OBJECTIVE To investigate the influence of CYP2C19 gene polymorphism on platelet function and inflammatory cytokines in elderly patients with ischemic stroke， and to analyze potential factors associated with poor prognosis. METHODS A retrospective study was conducted on elderly patients with ischemic stroke admitted to our hospital from June 2024 to June 2025， wh o underwent CYP2C19 genotype testing and received antiplatelet therapy with clopidogrel. The levels of platelet function indicators and inflammatory cytokines before and after treatment were compared among patients with different metabolic phenotypes. Based on the prognosis at 6 months post-treatment， patients were divided into poor prognosis group and good prognosis group. Univariate analysis was performed on general data， metabolic phenotype， the levels of platelet function indicators and inflammatory cytokines. Variables with P ＜0.05 and the levels of inflammatory cytokines before treatment were included in a multivariate Logistic regression analysis to identify independent risk factors for poor prognosis. Multiple linear regression was used to further analyze the relationship between metabolic phenotypes and inflammatory cytokines. RESULTS A total of 448 elderly patients with ischemic stroke were included； among them， 162 cases were normal metabolic phenotype， 218 were intermediate metabolic phenotype， and 68 were poor metabolic phenotype. No rapid or ultrarapid metabolic phenotypes were observed. After treatment， platelet aggregation rate， the levels of P-selectin and platelet activated complex-1 （PAC-1）， high-sensitivity C-reactive Protein （hs-CRP）， interleukin-1β （IL-1β）， IL-6 and tumor necrosis factor-α （TNF-α） in the normal metabolic phenotype group， intermediate metabolic phenotype group， and poor metabolic phenotype group （except for platelet aggregation rate， and the levels of P-selectin and PAC-1 in the poor metabolic phenotype group） were significantly lower than those before treatment in the same group. Moreover， the above indicators in the normal metabolic phenotype group were significantly lower than those in the intermediate and poor metabolic phenotype groups at the corresponding time， and the levels of platelet function indicators in the intermediate metabolic phenotype group were significantly lower than those in the poor metabol ic phenotype group at the corresponding time （ P ＜0.05）. Univariate and multivariate Logistic regression analyses showed that combined with hypertension， combined with diabetes mellitus， and intermediate or poor metabolic genotypes were independent risk factors for poor prognosis in elderly patients with ischemic stroke （ P ＜0.05）. Multiple linear regression analysis showed that serum levels of hs-CRP， IL-1β， IL-6 and TNF-α before treatment were significantly higher in patients with intermediate and poor metabolic genotypes compared to those with normal metabolic genotype （ P ＜0.05）， with a greater magnitude of increase in inflammatory cytokines observed in the patients with poor metabolic genotype. CONCLUSIONS The elderly ischemic stroke patients with CYP2C19 intermediate and poor metabolic genotypes have poor inhibition effect on platelet and higher levels of inflammatory cytokines than normal metabolic genotype； CYP2C19 gene polymorphism， and in combination with hypertension and diabetes， can be used as independent predictors of poor prognosis.

AIM:To automatically identify and quantitatively assess myopia-related fundus structural changes by combining non-mydriatic color fundus photography with an artificial intelligence(AI)-powered quantitative fundus analysis system and to further analyze the correlations between these fundus parameters and spherical equivalent(SE), axial length(AL), and age, providing the objective basis for monitoring myopia progression and supporting the formulation of personalized myopia prevention and control strategies. METHODS:A cross-sectional study was conducted enrolling myopic patients aged 18-50 y who underwent myopia screening from March 2023 to December 2023. Patients were stratified into three groups based on SE: the -3.00 D

