Objective To investigate the global burden of visceral leishmaniasis (VL) from 1990 to 2021 and predict the trends in the burden of VL from 2022 to 2035, so as to provide insights into global VL prevention and control. Methods The global age-standardized incidence, prevalence, mortality and disability-adjusted life years (DALYs) rates of VL and their 95% uncertainty intervals (UI) were captured from the Global Burden of Disease Study 2021 (GBD 2021) data resources. The trends in the global burden of VL were evaluated with average annual percent change (AAPC) and 95% confidence interval (CI) from 1990 to 2021, and gender-, age-, country-, geographical area- and socio-demographic index (SDI)-stratified burdens of VL were analyzed. The trends in the global burden of VL were projected with a Bayesian age-period-cohort (BAPC) model from 2022 to 2035, and the associations of age-standardized incidence, prevalence, mortality, and DALYs rates of VL with SDI levels were examined with a smoothing spline model. Results The global age-standardized incidence [AAPC = -0.25%, 95% CI: (-0.25%, -0.24%)], prevalence [AAPC = -0.06%, 95% CI: (-0.06%, -0.06%)], mortality [AAPC = -0.25%, 95% CI: (-0.25%, -0.24%)] and DALYs rates of VL [AAPC = -2.38%, 95% CI: (-2.44%, -2.33%)] all appeared a tendency towards a decline from 1990 to 2021, and the highest age-standardized incidence [2.55/10⁵, 95% UI: (1.49/10⁵, 4.07/10⁵)], prevalence [0.64/10⁵, 95% UI: (0.37/10⁵, 1.02/10⁵)], mortality [0.51/10⁵, 95% UI: (0, 1.80/10⁵)] and DALYs rates of VL [33.81/10⁵, 95% UI: (0.06/10⁵, 124.09/10⁵)] were seen in tropical Latin America in 2021. The global age-standardized incidence and prevalence of VL were both higher among men [0.57/10⁵, 95% UI: (0.45/10⁵, 0.72/10⁵); 0.14/10⁵, 95% UI: (0.11/10⁵, 0.18/10⁵)] than among women [0.27/10⁵, 95% UI: (0.21/10⁵, 0.33/10⁵); 0.06/10⁵, 95% UI: (0.05/10⁵, 0.08/10⁵)], and the highest mortality of VL was found among children under 5 years of age [0.24/10⁵, 95% UI: (0.08/10⁵, 0.66/10⁵)]. The age-standardized incidence (r = -0.483, P < 0.001), prevalence (r = -0.483, P < 0.001), mortality (r = -0.511, P < 0.001) and DALYs rates of VL (r = -0.514, P < 0.001) correlated negatively with SDI levels from 1990 to 2021. In addition, the global burden of VL was projected with the BAPC model to appear a tendency towards a decline from 2022 to 2035, and the age-standardized incidence, prevalence, mortality and DALYs rates were projected to be reduced to 0.11/10⁵, 0.03/10⁵, 0.02/10⁵ and 1.44/10⁵ in 2035, respectively. Conclusions Although the global burden of VL appeared an overall tendency towards a decline from 1990 to 2021, the burden of VL showed a tendency towards a rise in Central Asia and western sub-Saharan African areas. The age-standardized incidence and prevalence rates of VL were relatively higher among men, and the age-standardized mortality of VL was relatively higher among children under 5 years of age. The global burden of VL was projected to continue to decline from 2022 to 2035.

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.

