In recent years, cancer treatment methods and means are becoming more and more diversified, and single treatment methods often have limited efficacy, while the synergistic effect of immunity combined with chemotherapy can inhibit tumor growth more effectively. Based on this, we constructed a sodium alginate hydrogel composite system loaded with chemotherapeutic agents and tumor vaccines (named SA-DOX-NA) with a view to the combined use of chemotherapeutic agents and tumor vaccines. Firstly, the tumor vaccine (named NA) degradable under acidic conditions was constructed by in situ polymerization using chicken ovalbumin (OVA), acrylamide (AAM) and 2-(dimethylamino) ethyl methacrylate (DMAEMA) monomer. Then a hydrogel composite system SA-DOX-NA co-loaded with chemotherapeutic drug doxorubicin (DOX) and NA was prepared using sodium alginate as a matrix. The results showed that SA-DOX-NA had good in situ gel-forming ability and formed a mesh structure that could realize the co-loading of DOX and NA as well as the slow drug release. The electron microscopy results showed that SA-DOX-NA had good in situ gel-forming ability with good internal connectivity, and the three-dimensional mesh structure could realize the co-loading of DOX and NA as well as the slow drug release. The antitumor and immunomodulatory results showed that SA-DOX-NA both effectively inhibited the growth of tumor cells and efficiently promoted the proliferation and activation of DC2.4 dendritic cells without additional adjuvant. In summary, SA-DOX-NA exerts the dual efficacy of chemotherapy and immunotherapy for tumor treatment, and has a good application prospect in local tumor treatment.

Background/Aims: Obesity is associated with several gastrointestinal (GI) disorders and has been identified as a potential risk factor for various GI symptoms. Bowel frequency is an important indicator of bowel function. However, the causal link between obesity and gastrointestinal motility remains uncertain. This study aims to determine the causal effect of overall and central obesity on stool frequency. Methods: Four obesity-related anthropometric indicators–body mass index, body fat percentage, waist circumference (WC), and waist-tohip ratio (WHR)–were investigated. Individual-level baseline information from the UK Biobank was used to explore observational associations between obesity and stool frequency. Additionally, summary-level data from published genome-wide association studies were subjected to two-sample Mendelian randomization (MR) analyses to examine causal associations. Results: For all 4 indicators of obesity, higher levels of obesity were associated with more frequent bowel movements after adjusting for demographic characteristics, lifestyle, and dietary factors. After rigorous screening, 482 body mass index single nucleotide polymorphisms (SNPs), 7 body fat percentage SNPs, 48 WC SNPs, and 287 WHR SNPs were identified as instrument variables for MR analysis. The MR results were generally consistent with observational findings, proving that the associations observed in the overall obesity indicators were causal. For central obesity, the association between WHR and stool frequency remained consistent in both analysis phases, whereas WC showed a multidirectional association. Conclusions Obesity-related anthropometric indicators were causally associated with increased stool frequency in the overall and central obesity groups. Weight loss could be a potential approach to improve gastrointestinal regularity in individuals with obesity.

Background/Aims: Obesity is associated with several gastrointestinal (GI) disorders and has been identified as a potential risk factor for various GI symptoms. Bowel frequency is an important indicator of bowel function. However, the causal link between obesity and gastrointestinal motility remains uncertain. This study aims to determine the causal effect of overall and central obesity on stool frequency. Methods: Four obesity-related anthropometric indicators–body mass index, body fat percentage, waist circumference (WC), and waist-tohip ratio (WHR)–were investigated. Individual-level baseline information from the UK Biobank was used to explore observational associations between obesity and stool frequency. Additionally, summary-level data from published genome-wide association studies were subjected to two-sample Mendelian randomization (MR) analyses to examine causal associations. Results: For all 4 indicators of obesity, higher levels of obesity were associated with more frequent bowel movements after adjusting for demographic characteristics, lifestyle, and dietary factors. After rigorous screening, 482 body mass index single nucleotide polymorphisms (SNPs), 7 body fat percentage SNPs, 48 WC SNPs, and 287 WHR SNPs were identified as instrument variables for MR analysis. The MR results were generally consistent with observational findings, proving that the associations observed in the overall obesity indicators were causal. For central obesity, the association between WHR and stool frequency remained consistent in both analysis phases, whereas WC showed a multidirectional association. Conclusions Obesity-related anthropometric indicators were causally associated with increased stool frequency in the overall and central obesity groups. Weight loss could be a potential approach to improve gastrointestinal regularity in individuals with obesity.

