Background/Aims: Dysregulated cholesterol metabolism is a hallmark of hepatocellular carcinoma (HCC) that drives tumor initiation and progression. However, clinical targeting of cholesterol metabolism has yielded limited benefits due to stringent feedback in tumor cells. Identifying a central mediator capable of restoring cholesterol homeostasis within the cell’s intrinsically fine-tuned regulatory framework is urgently needed. Methods: We integrated a proteomic dataset from patients with cholesterol-dysregulated HCC into a global cholesterol metabolic regulatory network to identify potential therapeutic targets for disrupted cholesterol homeostasis. The prognostic significance of the candidate targets was further validated in an independent cohort through immunohistochemistry. Functional and mechanistic studies were conducted in vitro using HCC cell lines and in vivo using mouse models. The pharmacological efficacy of the candidate agent was evaluated in both subcutaneous and orthotopic HCC mouse models. Results: ER lipid raft-associated 1 (ERLIN1), a pivotal regulator of cholesterol metabolism reprogramming, was identified as an independent favorable prognostic indicator in HCC. ERLIN1 constrains HCC progression both in vitro and in vivo by stabilizing the INSIG1–SCAP–SREBP2 axis and maintaining the metabolic balance of intracellular cholesterol. Under hypoxia, impaired factor-inhibiting hypoxia-1-dependent hydroxylation of ASB11 at asparagine residues 90 and 92 enhances ASB11-mediated ERLIN1 degradation. Pharmacological targeting of this axis using zoledronic acid (ZoA) attenuated HCC progression by weakening the ASB11–ERLIN1 interaction and restoring cholesterol homeostasis. Conclusions ERLIN1 represents a druggable metabolic vulnerability in cholesterol-dysregulated HCC. Targeting the ASB11–ERLIN1 axis with the clinically approved ZoA reestablishes cholesterol homeostasis and offers a promising therapeutic strategy to overcome the current limitations of cholesterol-targeted HCC therapies.

Objective By using intravoxel incoherent motion(IVIM)double exponential model liver multi-b value diffusion-weighted imaging(DWI)scanning technique to analyze the lesion's IVIM parameters before and after interventional treatment of hepatocellular carcinoma(HCC)with conventional transcatheter arterial chemoembolization(TACE)combined with CalliSpheres drug-loaded microspheres(DEB-TACE),based on which to quantitatively evaluate the efficacy of interventional therapy for HCC.Methods A total of 40 HCC patients,who were admitted to the Department of Interventional Therapy of Anqing Municipal Hospital of China from June 2022 to November 2023 to receive DEB-T ACE,were enrolled in this study.Routine MR examination,DWI and IVIM-DWI scan were performed before and at 1,3 and 6 months after treatment,and a total of 40 interest lesions were selected.The ADC value,perfusion fraction(f),pure diffusion coefficient(D),and perfusion-related diffusion coefficient(D*)of each lesion were analyzed.The receiver operating characteristic(ROC)curve was drawn to analyze the prognosis assessment value of IVIM-DWI parameters.Results After DEB-TACE treatment,the ADC value and D value were increased,and the f value was decreased when compared with their preoperative values,the differences were statistically significant(all P＜0.01).The ADC value and D value in the patients of effective group were remarkably higher than those in the patients of ineffective group,the differences were statistically significant(both P＜0.01);the f value in the patients of effective group was slightly lower than that in the patients of ineffective group,and the difference was statistically significant(P＜0.05).The areas under ROC curve of ADC value,D value and f value for evaluating efficacy were 0.762,0.877,and 0.708 respectively.The area under the curve for the joint assessment of the three parameters was 0.928,with the highest efficacy.Conclusion IVIM-DWI can quantitatively determine the microperfusion and activity of HCC lesions before and after interventional DEB-TACE treatment,and it can also evaluate the curative efficacy of interventional therapy for HCC as well as the outcome of HCC lesions.

Objective To analyze the proportion and clinicopathological characteristics of HER2-positive breast cancer patients with BRCA1/2 pathogenic variants, and their response to neoadjuvant anti-HER2 targeted therapy. Methods The clinicopathological data of 531 breast cancer patients with germline BRCA1/2 pathogenic variants (201 with BRCA1 variants and 330 with BRCA2 variants) were analyzed. Results Among the 201 BRCA1 and 330 BRCA2 variants, 17 (8.5%) and 42 (12.7%) HER2-positive breast cancer cases were identified, respectively, accounting for 11.1% of all BRCA1/2-mutated breast cancers. Compared with BRCA1/2-mutated HR-positive/HER2-negative patients, HER2-positive patients did not present any significant differences in clinicopathological features; however, compared with triple-negative breast cancer patients, HER2-positive patients had a later onset age and lower tumor grade. Among the 17 patients who received neoadjuvant anti-HER2 targeted therapy, 10 cases achieved pCR (58.8%), whereas 7 cases did not (41.2%). Conclusion HER2-positive breast cancer accounts for more than 10% of BRCA1/2-mutated patients. Approximately 40% of these patients fail to achieve pCR after neoadjuvant targeted therapy. This phenomenon highlights the possibility of combining anti-HER2 targeted agents with poly (adenosine diphosphate-ribose) polymerase inhibitors.

