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.

Objective: The cross sectional study aimed to identify predominant co-occurrence patterns among six common mental health issues in college students, so as to provide empirical basis for designing targeted interventions. Methods: From October 2024, a total of 9 837 students from 4 universities in Xiangtan City, Hunan Province, participated in the current study by multistage random cluster sampling method. Participants completed self report measures, including the Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder 7 item Scale (GAD-7), Young s Internet Addiction Diagnostic Questionnaire, the Adolescent Insomnia Symptom Self rating Scale, the Ottawa Self injury Inventory, and the Brief Community Assessment of Psychic Experiences Questionnaire. Demographic and co-occurrence characteristics were first compared using Chi square or trend Chi-square tests, followed by application of the Apriori algorithm to mine association rules for primary co-occurrence patterns. Results: The detection rate of co-occuring the common mental health issues was 46.44%. The detection rate was significantly higher in female than in male students (50.42%, 43.61%; χ 2=44.46) and in students from rural versus urban areas (47.22%, 44.60%; χ 2=5.67) (both P <0.05). Significant differences were observed among freshmen, sophomores, juniors, and seniors (46.63%, 48.35%, 45.05% , 43.66%, respectively; χ 2=9.22, P <0.05), although no statistically significant trend was detected ( χ 2 trend =3.75, P = 0.05 ). Association rule mining identified “anxiety + depression” “anxiety + psychotic experiences + depression” and “anxiety + sleep disorder + depression” as the combinations with the highest support. In addition, “anxiety+depression+Internet addiction+psychotic experiences =>sleep disorder (>= refered to the occurrence of the latter item under the condition that the former item occurs)” and “anxiety + depression+Internet addiction=>sleep disorder” were combinations with relatively high confidence. Conclusions Co-occurrence of these mental health issues among college students is high and exhibits diverse patterns. Strategies to address this burden should prioritize integrated interventions that target these specific combinations of factors.

[摘 要] 目的：探究着丝粒蛋白M（CENPM）在脑胶质瘤中的表达特征、临床预后价值及其对肿瘤恶性生物学行为的调控机制，为脑胶质瘤的精准治疗提供潜在靶点。方法：基于中国胶质瘤基因组图谱（CGGA）和癌症基因组图谱（TCGA）数据库分析CENPM在胶质瘤中的表达及其与患者临床病理特征和预后的相关性。通过基因本体论（GO）分析、京都基因与基因组百科全书（KEGG）富集分析和单细胞转录组分析探索CENPM的生物学功能和作用机制。WB法检测CENPM在胶质瘤细胞（LN-18、LN-229、U-138MG、U-251MG）和正常胶质细胞（HEB）中的表达；构建CENPM敲低细胞后，通过CCK-8、集落形成、Transwell和划痕实验评估恶性表型改变。结果：CENPM在WHO高级别胶质瘤中呈高表达（P < 0.05），与肿瘤恶性程度正相关。高表达组患者总体生存期显著短于低表达组（P < 0.01），Cox回归证实CENPM是影响胶质瘤患者预后的独立危险因素（P < 0.05）。功能富集分析结果显示CENPM相关基因主要富集于细胞周期调控、PI3K-Akt通路和免疫相关过程。单细胞分析结果显示CENPM主要在CD8⁺ T细胞高表达，并通过PTN-PTPRZ1/NCL配受体调控细胞通信。体外实验证实CENPM在胶质瘤细胞表达高于正常胶质细胞（LN-18：P < 0.01，LN-299：P < 0.05）；敲低CENPM显著抑制迁移（P < 0.05），但增强集落形成，提示其在肿瘤进展中的双重调控作用。结论：CENPM作为胶质瘤独立预后危险因子，通过调控细胞周期、PTN通路和免疫微环境驱动肿瘤进展，其差异化调控机制（抑制迁移、促进增殖）具有潜在的临床转化价值，可作为分子分型和靶向治疗候选标志物。

