The precise diagnosis and treatment of hepatocellular carcinoma （HCC） face major challenges such as the complexity of tumor microenvironment， treatment resistance， and a high risk of recurrence and metastasis. In recent years， ultrasound technology has moved beyond its traditional role in screening and localization， gradually evolving into a multidimensional therapeutic platform capable of energy activation， targeted delivery， local ablation， immune modulation， and therapeutic feedback. This article systematically reviews the latest advances in the basic research on ultrasound techniques in HCC treatment and integrated management. In terms of treatment， intervention strategies represented by microbubble/nanobubble-mediated delivery， sonodynamic therapy， high-intensity focused ultrasound， and histotripsy not only enable in situ physical destruction of lesions， but also effectively reverse tumor immune tolerance networks through deep synergy with sonogenetics， metabolic reprogramming， and immunochemotherapy. In terms of integrated management， novel sonosensitive nanodelivery systems provide a platform for energy activation and targeted controlled release. To address the translational bottlenecks in this field， it is recommended to develop standardized consensus on preclinical therapeutic ultrasound parameters， in order to establish a new translational paradigm for individualized precise diagnosis and treatment of HCC.

ObjectiveTo systematically quantify the multidimensional effect of virtual reality-based exergaming (VREG) on health outcomes among individuals with cognitive impairment under the framework of the International Classification of Functioning, Disability and Health (ICF). MethodsMeta-analysis was conducted in accordance with the PRISMA statement. PubMed, Cochrane Library, Embase, Scopus, Web of Science, CNKI, Wanfang Data and VIP were researched for randomized controlled trials (RCTs) investigating VREG for cognitive impairment, with the search deadline set on February 1, 2026. The Cochrane Risk of Bias 2.0 tool was adopted to evaluate the methodological quality of included studies. A three-level meta-analytic model was implemented with R 4.4.2. The GRADE framework was further used to rate the certainty of pooled evidence. ResultsA total of 22 RCTs were included. VREG might improve global cognitive function (SMD = 0.69, 95%CI 0.11 to 1.28, P = 0.022), memory (SMD = 0.47, 95%CI 0.07 to 0.87, P = 0.023), attention (SMD = 0.62, 95%CI 0.23 to 1.01, P = 0.004), executive function (SMD = 0.42, 95%CI 0.09 to 0.75, P = 0.013), balance (SMD = 0.54, 95%CI 0.07 to 1.00, P = 0.027), muscle strength (SMD = 0.63, 95%CI 0.37 to 0.88, P = 0.001), mobility (SMD = 0.29, 95%CI 0.04 to 0.54, P = 0.024) and quality of life (SMD = 0.29, 95%CI 0.03 to 0.56, P = 0.029). No significant effect was observed for depressive symptoms, comprehensive physical fitness and fall risk (all P > 0.05). Subgroup and meta-regression analyses indicated that session duration < 45 minutes produced the largest improvement in attention (SMD = 0.95, 95%CI 0.55 to 1.34, P < 0.001); intervention cycles of twelve to 24 weeks were optimal for mobility (SMD = 0.85, 95%CI 0.44 to 1.25, P < 0.001); age negatively correlated to balance improvement (β = -0.11, 95%CI -0.20 to -0.02, P = 0.020), suggesting less intervention benefits among older participants. ConclusionVREG is an effective non-pharmacological intervention to improve multidimensional physical and mental health in people with cognitive impairment. Protocols featuring short single sessions with long-term duration should be prioritized.

