Background Meteorological factors are among the key extrinsic triggers for the onset and exacerbation of cardiovascular and cerebrovascular diseases (CVD). Against the backdrop of sustained global warming, elucidating the impact of ambient temperature and atmospheric pressure on CVD, especially on pre-hospital CVD emergent events, has become imperative for evidence-based prevention and emergency preparedness. Objective To quantify the temporal trends of daily mean temperature and atmospheric pressure and their associations with pre-hospital CVD emergent events in Yantai, and to explore effect modification by demographic subgroups and geographic areas, thereby providing an empirical basis for the rational allocation of emergency medical resources. Methods Pre-hospital CVD emergency data from January 1, 2016 to December 31, 2022 were selected from the Yantai 120 Emergency Medical Command System. Synchronous meteorological factors and environmental pollutant data were obtained from the websites of the National Oceanic and Atmospheric Administration and the National Centers for Environmental Information of the United States. Time-series analysis combined with distributed lag non-linear model was used to analyze the association between daily temperature, atmospheric pressure, and pre-hospital CVD emergencies. Average annual percentage changes (AAPC) were calculated using Joinpoint (version 5.2.0.0) to reflect temporal trends. Spearman correlation analysis was employed to screen variables with low collinearity for inclusion in the multi-pollutant adjusted models. Results From 2016 to 2022, a total of 268275 pre-hospital CVD emergency cases were recorded in Yantai City, showing an increasing annual trend (AAPC=7.16%, P=0.002). Emergency volume, daily temperature, atmospheric pressure, and PM₁₀ displayed marked seasonal patterns, with summer bottoms and winter peaks for emergencies, daily temperature higher in summer and lower in winter, and the inverse for atmospheric pressure. Correlation analysis showed that both daily temperature and atmospheric pressure were positively correlated with O₃, with correlation coefficients of 0.745 and 0.723, respectively; negatively correlated with PM_2.5, with correlation coefficients of −0.246 and −0.235, respectively; and negatively correlated with PM₁₀, with correlation coefficients of −0.241 and −0.229, respectively (P < 0.05). A U-shaped correlation was revealed between daily temperature and pre-hospital CVD emergency risk. Using 24 °C as the reference, risk was elevated at both low and high daily temperatures, with the strongest cold effect at –11 ℃ (RR=1.53, 95%CI: 1.35, 1.73) and strongest heat effect at 30 ℃ (RR=1.06, 95%CI: 1.01, 1.11); cold effects were prolonged (lag0–14d) compared to heat effects. Atmospheric pressure exhibited a positive association with emergencies; using a median of 1012.2 hPa as the reference, the maximum risk occurred at 1037 hPa (RR=1.25, 95%CI: 1.03, 1.52), with a 0–5 d lag. In the subgroup analysis, the impact of low temperature was more pronounced among females (RR_{−9 ℃}=1.66), people over 60 years (RR_{−9 ℃}=1.91), and rural residents (RR_{−9 ℃}=1.76). High atmospheric pressure significantly increased the risk of pre-hospital CVD emergency among females (RR_{1035 hPa}=1.54), people under 18 years (RR_{1035 hPa}=3.62), and rural residents (RR_{1035 hPa}=1.46). The sensitivity analysis results indicated that, after excluding the impact of pandemic and the degrees of freedom for time variations, the effects of daily average temperature and atmospheric pressure on pre-hospital CVD emergency volume were consistent with the primary analysis findings. Conclusion Both non-optimal temperature and atmospheric pressure significantly increase the pre-hospital CVD emergency volume; therefore, emergency medical services should develop targeted response protocols, optimize resource allocation, and intensify public health education to mitigate the pre-hospital burden attributable to temperature and pressure fluctuations.

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

Objective To evaluate the safety and efficacy of profunda femoral vein thrombosis clearance in endovascular treatment of acute lower extremity deep venous thrombosis (DVT). Methods From January 2022 to September 2023, clinical data of acute lower extremity DVT patients who underwent percutaneous mechanical thrombectomy (PMT) for profunda femoral vein thrombosis were retrospectively analyzed. The 12-month primary patency rate of iliofemoral vein and incidence of post-thrombotic syndrome(PTS) were analyzed. Results Twenty-two patients were included in the study, and all patients underwent PMT for profunda femoral vein thrombosis. Five patients were treated through the contralateral common femoral vein via crossover approach, and 17 patients were treated through the contralateral common femoral vein combined with the ipsilateral deep vein approach. The 12-month primary patency rate of iliofemoral vein was 90.9% (20/22), and the incidence of PTS was 9.1% (2/22). Conclusions For patients with acute lower extremity DVT undergoing endovascular treatment, PMT for profunda femoral vein thrombosis is safe and effective, achieving good primary patency of iliofemoral vein and low incidence of PTS.