Background/Aims: Obesity is associated with several gastrointestinal (GI) disorders and has been identified as a potential risk factor for various GI symptoms. Bowel frequency is an important indicator of bowel function. However, the causal link between obesity and gastrointestinal motility remains uncertain. This study aims to determine the causal effect of overall and central obesity on stool frequency. Methods: Four obesity-related anthropometric indicators–body mass index, body fat percentage, waist circumference (WC), and waist-tohip ratio (WHR)–were investigated. Individual-level baseline information from the UK Biobank was used to explore observational associations between obesity and stool frequency. Additionally, summary-level data from published genome-wide association studies were subjected to two-sample Mendelian randomization (MR) analyses to examine causal associations. Results: For all 4 indicators of obesity, higher levels of obesity were associated with more frequent bowel movements after adjusting for demographic characteristics, lifestyle, and dietary factors. After rigorous screening, 482 body mass index single nucleotide polymorphisms (SNPs), 7 body fat percentage SNPs, 48 WC SNPs, and 287 WHR SNPs were identified as instrument variables for MR analysis. The MR results were generally consistent with observational findings, proving that the associations observed in the overall obesity indicators were causal. For central obesity, the association between WHR and stool frequency remained consistent in both analysis phases, whereas WC showed a multidirectional association. Conclusions Obesity-related anthropometric indicators were causally associated with increased stool frequency in the overall and central obesity groups. Weight loss could be a potential approach to improve gastrointestinal regularity in individuals with obesity.

Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.

Acupuncture, a therapeutic treatment defined as the insertion of needles into the body at specific points (ie, acupoints), has growing in popularity world-wide to treat various diseases effectively, especially acute and chronic pain. In parallel, interest in the physiological mechanisms underlying acupuncture analgesia, particularly the neural mechanisms have been increasing. Over the past decades, our understanding of how the central nervous system and peripheral nervous system process signals induced by acupuncture has developed rapidly by using electrophysiological methods. However, with the development of neuroscience, electrophysiology is being challenged by calcium imaging in view field, neuron population and visualization in vivo. Owing to the outstanding spatial resolution, the novel imaging approaches provide opportunities to enrich our knowledge about the neurophysiological mechanisms of acupuncture analgesia at subcellular, cellular, and circuit levels in combination with new labeling, genetic and circuit tracing techniques. Therefore, this review will introduce the principle and the method of calcium imaging applied to acupuncture research. We will also review the current findings in pain research using calcium imaging from in vitro to in vivo experiments and discuss the potential methodological considerations in studying acupuncture analgesia.
Calcium ; Acupuncture Therapy ; Acupuncture ; Acupuncture Analgesia/methods* ; Acupuncture Points ; Technology

As the search for effective treatments for COVID-19 continues, the high mortality rate among critically ill patients in Intensive Care Units (ICU) presents a profound challenge. This study explores the potential benefits of traditional Chinese medicine (TCM) as a supplementary treatment for severe COVID-19. A total of 110 critically ill COVID-19 patients at the Intensive Care Unit (ICU) of Vulcan Hill Hospital between Feb., 2020, and April, 2020 (Wuhan, China) participated in this observational study. All patients received standard supportive care protocols, with a subset of 81 also receiving TCM as an adjunct treatment. Clinical characteristics during the treatment period and the clinical outcome of each patient were closely monitored and analysed. Our findings indicated that the TCM group exhibited a significantly lower mortality rate compared with the non-TCM group (16 of 81 vs 24 of 29; 0.3 vs 2.3 person/month). In the adjusted Cox proportional hazards models, TCM treatment was associated with improved survival odds (P < 0.001). Furthermore, the analysis also revealed that TCM treatment could partially mitigate inflammatory responses, as evidenced by the reduced levels of proinflammatory cytokines, and contribute to the recovery of multiple organic functions, thereby potentially increasing the survival rate of critically ill COVID-19 patients.
Humans ; COVID-19 ; Medicine, Chinese Traditional ; SARS-CoV-2 ; Critical Illness ; Treatment Outcome

Erythropoietic protoporphyria （EPP） is a rare inherited metabolic disease that often involves skin， blood， and nervous systems， and EPP with the main manifestations of severe liver damage and acute abdominal pain is extremely rare. By reviewing the clinical data and genetic testing results of a patient with EPP， this article discusses the clinical features and pathogenic genes of this disease， in order to improve the understanding of the disease among hepatologists and achieve early diagnosis and treatment.