Objective: To explore the protective effect of mild moxibustion on the ovary of mice with premature ovarian insufficiency (POI) and its mechanism. Methods: SPF female ICR mice with normal estrus cycle were divided into blank group, model group, moxibustion group and moxibustion + Compound C group according to the random number table method, with 20 mice in each group. The mice in the blank group were given normal saline daily. The mice in the other groups were gavaged with Tripterygium wilfordii polyglycosides[75 mg/(kg·d)] for 14 consecutive days for modeling. An hour later, the mice in the moxibustion group were treated with mild moxibustion every day, and bilateral "shenshu" and "guanyuan" "zhongwan" were alternately applied every other day, and each point was treated with mild moxibustion for 10 minutes each day. Thirty minutes after gavaging Tripterygium wilfordii polyglycosides, the mice in the moxibustion + Compound C group were given intraperitoneal injection of Compound C (10 mg/kg); an hour later, mild moxibustion was applied same as the moxibustion group. The mild moxibustion was applied once a day for 14 consecutive days. The protective effect of moxibustion on ovary was evaluated by ovarian index, rate of estrus cycle disorder, ovarian tissue morphology, the number of follicles at all levels and serum sex hormone levels. Quantitative real-time polymerase chain reaction and immunohistochemistry were used to detect the mRNA and protein expression of adenosine 5′-monophosphate-activated protein kinase (AMPK) and peroxisome proliferator-activated receptor gamma coactivator 1α (PGC-1α) in ovarian tissue. Serum sex hormones oxidative stress markers, adenosine triphosphate (ATP) and reactive oxygen species (ROS) levels in ovarian granulosa cells were detected by enzyme-linked immunosorbent assay, luciferase method and chemifluorescence method, respectively. Results: Compared with the model group, the ovarian index of the moxibustion group increased (P<0.05), the rate of estrous cycle disorder decreased (P<0.05), the number of atretic follicles decreased (P<0.05), and the number of primordial follicles, primary follicles, secondary follicles and antral follicles all increased (P<0.05). The levels of serum anti-Müllerian hormone and estrogen increased (P<0.05), while the level of follicle-stimulating hormone decreased (P<0.05); the expressions of protein and mRNA of AMPK and PGC-1α were upregulated (P<0.05); the activity of serum superoxide dismutase increased, the content of malondialdehyde decreased, and the ATP level of granulosa cells increased, while the mean fluorescence intensity of ROS decreased (P<0.05). However, when Compound C was given before moxibustion intervention, the protective effect on the ovary was significantly reduced, as shown by the reduction of ovarian index (P<0.05), the rate of estrus cycle disorder increased (P <0.05), the number of atretic follicles increased (P<0.05), and the number of primordial follicles, primary follicles, secondary follicles and antral follicles decreased (P<0.05). Conclusion Moxibustion can protect ovarian function in mice by promoting the activation of AMPK and PGC-1α signaling, inhibiting oxidative stress response and regulating hormone levels.

Gastric cancer has high incidence and mortality rate. Chemotherapy is the first-line treatment for gastric cancer and has achieved considerable success. However, due to genetic variations and tumor heterogeneity, the effectiveness of chemothrapy drugs varies among different patients. Therefore, accurate assessment of patient’s sensitivity to chemotherapy drugs is crucial for personalized treatment. Gastric cancer organoids serve as effective tools for predicting patient’s sensitivity to chemotherapy drugs. This review summarizes the applications and related research progress of gastric cancer organoids in determining chemotherapy drug sensitivity, discusses the strengths and limitations of organoid models, and proposes outlooks for future research directions, hoping that organoids can provide more effective personalized treatment options and a greater range of drug choices for gastric cancer treatment.

BACKGROUND: Chronic kidney disease (CKD) is associated with common pathophysiological processes, such as inflammation and fibrosis, in both the heart and the kidney. However, the underlying molecular mechanisms that drive these processes are not yet fully understood. Therefore, this study focused on the molecular mechanism of heart and kidney injury in CKD. METHODS: We generated an microRNA (miR)-26a knockout (KO) mouse model to investigate the role of miR-26a in angiotensin (Ang)-II-induced cardiac and renal injury. We performed Ang-II modeling in wild type (WT) mice and miR-26a KO mice, with six mice in each group. In addition, Ang-II-treated AC16 cells and HK2 cells were used as in vitro models of cardiac and renal injury in the context of CKD. Histological staining, immunohistochemistry, quantitative real-time polymerase chain reaction (PCR), and Western blotting were applied to study the regulation of miR-26a on Ang-II-induced cardiac and renal injury. Immunofluorescence reporter assays were used to detect downstream genes of miR-26a, and immunoprecipitation was employed to identify the interacting protein of LIM and senescent cell antigen-like domain 1 (LIMS1). We also used an adeno-associated virus (AAV) to supplement LIMS1 and explored the specific regulatory mechanism of miR-26a on Ang-II-induced cardiac and renal injury. Dunnett's multiple comparison and t -test were used to analyze the data. RESULTS: Compared with the control mice, miR-26a expression was significantly downregulated in both the kidney and the heart after Ang-II infusion. Our study identified LIMS1 as a novel target gene of miR-26a in both heart and kidney tissues. Downregulation of miR-26a activated the LIMS1/integrin-linked kinase (ILK) signaling pathway in the heart and kidney, which represents a common molecular mechanism underlying inflammation and fibrosis in heart and kidney tissues during CKD. Furthermore, knockout of miR-26a worsened inflammation and fibrosis in the heart and kidney by inhibiting the LIMS1/ILK signaling pathway; on the contrary, supplementation with exogenous miR-26a reversed all these changes. CONCLUSIONS Our findings suggest that miR-26a could be a promising therapeutic target for the treatment of cardiorenal injury in CKD. This is attributed to its ability to regulate the LIMS1/ILK signaling pathway, which represents a common molecular mechanism in both heart and kidney tissues.
Animals ; MicroRNAs/metabolism* ; Angiotensin II/toxicity* ; Mice ; Renal Insufficiency, Chronic/chemically induced* ; Mice, Knockout ; Disease Models, Animal ; Male ; Signal Transduction/genetics* ; LIM Domain Proteins/genetics* ; Mice, Inbred C57BL ; Cell Line ; Humans

