OBJECTIVE To systematically review medication-related risk factors for falls in older adults， to provide references for ensuring medication safety among older adults. METHODS A systematic search was conducted in PubMed， Embase， Web of Science， and CNKI for relevant literature published from database inception to November 1， 2025. Relevant studies on medication-related falls in older adults， both domestic and international， were included. Drug factors influencing falls in older adults were summarized and analyzed. RESULTS A total of 22 studies were included. Four major classes of fall-risk-increasing drugs were identified： psychotropic medications [12 studies， odds ratio （OR） range 1.500-5.790]， cardiovascular system drugs （5 studies， OR range 1.236-4.784）， analgesics （3 studies， OR range 1.500-4.490）， and hypoglycemic agents （3 studies， OR range 2.070-2.751）. Additionally， anticholinergic burden （1 study， OR was 2.610） and polypharmacy （7 studies， OR range 2.902-25.897 for the use of ≥4 medications） were identified as significant risk factors for falls. CONCLUSIONS Falls in older adults are significantly associated with psychotropic medications， cardiovascular system drugs， analgesics， and hypoglycemic agents， among which psychotropic medications pose the highest risk. Anticholinergic burden and polypharmacy are also important risk factors. In clinical practice， interventions should be implemented through deprescribing and risk monitoring to effectively reduce the risk of falls in older adults.

Primary cilia—those solitary, microtubule-based projections extending from the surface of most eukaryotic cells—are increasingly recognized not merely as cellular appendages, but as sophisticated signaling hubs. By compartmentalizing specific receptors (e.g., GPCRs) and effectors within a microdomain guarded by the transition zone, these organelles function effectively as high-gain sensors capable of integrating mechanical stimuli with metabolic cues. In this review, we examine the pivotal role of primary cilia across the nervous, bone-vascular, and renal landscapes, arguing for a unified “mechano-metabolic coupling” framework. Here, conserved ciliary modules are not static; rather, they are differentially deployed to uphold systemic homeostasis. Within the central nervous system, we position primary cilia as upstream integrators. We highlight how hypothalamic neuronal cilia concentrate metabolic receptors, such as the melanocortin 4 receptor (MC4R), to interpret energy status. Moreover, the recent identification of serotonergic “axon-cilium synapses” points to a direct mode of neurotransmission, wherein 5-HT6 receptors drive nuclear signaling and chromatin accessibility to rapidly modulate gene expression. Through these mechanisms, central cilia modulate sympathetic tone and neuroendocrine output, effectively establishing the mechanical and metabolic “boundary conditions” under which peripheral organs operate. Dysfunction in these central hubs is linked to obesity and neurodevelopmental disorders, including Bardet-Biedl syndrome. In peripheral tissues, cilia serve as versatile mechanotransducers that convert physical forces into biochemical responses. Regarding the bone-vascular system, we discuss the translation of mechanical loads and fluid shear stress into structural remodeling. In osteoblasts, specifically, ciliary integrity is intrinsically linked to cholesterol and glucose metabolism, fine-tuning the balance between Hedgehog and Wnt/β-catenin signaling to govern osteogenesis and bone repair. A similar dynamic exists in the vasculature, where endothelial cilia sense shear stress to modulate KLF4 expression and endothelial-to-mesenchymal transition—processes critical for valvulogenesis and vascular remodeling. Meanwhile, in the kidney, tubular cilia act as terminal effectors within a “shear-cilia-metabolism” axis. Here, fluid shear stress engages ciliary signaling to trigger AMPK-mediated lipophagy and mitochondrial biogenesis, thereby securing the ATP supply required for solute transport. Notably, dysregulation of this axis leads to metabolic reprogramming and aberrant proliferation, acting as a hallmark driver of cystogenesis in polycystic kidney disease (PKD). Crucially, this review attempts to dissect the often-conflated logic of cross-system integration by distinguishing 3 non-equivalent pathways: direct communication via ciliary extracellular vesicles, though this remains largely hypothetical in long-range signaling; “physiology-mediated cascades”, where ciliary dysfunction in a single organ—such as the kidney—precipitates systemic pathology through hemodynamic and metabolic shifts (e.g., altered blood pressure, fluid volume, or uremic toxins); and “parallel molecular defects”, where shared genetic mutations in ubiquitous components like the IFT machinery cause simultaneous, independent failures across multiple organ systems. Building on these distinctions, we propose a nested-loop model that links central set-points with peripheral feedback via physiological variables. Furthermore, we construct a “causality-to-translation” roadmap that pinpoints structural repair (e.g., targeting IFT assembly) and metabolic rescue (e.g., AMPK activation or autophagy induction) as promising therapeutic avenues. Ultimately, this framework provides a theoretical basis for deciphering the shared pathological mechanisms of multisystem ciliopathies, offering a strategic guide for the development of targeted interventions that go beyond symptomatic treatment.