OBJECTIVE: To preliminarily investigate the effects and mechanism of action of Yishen Yangsui Formula (, YSYSF)on the recovery of neurological function in rats with degenerative cervical myelopathy. METHODS: Fifty adult SD female rats were randomly divided into control group, sham group, model group, YSYSF group and positive drug group by using randomized numerical table method. In the model group, YSYSF group and positive drug group, polyvinyl alcohol acrylamide interpenetrating network hydrogel(water-absorbent swelling material) was used to construct a rat spinal cord chronic compression model. The sham group was implanted with the water-absorbent swelling material and then removed without causing spinal cord compression. The control group, the sham group and the model group were given equal amounts of saline by gavage, the group of YSYSF was given Chinese herbal medicine soup by gavage 9.1 g·kg^-1 once a day, and the positive drug group was given tetrahexylsalicylglucoside sodium monosialate ganglioside by intraperitoneal injection 4.2 mg·kg^-1 once a day. The motor function of the rats was assessed by the BBB method after 1, 3, 7, and 14 d of drug administration. The spinal cord tissues were taken from rats executed 14 d after drug administration, and the morphological changes of the spinal cord compression site were observed by HE staining, and the expression levels of Caspase-1, GSDMD, NLRP3, PYCARD, IL-1β, and IL-18 were detected in the area of spinal cord injury by Western blot method. RESULTS: The BBB scores of the control group and the sham group were normal at all time points after modeling, which were higher than the BBB scores of the model group, the YSYSF, and the positive drug group (P<0.05). From the 3rd day after gavage, at all time points, the BBB scores of rats in the YSYSF group and the positive drug group were higher than those of rats in the model group (P<0.05). The staining pattern of HE spinal cord tissue was normal in the control group and the sham group, and the HE spinal cord in the model group was severely damaged with a large number of neuron deaths, whereas the damage to the spinal cord and neuron cells was reduced in the YSYSF group and the positive drug group. The expression levels of caspase-1, GSDMD, NLRP3, PYCARD, IL-1β and IL-18 in the spinal cord of the model group were significantly higher than those of the sham group (P<0.0001), and the expression levels of caspase-1, GSDMD, NLRP3, PYCARD, IL-1β, and IL-18 in the YSYSF group and the drug group were significantly lower than those in the model group (P<0.05). CONCLUSION YSYSF can improve the motor function of rats with degenerative cervical spinal cord disease, alleviate the pathological changes, and promote the recovery of spinal cord neurological function. The specific mechanism may be related to the inhibition of the activation of inflammatory vesicles NLRP3 and PYCARD, the reduction of the release of inflammatory factors IL-1β and IL-18, the reduction of the expression of caspase-1 and GSDMD, the reduction of cellular death, and the inhibition of inflammatory response.
Animals ; Female ; Drugs, Chinese Herbal/administration & dosage* ; Rats ; Rats, Sprague-Dawley ; Pyroptosis/drug effects* ; Spinal Cord/pathology* ; NLR Family, Pyrin Domain-Containing 3 Protein ; Spinal Cord Diseases/drug therapy* ; Interleukin-1beta/metabolism*

OBJECTIVE: To develop an original-mirror alignment associated deep learning algorithm for intelligent registration of three-dimensional maxillofacial point cloud data, by utilizing a dynamic graph-based registration network model (maxillofacial dynamic graph registration network, MDGR-Net), and to provide a valuable reference for digital design and analysis in clinical dental applications. METHODS: Four hundred clinical patients without significant deformities were recruited from Peking University School of Stomatology from October 2018 to October 2022. Through data augmentation, a total of 2 000 three-dimensional maxillofacial datasets were generated for training and testing the MDGR-Net algorithm. These were divided into a training set (1 400 cases), a validation set (200 cases), and an internal test set (200 cases). The MDGR-Net model constructed feature vectors for key points in both original and mirror point clouds (X, Y), established correspondences between key points in the X and Y point clouds based on these feature vectors, and calculated rotation and translation matrices using singular value decomposition (SVD). Utilizing the MDGR-Net model, intelligent registration of the original and mirror point clouds were achieved, resulting in a combined point cloud. The principal component analysis (PCA) algorithm was applied to this combined point cloud to obtain the symmetry reference plane associated with the MDGR-Net methodology. Model evaluation for the translation and rotation matrices on the test set was performed using the coefficient of determination (R²). Angle error evaluations for the three-dimensional maxillofacial symmetry reference planes were constructed using the MDGR-Net-associated method and the "ground truth" iterative closest point (ICP)-associated method were conducted on 200 cases in the internal test set and 40 cases in an external test set. RESULTS: Based on testing with the three-dimensional maxillofacial data from the 200-case internal test set, the MDGR-Net model achieved an R² value of 0.91 for the rotation matrix and 0.98 for the translation matrix. The average angle error on the internal and external test sets were 0.84°±0.55° and 0.58°±0.43°, respectively. The construction of the three-dimensional maxillofacial symmetry reference plane for 40 clinical cases took only 3 seconds, with the model performing optimally in the patients with skeletal Class Ⅲ malocclusion, high angle cases, and Angle Class Ⅲ orthodontic patients. CONCLUSION This study proposed the MDGR-Net association method based on intelligent point cloud registration as a novel solution for constructing three-dimensional maxillofacial symmetry reference planes in clinical dental applications, which can significantly enhance diagnostic and therapeutic efficiency and outcomes, while reduce expert dependence.
Humans ; Deep Learning ; Algorithms ; Imaging, Three-Dimensional/methods* ; Male ; Female ; Maxilla/diagnostic imaging* ; Adult

