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 To develope a predictive model for medication deviation risks during the hospital-to-home transition period in coronary heart disease （CHD） patients with initial treatment， aiming to assist medical staff in rapidly identifying high-risk groups for medication deviation. METHODS A total of 462 CHD patients with initial treatment from the Affiliated Hospital of North China University of Science and Technology （hereinafter referred to as “our hospital”） between January and July 2024 were enrolled. The patients were randomly divided into a modeling group and an internal validation group. The modeling group was further categorized into a medication deviation group and a non-medication deviation group based on whether medication deviations occurred. Similarly， 57 CHD patients with initial treatment from the cardiology department of our hospital between June and September 2025 were collected as an external validation group. Univariate analysis was used to screen predictive factors， followed by multivariate Logistic regression to construct the predictive model. Internal validation methods were employed to evaluate model performance， while external validation methods were used to test the model’s generalizability. RESULTS The 462 patients were divided into a modeling group （319 cases） and an internal validation group （143 cases）. In the modeling group， the medication deviation group （192 cases， 60.19%） and the non-medication deviation group （127 cases， 39.81%） were identified. Multivariate Logistic regression analysis revealed that age， medication type， medication adherence， and self-efficacy in rational medication use were predictive factors for medication deviations in CHD patients with initial treatment （ P ＜0.05）. The predictive model equation was logit P ＝ln[ P /（1－ P ） ] ＝1.321+1.732×age+4.091×medication type －4.360×medication adherence －3.081×self-efficacy in rational medication use. The model demonstrated good discrimination， with a Hosmer-Lemeshow goodness-of-fit test P -value of 0.439， an area under the receiver operating characteristic curve （AUC） of 0.870， sensitivity of 0.970， and specificity of 0.607. A risk nomogram with a total score of 350 points and a cutoff value of 110 points was plotted. The internal validation group showed an AUC o f 0.787 and a prediction accuracy of 77.6%， while the external validation group exhibited an AUC of 0.802 and a prediction accuracy of 73.7%. CONCLUSIONS This study successfully developed a predictive model for medication deviation risks during the hospital-to-home transition period in CHD patients with initial treatment. The model demonstrates excellent discrimination and predictive accuracy， effectively identifying high-risk populations for medication deviations. Age （＞70 years）， number of drug types≥5， poor medication adherence， and poor self-efficacy in rational medication use are independent risk factors for medication deviations.

: To analyze the prevalence of anemia and iron deficiency among primary and secondary school students in Rural Nutrition Improvement Program areas of Guizhou Province in 2023, and to explore the related factors, so as to provide evidence for Rural Nutrition Improvement Program optimization. Methods: In September 2023, a stratified random cluster sampling strategy was used to select 40 rural compulsory education schools with rural nutrition improvement program in five counties of Guizhou Province. School level questionnaire was employed to collect information of basic characteristics and school meal implementation. A total of 7 826 primary and secondary school students aged 6-16 underwent anthropometry and hemoglobin (Hb) determination; serum ferritin (SF) was additionally measured in a random subsample of 1 795 pupils. Students in Grade 3 and above also completed a questionnaire covering demographic characteristics, dietary behaviours and nutrition knowledge. Group comparisons were conducted by Chi square test or Fisher s exact test, and multivariable Logistic regression models were constructed to identify factors associated with anemia and iron deficiency. Results: The overall Hb level was (133.21±12.95)g/L, with an anemia prevalence of 7.17%. The overall SF level was (69.58±59.01)μg/L, with an iron deficiency prevalence of 2.73%. Multivariable analysis showed that stunting ( OR =1.88), school menus without nutrient calculation ( OR =1.61) and absence of menu planning software in the current semester ( OR =2.34) independently increased anemia risk, whereas obesity reduced it ( OR =0.54) (all P <0.05). Girls ( OR =4.16) and Grades 7-9 ( OR =5.93) increased iron deficiency risk (both P <0.05). Compared with rarely eating fresh vegetables, students with consuming <3 kinds per day ( OR =0.08) or exactly 3 kinds per day ( OR =0.06) had lower iron deficiency risks (both P <0.05). Conclusions Anemia and iron deficiency are prevalent among primary and secondary school students in Guizhou. Targeted intervention measures should be implemented for key populations to enhance the effectiveness of nutrition improvement program.

As new evidence emerges, treatment strategies toward the functional cure of chronic hepatitis B are evolving. In 2019, a panel of national hepatologists published a Consensus Statement on the functional cure of chronic hepatitis B. Currently, an international group of hepatologists has been assembled to evaluate research since the publication of the original consensus, and to collaboratively develop the updated statements. The 2.0 Consensus was aimed to update the original consensus with the latest available studies, and provide a comprehensive overview of the current relevant scientific literatures regarding functional cure of hepatitis B, with a particular focus on issues that are not yet fully clarified. These cover the definition of functional cure of hepatitis B, its mechanisms and barriers, the effective strategies and treatment roadmap to achieve this endpoint, in particular new surrogate biomarkers used to measure efficacy or to predict response, and the appropriate approach to pursuing a functional cure in special populations, the development of emerging antivirals and immunomodulators with potential for curing hepatitis B. The statements are primarily intended to offer international guidance for clinicians in their practice to enhance the functional cure rate of chronic hepatitis B.

