Objective In this preliminary survey,we sought to determine the composition of mosquito species inhabiting the Emeifeng Nature Reserve,Fujian Province,China.Methods Mosquito larvae were collected by straw and spoon trapping,and adult mosquitoes were collected by lamp trapping at selected breeding sites in the reserve.The specimens were initially identified based on morphology,with subsequent verification using molecular biology methods.Results A total of 34 mosquito species in 13 genera were collected,among which,there were 4 species of Anopheles(Genus Anopheles Meigen,1818),2 species of Lutzia(Genus Lutzia Theobald,1903),15 species of Culex(Genus Culex Linnaeus,1758),4 species of Stegomyia(Genus Stegomyia Theobald,1901),and single species of Hulecoeteomyia(Genus Hulecoeteomyia Theobald,1904),Luius(Genus Luius Reinert,Harbach et Kitching,2008),Aedes(Genus Aedes Meigen,1818),Downsiomyia(Genus Downsiomyia Vargas,1950),Collessius(Genus Collessius Reinert,Harbach et kitching,2006),Uranotaenia(Genus Uranotaenia Lynch 1891),Armigeres(Genus Armigeres Theobald,1901),Toxorhynchites(Genus Toxorhynchites Theobald,1901),and pestle mosquito(Genus Tripteroides Giles,1904).Conclusions The species composition of mosquitoes sampled in the Emeifeng Nature Reserve will provide a basis for further research on mosquito vectors and contribute to measures for local mosquito control.

Traditional Chinese medicine(TCM)exerts integrative effects on complex diseases owing to the char-acteristics of multiple components with multiple targets.However,the syndrome-based system of diagnosis and treatment in TCM can easily lead to bias because of varying medication preferences among physicians,which has been a major challenge in the global acceptance and application of TCM.Therefore,a standardized TCM prescription system needs to be explored to promote its clinical application.In this study,we first developed a gradient weighted disease-target-herbal ingredient-herb network to aid TCM formulation.We tested its efficacy against intracerebral hemorrhage(ICH).First,the top 100 ICH targets in the GeneCards database were screened according to their relevance scores.Then,SymMap and Traditional Chinese Medicine Systems Pharmacology(TCMSP)databases were applied to find out the target-related ingredients and ingredient-containing herbs,respectively.The relevance of the resulting ingredients and herbs to ICH was determined by adding the relevance scores of the corresponding targets.The top five ICH therapeutic herbs were combined to form a tailored TCM prescriptions.The absorbed components in the serum were detected.In a mouse model of ICH,the new prescription exerted multifaceted effects,including improved neurological function,as well as attenuated neuronal damage,cell apoptosis,vascular leakage,and neuroinflammation.These effects matched well with the core pathological changes in ICH.The multi-targets-directed gradient-weighting strategy presents a promising avenue for tailoring precise,multipronged,unbiased,and standardized TCM prescriptions for complex diseases.This study provides a paradigm for advanced achievements-driven modern innovation in TCM concepts.

OBJECTIVE: To investigate the association between ABO blood types and gestational diabetes mellitus (GDM) risk. METHODS: A prospective birth cohort study was conducted. ABO blood types were determined using the slide method. GDM diagnosis was based on a 75-g, 2-h oral glucose tolerance test (OGTT) according to the criteria of the International Association of Diabetes and Pregnancy Study Groups. Logistic regression was applied to calculate the odds ratios ( ORs) and 95% confidence intervals ( CIs) between ABO blood types and GDM risk. RESULTS: A total of 30,740 pregnant women with a mean age of 31.81 years were enrolled in this study. The ABO blood types distribution was: type O (30.99%), type A (26.58%), type B (32.20%), and type AB (10.23%). GDM was identified in 14.44% of participants. Using blood type O as a reference, GDM risk was not significantly higher for types A ( OR = 1.05) or B ( OR = 1.04). However, women with type AB had a 19% increased risk of GDM ( OR = 1.19, 95% CI = 1.05-1.34; P < 0.05), even after adjusting for various factors. This increased risk for type AB was consistent across subgroup and sensitivity analyses. CONCLUSION The ABO blood types may influence GDM risk, with type AB associated with a higher risk. Incorporating it-either as a single risk factor or in combination with other known factors-could help identify individuals at risk for GDM before or during early pregnancy.
Humans ; Female ; Pregnancy ; Diabetes, Gestational/etiology* ; ABO Blood-Group System ; Adult ; Prospective Studies ; Risk Factors ; Young Adult

