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: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.

Objective To establish an efficient DNA extraction method for the batch identification of genotypes in model mice.Methods We extracted total DNA from transgenic mouse tails using four methods:alkaline simplified group,alkaline routine group,protease K cleavage group and DNA extraction kit group.The purity and concentration of DNA obtained by the four methods were measured,the effects of gel electrophoresis were evaluated,and the time and experimental costs of the four methods were compared.Results The protease K cleavage method produced the highest concentration of DNA,followed by the simplified alkaline boiling and routine alkaline boiling method.The reagent kit produced the highest DNA purity,followed by the simplified alkaline boiling method.The DNA templates obtained by the four method could be amplified by polymerase chain reaction and gel electrophoresis to obtain clear DNA target bands.In addition,the DNA template extracted by the simplified alkaline boiling method could be used for gene identification after storage at-20℃for 1 month,as well as requiring the least time and lowest costs.Conclusions The simplified alkaline boiling method is currently the simplest,fastest,and most economical DNA template-extraction method for batch identification of genotypes in model mice.

This study explored the drying kinetics of Salviae Miltiorrhizae Radix et Rhizoma(SM), established the suitable models simulating the drying kinetics, and then analyzed the dynamic changes of active components during the drying processes with different methods, aiming to provide a basis for the establishment of suitable drying methods and the quality control of SM. The drying kinetics were studied based on the drying curve, drying rate, moisture effective diffusion coefficient, and drying activation energy, and the appropriate drying kinetics model of SM was established. The drying performance of different methods, such as hot air drying, infrared drying, and microwave drying of SM was evaluated, and the changes in the content of 10 salvianolic acids and 6 tanshinones during drying were analyzed by UPLC-TQ-MS. The Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS) was employed to evaluate the quality of SM dried with different methods. The results showed that the drying rate and moisture effective diffusion coefficient of SM increased with the rise in drying temperature, and the maximum drying rates of different methods were in the order of microwave drying > infrared drying > hot air drying, slice > whole root. The drying rate decreased with the rise in temperature and the extension of drying time. The activation energy of hot air drying was higher than that of infrared drying in SM. The most suitable model for simulating the drying process of SM was the Page model. The TOPSIS results suggested infrared drying at 50 ℃ was the optimal drying method for SM. During the drying process, the content of salvianolic acids increased in different degrees with the loss of moisture, among which salvianolic acid B showed the largest increase of 44 times compared with that in the fresh medicinal material. Tanshinones also existed in the fresh herb of SM, and the content of tanshinone Ⅱ_A increased by 3 times after drying. The results provided a basis for the establishment of suitable drying methods and the quality control of SM.
Salvia miltiorrhiza/chemistry* ; Desiccation/methods* ; Drugs, Chinese Herbal/chemistry* ; Rhizome/chemistry* ; Kinetics ; Quality Control ; Abietanes

Asthma is a chronic inflammatory disease involving multiple inflammatory cells and cytokines. Its pathogenesis is complex, involving various cells and cytokines. Traditional Chinese medicine(TCM) theory suggests that the pathogenesis of asthma is closely related to the dysfunction of internal organs such as the lungs, spleen, and kidneys. In contrast, modern immunological studies have revealed the central role of T helper 1(Th1)/T helper 2(Th2) and T helper 17(Th17)/regulatory T(Treg) cellular immune imbalance in the pathogenesis of asthma. Th1/Th2 imbalance is manifested as hyperfunction of Th2 cells, which promotes the synthesis of immunoglobulin E(IgE) and the activation of eosinophil granulocytes, leading to airway hyperresponsiveness and inflammation.Meanwhile, Th17/Treg imbalance exacerbates the inflammatory response in the airways, further contributing to asthma pathology.Currently, therapeutic strategies for asthma are actively exploring potential targets for regulating the balance of Th1/Th2 and Th17/Treg immune responses. These targets include cytokines, transcription factors, key proteins, and non-coding RNAs. Precisely regulating the expression and function of these targets can effectively modulate the activation and differentiation of immune cells. In recent years,traditional Chinese medicine active ingredients have shown unique potential and prospects in the field of asthma treatment. Based on this, the present study systematically summarizes the efficacy and specific mechanisms of TCM active ingredients in treating asthma by regulating Th1/Th2 and Th17/Treg immune balance through literature review and analysis. These active ingredients, including flavonoids, terpenoids, polysaccharides, alkaloids, and phenolic acids, exert their effects through various mechanisms, such as inhibiting the activation of inflammatory cells, reducing the release of cytokines, and promoting the normal differentiation of immune cells. This study aims to provide a solid foundation for the widespread application and in-depth development of TCM in asthma treatment and to offer new ideas for clinical research and drug development of asthma.
Asthma/genetics* ; Humans ; Drugs, Chinese Herbal/chemistry* ; Th2 Cells/drug effects* ; Th17 Cells/drug effects* ; T-Lymphocytes, Regulatory/drug effects* ; Th1 Cells/drug effects* ; Animals ; Cytokines/immunology* ; Medicine, Chinese Traditional