As new evidence emerges, treatment strategies toward the functional cure of chronic hepatitis B are evolving. In 2019, a panel of national hepatologists published a Consensus Statement on the functional cure of chronic hepatitis B. Currently, an international group of hepatologists has been assembled to evaluate research since the publication of the original consensus, and to collaboratively develop the updated statements. The 2.0 Consensus was aimed to update the original consensus with the latest available studies, and provide a comprehensive overview of the current relevant scientific literatures regarding functional cure of hepatitis B, with a particular focus on issues that are not yet fully clarified. These cover the definition of functional cure of hepatitis B, its mechanisms and barriers, the effective strategies and treatment roadmap to achieve this endpoint, in particular new surrogate biomarkers used to measure efficacy or to predict response, and the appropriate approach to pursuing a functional cure in special populations, the development of emerging antivirals and immunomodulators with potential for curing hepatitis B. The statements are primarily intended to offer international guidance for clinicians in their practice to enhance the functional cure rate of chronic hepatitis B.

Objective To propose a brain electrical phase prediction method based on long short-term memory network(LSTM)to improve the accuracy and robustness of phase synchronization prediction in transcranial magnetic stimulation(TMS).Methods First,an LSTM consisting of an input layer,an LSTM layer,an ReLU activation layer,a fully connected layer and a regression layer was constructed to capture the EEG signal features through the synergistic action of input gates,forgetting gates and output gates.Second,eye-open resting-state EEG data from 30 healthy subjects were trained using the LSTM to obtain a predictive model for EEG signal and EEG phase prediction.Finally,the LSTM method and the traditional autoregressive(AR)method were compared in terms of the phase prediction errors at the overall and individual levels and the prediction performance for peaks and troughs.A regression model was used to explore the relationships between instantaneous EEG amplitude,signal-to-noise ratio and phase prediction error with the LSTM method.Results The LSTM method achieved a total phase prediction error of 0.04°±5.69°,which was lower than that of the traditional AR method(-3.36°±51.13°).For each subject,the LSTM method demonstrated superior phase prediction accuracy compared to the traditional AR method(P＜0.001).The accuracy for predicting peaks(troughs)by the LSTM method(about 89％)was higher than that by the traditional AR method(about 10％).Unlike the traditional AR method,the LSTM method didnot result in linear relationships between instantaneous EEG amplitude,signal-to-noise ratio and phase prediction error,with Pvalues being 0.58 and 0.18,respectively.Conclusion The LSTM-based brain electrical phase prediction method shows high accuracy and robustness when used for EEG phase-synchronized TMS.[Chinese Medical Equipment Journal,2025,46(3):1-8]

Anticipatory anxiety is a negative emotion that arises when individuals encounter potential threats or uncertainties in the future. It is the core symptom of a variety of anxiety disorders, and is closely associated with the occurrence, severity, treatment outcome, and prognosis of anxiety disorders, which has garnered a growing amount of focus in clinical practice. Nevertheless, scientific research on anticipatory anxiety continues to face obstacles such as unclear pathological mechanisms, the absence of simple and consistent self-assessment tools, and effective interventions. To improve understanding of the role of anticipatory anxiety in the diagnosis and treatment of anxiety disorders, this study reviews pertinent domestic and international literature, and briefly introduces the concept, assessment and measurement, activation paradigm, pathological mechanisms, and interventions of anticipatory anxiety.

Objective To investigate the impact of different application methods of tissue compensators(bolus)on the skin dose delivered to the chest wall following radical mastectomy for breast cancer.Methods A retrospective analysis was conducted on 60 female patients who underwent radical mastectomy and required chest wall radiotherapy at the hospital between January 2023 and March 2025.The Pinnacle3 9.10 radiotherapy planning system(TPS)was utilized to design two VMAT dual semi-arc radiotherapy plans for each patient,with a prescribed target dose of 50 Gy delivered in 2 Gy fractions over 25 sessions.In Plan 1,a Bolus was applied and optimized during the first 15 fractions,and subsequently removed for the remaining 10 fractions without re-optimization.The sub-field configuration and dose weighting from the initial optimization were retained,and only dose recalculations were performed.The final treatment plan combined both the Bolus-included and Bolus-excluded phases.In contrast,Plan 2 involved the application and optimization of Bolus during the first 15 fractions,followed by its removal and re-optimization of the plan for the last 10 fractions.The two optimized plans were then combined for the overall treatment delivery.Data from the two plan groups were analyzed using a paired sample t-test with SPSS 29.0 software.Results There was a statistically significant difference(P＜0.05)in skin Dmean,V52.5,and V55;heart Dmean,V5,V30,and V40;affected lung Dmean,V5,and V20;PRVcord Dmean and Dmax;healthy breast Dmean,V5,and V10;affected humeral head Dmean and V30;as well as PTV Dmean,V50,V55,D2％,D98％,CI,and MU.Moreover,the dose distribution on the target layer and the DVH curves showed marked differences.However,no statistically significant difference was observed in PTV HI(P=0.125).Conclusion The combination of the two optimized plans,consisting of 15 fractions with bolus and 10 fractions without bolus,more accurately reflects the dose distri-bution within the planned target area and organs at risk,thereby providing enhanced protection for the patient's chest wall skin.