BACKGROUND:High-frequency repetitive transcranial magnetic stimulation has garnered significant attention due to its potential non-invasive benefits in modulating brain function.However,no studies have comprehensively analyzed the current research landscape and development trends of this field from a macroscopic perspective.OBJECTIVE:To explore research hotspots,current trends,and emerging frontiers in the field of high-frequency repetitive transcranial magnetic stimulation through visualized analysis.METHODS:Data were collected from the Web of Science Core Collection database from January 1,2014 to November 15,2024.CiteSpace was used for analyzing publication volume,collaborations among countries/regions,institutions and authors,citation analysis of journals and co-cited literature,as well as disciplinary distribution.Additionally,keyword co-occurrence,clustering,and burst analyses were conducted,and visualized knowledge maps were generated.RESULTS AND CONCLUSION:A total of 860 articles were included.The publication volume of high-frequency repetitive transcranial magnetic stimulation showed an overall upward trend from 2014 to 2022,followed by a decline from 2022 to 2024.China had the highest publication volume,while Ghent University ranked as the most productive institution.Universities acted as the most high-output institutions.Chris Baeken from Ghent University was identified as the most prolific author.Collaboration among leading authors and institutions worldwide remained limited.The main research hotspots in this field were associated with keywords such as depression,stroke,neuropathic pain,and Parkinson's disease.Burst keywords focused on mild cognitive impairment,reflecting a diversification in research directions.The overall research activity in high-frequency repetitive transcranial magnetic stimulation continues to rise,with primary focuses on its clinical applications for psychiatric and neurological disorders,as well as explorations of its underlying mechanisms.Future research may focus on optimizing treatment parameters for targeting different brain regions in clinical applications and expanding its applications and mechanisms across various domains.

BACKGROUND:High-frequency repetitive transcranial magnetic stimulation has garnered significant attention due to its potential non-invasive benefits in modulating brain function.However,no studies have comprehensively analyzed the current research landscape and development trends of this field from a macroscopic perspective.OBJECTIVE:To explore research hotspots,current trends,and emerging frontiers in the field of high-frequency repetitive transcranial magnetic stimulation through visualized analysis.METHODS:Data were collected from the Web of Science Core Collection database from January 1,2014 to November 15,2024.CiteSpace was used for analyzing publication volume,collaborations among countries/regions,institutions and authors,citation analysis of journals and co-cited literature,as well as disciplinary distribution.Additionally,keyword co-occurrence,clustering,and burst analyses were conducted,and visualized knowledge maps were generated.RESULTS AND CONCLUSION:A total of 860 articles were included.The publication volume of high-frequency repetitive transcranial magnetic stimulation showed an overall upward trend from 2014 to 2022,followed by a decline from 2022 to 2024.China had the highest publication volume,while Ghent University ranked as the most productive institution.Universities acted as the most high-output institutions.Chris Baeken from Ghent University was identified as the most prolific author.Collaboration among leading authors and institutions worldwide remained limited.The main research hotspots in this field were associated with keywords such as depression,stroke,neuropathic pain,and Parkinson's disease.Burst keywords focused on mild cognitive impairment,reflecting a diversification in research directions.The overall research activity in high-frequency repetitive transcranial magnetic stimulation continues to rise,with primary focuses on its clinical applications for psychiatric and neurological disorders,as well as explorations of its underlying mechanisms.Future research may focus on optimizing treatment parameters for targeting different brain regions in clinical applications and expanding its applications and mechanisms across various domains.