BACKGROUND: The role of inflammation in the development of gestational diabetes mellitus (GDM) has recently become a focus of research. The systemic immune-inflammation index (SII) and systemic inflammation response index (SIRI), novel indices, reflect the body's chronic immune-inflammatory state. This study aimed to investigate the associations between the SII or SIRI and GDM. METHODS: A prospective birth cohort study was conducted at Beijing Obstetrics and Gynecology Hospital from February 2018 to December 2020, recruiting participants in their first trimester of pregnancy. Baseline SII and SIRI values were derived from routine clinical blood results, calculated as follows: SII = neutrophil (Neut) count × platelet (PLT) count/lymphocyte (Lymph) count, SIRI = Neut count × monocyte (Mono) count/Lymph count, with participants being grouped by quartiles of their SII or SIRI values. Participants were followed up for GDM with a 75-g, 2-h oral glucose tolerance test (OGTT) at 24-28 weeks of gestation using the glucose thresholds of the International Association of Diabetes and Pregnancy Study Groups (IADPSG). Logistic regression was used to analyze the odds ratios (ORs) (95% confidence intervals [CIs]) for the the associations between SII, SIRI, and the risk of GDM. RESULTS: Among the 28,124 women included in the study, the average age was 31.8 ± 3.8 years, and 15.76% (4432/28,124) developed GDM. Higher SII and SIRI quartiles were correlated with increased GDM rates, with rates ranging from 12.26% (862/7031) in the lowest quartile to 20.10% (1413/7031) in the highest quartile for the SII ( Ptrend <0.001) and 11.92-19.31% for the SIRI ( Ptrend <0.001). The ORs (95% CIs) of the second, third, and fourth SII quartiles were 1.09 (0.98-1.21), 1.21 (1.09-1.34), and 1.39 (1.26-1.54), respectively. The SIRI findings paralleled the SII outcomes. For the second through fourth quartiles, the ORs (95% CIs) were 1.24 (1.12-1.38), 1.41 (1.27-1.57), and 1.64 (1.48-1.82), respectively. These associations were maintained in subgroup and sensitivity analyses. CONCLUSION The SII and SIRI are potential independent risk factors contributing to the onset of GDM.
Humans ; Female ; Pregnancy ; Diabetes, Gestational/immunology* ; Prospective Studies ; Adult ; Inflammation/immunology* ; Glucose Tolerance Test ; Birth Cohort

Facing the requirements of promoting the healthy China initiative and improving people's health, the "bone health program" was proposed in 2024. In-depth development of a traditional Chinese medicine(TCM) prevention and control system is of strategic significance to the implementation of the "bone health program". Focusing on osteoporosis(OP), a representative disease affecting people's bone health, this paper concludes that accelerating the research on the prevention and control of OP by TCM is conducive to enhancing the knowledge and awareness of OP among the public, and it is beneficial to revealing the evolutionary pattern of OP and improving the understanding and management of this disease. Additionally, it can provide an overall framework for and strengthen the systematicity and completeness of the research on the prevention and treatment of OP by TCM. Meanwhile, it can help to explore new research paradigms and optimize the existing research model, so as to promote innovative breakthroughs in the prevention and treatment of bone health-related diseases by TCM. Under the overall layout of the "bone health program", importance should be attached to the early prevention and the innovation of very early diagnosis and intervention of OP. Emphasis should be put on the discovery of the target network of disease and treatment mechanism for revealing the core pathogenesis of OP and the therapeutic mechanism of TCM. In addition to local lesions of the bone and its clinical outcomes, attention should be paid to the development of multiple metabolic complications. The fusion of advanced interdisciplinary technologies should be promoted for OP and its complications, and thus a research and development system based on clinical application scenarios and driven by big data can be built. The measures above will facilitate the progress in the prevention and treatment of OP and other bone diseases by TCM and provide new momentum for enriching and deepening the research connotation of the "bone health program".
Osteoporosis/therapy* ; Humans ; Medicine, Chinese Traditional/methods* ; Drugs, Chinese Herbal/therapeutic use* ; China ; Bone and Bones/drug effects*