OBJECTIVE: The present study evaluated the effects of deep acupuncture at Weizhong acupoint (BL40) on bladder function and brain activity in a rat model of overactive bladder (OAB), and investigated the possible mechanisms around the acupuncture area that initiate the effects of acupuncture. METHODS: Adult female Sprague-Dawley rats were randomly divided into six groups, comprising a control group, model group, group treated with deep acupuncture at BL40, group treated with shallow acupuncture at BL40, group treated with acupuncture at non-acupoint next to BL40, and group treated with acupuncture at Xuanzhong (GB39). Urodynamic evaluation was used to observe the urination, and functional magnetic resonance imaging was used to observe the brain activation. The mechanism of acupuncture at BL40 in regulating bladder function was explored by toluidine blue staining and enzyme-linked immunosorbent assay, and the mechanism was verified by stabilizing mast cells (MCs) or blocking tibial nerve. RESULTS: Deep acupuncture at BL40 significantly increased the intercontraction interval in OAB rats and enhanced the mean amplitude of low frequency fluctuation of primary motor cortex (M1), periaquaductal gray matter (PAG), and pontine micturition center (PMC). It also increased the zero-lag functional connectivity between M1 and PAG and between PAG and PMC. Shallow acupuncture at BL40 and acupuncture at non-acupoint or GB39 had no effect on these indexes. Further studies suggested that deep acupuncture at BL40 increased the number and degranulation rate of MCs as well as the contents of 5-hydroxytryptamine, substance P, and histamine in the tissues around BL40. Blocking the tibial nerve by lidocaine injection or inhibiting MC degranulation by sodium cromoglycate injection obstructed the effects of acupuncture on restoring urinary function and modulating brain activation in OAB rats. CONCLUSION Deep acupuncture at BL40 may be more effective for inhibiting OAB by promoting degranulation of MCs around the acupoint and stimulating tibial nerve, thereby regulating the activation of the brain area that controls the lower urinary tract. Please cite this article as: Liu X, Zhang CY, Du XY, Li SS, Wang YQ, Zheng Y, Deng HZ, Fang XQ, Li JY, Wang ZQ, Xu SF, Mi YQ. Acupuncture at Weizhong (BL40) attenuates acetic acid-induced overactive bladder in rats by regulating brain neural activity through the modulation of mast cells and tibial nerves. J Integr Med. 2025; 23(1): 46-55.
Animals ; Urinary Bladder, Overactive/physiopathology* ; Mast Cells/physiology* ; Rats, Sprague-Dawley ; Female ; Acupuncture Therapy ; Acupuncture Points ; Rats ; Brain/physiopathology* ; Tibial Nerve/physiopathology* ; Acetic Acid ; Urinary Bladder/physiopathology*