This study aims to investigate the mechanism of Qingrun Decoction in alleviating hepatic insulin resistance in type 2 diabetes mellitus(T2DM) rats through the reprogramming of amino acid metabolism. A T2DM rat model was established by inducing insulin resistance through a high-fat diet combined with intraperitoneal injection of streptozotocin. The model rats were randomly divided into five groups: model group, high-, medium-, and low-dose Qingrun Decoction groups, and metformin group. A normal control group was also established. The rats in the normal and model groups received 10 mL·kg~(-1) distilled water daily by gavage. The metformin group received 150 mg·kg~(-1) metformin suspension by gavage, and the Qingrun Decoction groups received 11.2, 5.6, and 2.8 g·kg~(-1) Qingrun Decoction by gavage for 8 weeks. Blood lipid levels were measured in different groups of rats. Pathological damage in rat liver tissue was assessed by hematoxylin-eosin(HE) staining and oil red O staining. Transcriptome sequencing and untargeted metabolomics were performed on rat liver and serum samples, integrated with bioinformatics analyses. Key metabolites(branched-chain amino acids, BCAAs), amino acid transporters, amino acid metabolites, critical enzymes for amino acid metabolism, resistin, adiponectin(ADPN), and mammalian target of rapamycin(mTOR) pathway-related molecules were quantified using quantitative real-time polymerase chain reaction(qRT-PCR), Western blot, and enzyme-linked immunosorbent assay(ELISA). The results showed that compared with the normal group, the model group had significantly increased serum levels of total cholesterol(TC), triglycerides(TG), low-density lipoprotein cholesterol(LDL-C), and resistin and significantly decreased ADPN levels. Hepatocytes in the model group exhibited loose arrangement, significant lipid accumulation, fatty degeneration, and pronounced inflammatory cell infiltration. In liver tissue, the mRNA transcriptional levels of solute carrier family 7 member 2(Slc7a2), solute carrier family 38 member 2(Slc38a2), solute carrier family 38 member 4(Slc38a4), and arginase(ARG) were significantly downregulated, while the mRNA transcriptional levels of solute carrier family 1 member 4(Slc1a4), solute carrier family 16 member 1(Slc16a1), and methionine adenosyltransferase(MAT) were upregulated. Furthermore, the mRNA transcription and protein expression levels of branched-chain α-keto acid dehydrogenase E1α(BCKDHA) and DEP domain-containing mTOR-interacting protein(DEPTOR) were downregulated, while mRNA transcription and protein expression levels of mTOR, as well as ribosomal protein S6 kinase 1(S6K1), were upregulated. The levels of BCAAs and S-adenosyl-L-methionine(SAM) were elevated. The serum level of 6-hydroxymelatonin was significantly reduced, while imidazole-4-one-5-propionic acid and N-(5-phospho-D-ribosyl)anthranilic acid levels were significantly increased. Compared with the model group, Qingrun Decoction significantly reduced blood lipid and resistin levels while increasing ADPN levels. Hepatocytes had improved morphology with reduced inflammatory cells, and fatty degeneration and lipid deposition were alleviated. Differentially expressed genes and differential metabolites were mainly enriched in amino acid metabolic pathways. The expression levels of Slc7a2, Slc38a2, Slc38a4, and ARG in the liver tissue were significantly upregulated, while Slc1a4, Slc16a1, and MAT expression levels were significantly downregulated. BCKDHA and DEPTOR expression levels were upregulated, while mTOR and S6K1 expression levels were downregulated. Additionally, the levels of BCAAs and SAM were significantly decreased. The serum level of 6-hydroxymelatonin was increased, while those of imidazole-4-one-5-propionic acid and N-(5-phospho-D-ribosyl)anthranilic acid were decreased. In summary, Qingrun Decoction may improve amino acid metabolism reprogramming, inhibit mTOR pathway activation, alleviate insulin resistance in the liver, and mitigate pathological damage of liver tissue in T2DM rats by downregulating hepatic BCAAs and SAM and regulating key enzymes involved in amino acid metabolism, such as BCKDHA, ARG, and MAT, as well as amino acid metabolites and transporters.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Rats ; Insulin Resistance ; Diabetes Mellitus, Type 2/genetics* ; Male ; Liver/drug effects* ; Amino Acids/metabolism* ; Rats, Sprague-Dawley ; Humans ; Metabolic Reprogramming

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.