ObjectiveTo construct and evaluate various machine learning models for predicting the risk of chronic obstructive pulmonary disease （COPD） in individuals， thereby providing data support for early screening and intervention. MethodsA total of 823 subjects were selected for this study， comprising 142 individuals in the high-risk group for COPD and 681 individuals in the low-risk group. Data collected included demographic characteristics， smoking history， symptoms （such as cough and shortness of breath）， and scores from the Chronic obstructive pulmonary disease screening questionnaire. Four machine learning algorithms—Logistic regression， random forest， support vector machine， and XGBoost—were utilized to construct risk prediction models. The performance of these models was assessed using 5-fold cross-validation， with evaluation metrics including accuracy， precision， recall， F1-score， area under the receiver operating characteristic curve （AUC）， and average precision （AP）. Furthermore， a feature importance analysis was performed. ResultsThe Logistic Regression model exhibited superior performance， achieving an AUC of 0.982 and an AP of 0.939. This was closely followed by the Random Forest model， which recorded an AUC of 0.975 and an AP of 0.890. Feature importance analysis revealed that smoking history， symptoms of shortness of breath， and body weight were significant predictors. All models demonstrated robust performance in identifying low-risk populations； however， variations were observed in their efficacy in identifying high-risk populations. ConclusionMachine learning models have proven effective in identifying individuals at high risk for COPD. Among these， the Logistic regression model exhibits the best overall performance， efficiently identifying high-risk populations and serving as a valuable clinical auxiliary screening tool. Various models， each with distinct performance characteristics， are suited to different clinical screening scenarios， thereby offering targeted decision-making support for the establishment of a hierarchical and intelligent COPD screening pathway.

BACKGROUND:Studies have shown that ischemia-induced cellular autophagy dysfunction is a key factor in brain injury.Autophagy related genes 6(ATG6),microtubule-associated protein 1 light chain(LC3),p62,and other autophagy key proteins are involved in the processes such as neuronal axonal degeneration,death,and intracellular homeostasis maintenance,playing an important role in the recovery of neural function. OBJECTIVE:To review the research progress in the role of cellular autophagy in cerebral ischemic injury and the regulatory mechanism of traditional Chinese medicine. METHODS:The first author used"ischemic stroke,brain tissue injury,cellular autophagy,signaling pathways,traditional Chinese medicine compounds,terpenoids,alkaloids,flavonoids,saponins,lignans,phthalates"as Chinese and English keywords respectively to search for literature on autophagy,cerebral ischemic injury,and the regulatory mechanisms of traditional Chinese medicine from China National Knowledge Infrastructure(CNKI)and PubMed databases from January 2016 to February 2024.Literature that is not highly relevant,repetitive,or outdated was excluded.A total of 1 746 relevant literature were retrieved,and 92 articles were ultimately included. RESULTS AND CONCLUSION:Numerous studies have confirmed that autophagy plays an important role in cerebral ischemic injury.Moderate autophagy can promote cell survival,while excessive autophagy exacerbates brain injury.Traditional Chinese medicine can regulate the expression of autophagy related proteins,inhibit neuronal necrosis and apoptosis,and exert neuroprotective effects at different stages of cerebral ischemia by regulating signaling pathways such as PI3K/Akt/mTOR,AMPK-mTOR,and mitogen activated protein kinase.

ObjectiveTo observe the clinical efficacy and safety of Modified Guomin Decoction （加味过敏煎， MGD） in patients with mild to moderate atopic dermatitis （AD） of the traditional Chinese medicine （TCM） pattern of heart fire and spleen deficiency， and to explore its possible mechanisms. MethodsIn this randomized， double-blind， placebo-controlled study， 72 patients with mild to moderate AD and the TCM pattern of heart fire and spleen deficiency were randomly divided into a treatment group and a control group， with 36 cases in each group. The treatment group received oral MGD granules combined with topical vitamin E emulsion， while the control group received oral placebo granules combined with topical vitamin E treatment. Both groups were treated twice daily for 4 weeks. Clinical efficacy， TCM syndrome scores， Visual Analogue Scale （VAS） for pruritus， Dermatology Life Quality Index （DLQI） scores， Scoring Atopic Dermatitis （SCORAD） and serum biomarkers， including interleukin-33 （IL-33）， interleukin-1β （IL-1β）， immunoglobulin E （IgE）， and tumor necrosis factor-α （TNF-α） were compared before and after treatment. Safety indexes was also assessed. ResultsThe total clinical effective rates were 77.78% （28/36） in the treatment group and 38.89% （14/36） in the control group， with cure rates of 19.44% （7/36） and 2.78% （1/36）， respectively. The treatment group showed significantly better clinical outcomes compared to the control group （P＜0.05）. The treatment group exhibited significant reductions in total TCM syndrome scores， including erythema， edema， papules， scaling， lichenification， pruritus， irritability， insomnia， abdominal distension， and fatigue scores， as well as reductions in VAS， DLQI， SCORAD， and serum IgE and IL-33 levels （P＜0.05 or P＜0.01）. Compared to the control group， the treatment group had significantly better improvements in all indicators except for insomnia （P＜0.05）. No adverse events occurred in either group. ConclusionMGD is effective and safe in treating mild to moderate AD patients with heart fire and spleen deficiency pattern. It significantly alleviates pruritus， improves TCM syndromes and quality of life， and enhances clinical efficacy， possibly through modulation of immune responses.