Objective:To investigate the imaging characteristics of fibrous dysplasia(FD) in children with McCune-Albright syndrome(MAS) and the correlation between FD severity and bone metabolism markers, so as to provide a basis for clinical diagnosis and treatment.Methods:A total of 46 children(38 females and 8 males) with MAS with FD who were admitted to the Department of Pediatrics of Ruijin Hospital, Shanghai Jiao Tong University School of Medicine from January 2010 to December 2016 were included in the retrospective study, and all of them met the diagnostic criteria for either the MAS triad or dual manifestations. The extent and characteristics of FD lesions were evaluated by imaging analysis(X-ray and CT). The distribution of café-au-lait spots and endocrine abnormalities were recorded. The serum bone metabolism levels [total procollagen type 1 amino-terminal propeptide(TP1NP), osteocalcin, β-C-terminal telopeptide(β-CTX), alkaline phosphatase(ALP)], and other related indicators such as calcium, phosphorus, magnesium, and fibroblast growth factor(FGF23) levels were detected, and the association between FD severity and indicators was evaluated by Spearman correlation analysis.Results:Among the 46 children, there were 24 cases of triad(FD+ café-au-lait spots + precocious puberty) and 22 cases of dual manifestations(11 cases of FD+ café-au-lait spots or precocious puberty). The age of onset of FD patients(24 cases) with bilateral long bones and skull FD was significantly earlier than that in the unilateral FD group [(3.33±1.34)years vs(5.26±2.34)years, P<0.01], and all of them had extensive café-au-lait spots across the midline. Polyostotic FD accounted for 71.7%(33/46), mainly cystic expansive lesions involving the femur(30 cases) and tibia(24 cases), and skull FD(25 cases) mostly showed ground-glass changes; Monostotic FD(13 cases) was more common in the skull(5 cases) and phalanges(5 cases). FD severity was significantly positively correlated with ALP( ρ=0.554, P=0.002), and negatively correlated with serum phosphorus( ρ=-0.522, P=0.006). All 6 children with severe fractures had FGF23-mediated hypophosphatemia [(1.03±0.12) mmol/L vs control(1.52±0.15) mmol/L, P=0.003]. Conclusions:Extensive café-au-lait spots(across the midline) in children with MAS are strongly associated with early-onset polyostotic FD; FD severity was strongly associated with bone turnover markers(TP1NP, β-CTX, ALP) and FGF23-mediated hypophosphatemia. Early comprehensive skeletal assessment and regular FGF23 monitoring are recommended for children with MAS presenting with extensive cutaneous café-au-lait spots.

Objective:To explore the application of machine learning (ML) models based on radiomics and dosiomics to the assessment of hematologic toxicity (HT) in patients with locally advanced cervical cancer, and to preliminarily explore the comprehensive application of multi-omics features.Methods:A retrospective study was conducted on the clinical data, planning computed tomography (CT) images, and dose files of 205 patients with locally advanced cervical cancer who received concurrent chemoradiotherapy at the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, from January 2022 to June 2023. Patients were categorized according to the severity of HT. Radiomics and dosiomics features were extracted from the same regions of interest (ROIs), followed by feature selection utilizing a random forest algorithm. Then, radiomics, dosiomics, and hybrid models were established based on extreme gradient boosting (XGBoost). The classification performance of these models was assessed by calculating their sensitivity, specificity, and area under the receiver operating characteristic curve (AUC).Results:The radiomics model yielded sensitivity, specificity, and AUC of 0.42, 0.86, and 0.78, respectively. The dosiomics model exhibited sensitivity, specificity, and AUC of 0.50, 0.90, and 0.74, respectively. In contrast, the hybrid model achieved sensitivity, specificity, and AUC of 0.50, 0.83, and 0.83, respectively. These findings suggest that the hybrid model possessed an enhanced classification capability compared to the individual radiomics and dosiomics models.Conclusions:It is feasible to use ML models based on radiomics and dosiomics to conduct the classification and prediction of HT in patients with locally advanced cervical cancer treated with concurrent chemoradiotherapy. Furthermore, integrating both radiomics features and dosiomics features can improve the classification performance of relevant prediction models, thus holding application potentials to optimize treatment strategies for patients with locally advanced cervical cancer.