Objective: To understand the distribution characteristics of high-risk populations for chronic obstructive pulmonary disease (COPD) among residents aged ≥40 years in Inner Mongolia Autonomous Region, so as to provide a basis for comprehensive prevention and control of COPD. Methods: A multi-stage stratified cluster random sampling method combined with probability proportional to size sampling was used to select residents aged ≥40 years from May to December 2019 in 4 monitoring sites in Inner Mongolia Autonomous Region for a questionnaire survey. Information on demographics, current or past smoking, severe respiratory infections in childhood, exposure to occupational harmful factors, exposure to indoor polluting fuels, chronic respiratory symptoms, personal history of chronic respiratory diseases, and family history of chronic respiratory diseases was collected. The distribution characteristics of high risk populations of COPD and high-risk factors were analyzed. Results: A total of 2 302 people were surveyed, including 1 234 males (53.61%) and 1 068 females (46.39%). The mean age was (57.87±8.67) years. A total of 2 114 people (91.83%) were exposed to at least one high-risk factor. The exposure rate of risk factors was 87.88%. There were significant differences in the exposure rates of risk factors among residents of different genders, ages, residence, and occupations (all P<0.05). The exposure rate was higher in males than in females, higher in the 50-60 years than in the 60-<70 years, higher in rural areas than in urban areas, and higher among those engaged in agriculture, forestry, animal husbandry, fishery, and water conservancy than among national enterprise clerks, professional and technical personnel, and retirees (all P<0.05). The prevalence of chronic respiratory symptoms was 14.73%. There were significant differences in the prevalence of chronic respiratory symptoms among residents of different residence and occupations (all P<0.05). The prevalence was higher in rural areas than in urban areas, and higher among those engaged in agriculture, forestry, animal husbandry, fishery, and water conservancy than among retirees (all P<0.05). The exposure rate of personal history of chronic respiratory diseases was 10.90%. There were significant differences in the exposure rate of personal history of chronic respiratory diseases among residents of different educational levels, residence, and occupations (all P<0.05). The exposure rate was higher among those with primary education or below and junior high school education than among those with high school education or above, higher in rural areas than in urban areas, and higher among those engaged in agriculture, forestry, animal husbandry, fishery, and water conservancy than among retirees (all P<0.05). The exposure rate of family history of chronic respiratory diseases was 22.85%. The exposure rate was higher in rural areas than in urban areas (P<0.05). Among residents exposed to risk factors, the exposure rate of current or past smoking was 38.84%, the exposure rate of severe respiratory infections in childhood was 2.13%, the exposure rate of occupational harmful factors was 44.27%, and the exposure rate of indoor polluting fuels was 60.12%. The exposure rates of current or past smoking and occupational harmful factors were higher in males and rural residents (all P<0.05). Conclusions The proportion of high-risk populations for COPD among residents aged ≥40 years in Inner Mongolia Autonomous Region is relatively high. It is recommended to strengthen health education for male residents, rural residents, and those engaged in agriculture, forestry, animal husbandry, fishery, and water conservancy, and to adopt comprehensive prevention and control strategies to reduce the exposure level of risk factors among residents.

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 propose a functional method for locating the shoulder joint center of rotation aimed at rapid estimation of the upper limb reachable domain envelope, thereby informing ergonomic design and task optimization.Methods:In March 2024, shoulder kinematics during gait were recorded from ten adults using a three-dimensional motion-capture system. Assuming the existence of a point near the glenohumeral joint that maintains a fixed spatial relationship to the humerus and the acromion, we estimated both static and dynamic centers of rotation. Localization accuracy was quantified by the standard deviation of distance residuals to upper-arm markers. Upper-limb joint angles and anthropometric parameters were modeled via regression; combined with maximal joint ranges of motion, these were used to infer the reachable domain envelope.Results:The static center of rotation was located approximately twenty-two millimeters medial to the acromial landmark in the coronal plane and thirty-seven millimeters inferior to it. The standard deviation of the residuals for the distances from the dynamic shoulder joint center of rotation to upper-arm markers averaged 1.02 mm, which was 47.42% lower than that of the static center of rotation and 66.56% lower than that of the acromion. Moreover, the trajectory of this dynamic center showed a strong correlation with upper-limb joint angles ( R2>0.7) . Conclusion:The proposed method enables rapid and accurate estimation of the upper limb reachable domain envelope to support ergonomic design and may help reduce the risk of work-related musculoskeletal disorders.