To investigate the phenotype and genomic characterization of a mucoid-type Salmonella Saintpaul ST50 isolate from a urinary tract infection patient,promoting clinical diagnosis and treatment for urinary tract infections caused by Salmo-nella spp.Culture-based quantitative counts of midstream urine sample from the patient were conducted,and further biochemi-cal identification,mass spectrometry detection,serum agglutination test and antimicrobial susceptibility test(AST)were con-ducted on Salmonella isolate(2024JD5).Whole-genome sequencing(WGS)was performed on isolate 2024JD5 to predict sero-type,multilocus sequence type(MLST),resistance genes,and virulence genes.Two smooth-type of Salmonella Saintpaul ST50 were selected as comparative genomic reference strains from the Chinese local Salmonella genome database.The literature reviews of global Salmonella serotype of urinary tract infection were summarized.Specific serum agglutination confir-mation of isolate 2024JD5 failed due to characterization of the mucus type.The strain 2024JD5 was predicted as Salmonella Saintpaul(4,5,12:e,h:1,2)ST50 using WGS,and was resistant to ciprofloxacin,nalidixic acid,chloramphenicol and tetracy-cline with carrying aminoglycoside resistance genes aac(6')-Ⅰaa and aph(3)-Ⅱa,chloramphenicol resistance gene floR,tetra-cycline resistance gene tet,quinolone resistance gene qnrS1,and S83Y substitution in the gyrA gene was found in the quinolo-ne resistance determination region(QRDR).In addition,the strain 2024JD4 carried six types of non-plasmid-based mobile ge-netic elements and 144 virulence genes,including 71 secretion transporter genes and 58 fimbriae adhesion genes,respectively.Four types of fimbriae regulatory genes(csgB,csgC,fimW,fimY)were absent in comparison with smooth-type Salmonella Saintpaul.The literature reviews showed Salmonella Saintpaul was currently a rare Salmonella serotype in cases of urinary tract infections worldwide.Salmonella Saintpaul ST50 with mucoid-type is the pathogen of urinary tract infection with multi-drug resistant phenotypic and genotypic characteristics,and the high mucoid expression may be related to the compensatory mechanism of fimbriae regulatory genes absence in urinary tract colonization and adaptation.WGS combined with the Chinese local Salmonella genome database can effectively solve the diagnosis and biosafety assessments of rare Salmonella phenotypes.

This study was aimed at tracing the molecular typing and drug resistance characteristics of a suspected food poi-soning event caused by Clostridium perfringens in a district of Wuhan City.The FilmArray detection system and multiple fluo-rescence quantitative PCR methods were used to rapidly screen for pathogens in samples from the poisoning event.According to the initial screening results,bacteria were isolated,cultured,and identified by mass spectrometry.Fluorescence PCR was used to detect six virulence genes of the isolated Clostridium perfringens strains.On the basis of whole genome sequencing results,we conducted virulence genes,resistance genes,and whole genome single nucleotide polymorphism genetic evolution(wgSNPs)analyses.Antibiotic sensitivity testing was conducted with the agar dilution method.A total of ten strains of Clos-tridium perfringens were isolated,including eight strains from seven anal swab samples,one strain from fecal samples,and one strain from food samples.Food with suspected contamination had a Clostridium perfringens count of 7.8×106 CFU/g.The PLC(a)toxin gene was detected in all ten gas producing capsule isolation strains,but no other 5 tox-in genes such as CPE were detected,thus confirming that all were type A bacteria producing capsule Clostridium.All strains were 100％resistant to clindamycin and almost completely sensitive to antibiotics such as vancomycin,cefoxitin,and meropenem.Ten strains of Clos-tridium perfringens carried resistance genes such as tetB(P),tetA(P),and mprF,followed by ermQ(70％),ant(6)-Ⅰb(10％),and LnuP(10％).Genetic evolution analysis of wgSNPs indicated that the four outbreak strains clustered together and belonged to an independent subbranch with the suspected food sourcestrains,thus indicating close genetic relationships.In con-clusion,this food poisoning incident might have been be caused by hand torn chickens contaminated with Clostridium perfrin-gens,and the molecular types of the strains revealed high genetic diversity.No multiple drug resistance was observed,but all strains were resistant to clindamycin,an aspect requiring further clinical attention.