OBJECTIVE To analyze trends in the burden of disease associated with falls from 1990 to 2023， identify risk factors for falls， and provide a reference for the development of measures to reduce the burden of disease associated with falls and the formulation of public health policies. METHODS Based on the data of 2023 from the Global Burden of Disease （GBD） database， the changes in fall-related prevalence， mortality， disability-adjusted life years （DALYs） and incidence in China and globally from 1990 to 2023 were analyzed， and the stratified analyses by gender， age and socio-demographic index （SDI） were conducted. The risk factors related to falls in 2023 were systematically analyzed， and the impact of multimorbidity and polypharmacy on the occurrence of falls by combining relevant literature evidence was explored. RESULTS & CONCLUSIONS Globally， the percentage changes in age-standardized rates of fall-related prevalence， mortality， DALYs and incidence from 1990 to 2023 were －2.4% （95%UI： －4.8% to －0.3%）， －7.8% （95%UI： －20.5% to 10.9%）， －10.6% （95%UI： －16.5% to －4.3%）， and －4.6% （95%UI： －8.1% to －0.8%）， respectively. However， in some regions， the percentage changes in age-standardized rates for these indicators were greater than 0 （e.g.， prevalence， mortality and DALYs in Australasia， and incidence in Andean Latin America）. In China， the percentage changes in age-standardized rates of fall-related mortality and DALYs from 1990 to 2023 were －18.3% （95%UI： －56.7% to 32.3%） and 1.9% （95%UI： －10.1% to 12.4%）， while the percentage changes in age-standardized rates of prevalence and incidence were 25.9% （95%UI： 20.2% to 32.0%） and 35.7% （95%UI： 28.5% to 44.1%）， respectively. Globally， in regions with high and medium-to-high SDI levels， the percentage changes in age-standardized rates of fall-related prevalence and incidence showed an upward trend， while DALYs showed a downward trend； however， the trend in mortality was unclear. In regions with a middle SDI level， the percentage changes in age-standardized rates of fall-related prevalence and incidence both showed an upward trend， while the trends in mortality and DALYs were unclear. In regions with low-to-medium SDI level， the percentage changes in age-standardized rate of fall-related prevalence， DALYs and incidence all showed a downward trend， while the trend in mortality was unclear； in regions with low SDI level， the trends for all above indicators were unclear. Correlation analyses of the burden of fall-related diseases in China and globally indicated that the risk of fall-related diseases was higher among younger and middle-to-older adult male populations， while women were concentrated in older age groups. Meanwhile， as the SDI levels increase， the percentage change in age-standardized rate of DALYs for fall-related diseases showed a clear upward trend， and this trend was more pronounced in high-SDI regions. Tobacco use， alcohol consumption， low bone density， and occupational risks were risk factors for falls， with low bone density and occupational risks contributing significantly （exceeding 20% in some regions）； multimorbidity and polypharmacy could also significantly increase the risk of falls. It is recommended that clinical settings establish a list of fall-risk increasing drugs and a warning system， improve medication reviews， strengthen medication education and adherence management， foster multidisciplinary collaboration， and develop medication strategies for specific patient populations to reduce the incidence of falls and alleviate the burden of disease.

Metabolic dysfunction-associated fatty liver disease （MAFLD） is a chronic liver disease closely related to metabolic dysfunction. Its global prevalence is increasing year by year and shows a trend toward younger onset. It is closely associated with cardiovascular and cerebrovascular diseases， chronic kidney disease， and extrahepatic malignant tumors， and has become a major public health problem affecting the health of the Chinese population. At present， the treatment of MAFLD mainly focuses on lifestyle intervention. When metabolic cardiovascular risk factors and liver injury are present， pharmacological intervention is required. However， there is still no specific drug therapy for MAFLD. In recent years， many studies have found that the pathogenesis of MAFLD involves interactions among multiple factors， including insulin resistance， oxidative stress， endoplasmic reticulum stress， programmed cell death， immune dysregulation， inflammasomes， gut microbiota imbalance， and bile acid metabolism. Traditional Chinese medicine （TCM） has advantages in integrated regulation with multiple components and multiple targets， and shows significant efficacy in the treatment of MAFLD. Active components of Chinese medicinal herbs and Chinese medicine compound formulas exert definite therapeutic effects by regulating multiple signaling pathways to improve lipid metabolism disorders， inhibit inflammatory responses， and regulate the gut microbiota， thereby effectively improving clinical symptoms and delaying the occurrence and development of MAFLD. Therefore， strengthening research on the mechanisms of action of TCM in MAFLD is of crucial importance and significance for its treatment. This article summarizes the mechanisms by which Chinese medicine monomers and compound formulas intervene in MAFLD through the regulation of related signaling pathways， based on the retrieval and analysis of relevant literature from multiple databases， with the aim of providing theoretical support and a reference basis for the clinical application of TCM in the treatment of MAFLD.