PURPOSE: Septic shock is associated with high mortality and poor outcomes among sepsis patients with coagulopathy. Although traditional statistical methods or machine learning (ML) algorithms have been proposed to predict septic shock, these potential approaches have never been systematically compared. The present work aimed to develop and compare models to predict septic shock among patients with sepsis. METHODS: It is a retrospective cohort study based on 484 patients with sepsis who were admitted to our intensive care units between May 2018 and November 2022. Patients from the 908th Hospital of Chinese PLA Logistical Support Force and Nanchang Hongdu Hospital of Traditional Chinese Medicine were respectively allocated to training (n=311) and validation (n=173) sets. All clinical and laboratory data of sepsis patients characterized by comprehensive coagulation indexes were collected. We developed 5 models based on ML algorithms and 1 model based on a traditional statistical method to predict septic shock in the training cohort. The performance of all models was assessed using the area under the receiver operating characteristic curve and calibration plots. Decision curve analysis was used to evaluate the net benefit of the models. The validation set was applied to verify the predictive accuracy of the models. This study also used Shapley additive explanations method to assess variable importance and explain the prediction made by a ML algorithm. RESULTS: Among all patients, 37.2% experienced septic shock. The characteristic curves of the 6 models ranged from 0.833 to 0.962 and 0.630 to 0.744 in the training and validation sets, respectively. The model with the best prediction performance was based on the support vector machine (SVM) algorithm, which was constructed by age, tissue plasminogen activator-inhibitor complex, prothrombin time, international normalized ratio, white blood cells, and platelet counts. The SVM model showed good calibration and discrimination and a greater net benefit in decision curve analysis. CONCLUSION The SVM algorithm may be superior to other ML and traditional statistical algorithms for predicting septic shock. Physicians can better understand the reliability of the predictive model by Shapley additive explanations value analysis.
Humans ; Shock, Septic/blood* ; Machine Learning ; Male ; Female ; Retrospective Studies ; Middle Aged ; Aged ; Sepsis/complications* ; ROC Curve ; Cohort Studies ; Adult ; Intensive Care Units ; Algorithms ; Blood Coagulation ; Critical Illness

Traditional Chinese medicine (TCM) exerts integrative effects on complex diseases owing to the characteristics of multiple components with multiple targets. However, the syndrome-based system of diagnosis and treatment in TCM can easily lead to bias because of varying medication preferences among physicians, which has been a major challenge in the global acceptance and application of TCM. Therefore, a standardized TCM prescription system needs to be explored to promote its clinical application. In this study, we first developed a gradient weighted disease-target-herbal ingredient-herb network to aid TCM formulation. We tested its efficacy against intracerebral hemorrhage (ICH). First, the top 100 ICH targets in the GeneCards database were screened according to their relevance scores. Then, SymMap and Traditional Chinese Medicine Systems Pharmacology (TCMSP) databases were applied to find out the target-related ingredients and ingredient-containing herbs, respectively. The relevance of the resulting ingredients and herbs to ICH was determined by adding the relevance scores of the corresponding targets. The top five ICH therapeutic herbs were combined to form a tailored TCM prescriptions. The absorbed components in the serum were detected. In a mouse model of ICH, the new prescription exerted multifaceted effects, including improved neurological function, as well as attenuated neuronal damage, cell apoptosis, vascular leakage, and neuroinflammation. These effects matched well with the core pathological changes in ICH. The multi-targets-directed gradient-weighting strategy presents a promising avenue for tailoring precise, multipronged, unbiased, and standardized TCM prescriptions for complex diseases. This study provides a paradigm for advanced achievements-driven modern innovation in TCM concepts.

