Human milk is universally recognized as the optimal and most natural source of nutrition for newborns, offering benefits that extend far beyond basic energy and macronutrient provision. Among its complex constituents, human milk oligosaccharides (HMOs) represent the third most abundant solid component, surpassed only by lactose and lipids. HMOs are distinguished by their exceptionally high structural diversity—over 200 distinct structures have been identified to date. This structural complexity underlies the extensive biological functions HMOs perform within the infant’s body. HMOs play a pivotal role in promoting healthy growth, development, and overall well-being in infants and young children, functioning as indispensable bioactive molecules. Their key physiological activities include: immunomodulation and allergy prevention by promoting immune tolerance and reducing the risk of allergic diseases; potent anti-inflammatory and antioxidant effects that protect vulnerable infant tissues; support for brain development and cognitive enhancement through multiple mechanisms; anti-pathogenic properties, acting as soluble receptor analogs or “decoy” molecules to competitively block viral, bacterial, and other pathogen adhesion, thereby preventing colonization and infection in the gastrointestinal tract; and functioning as blood group substances. At the translational and application level, HMO research is actively driving cross-disciplinary innovation. Building on a deep understanding of their immunological and neurodevelopmental benefits, certain structurally defined HMOs have been successfully incorporated into infant formula. These HMO-supplemented formulas have received regulatory approval and are now commercially available worldwide, providing a nutritional alternative that more closely resembles human milk for infants who are not exclusively breastfed. This represents a significant step toward narrowing the compositional gap between formula and breast milk. Simultaneously, research into the symbiotic relationship between HMOs and the gut microbiota—particularly their role as selective prebiotic substrates promoting the growth of beneficial bacteria—has catalyzed the development of novel functional foods, dietary supplements, and microbiome-targeted therapies. These include advanced synbiotic formulations that combine specific probiotic strains with HMOs to synergistically optimize gut health and function. Furthermore, the intrinsic qualities of HMOs—including their natural origin, safety profile, biocompatibility, and proven antioxidant properties—have attracted growing interest in the emerging field of high-performance cosmetics. They are increasingly being explored as innovative functional ingredients in skincare products aimed at reducing oxidative stress and supporting skin health. This review aims to systematically synthesize recent advancements in HMO research, offering a comprehensive analysis centered on their complex composition and structural diversity; the molecular and cellular mechanisms underlying their diverse biological functions; their translational potential across sectors such as nutrition, medicine, and consumer care (including cosmetics); and the major challenges that persist in the field. It critically examines both foundational discoveries and recent breakthroughs. By integrating these interconnected themes, the review provides a holistic and up-to-date perspective on the scientific landscape of HMOs, highlighting their essential role in early-life nutrition and their expanding relevance across health and wellness applications. It also outlines promising directions for future research, with the goal of advancing evidence-based innovation in infant health and beyond.

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.

Based on the high-fat diet-induced hyperlipidemia rat model, this study aimed to evaluate the lipid-lowering effect of Arisaema Cum Bile and explore its mechanisms, providing experimental evidence for its clinical application. Biochemical analysis was used to detect serum levels of alanine aminotransferase(ALT), aspartate aminotransferase(AST), high-density lipoprotein cholesterol(HDL-C), low-density lipoprotein cholesterol(LDL-C), triglycerides(TG), and total cholesterol(TC) to assess the lipid-lowering activity of Arisaema Cum Bile. Additionally, 16S rDNA sequencing and metabolomics techniques were employed to jointly elucidate the lipid-lowering mechanisms of Arisaema Cum Bile. The experimental results showed that high-dose Arisaema Cum Bile(PBA-H) significantly reduced serum ALT, AST, LDL-C, TG, and TC levels(P<0.01), and significantly increased HDL-C levels(P<0.01). The effect was similar to that of fenofibrate, with no significant difference. Furthermore, Arisaema Cum Bile significantly alleviated hepatocyte ballooning and mitigated fatty degeneration in liver tissues. As indicated by 16S rDNA sequencing results, PBA-H significantly enhanced both alpha and beta diversity of the gut microbiota in the model rats, notably increasing the relative abundance of Akkermansia and Subdoligranulum species(P<0.01). Liver metabolomics analysis revealed that PBA-H primarily regulated pathways involved in arachidonic acid metabolism, vitamin B_6 metabolism, and steroid biosynthesis. In summary, Arisaema Cum Bile significantly improved abnormal blood lipid levels and liver pathology induced by a high-fat diet, regulated hepatic metabolic disorders, and improved the abundance and structural composition of gut microbiota, thereby exerting its lipid-lowering effect. The findings of this study provide experimental evidence for the clinical application of Arisaema Cum Bile and the treatment of hyperlipidemia.
Animals ; Gastrointestinal Microbiome/drug effects* ; Rats ; Male ; Metabolomics ; Hyperlipidemias/microbiology* ; Drugs, Chinese Herbal/administration & dosage* ; Rats, Sprague-Dawley ; Hypolipidemic Agents/pharmacology* ; Liver/metabolism* ; Humans ; Alanine Transaminase/metabolism* ; Triglycerides/metabolism* ; Aspartate Aminotransferases/metabolism*