OBJECTIVE To predict and verify the mechanism of Jiawei qifang weitong granule in ameliorating precancerous lesions of gastric cancer （PLGC）. METHODS Transcriptomic data of PLGC-related were obtained from the GEO database to screen differentially expressed genes and conduct functional enrichment analysis. Targets related to gastric mucosal injury repair were screened via the GeneCards database. The active ingredient targets of Jiawei qifang weitong granule were predicted using the TCMSP and other databases. The intersection of differentially expressed genes， gastric mucosal repair targets and active ingredient targets was extracted. A protein-protein interaction network was constructed based on the STRING database， and the top 6 hub target genes with the highest connectivity were screened. A PLGC rat model was established by combining 1-methyl-3-nitro-1-nitrosoguanidine with alternating fasting and full feeding. Model rats were divided into model group， weifuchun group （positive control， 0.40 g/kg）， low-， medium- and high-dose Jiawei qifang weitong granule groups （9.73， 19.44， 38.90 g/kg）， with 10 rats in each group. Another 10 unmodeled rats were set as control group. Rats in each group were intragastrically administered corresponding liquid medicine or normal saline once a day for 30 consecutive days. After the last administration， pathological morphological changes of rat gastric tissues were observed， and the mRNA expression levels of hub target genes as well as partial protein expression levels in gastric tissues were detected. RESULTS Transcriptomics and network pharmacology analyses revealed that the top 6 hub target genes ranked by connectivity included MMP9 （matrix metalloproteinase 9）， BCL2（B-cell lymphoma 2）， IL10（interleukin 10），ICAM1（intercellular adhesion molecule 1）， PTGS2 （prostaglandin-endoperoxide synthase 2）， and HIF1A （hypoxia-inducible factor 1α subunit）. Animal experiments showed that compared with the model group， gastric mucosal pathological injury was significantly alleviated in medium- and high-dose Jiawei qifang weitong granule groups and weifuchun group. The pathological injury score of gastric mucosa， the mRNA expression levels of MMP9， PTGS2， ICAM1， BCL2 and HIF1A， as well as the protein expression levels of PTGS2 and BCL2 in gastric tissues were significantly decreased （P＜0.05）， while the mRNA expression level of IL10 was significantly increased （P＜0.05）. CONCLUSIONS Jiawei qifang weitong granule may ameliorate PLGC by targeted down-regulating the mRNA expression of MMP9， PTGS2， ICAM1， BCL2 and HIF1A， up-regulating IL10 mRNA expression， and regulating the imbalance between gastric mucosal inflammatory response and injury repair.

Pancreatic cancers (PCs) is a common malignant tumor with poor prognosis in the digestive system. Its main treatment methods include surgery, radiotherapy, chemotherapy, and targeted therapy. The early diagnosis rate of hidden onset of PCs is low, and most patients have already lost the opportunity to undergo surgery when diagnosed with PCs. Chemotherapy is still the main treatment for advanced PCs, but the use of chemotherapy drugs in PCs can easily lead to drug resistance. The most significant feature that distinguishes PCs from other tumors is its rich and dense matrix, which not only hinders drug penetration but also impedes the infiltration of immune cells. The above reasons have led to a very low survival rate of PCs patients. Therefore, drug delivery systems are very important in the diagnosis and treatment of PCs. They can improve drug delivery, enhance biological barrier penetration, reduce side effects, and combine multiple treatment methods. Therefore, the treatment prospects of PCs are very broad. Currently, drug delivery systems widely applied in PCs primarily include nanodrug delivery systems, tumor microenvironment-targeted drug delivery system, immunotherapy drug delivery system, gene therapy drug delivery system, and combination therapy drug delivery system that synergize multiple therapeutic modalities. Emerging drug delivery systems (DDSs) have revolutionized PCs treatment by addressing these challenges through multiple mechanisms. Nanoformulations improve drug solubility, prolong circulation time, and reduce systemic toxicity via passive/active targeting. Smart DDSs responsive to PCs-specific stimuli enable extracellular matrix degradation, tumor-associated fibroblasts reprogramming, and vascular normalization to enhance drug accessibility. Last but not least, carrier systems loaded with myeloid-derived suppressor cell inhibitors or T cell activators can reverse immunosuppression and potentiate immunotherapy efficacy. Advanced platforms co-deliver chemotherapeutics with immunomodulators, gene-editing tools, or sonodynamic agents to achieve synergistic antitumor effects. These platforms aim to address critical challenges in PCs treatment, such as enhancing drug bioavailability, overcoming stromal barriers, reprogramming immunosuppressive niches, and achieving multi-mechanistic antitumor effects. This article provides a systematic summary and prospective analysis of the current development status, latest cutting-edge advances, opportunities, and challenges of the above-mentioned drug delivery systems in the field of PCs therapy.