Background: This study was performed to characterize the incidence, costs, and risk factors associated with renal and cardiovascular adverse outcomes following primary percutaneous coronary intervention (pPCI) in patients with ST-elevation myocardial infarction (STEMI). Methods: Patients with STEMI who underwent pPCI using iso-osmolar contrast were enrolled at 39 centers. The incidence of acute kidney injury (AKI) and major adverse renal and cardiovascular events (MARCE) was analyzed, as well as inpatient costs. Logistic regression analysis was performed to identify risk factors. Results: Among 2,293 patients, the incidence of AKI and MARCE within 72 hours post-pPCI was 4.14% (n = 95) and 4.40% (n = 101), respectively. AKI and/or MARCE were associated with systolic blood pressure (AKI: odds ratio [OR], 1.009; 95% confidence interval [CI], 1.000–1.018), hypertension (AKI: OR, 1.815; 95% CI, 1.133–2.906; MARCE: OR, 1.760;95% CI, 1.118–2.769), anterior wall infarction (AKI: OR, 1.895; 95% CI, 1.196–3.004; MARCE:OR, 1.939; 95% CI, 1.240–3.032), Killip class (AKI: OR, 1.465; 95% CI, 1.117–1.922; MARCE:OR, 1.467; 95% CI, 1.131–1.903), and serum creatinine (SCr; MARCE: OR, 1.006; 95% CI, 1.000–1.012). Hospitalization costs for patients with STEMI who developed AKI or MARCE were significantly higher than for those without AKI (9,595 ± 5,795 vs. 8,279 ± 3,872 USD, P = 0.003) or without MARCE (9,890 ± 5,616 vs. 8,255 ± 3,859 USD, P < 0.001). Conclusions In patients with STEMI undergoing pPCI with iso-osmolar contrast, the incidence of AKI and MARCE was associated with higher hospitalization costs. Systolic blood pressure, hypertension, anterior wall infarction, Killip class, and SCr were identified as risk factors for these outcomes.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

With the widespread adoption of low-dose CT screening and the extensive application of high-resolution CT, the detection rate of sub-centimeter lung nodules has significantly increased. How to scientifically manage these nodules while avoiding overtreatment and diagnostic delays has become an important clinical issue. Among them, lung nodules with a consolidation tumor ratio less than 0.25, dominated by ground-glass shadows, are particularly worthy of attention. The therapeutic challenge for this group is how to achieve precise and complete resection of nodules during surgery while maximizing the preservation of the patient's lung function. The "watershed topography map" is a new technology based on big data and artificial intelligence algorithms. This method uses Dicom data from conventional dose CT scans, combined with microscopic (22-24 levels) capillary network anatomical watershed features, to generate high-precision simulated natural segmentation planes of lung sub-segments through specific textures and forms. This technology forms fluorescent watershed boundaries on the lung surface, which highly fit the actual lung anatomical structure. By analyzing the adjacent relationship between the nodule and the watershed boundary, real-time, visually accurate positioning of the nodule can be achieved. This innovative technology provides a new solution for the intraoperative positioning and resection of lung nodules. This consensus was led by four major domestic societies, jointly with expert teams in related fields, oriented to clinical practical needs, referring to domestic and foreign guidelines and consensus, and finally formed after multiple rounds of consultation, discussion, and voting. The main content covers the theoretical basis of the "watershed topography map" technology, indications, operation procedures, surgical planning details, and postoperative evaluation standards, aiming to provide scientific guidance and exploration directions for clinical peers who are currently or plan to carry out lung nodule resection using the fluorescent microscope watershed analysis method.

Objective To investigate the detection rate and related influencing factors of gastrointestinal diseases in grass-roots personnel.Methods A total of 481 grass-roots personnel were enrolled and examined by magnetic-controlled capsule endoscopy(MCCE).Multivariate logistic regression were used to analyze the influencing factors of gastrointestinal diseases detected by MCCE.Results All personnel completed MCCE,and gastrointestinal diseases were detected in 154(32.0%)cases,including 106 cases of erosive gastritis,25 cases of chronic atrophic gastritis,17 cases of digestive tract polyp,16 cases of gastric ulcer,5 cases of reflux esophagitis,4 cases of cardia,1 case of duodenitis,and 1 case of enteritis.Gastrointestinal diseases was correlated with special operation posts,long-term tasks within recent 6 months,abdominal distension,belching,nausea and vomiting,diarrhea and other symptoms(all P＜0.05).Multivariate logistic regression analysis showed that the risk factors of gastrointestinal diseases were working in special operation posts,performing long tasks within 6 months,belching,nausea and vomiting symptoms(all P＜0.05).Conclusion The overall detection rate of gastrointestinal diseases(mainly acid related diseases)is relatively high,and its incidence is closely related to working in special operation posts and performing long-term tasks within recent 6 months.Personnel working in special operation posts should be more alert to gastrointestinal diseases.Gastrointestinal symptoms have reference value for the prediction of lesions,but more attention should be paid to the identification of functional gastrointestinal diseases with endoscopy.