Objective To investigate the relationship between serum cystatin C(CysC)level and the risk of Parkinson's disease(PD)in middle-aged and elderly people in China.Methods Based on the baseline survey data from the China Health and Retirement Longitudinal Study(CHARLS)in 2011,participants who were not diagnosed with PD at the time of the baseline survey were recruited.The onset of PD was tracked and followed up until 2020,and the participants were divided into PD group and non-PD group according to whether they were newly diagnosed with PD in 2020.Multivariable Logistic regression analysis was performed to assess the association between serum CysC level and the risk of PD.Subgroup and interaction analyses were performed to assess effect modifications by age,gender and depression.Additionally,restricted cubic spline(RCS)was used to explore the linear or non-linear relationship between serum CysC level and the risk of PD in different subgroups.Results We included a total of 3 339 subjects in this study,who consisted of 1 495 males(44.77％)and 1 844 females(55.23％).While baseline participants were followed until 2020,32 subjects had a new PD,and the incidence of PD was 0.96％.The median age of PD group was 63.00 years.Multivariable Logistic regression analysis found that CysC was an independent risk factor for the risk of PD,and CysC was positive significantly associated with the risk of PD(OR=2.34,95％ CI:1.14-4.82,P=0.021).Subgroup analysis showed that CysC was positively associated with PD in females(OR=2.70,95％ CI:1.30-5.58,P=0.007)and subjects aged 60 years or older(OR=5.29,95％ CI:1.69-16.53,P=0.004).RCS model indicated a linear relationship between serum CysC level and the risk of PD in females(Ptotal=0.018,Pnon-linear=0.062)and subjects aged 60 years or older(Ptotal=0.024,Pnon-linear=0.379).Conclusion High level of CysC may increase the risk of PD in middle-aged and elderly people,especially in females and those aged 60 years or older.

Peripheral artery disease(PAD),commonly encountered in vascular surgery,predominantly affects the lower limbs and presents with ischemic symptoms resulting from atherosclerosis.It carries risks of adverse limb events and cardiovascular events.Antithrombotic therapy remains a cornerstone in the management of PAD.This article reviews the evidence and research progress regarding dual-pathway antithrombotic therapy for PAD.Multiple clinical trials have demonstrated that,compared to single antiplatelet therapy,dual-pathway antithrombotic therapy significantly reduces the risks of major adverse limb events and major adverse cardiovascular events without a significant increase in bleeding risk.For high-risk patients,such as those with advanced age,multivessel disease,comorbid coronary artery disease,or those undergoing endovascular revascularization,the benefits of dual-pathway antithrombotic therapy are particularly pronounced.Current clinical guidelines have incorporated dual-pathway antithrombotic therapy into their recommendations,standardized criteria for identifying the most appropriate patient populations remain lacking.Despite its advantages in reducing adverse events,its long-term safety profile and optimal target populations warrant further investigation.

ObjectiveTo investigate the effect of Qingrun prescription（QRP）-containing serum on improving insulin resistance in HepG2 cells and its potential mechanisms. MethodsAn insulin resistance model was established in HepG2 cells with 1×10^-6 mol·L^-1 insulin. Branched-chain α-keto acid dehydrogenase （BCKDH） gene silencing was achieved using siRNA， and the cells were divided into 8 groups： normal group， model group （1×10^-6 mol·L^-1 insulin）， metformin group （1 mmol·L^-1 metformin）， high-， medium-， and low-dose QRP groups （20%， 10%， and 5% QRP-containing serum， respectively）， QRP + siRNA-silenced BCKDH （si-BCKDH） group （10% QRP-containing serum + si-BCKDH）， and QRP + si-NC group （10% QRP-containing serum + si-NC）. Glucose levels in the supernatant were measured with a glucose assay kit， while glycogen content was assessed using a glycogen assay kit. Levels of branched-chain amino acids （BCAAs） and branched-chain keto acids （BCKAs） were determined using ultra-high performance liquid chromatography-tandem mass spectrometry （UHPLC-MS/MS）. mRNA transcription and protein expression levels of BCKDH， dishevelled， Egl-10， and pleckstrin （DEP） domain-containing mammalian target of rapamycin （mTOR）-interacting protein （DEPTOR）， mTOR， and ribosomal protein S6 kinase 1 （S6K1） were detected using real-time quantitative polymerase chain reaction （Real-time PCR） and Western blot. ResultsCompared to the normal group， the model group exhibited significantly decreased glucose consumption and glycogen content， increased levels of BCAAs and BCKAs， downregulated expression of BCKDH and DEPTOR， and upregulated mTOR and S6K1 expression （P<0.01）. In comparison to the model group， QRP treatment at all doses significantly enhanced glucose consumption and glycogen content while reducing BCAAs and BCKAs levels （P<0.01）. The high- and medium-dose QRP groups demonstrated significant upregulation of BCKDH mRNA transcription and protein expression， as well as DEPTOR mRNA transcription. Moreover， the DEPTOR protein expression level was significantly increased in high-， medium-， and low-dose QRP groups， while mTOR and S6K1 mRNA and protein expression levels were markedly downregulated （P<0.05， P<0.01）. Compared to the QRP + si-NC group， the QRP + si-BCKDH group exhibited increased BCAAs and BCKAs levels， significantly decreased BCKDH mRNA transcription and protein expression， downregulated DEPTOR mRNA and protein expression， and upregulated mTOR and S6K1 mRNA and protein expression （P<0.05， P<0.01）. ConclusionQRP may improve insulin resistance by reprogramming BCAAs metabolism. This effect involves upregulating BCKDH， reducing BCAAs and BCKAs levels， and suppressing the mTOR pathway activation.