Objective To investigate the predictive value of new simplified insulin resistance(IR)assessment indexes in identifying subclinical left ventricular systolic function impairment in patients with type 2 diabetes mellitus(T2DM).Methods A total of 150 T2DM patients with preserved left ventricular ejection fraction(LVEF≥50%)who were admitted to Department of Endocrinology of the First Affiliated Hospital of Air Force Medical University from June 2021 to December 2021 were retrospectively analyzed.All patients underwent two-dimensional speckle tracking echocardiography to measure left ventricular global longitudinal strain(GLS).According to GLS value,the subjects were divided into the normal group(GLS≥18%group,n=80)and the impaired group(GLS<18%group,n=70).Some new simplified IR assessment indicators were calculated and compared between the two groups,including body mass index(BMI),TG/HDL-C ratio,triglyceride-glucose(TyG)index,TyG-BMI index,TyG-WHR and metabolic score for IR(METS-IR).Correlation between the GLS and the new simplified IR assessment indexes was analyzed.The receiver operating characteristic(ROC)curve was used to analyze the diagnostic efficacy of different simplified IR assessment indexes,with the area under the curve(AUC)calculated.Furthermore,according to whether the subjects were complicated with hypertension,binary logistics regression analysis was performed to explore the independent correlation between the simplified IR assessment index and GLS<18%.Results Total 150 were included with aged(54.5±13.7)years with 96(64.0%)men and 54(36.0%)women.Compared with the GLS≥18%group,the TG/HDL-C ratio,TyG index,TyG-BMI,and METS-IR of subjects in the GLS<18%group were significantly increased(P<0.05).Pearson correlation analysis showed that TG/HDL-C ratio,TyG index,TyG-BMI,TyG-WHR,and METS-IR were negatively correlated with GLS(P<0.05).ROC analysis showed that TyG index had a certain predictive value for the evaluation of GLS<18%(AUC=0.678,95%CI 0.591-0.765,P<0.001).Stratification based on hypertension and further adjusting for confounding factors,TyG index remains significantly associated with GLS<18%(OR=3.249,95%CI 1.045-10.103,P=0.042).Conclusions The novel simplified insulin resistance evaluation indexes are closely associated with left ventricular subclinical systolic dysfunction in T2DM patients with preserved ejection fraction.TyG index is an effective index to identify left ventricular subclinical dysfunction in these populations.

Objective:To compare clinical characteristics,treatment patterns and physiological indicators in bipolar disorder(BD)patients with different age of onset.Methods:Totally 380 patients with DSM-5 BD were se-lected in this study.Psychiatrists diagnosed the patients using the Mini International Neuropsychiatric Interview.The clinical information questionnaire and the Global Assessment of Functioning scale were utilized to collected clinical characteristics,treatment status,and physiological indicators.The onset age of BD was divided into 21 and 35 years as cut-off points.Multivariate logistic regression and linear regression were used to analyze related factors.Results:Among the 380 patients with BD,199 cases were early-onset group(52.4％),121 cases were middle-onset group(31.8％),and 60 cases were late-onset group(15.8％).There were 26.6％of patients in the early-onset group in-itially diagnosed as depression,23.1％in the middle-onset group,and 11.7％in the late-onset group.Multivariate analysis revealed that compared to the early-onset group of BD,the middle-onset(OR=2.22)and late-onset(OR=4.99)groups had more risk to experience depressive episodes,and the late-onset group(OR=6.74)had 6.74 times of risk to suffer from bipolar Ⅱ disorder.Additionally,patients in the middle-onset(β=-1.52)and late-on-set(β=-4.29)groups had shorter durations of delayed treatment,and those in the middle-onset(β=-1.62)and late-onset(β=-3.14)groups had fewer hospitalizations.Uric acid levels were lower in both the middle-onset(β=-28.39)and late-onset(β=-31.47)groups,and total cholesterol level was lower in the middle-onset group(β=-0.23).Conclusion:Patients with BD in different age of onset show significant differences in clinical charac-teristics,treatment conditions and physiological indicators.