OBJECTIVE: To investigate the associations between eight serum per- and polyfluoroalkyl substances (PFASs) and regional fat depots, we analyzed the data from the National Health and Nutrition Examination Survey (NHANES) 2011-2018 cycles. METHODS: Multiple linear regression models were developed to explore the associations between serum PFAS concentrations and six fat compositions along with a fat distribution score created by summing the concentrations of the six fat compositions. The associations between structurally grouped PFASs and fat distribution were assessed, and a prediction model was developed to estimate the ability of PFAS exposure to predict obesity risk. RESULTS: Among females aged 39-59 years, trunk fat mass was positively associated with perfluorooctane sulfonate (PFOS). Higher concentrations of PFOS, perfluorohexane sulfonate (PFHxS), perfluorodecanoate (PFDeA), perfluorononanoate (PFNA), and n-perfluorooctanoate (n-PFOA) were linked to greater visceral adipose tissue in this group. In men, exposure to total perfluoroalkane sulfonates (PFSAs) and long-chain PFSAs was associated with reductions in abdominal fat, while higher abdominal fat in women aged 39-59 years was associated with short-chain PFSAs. The prediction model demonstrated high accuracy, with an area under the curve (AUC) of 0.9925 for predicting obesity risk. CONCLUSION PFAS exposure is associated with regional fat distribution, with varying effects based on age, sex, and PFAS structure. The findings highlight the potential role of PFAS exposure in influencing fat depots and obesity risk, with significant implications for public health. The prediction model provides a highly accurate tool for assessing obesity risk related to PFAS exposure.
Humans ; Fluorocarbons/blood* ; Female ; Adult ; Middle Aged ; Male ; Environmental Pollutants/blood* ; Abdominal Fat ; Nutrition Surveys ; Alkanesulfonic Acids/blood* ; Obesity ; Environmental Exposure

OBJECTIVES: This study aimed to evaluate the repeatability and reliability of a self-developed domestic wireless surface electromyography (sEMG) system (Oralmetry) in assessing the activity of the temporalis and masseter muscles to provide theoretical support for its clinical application. METHODS: Twenty-two volunteers were recruited. Through multiple repeated measurements, the sEMG signals of bilateral anterior temporalis and masseter muscles during maximum voluntary clenching were collected using the self-developed sEMG device, Oralmetry, and two commercial sEMG devices (Zebris and Teethan), filtered, screened, and standardized. Seven sEMG indicators for assessing masticatory muscle function were calculated. The intraclass correlation coefficient (ICC) was used to evaluate the repeatability of the measurements from the three sEMG devices, and statistical analysis was conducted to compare the consistency of the seven sEMG indicators obtained from the devices. RESULTS: Among the 22 participants, the ICC values of the repeated measurements from the three sEMG devices ranged from 0.88 to 0.99. The measurements of three sEMG indicators (antero-posterior coeffificient, percentage overlapping coeffificient_MM, and percentage overlapping coeffificient_TA) obtained by Zebris were significantly different from those obtained by Oralmetry and Teethan (P<0.05). No significant differences in the measurements of the seven sEMG indicators were found between Oralmetry and Teethan. CONCLUSIONS Oralmetry and the two commercial sEMG devices demonstrated good repeatability in capturing sEMG indicators for evaluating masticatory muscle function. In particular, Oralmetry showed the highest ICC values. All three devices also exhibited good consistency in measuring sEMG indicators, and a high agreement was observed between the two wireless sEMG devices (Oralmetry and Teethan). These findings provide theoretical support for the clinical application of Oralmetry.
Humans ; Electromyography/methods* ; Masseter Muscle/physiology* ; Masticatory Muscles/physiology* ; Wireless Technology ; Reproducibility of Results ; Temporal Muscle/physiology* ; Male ; Adult ; Female ; Young Adult