Chaihu and Longgu Muli Decoction has demonstrated significant efficacy in the treatment of tachyarrhythmia accompanied by anxiety and depression. However, there is a lack of standardized guidelines for its clinical application. In this study, the Chaihu and Longgu Muli Decoction was investigated through extensive research on ancient and modern literature, as well as a collection of clinical medical records. The basic information, medication details, and diagnostic information from medical records, personal experience literature, and clinical cases in the treatment of tachyarrhythmia accompanied by anxiety were extracted and analyzed to preliminarily identify the prescription characteristics and syndrome patterns. Subsequently, the Delphi method was employed to construct an item pool based on the data obtained in the first step. An expert questionnaire was prepared to collect scores and revision opinions from experts regarding these items. After statistical analysis and group discussions, a second round of questionnaires was formed by screening out certain items. This process was repeated until a final item set for the treatment of tachyarrhythmia accompanied by anxiety with Chaihu and Longgu Muli Decoction was determined. These findings provided guidance for clinical prescription practices. By extracting 71 syndromes and signs, as well as 33 tongue and pulse characteristics, the main syndrome features included palpitations, chest tightness, irritability, etc., which were basically consistent with the ancient syndromes. Through frequency analysis and group discussions, 71 items were screened out. After screening, modification, and primary and secondary division, 11 main diagnostic items and 10 secondary diagnostic items were determined. On this basis, the research team believes that Chaihu and Longgu Muli Decoction is mainly indicated for the following syndromes in the treatment of tachyarrhythmia accompanied by anxiety(palpitations, poor sleep, bitter taste, dry mouth, irritability/easily angered/anxiety/fearfulness/easily startled, red tongue with greasy yellow coating, rapid pulse, high work/life pressure, tachyarrhythmia on electrocardiogram/Holter monitor, and positive results on anxiety scale). Secondary syndromes include chest tightness, shortness of breath, feeling heavy and weak in the body, sweating, poor appetite, constipation, greasy white tongue coating, wiry pulse, slippery pulse, or knotted and intermittent pulse.
Drugs, Chinese Herbal/therapeutic use* ; Humans ; Delphi Technique ; Anxiety/complications* ; Tachycardia/psychology* ; Female ; Male ; Middle Aged ; Adult ; Aged

OBJECTIVES: To explore the influencing factors for very preterm birth at a gestational age of <32 weeks in the Xinjiang Uygur Autonomous Region. METHODS: Clinical data of women with preterm deliveries and their newborns admitted to five hospitals in Xinjiang from January 2023 to December 2024 were retrospectively collected. The subjects were divided by gestational age into very preterm (<32 weeks of gestation) and moderate/late preterm (32-36⁺⁶ weeks of gestation) groups. Risk factors associated with very preterm birth were analyzed. RESULTS: A total of 4 105 pregnant women with preterm deliveries were included, with 793 cases (19.32%) in the very preterm group and 3 312 cases (80.68%) in the moderate/late preterm group. The factors significantly associated with very preterm birth were as following: hypertensive disorders of pregnancy (OR=1.785, 95%CI: 1.492-2.135, P<0.05), excessive gestational weight gain (GWG, OR=2.002, 95%CI: 1.672-2.397, P<0.05), insufficient GWG (OR=1.746, 95%CI: 1.326-2.300, P<0.05), chorioamnionitis (OR=2.163, 95%CI: 1.694-2.763, P<0.05), premature rupture of membranes ≥18 hours (OR=2.158, 95%CI: 1.599-2.912, P<0.05), placental abruption (OR=2.228, 95%CI: 1.646-3.014, P<0.05), and ≤7 prenatal visits (OR=3.419, 95%CI: 2.882-4.055, P<0.05). CONCLUSIONS In the Xinjiang Uygur Autonomous Region, hypertensive disorders of pregnancy, excessive or insufficient GWG, chorioamnionitis, premature rupture of membranes ≥18 hours, placental abruption, and ≤7 prenatal visits are risk factors for very preterm birth. Strengthening high-risk pregnancy management is necessary for reducing the incidence of very preterm birth.
Humans ; Female ; Retrospective Studies ; Pregnancy ; Premature Birth/etiology* ; Gestational Age ; Adult ; Risk Factors ; Infant, Newborn ; Gestational Weight Gain