Aim To verify the mechanism of action of Carthami Flos-Lycopodii Herba in treating KOA carti-lage inflammation based on network pharmacology and in vitro and in vivo experiments.Methods The effec-tive ingredients of Carthami Flos-Lycopodii Herba were screened through the database,the core targets of"drug disease"were analyzed,and pathway enrichment analy-sis and molecular docking verification were conducted.Experimental verification:Primary chondrocytes were extracted from mice and divided into the control group,IL-1β group,treatment group,and treatment+TLR4 agonist group.CCK-8 method was used to screen the optimal intervention concentration of Carthami Flos-Ly-copodii Herba.ELISA was used to detect the content of inflammatory factors in chondrocytes.Western blot was employed to detect the protein expression related to cellular pathways.Subsequently,a KOA mouse model was constructed using the DMM method.After admin-istration,the knee joint injury of mice was evaluated u-sing safranin O-green staining.ELISA was used to de-tect the levels of inflammatory factors in serum.West-ern blot was employed to detect collagen Ⅱ,MMP13,Aggrecan,and apoptosis related protein expression in cartilage tissue.TUNEL staining was used to detect the apoptosis rate of cells.Results A total of 26 active ingredients of Carthami Flos-Lycopodii Herba were screened,as well as 123 potential targets for treating KOA.The enrichment analysis results indicated that it mainly involved mechanisms such as Toll like receptors and cell apoptosis.The experimental results showed that Carthami Flos-Lycopodii Herba alleviated the in-flammatory response of chondrocytes and affected the expression of pathway related proteins.Compared with KOA mice,safflower stretched muscle grass could im-prove cartilage damage and reduce the concentration of serum inflammatory factors,regulate the expression of collagen Ⅱ,MMP13,Aggrecan,and apoptosis related proteins in cartilage tissue,and reduce the fluorescence intensity of TUNEL staining in the tissue.Conclusions Carthami Flos-Lycopodii Herba can improve KOA cartilage inflammation,and its mechanism may be relat-ed to the TLR4/MyD88/NF-κB signaling pathway.

Aim To investigate the therapeutic effects of cinnamaldehyde on synovial lesions in mice with knee osteoarthritis(KOA)and its regulatory mecha-nism in the phagocytic function of synovial macropha-ges.Methods In the animal experiments,mouse ser-um and synovial tissue were extracted.HE staining was used to evaluate the inflammatory cell infiltration in the synovial tissue.ELISA was employed to detect the lev-els of inflammatory factors such as interleukins in the serum.Western blot was used to detect the expression of Ras homolog family member A(RhoA),Rho-associ-ated protein kinase 1(ROCK1),myosin light chain(MLC),and p-MLC proteins in the synovial tissue.RT-qPCR was utilized to detect the expression of in-flammatory factors and pathway-related mRNA in the synovial tissue.TUNEL staining was used to detect ap-optosis in the synovial tissue.In the cellular experi-ments,after the intervention,RAW267.4 cells were subjected to Western blot and RT-qPCR for the detec-tion of the aforementioned indicators,and confocal mi-croscopy was used to assess phagocytic function.Re-sults After cinnamaldehyde intervention,the synovial inflammatory infiltration was significantly reduced,the protein and mRNA expression of the RhoA/ROCK1/MLC signaling pathway was markedly downregulated,the fluorescence intensity of TUNEL staining signifi-cantly decreased,and the phagocytic function of macro-phages was enhanced.Conclusion Cinnamaldehyde can inhibit RhoA/Rock1/MLC signaling pathway,en-hance macrophage burial,improve synovial inflamma-tion,and delay the progression of KO A mice.

Objective To explore the risk factors for noncontiguous spinal fractures(NSFs)in the elderly.Methods The clinical data of 614 elderly patients with spinal fracture from January 2013 to December 2019 were analyzed retrospectively.Patients were divided into the NSFs group and the Non-NSFs group according to whether NSFs occurred or not.Univariate analysis and multivariate Logistic regression analysis were used to screen the risk factors of NSFs.Results Univariate analysis showed that female(P=0.003),high-energy violent injury(P=0.032),osteoporosis(P=0.004),fracture in spring(P=0.020),and previous spinal fracture history(P<0.001)were associated with the occurrence of NSFs.Multivariate Logistic regression analysis showed that fracture in spring(P=0.024),previous spinal fracture history(P<0.001)and high-energy violent injury(P=0.038)were the independent risk factors for the occurrence of NSFs in the elderly.Conclusion High-energy violent injury,fracture in spring and previous spinal fracture history are the independent risk factors for the occurrence of NSFs in the elderly.Therefore,elderly patients with the above risk factors should be examined more carefully and comprehensively to avoid missed diagnosis and delayed diagnosis.In order to reduce the incidence of this disease,corresponding measures should be taken according to the preventable risk factors.