OBJECTIVES: To evaluate the accuracy of a self-developed extraoral scanning system based on four-camera stereophotogrammetric technology in the acquisition of three-dimensional positional information on dental implants and conduct a comparative study involving an intraoral scanning system. METHODS: With the use of an in vitro edentulous jaw model with implants, extraoral (experimental group) and intraoral (control group) scanning systems were employed to obtain STL (Standard Tessellation Language) datasets containing three-dimensional morphological and positional information on scan bodies. In addition, a dental model scanner was used to obtain reference data. The three-dimensional morphological, linear, and angular deviations between groups and reference data were analyzed using Geomagic Wrap 2021 software to compare trueness and precision. RESULTS: The extraoral scanning system demonstrated superior trueness in three-dimensional morphological, linear, and angular deviations compared with the intraoral scanning system, with statistically significant differences (P<0.001). The extraoral scanning system also showed a higher precision in three-dimensional morphological deviation (P<0.001). As the number of implants increased, the extraoral scanning system exhibited increased three-dimensional morphological and linear deviations (P<0.001) but maintained a stable angular deviation. The intraoral scanning system displayed significant increases in three-dimensional morphological, linear, and angular deviations with the increase in the number of implants (P<0.05). CONCLUSIONS The stereophotogrammetry-based extraoral scanning system outperforms intraoral scanning system in terms of the accuracy for multi-unit implant positioning and provides a novel approach for attaining a fully digital workflow for implant rehabilitation in edentulous jaws.
Jaw, Edentulous ; Humans ; Dental Impression Technique ; Dental Implants ; Imaging, Three-Dimensional/methods* ; Photogrammetry/methods* ; Models, Dental

Background::Scleroderma is characterized by inflammation and fibrosis, predominantly occurring in the skin and extending to various parts of the body. The pathophysiology of scleroderma is multifaceted, with the current understanding including endothelial damage, inflammatory cell infiltration, and fibroblast activation in its progression. Nonetheless, the mechanism of cellular interactions and the precise spatial distribution of these cellular events within the fibrotic tissues remain elusive, highlighting a critical gap in our comprehensive understanding of scleroderma’s pathogenesis.Methods::In this study, we administered bleomycin intradermally to the dorsal skin of four individual murine models. Subsequently, skin tissues were harvested at predetermined intervals for comprehensive spatial transcriptomic analysis to determine the spatial dynamics influencing scleroderma pathogenesis. To validate the possible results from bioinformatic analysis, further in vitro and in vivo experiments were conducted. Results::Analysis of the spatial transcriptome revealed significant alterations in cell clusters during the progression of scleroderma. Gene Ontology analysis identified disruptions in lipid metabolism as the disease advanced. Pseudotime analysis provided evidence for a phenotypic transition from adipocytes to fibroblasts. In vitro studies demonstrated increased expression of Col1a1 and α-SMA as the disease progressed. These fibroblasts have been identified as key contributors to the increasing inflammation. Co-culturing TGF-β induced adipocytes with RAW264.7 cells resulted in overexpression of pro-inflammatory cytokines in the RAW264.7 cells. Both in vitro and in vivo experiments confirmed adipocyte loss and fibroblast formation, with transformed fibroblasts showing pronounced pro-inflammatory characteristics, highlighting their crucial role in the disease mechanism. Conclusions::Our study showed the spatial distribution and dynamic alterations of various cell types during scleroderma progression. Crucially, we identified the transformation of adipocytes into fibroblasts as a key factor promoting disease advancement. These emergent fibroblasts intensify inflammation, indicating that research on these cell clusters could reveal key scleroderma mechanisms and guide future therapies.

Alzheimer's disease is a common central neurodegenerative disease， mainly manifested by cognitive impairment and non-cognitive neuropsychiatric symptoms that severely affect patients' daily life and behavioral functioning. The pathogenesis of Alzheimer's disease is still unclear， and the western medicine currently used to treat Alzheimer's disease is only symptomatic， with a single pathway， limited efficacy， and many side effects. In recent years， with the deepening of research on Alzheimer's disease， the study and application of traditional Chinese medicine （TCM） in the treatment of Alzheimer's disease have gradually increased. Several studies have shown that TCM and its effective components can exert anti-Alzheimer's disease effects by regulating molecular mechanisms such as pathological protein production and aggregation， oxidative stress， neuroinflammation， ferroptosis， mitochondrial dysfunction， neurogenesis and neurotransmission， and brain-gut axis. This paper summarized the research progress of TCM in the treatment of Alzheimer's disease in recent years， so as to provide a reference for further study of the specific mechanism of TCM in the prevention and treatment of Alzheimer's disease and the discovery of effective components of TCM.