals in Shanghai.The internal consistency reliability,split-half reliability,retest reliability and calibration validity of the scale were evaluated and analyzed[the western aphasia battery(WAB)as a calibrated measurcment instrument].Results The scale consists of 30 questions,including five types of phrases:coordinate phrases,verb-object phrases,subject-predicate phrases,endocentric phrases and interface-object phrases.Compared with the ordinary adult group,the total score of the scale and the scores of each dimension in the aphasia group were significantly lower than those in the control group(P＜0.001).The Cronbach's alpha coefficient for the total score was 0.894,the half coefficient was 0.924,and the correlation coefficient for the retest reliability of the total score was 0.923,with retest reliability for each type of word group ranging from 0.731 to 0.903.With the exception of the repetition scores,correlation coefficients be-tween the scale and all other scores of WAB were all＞0.6(P＜0.01).Conclusion The self-developed"Adult Double Conditional Phrases Auditory Comprehension Assessment Scale"demonstrates good reliability and validity.It serves as a scientific and reliable tool for evaluating the auditory comprehension ability of adult patients.

Objective To develop the value of machine learning(ML)models based on contrast-transthoracic echocardiography(cTTE)and transesophageal echocardiography(TEE)combined with clinical and laboratory indicators for predicting patent foramen ovale-associated stroke(PFO-AS).Methods Totally 313 patients with PFO diagnosed with cTTE and TEE were retrospectively enrolled.Among them,65 cases were found complicated with ischemic stroke and confirmed as PFO-AS(PFO-AS group),and the rest 248 cases without ischemic stroke were classified as non-PFO-AS group.The patients were divided into training set(n=219,including 48 cases of PFO-AS and 171 cases of non-PFO-AS)and test set(n=94,including 17 cases of PFO-AS and 77 cases of non-PFO-AS)at the ratio of 7∶3.Univariable and multivariable logistic regression(LR)were used to analyze clinical and laboratory indicators as well as cTTE and TEE parameters in training set to screen independent predictive factors of PFO-AS.ML models,including LR,K-nearest neighbor(KNN),support vector machine(SVM),random forest(RF),decision tree(DT),back propagation neural network(BPNN)and gradient boosting machine(GBM)were constructed,and the predictive efficacy of the models for predicting PFO-AS was evaluated,then the optimal model was selected.Results Patient's age＞49-69 years,with smoking history,plasma albumin≥43.8 g/L,significant right-to-left shunt at rest shown on cTTE and complicated atrial septal aneurysm shown on TEE were all independent predictors of PFO-AS,which were used to construct ML models.The area under the curve(AUC)of LR,KNN,SVM,RF,DT,BPNN and GBM models in training set was 0.779-0.853,while in test set was 0.730-0.877.RF model had relatively high and comparable sensitivity,specificity and AUC in both training and test sets,also higher precision and smaller Brier score in test set,hence was regarded as the optimal ML model.Conclusion RF model based on cTTE and TEE combined with clinical and laboratory indicators could be used to effectively predict PFO-AS.

Objective:To investigate the prevalence and severity of symptom burden among long-term survivors of oropharyngeal cancer after radiotherapy, to identify core symptom clusters, and to explore their correlation with quality of life.Methods:A previous retrospective study was conducted by the Cancer Hospital, Chinese Academy of Medical Sciences on patients with oropharyngeal cancer who underwent radiotherapy between January 2010 and December 2020. Patients who were still alive as of December 2023 were further followed and analyzed. From December 2023 to August 2024, symptom burden and quality of life were assessed using the Chinese version of the MD Anderson Symptom Inventory–Head and Neck Module (MDASI-HN) and the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ). Exploratory factor analysis (principal component analysis with Promax rotation) were used to identify symptom clusters. Spearman correlation analysis was performed to explore the relationship between total symptom cluster scores and standardized domain scores of quality of life. Multivariate linear regression analysis was further employed to determine the relationship between identified symptom clusters and overall quality of life.Results:A total of 273 patients were included, with a median follow-up duration of 6.2 years (range: 3.5-14.5 years) and a median age of 61 years (range: 27-88 years) at follow-up. The top 5 incidence rates of symptom reported by patients were mucus problems in the mouth or throat (147 cases, 53.8%), dental or gum issues (143 cases, 52.4%), xerostomia (140 cases, 51.3%), difficulty swallowing or chewing (95 cases, 34.8%), and taste disturbance (79 cases, 28.9%). Among them, xerostomia was the most serious symptom. The most frequently reported interference was impact on work (including household chores) (55 cases, 20.1%). Exploratory factor analysis identified 3 symptom clusters: fatigue-nausea cluster, eating-voice cluster, and xerostomia-sleep cluster, all of which were significantly correlated with lower overall quality of life of patients (all P<0.001). Conclusion:Long-term survivors of oropharyngeal cancer after radiotherapy experience substantial symptom burden. The fatigue-nausea, eating-voice, and xerostomia-sleep clusters are the core symptom clusters impacting quality of life.