OBJECTIVE: To investigate the association between ABO blood types and gestational diabetes mellitus (GDM) risk. METHODS: A prospective birth cohort study was conducted. ABO blood types were determined using the slide method. GDM diagnosis was based on a 75-g, 2-h oral glucose tolerance test (OGTT) according to the criteria of the International Association of Diabetes and Pregnancy Study Groups. Logistic regression was applied to calculate the odds ratios ( ORs) and 95% confidence intervals ( CIs) between ABO blood types and GDM risk. RESULTS: A total of 30,740 pregnant women with a mean age of 31.81 years were enrolled in this study. The ABO blood types distribution was: type O (30.99%), type A (26.58%), type B (32.20%), and type AB (10.23%). GDM was identified in 14.44% of participants. Using blood type O as a reference, GDM risk was not significantly higher for types A ( OR = 1.05) or B ( OR = 1.04). However, women with type AB had a 19% increased risk of GDM ( OR = 1.19, 95% CI = 1.05-1.34; P < 0.05), even after adjusting for various factors. This increased risk for type AB was consistent across subgroup and sensitivity analyses. CONCLUSION The ABO blood types may influence GDM risk, with type AB associated with a higher risk. Incorporating it-either as a single risk factor or in combination with other known factors-could help identify individuals at risk for GDM before or during early pregnancy.
Humans ; Female ; Pregnancy ; Diabetes, Gestational/etiology* ; ABO Blood-Group System ; Adult ; Prospective Studies ; Risk Factors ; Young Adult

ObjectiveTo investigate the application value of a multimodal model integrating radiomics features， deep learning features， and clinical structured data in predicting severe acute pancreatitis （SAP）， and to provide more accurate tools for the early identification of SAP in clinical practice. MethodsThe patients with acute pancreatitis （AP） who attended The First Affiliated Hospital of Soochow University， Jintan Hospital Affiliated to Jiangsu University， and Suzhou Yongding Hospital from January 1， 2017 to December 31， 2023 were included. Related data were collected， including demographic information， previous medical history， etiology， laboratory test data， and systemic inflammatory response syndrome （SIRS） within 24 hours after admission， as well as imaging data within 72 hours after admission， while related scores were calculated， including Ranson score， modified CT severity index （MCTSI）， bedside index for severity in acute pancreatitis （BISAP）， and systemic inflammatory response syndrome， albumin， blood urea nitrogen and pleural effusion （SABP） score. The model was constructed in the following process： （1） three-dimensional CT images were used to extract and identify radiomics features， and a radiomics classification model was established based on the extreme gradient Boost （XGBoost） algorithm； （2） U-Net is used to perform semantic segmentation of three-dimensional CT images， and then the results of segmentation were imported into 3D ResNet50 to construct a deep learning classification model； （3） the predicted values of the above two models were integrated with clinical structured data to establish a multimodal model based on the XGBoost algorithm. The variable importance plot and local interpretability plot were used to perform visual interpretation of the model. The independent samples t-test was used for comparison of normally distributed continuous data between groups， and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between groups； the chi-square test or Fisher’s exact test was used for comparison of categorical data between groups. The receiver operating characteristic （ROC） curve was plotted for each model and existing scoring systems， and the area under the ROC curve （AUC） was calculated to assess their performance； the Delong test was used for comparison of AUC. ResultsA total of 609 patients who met the criteria were included， among whom 114 （18.7%） developed SAP. In this study， the data of 426 patients from The First Affiliated Hospital of Soochow University was used as the training set， and the data of 183 patients from Jintan Hospital Affiliated to Jiangsu University and Suzhou Yongding Hospital were used as the independent test set. The multimodal model had an AUC of 0.914 in the test set， which was significantly higher than the AUC of traditional scoring systems such as MCTSI （AUC=0.827）， Ranson score （AUC=0.675）， BISAP （AUC=0.791）， and SABP score （AUC=0.648）； in addition， the multimodal model showed a significant improvement in performance compared with the radiomics classification model （AUC=0.739） and the deep learning classification model （AUC=0.685） （the Delong test： Z=-3.23， -4.83， -3.48， -4.92， -4.31， and -4.59， all P <0.01）. The top 10 variables in terms of importance in the multimodal model were pleural effusion， predicted value of the deep learning model， predicted value of the radiomics model， triglycerides， calcium ions， SIRS， white blood cell count， age， platelets， and C-reactive protein， suggesting that the above variables had significant contributions to the performance of the model in predicting SAP. ConclusionBased on structured data， radiomic features， and deep learning features， this study constructs a multicenter prediction model for SAP based on the XGBoost algorithm， which has a better predictive performance than existing traditional scoring systems and unimodal models.