Objective To analyze the risk factors for increased drainage volume after open transforaminal lumbar interbody fusion(TLIF),and to establish a predictive model and then validate it.Methods The clinical data of 680 patients who underwent open TLIF at the General Hospital of Northern Theater Command from January 2016 to December 2019 were collected and the patients were randomly divided into the training group(n=476)and the validation group(n=204).Taking the predictive factors screened out by LASSO regression analysis as independent variables,a multivariate Logistic regression predictive model was constructed.The model was internally validated through the receiver operating characteristic(ROC)curve,Hosmer-Lemeshow goodness-of-fit test,and calibration curve,and its clinical utility was assessed via decision curve analysis(DCA).Results LASSO regression analysis screened out four predictive variables:age,number of surgical segments,operative duration,and intraoperative blood loss.The multivariate Logistic regression predictive model demonstrated that age≥60 years,number of surgical segments≥4,operative duration≥2 hours,and intraoperative blood loss≥200 mL were independent influencing factors for the increased postoperative drainage volume in patients undergoing TLIF(P<0.05).ROC curve analysis revealed an area under the curve(AUC)of 0.816(95%CI:0.798 to 0.867)in the training group and 0.783(95%CI:0.685 to 0.823)in the validation group,indicating that the predictive model had good discriminatory ability.Additionally,the Hosmer-Lemeshow goodness-of-fit test and calibration curve indicated that the predictive model had a good degree of fit,and the predicted probability was basically consistent with the actual probability,demonstrating a good calibration.The DCA results confirmed that this predictive model could be applied in clinical practice.Conclusion The risk factors for increased drainage volume after open TLIF include age,number of surgical segments,operative duration,and intraoperative blood loss.The predictive model established based on these factors demonstrates good performance,and it can be applied in clinical guidance for the selection of drainage tube removal time after TLIF.

Depression is a common psychiatric disorder characterized by persistent low mood or mental disorders. Current treatments primarily focus on regulating neurotransmitter levels， but their effectiveness is limited. The mechanisms underlying its onset are complex， and there is no unified consensus. Abnormal signaling pathway transmission plays a crucial role in the development of depression， involving multiple pathways， including Toll-like receptor 4/nucleotide-binding oligomerization domain-like receptor protein 3 （TLR4/NLRP3）， nuclear factor-κB （NF-κB）， Janus kinase/signal transducer and activator of transcription （JAK/STAT）， mitogen-activated protein kinase/extracellular signal-regulated kinase （MAPK/ERK）， brain-derived neurotrophic factor/tyrosine kinase receptor B （BDNF/TrkB）， cyclic AMP/protein kinase A/cAMP response element-binding protein （cAMP/PKA/CREB）， and others. Traditional Chinese medicine（TCM） is based on a holistic approach and the principle of treatment based on the differentiation of syndromes， regulating the balance of multiple systems and organ functions from a macroscopic perspective. This approach has shown unique advantages in the treatment of depression. TCM attributes the onset of depression to dysfunction of the organ systems， involving liver Qi stagnation， heart spirit deficiency， kidney essence depletion， and spleen dysfunction. TCM compound treatments focus on soothing the liver， strengthening the spleen， calming the heart， and replenishing essence， with formulas such as Xiaoyaosan， Zishui Qinggan Yin， and Chahu Jia Guizhi Longgu Muli Tang. The active components of Chinese herbs mainly aim to tonify and regulate Qi， such as salidroside， ginsenoside Rb₁， astragaloside， and muscone. External TCM treatments， primarily acupuncture， aim to open the orifices and invigorate the spirit. Acupoints such as Baihui， Shenting， and Yintang are commonly used. Additionally， massage and moxibustion therapy can intervene in depression by regulating signaling pathways. This article reviews the core role of signaling pathways in the development of depression and the mechanism of TCM regulation of signaling pathways to intervene in depression， aiming to discover new therapeutic approaches that can improve the symptoms of depressed patients.