When the epidemiology of infectious diseases is more complex, it is often difficult for disease prediction studies based on a single model to capture the multidimensional nature of disease transmission. In recent years, combining different models to improve infectious disease prediction has gradually become a research trend and hotspot. Existing studies have shown that combined models usually have higher prediction performance and better generalization ability. The current combined models mainly combine machine learning and other models, including time-series models, dynamic models, etcetera. In addition, integrated learning that combines diverse machine learning techniques also holds significant importance across various research domains. This paper reviews the progress of applying combined models around machine learning in infectious disease prediction to promote the innovation and practice of combined models for infectious diseases and help to build smarter and more efficient infectious disease early warning and prediction methods and systems.

Methods such as compartmental models, agent-based models, time series models, and machine learning can be used for the prediction of infectious disease incidence. When disease epidemics are complex, it is often difficult to use a single model to comprehensively and accurately capture the multi dimensional nature of the disease. Exploring the combined application of different models has gradually become a research trend and hotspot in recent years, and the prediction performance of combined models is often better than that of single ones. Current research related to combined models mainly focus on machine learning or compartmental models. In this review, we focus on the combination of compartmental models and other models, and summarize their combination principles, application progress, and advantages or disadvantages for the purpose of promoting the innovation and application of combined models for infectious disease incidence prediction, and establishing a more intelligent and efficient early warning and prediction method or systems for the prevention and control of infectious disease.

Objective To develop a three-compartment kinetic fatigue model for the isometric muscle endurance of the hip,knee,and ankle joints at 50％IPT(isometric peak torque),so as to provide a theoretical basis for simulation-based assessments and load evaluations in biomechanics and sports science.Methods The IPT of the hip,knee,and ankle joints was measured in 40 male university students.Isometric endurance tests were then performed on all three joints at 50％IPT until exhaustion.Electromyography data and endurance time(ET)of major lower limb muscles were collected concurrently.The differences between ETs predicted by models based on previously recommended F and R parameters and actual ETs were analyzed.Subsequently,experimental ETs were used in a grid search to optimize Fand R parameters,allowing for the development of an accurate three-compartment kinetic model.Results The ET of the hip and ankle joints was significantly longer than that of the knee joint(P＜0.001).Models using previously recommended Fand R parameters overestimated ET,with significantly higher predicted values than experimentally measured ET(P＜0.001),as well as elevated root mean squared error(RMSE)and mean relatvie error(MRE)values.The grid search successfully identified Fand R parameters for the three-compartment model in isometric endurance tests of lower limb joints,with no statistical difference between model-predicted ET and experimental ET(P＞0.05).Conclusions The developed model in this study can serve as an indirect measurement tool for evaluating load in similar activities.

Objective:To assess the prognostic impact of the thoracic aorta and aortic valve calcification volume (TAC, AVC) score based on CT measurementsin patients undergoing transcatheter aortic valve implantation (TAVI).Methods:We retrospectively analyzed 102 patients who underwent TAVI for severe aortic stenosis from March 2018 to April 2022 at Fuwai Central China Cardiovascular Hospital. The patients were stratified into low TAC and AVC group (TAC low, AVC low) and high TAC and AVC group (TAC high, AVC high) based on median TAC and AVC. The independent risk factors affecting the prognosis of TAVI patients were analyzed using univariate and multivariate Cox proportional risk regression, and the independent risk factors affecting the prognosis of TAVI were analyzed by survival curve. Results:A total of 102 patients were included with a median follow-up of 695 (602, 923) days, during which 9 (8.8%) all-cause deaths and 33 (32.4%) composite end-point events occurred. Univariate Cox risk regression analysis found that TAC was a risk factor for all-cause mortality events in TAVI patients ( P=0.039), TAC and AVC were risk factors for composite endpoint events in TAVI patients ( P=0.047, 0.035).TAC was an independent predictor of all-cause mortality after TAVI in multivariate analysis ( HR=8.971, 95% CI 1.121-71.790, P=0.039), and TAC and AVC were independent risk factors for composite endpoint events after TAVI ( HR=2.243, 95% CI 1.099-4.578, P=0.026; HR=2.346, 95% CI 1.146-4.804, P=0.020). Kaplan-Meier survival curves showed that high TAC and AVC scores increased the risk of end-point events ( P<0.05). Conclusion:CT-quantified TAC and AVC volume scores are independent prognostic markers in TAVI patients, with greater calcification burden portending poorer clinical outcomes.