BACKGROUND: It remains unclear whether sleep duration and physical activity (PA) trajectories in middle-aged and older adults are associated with different risks of cardiovascular diseases (CVDs). This study aimed to explore the trajectories of total sleep duration and PA among middle-aged and older Chinese adults and their impact on CVD risk. METHODS: This study was based on the China Health and Retirement Longitudinal Study. 12009 adults aged 45 years and older from five waves were included. CVD events were measured by self-reports of heart disease and stroke. We first used group-based trajectory modeling to identify total sleep duration and PA trajectories from 2011 to 2020, and then employed logistic regression models to analyze their risk for CVD. RESULTS: We identified three sleep duration and PA trajectories. The risk of heart disease increased by 33% (OR = 1.31, 95% CI: 1.12-1.53) for the short sleep duration trajectory (vs. moderate sleep duration trajectory), by 40% (OR = 1.40, 95% CI: 1.06-1.84) for the high decreasing PA trajectory, and by 20% (OR = 1.20, 95% CI: 1.01-1.42) for the low stable PA trajectory (vs. high stable PA trajectory), respectively. Similar results for stroke and CVD as the outcomes were also observed, but the higher risk of stroke in the high decreasing PA trajectory group was not statistically significant. The joint effects of sleep and PA showed lower risks of heart disease and stroke in trajectories with moderate or long sleep duration and high stable PA compared with short sleep duration and a low stable PA trajectory. CONCLUSIONS Short total sleep duration, high decreasing PA, and low stable PA trajectories could increase the risk of CVDs among middle-aged and older adults. Long-term moderate to long total sleep durations and high stable PA trajectories might be optimal for preventing CVDs.

OBJECTIVE: Humans are exposed to complex mixtures of environmental chemicals and other factors that can affect their health. Analysis of these mixture exposures presents several key challenges for environmental epidemiology and risk assessment, including high dimensionality, correlated exposure, and subtle individual effects. METHODS: We proposed a novel statistical approach, the generalized functional linear model (GFLM), to analyze the health effects of exposure mixtures. GFLM treats the effect of mixture exposures as a smooth function by reordering exposures based on specific mechanisms and capturing internal correlations to provide a meaningful estimation and interpretation. The robustness and efficiency was evaluated under various scenarios through extensive simulation studies. RESULTS: We applied the GFLM to two datasets from the National Health and Nutrition Examination Survey (NHANES). In the first application, we examined the effects of 37 nutrients on BMI (2011-2016 cycles). The GFLM identified a significant mixture effect, with fiber and fat emerging as the nutrients with the greatest negative and positive effects on BMI, respectively. For the second application, we investigated the association between four pre- and perfluoroalkyl substances (PFAS) and gout risk (2007-2018 cycles). Unlike traditional methods, the GFLM indicated no significant association, demonstrating its robustness to multicollinearity. CONCLUSION GFLM framework is a powerful tool for mixture exposure analysis, offering improved handling of correlated exposures and interpretable results. It demonstrates robust performance across various scenarios and real-world applications, advancing our understanding of complex environmental exposures and their health impacts on environmental epidemiology and toxicology.
Humans ; Environmental Exposure/analysis* ; Linear Models ; Nutrition Surveys ; Environmental Pollutants ; Body Mass Index

Objective To investigate the internalized weight bias and weight control beliefs regarding the current status,influencing factors,and impacts on eating behaviors of women losing weight. Methods A convenient sampling method was used to select the females who underwent physical examination in the Peking Union Medical College Hospital from August to December 2023.The general information questionnaire,Weight Bias Internalization Scale,Weight Control Belief Questionnaire,and Chinese version of Three-Factor Eating Questionnaire were utilized for investigation.Latent class analysis was conducted to explore the potential categories based on the characteristics of internalized weight bias and weight control beliefs.Univariate analysis and multiple-factor linear regression analysis were performed to explore influencing factors of potential categories and their effects on eating behaviors. Results A total of 518 subjects were included in this study.The internalized weight bias and weight control beliefs could be classified into three potential categories: low weight bias tolerance type(53.7%),medium weight bias persistence type(29.5%),and high weight bias overcritical type(16.8%).Logistic regression analysis showed that body mass index,unmarriage,and divorce were the influencing factors of the high weight bias overcritical type.The scores of non-control eating and emotional eating in medium weight bias persistence type and high weight bias overcritical type were higher than those in low weight bias tolerance type(all P<0.001). Conclusions The attitudes of Chinese women towards body weight can be categorized into low weight bias tolerance type,medium weight bias persistence type,and high weight bias overcritical type.The high weight bias overcritical type is characterized by high weight bias and high personal responsibility attribution,and it is closely associated with negative eating behaviors.A high body mass index,unmarriage,and divorce are high-risk factors for developing the high weight bias overcritical type.
Humans ; Female ; Feeding Behavior/psychology* ; Surveys and Questionnaires ; Adult ; Body Mass Index ; Weight Loss ; Body Weight ; Body Image ; Middle Aged ; Weight Prejudice