Objective To evaluate the predictive ability and clinical application value of artificial intelligence (AI) systems in the benign and malignant differentiation and pathological type of pulmonary nodules, and to summarize clinical application experience. Methods A retrospective analysis was conducted on the clinical data of patients with pulmonary nodules admitted to the Department of Thoracic Surgery, Second Hospital of Lanzhou University, from February 2016 to February 2025. Firstly, pulmonary nodules were divided into benign and non-benign groups, and the discriminative abilities of AI systems and clinicians were compared. Subsequently, lung nodules reported as precursor glandular lesions (PGL), microinvasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC) in postoperative pathological results were analyzed, comparing the efficacy of AI systems and clinicians in predicting the pathological type of pulmonary nodules. Results In the analysis of benign/non-benign pulmonary nodules, clinical data from a total of 638 patients with pulmonary nodules were included, of which there were 257 males (10 patients and 1 patient of double and triple primary lesions, respectively) and 381 females (18 patients and 1 patient of double and triple primary lesions, respectively), with a median age of 55.0 (47.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis of the two groups of variables showed that, except for nodule location, the differences in the remaining variables were statistically significant (P<0.05). Multivariate logistic regression analysis showed that age, nodule type (subsolid pulmonary nodule), average density, spicule sign, and vascular convergence sign were independent influencing factors for non-benign pulmonary nodules, among which age, nodule type (subsolid pulmonary nodule), spicule sign, and vascular convergence sign were positively correlated with non-benign pulmonary nodules, while average density was negatively correlated with the occurrence of non-benign pulmonary nodules. The area under the receiver operating characteristic curve (AUC) of the malignancy risk value given by the AI system in predicting non-benign pulmonary nodules was 0.811, slightly lower than the 0.898 predicted by clinicians. In the PGL/MIA/IAC analysis, clinical data from a total of 411 patients with pulmonary nodules were included, of which there were 149 males (8 patients of double primary lesions) and 262 females (17 patients of double primary lesions), with a median age of 56.0 (50.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis results showed that, except for gender, nodule location, and vascular convergence sign, the differences in the remaining variables among the three groups of PGL, MIA, and IAC patients were statistically significant (P<0.05). Multinomial multivariate logistic regression analysis showed that the differences between the parameters in the PGL group and the MIA group were not statistically significant (P>0.05), and the maximum diameter and average density of the nodules were statistically different between the PGL and IAC groups (P<0.05), and were positively correlated with the occurrence of IAC as independent risk factors. The average AUC value, accuracy, recall rate, and F1 score of the AI system in predicting lung nodule pathological type were 0.807, 74.3%, 73.2%, and 68.5%, respectively, all better than the clinical physicians’ prediction of lung nodule pathological type indicators (0.782, 70.9%, 66.2%, and 63.7% respectively). The AUC value of the AI system in predicting IAC was 0.853, and the sensitivity, specificity, and optimal cutoff value were 0.643, 0.943, and 50.0%, respectively. Conclusion This AI system has demonstrated high clinical value in predicting the benign and malignant nature and pathological type of lung nodules, especially in predicting lung nodule pathological type, its ability has surpassed that of clinical physicians. With the optimization of algorithms and the adequate integration of multimodal data, it can better assist clinical physicians in formulating individualized diagnostic and treatment plans for patients with lung nodules.

Objective This research was performed to identify rodent-borne pathogens in Hekou Port,Yunnan Province.Methods Rodents were captured using cages and dissected to collect their lungs,liver,spleen,and other viscera.Eight pathogens,including Yersinia pestis,Leptospira,Bartonella,and Anaplasmataceae,were identified using polymerase chain reaction amplification.Amplified pathogen sequences from positive samples were sequenced,and BLAST homology searches were conducted using GenBank to confirm pathogen identities.A phylogenetic tree of the identified pathogens was constructed using the neighbor joining method.Results The total of 31 rodents,identified as Rattus tanezumi,R.norvegicus,and Mus musculus,were captured.Among these,R.tanezumi was the dominant species,accounting for 64.52％of the total.Two pathogens,Leptospira interrogans and Neoehrlichia mikurensis,were detected,with positivity rates of 9.68％and 29.03％,respectively.No other pathogens were detected.The overall positivity rate for rodent-borne pathogens was 35.48％.Conclusions The single 16S rRNA gene fragment is insufficient for the molecular identification of all Neoehrlichia species.Accurate species identification should be based on a combined analysis of multiple genes.The prevalence of rodent-borne pathogens in Hekou Port indicates the necessity for enhanced surveillance of rodent-borne diseases and implementation of additional prevention and control measures in border ports.