Arrhythmia refers to abnormal heart rhythm or frequency,which causes the heart unable to pump blood effectively,thus affecting the overall heart function.Its occurrence can be attributed to a variety of factors.The pathological mechanisms of arrhythmia are closely related to the"Xuanfu-Qiye-Luomai"framework.From a clinical perspective,the direct cause of arrhythmia is the disorder of Xuanfu opening and closing,where the imbal-ance of Qi and fluids is the key factor.Furthermore,the underlying cause of the disease's progression lies in the defi-ciency and stagnation of the Luo vessels.Based on this"Xuanfu-Qiye-Luomai"pathogenesis model,traditional Chinese medicine(TCM)treatment should focus on the holistic principles of"opening the Xuanfu,regulating Qi and fluids,and nourishing the vessels".This approach involves the flexible use of herbal medicines to regulate the Xuan-fu,blood-activating and blood-stasis-eliminating herbs to balance Qi and fluids,along with tonifying agents to nourish and unblock the vessels.The goal is to transform tangible pathogenic factors,such as phlegm and dampness,into intangible Qi,thereby harmonizing the Qi and blood to restore heart function.This approach provides new in-sights into the TCM diagnosis and treatment of arrhythmia.

Objective:To Exploring the protective effect of hearing protectors worn by noise workers in the petrochemical industry and the factors affecting the protective effect of hearing protectors.Methods:From June 2021 to July 2023, 929 petrochemical workers were selected as the research subjects through cluster sampling. The noise exposure of workers and the usage of two types of hearing protectors were surveyed through questionnaire surveys and on-site occupational hygiene surveys. The protective effect of hearing protectors were evaluated by testing the PAR of workers. If the noise exposure value of workers minus the PAR value was less than 85 dB (A) , it was considered passed. Otherwise, it was considered not passed. The passing rate of the protective effect test of hearing protectors was analyzed through chi square test and the influencing factors for the effectiveness of workers hearing protectors in test were explored through single factor analysis and logistic regression models.Results:Among the research subjects, 80.5% of workers (748/929) had noise exposure levels greater than 85 dB (A) . The passing rate (80.9%) of the earmuff is greater than that of the earplug (52.6%) , and the median of PAR of the earmuff is 22 (16, 25) , which is greater than that of the earplug 15 (3, 22) dB dB, with a statistically significant difference ( P<0.001) . Univariate analysis and logistic regression models showed that length of service, exposure level to noise, and wearing comfort were the influencing factors of earplug protection effect ( P<0.05) , while wearing comfort was the influencing factor of earmuff protection effect ( P<0.05) . Conclusion:This study indicates that the protective effect of hearing protectors on workers in the petrochemical enterprise is poor, and the protective effect of earmuffs is greater than that of earplugs. Working experience, noise exposure level, and wearing comfort are the influencing factors of earplug protection effect, while wearing comfort is the influencing factor of earplug protection effect.

Objective To summarize the potential risk factors that may arise in the national drug sampling and testing inspection process in recent years,to focuse on the operation of the quality management system,and to put forward proposals on how to do a good job under the new drug regulatory model of sampling and testing work.Methods Focusing on the investigation of data integrity and authenticity,the analysis focuses on the analysis of risk points such as reagent management,standard substance management,instrument,and facility management,electronic data management and other issues,and carries out a comprehensive verification of the effectiveness of the operation of the quality management system and so on.Results National drug sampling and testing institutes should strengthen the overall quality management,according to the operation of the laboratory,combined with their respective risk characteristics,reagent management,standard substance management,instrument and facility management,electronic data management and other aspects of the risk of systematic sorting and the establishment of the risk alert function,the development of risk warning lists,and the implementation of the corresponding risk control strategy.Conclusion National drug sampling and testing institutes must strengthen the operation of the process of influencing factors in the effective control of the emphasis on the testing of the work of the key control points and continue to standardize and improve the inspection process of the quality system to ensure that the quality of the various activities in a controlled state.