Adolescent idiopathic scoliosis(AIS)is a complex three-dimensional deformity involving coronal,sagittal,and axial planes,with a prevalence that should not be overlooked.With advancements in technology and in-depth research,an increasing number of hospitals and physicians are exploring standardized diagnostic and treatment approaches for AIS.Comprehensive and in-depth understanding is required for AIS,including its etiology,screening and diagnosis,classification,assessment and examination,treatment options,exploration of current focus,and evaluation of quality of life.Such understanding ensures that the diagnostic and treatment are scientific,standardized,and timely.Based on the principles of evidence-based medicine,a consensus on the diagnosis and treatment of AIS is reached after multiple discussions among spinal surgery experts,aiming to provide reference and guidance for clinical practice.

Objective:To investigate the feasibility and effectiveness of three-dimensional visualization technology in the precise diagnosis and treatment of locally advanced differentiated thyroid cancer(DTC).Methods:A retrospective analysis was conducted on the clinical data of 196 patients with locally advanced DTC treated at the 960th Hospital of the PLA from December 2021 to August 2023. The cohort included 71 male and 125 female patients, with a mean age of 43.7 years (rangd from 18 to 77 years). All patients underwent neck-enhanced CT scans and were divided into two groups: the study group( n=102), which underwent preoperative three-dimensional visualization of CT data, and the control group( n=94), which did not. Baseline data for both groups were matched using SPSS27.0 with 1∶1 propensity score matching (PSM) and the caliper value was 0.02. A total of 49 patients were included in each group, including 35 first-time surgeries and 14 reoperation. Among the 70 first-time surgeries, 29 patients underwent robotic surgery and 41 underwent open surgery. Among the 28 reoperations, 4 underwent robotic surgery and 24 underwent open surgery. In the study group, three-dimensional visual models were used to comprehensively evaluate the tumor and metastatic lesion size, spatial location, and adjacent relationship with surrounding organs, surgical treatments were guided by these models, whereas the control group relied on two-dimensional imaging for guidance. The clinical data were statistically analyzed using SPSS27.0. Results:All operations were successfully completed. There were no statistical differences in baseline data between the two groups( P>0.05). Among first-time surgeries, the study group showed shorter operation times [175(145, 200) min vs 205(182, 249) min, P<0.001], a lower incidence of postoperative chyle leak (0 vs 8.57%, P=0.027), a higher rate of robotic surgery (48.57% vs 34.28%, P=0.225), a greater number of harvested lymph nodes [46(40, 62) vs 37(28, 56), P=0.032], a greater number of cervical lymph node metastasis[15(7, 22) vs 5(1, 14), P=0.004] and a larger diameter of metastasis lymph nodes[12(10, 16) mm vs 4(1, 10) mm, P<0.001]. There were no significant differences in intraoperative blood loss, postoperative drainage days and incidence of hypoparathyroidism( P>0.05). During the reoperation, the study group had shorter operation times[103.5(95.0, 122.5) min vs 146.50(133.25, 172.25) min, P<0.001], less intraoperative blood loss[12.50(8.75, 22.50) mL vs 30.00(17.50, 35.00) mL, P=0.021], fewer postoperative drainage days[5.00(4.00, 6.00) d vs 6.00(5.00, 7.25) d, P=0.016] and a lower incidence of hypoparathyroidism(7.14% vs 42.86%, P=0.038).The robotic surgery rate was higher in the study group (21.42% vs 7.14%, P=0.596). There were no significant differences in lymph node dissection numbers, metastatic lymph node counts, or chyle leak incidences between the two groups ( P>0.05). No acute bleeding or incision infection occurred in any patient postoperatively. Conclusion:Three-dimensional visualization technology is an effective preoperative assessment method for evaluating the resectability of tumors and metastases lesions in locally advanced DTC. It enhances the accuracy and safety of surgery for locally advanced DTC.