ObjectiveTo study the effects of applying different microbial fertilizers on the growth and rhizosphere soil environment of Codonopsis pilosula and provide a theoretical basis for ecological cultivation of this medicinal plant. MethodsSeven groups were designed， including CK （no application of microbial fertilizer）， T1 （Trichoderma longibrachiatum fertilizer）， T2 （Bacillus subtilis fertilizer）， T3 （Trichoderma viride fertilizer）， T4 （compound microbial fertilizer）， T5 （C. pilosula stems and leaves fermented with compound microbial fertilizer）， and T6 （Scutellaria baicalensis stems and leaves fermented with T. viride fertilizer）. The physiological indicators， yield， and quality of C. pilosula and the physicochemical properties， enzyme activities， and microbial diversity in the rhizosphere soil of different fertilizer treatments were measured. ResultsGroup T1 showed slight decreases in soluble protein content （SPC） and superoxide dismutase （SOD）. Groups T2-T6 showed increases in physiological indicators such as proline （Pro）， soluble solids content （SSC）， SPC， catalase （CAT）， and peroxidase （POD） and a decrease in malondialdehyde （MDA） in C. pilosula leaves. All the fertilizer treatments increased the yield of C. pilosula and the total polysaccharide content in the roots. T1， T2， T3， T4， and T5 increased the total flavonoid content in the roots. Meanwhile， T4 increased the total saponin content in the roots. All the fertilizer treatments reduced the pH and increased the electric conductivity （EC）， soil organic matter （SOM）， and alkaline nitrogen （AN） in the soil. T2 and T5 increased the available phosphorus （AP）， and T3， T4， T5， and T6 increased the available potassium （AK） in the soil. All the fertilizer treatments increased the activities of urease， sucrase， and CAT in the soil. Except that T1 decreased the bacterial diversity in the soil， other fertilizer treatments significantly increased bacterial and fungal diversity in the soil. Different fertilizer treatments significantly affected the composition of bacterial and fungal communities in the soil. At the phylum level， the dominant bacterial phyla included Proteobacteria， Acidobacteriota， and Bacteroideta， and the dominant fungal phyla were Ascomycota， Mortierellomycota， and unclassified_fungi in the rhizosphere soil of C. pilosula after bacterial fertilizer treatment. At the genus level， unclassified Gemmatimonadaceae， Sphingomonas， and unclassified Vicinamibacteraceae were the dominant bacterial genera， while unidentified， unclassified Fungi， and unclassified Sordariomycetes were the dominant fungal genera in the rhizosphere soil. The results of redundancy analysis indicated that the main physicochemical factors affecting changes of microbial communities in the rhizosphere soil of C. pilosula were pH， EC， AK， AN， AP， and soil organic matter （SOM） in the soil. The correlation heatmap showed that Bryobacter had significantly positive correlations with EC， AK， and AN. There was a significantly negative correlation between Fusarium and SOM. In summary， applying an appropriate amount of microbial fertilizer can promote the growth and improve the rhizosphere soil environment of C. pilosula. ConclusionThe compound microbial fertilizer and the C. pilosula stems and leaves fermented with compound microbial fertilizer can improve the soil nutrients， growth， development， yield， and quality of C. pilosula， and thus they can be applied to the artificial cultivation of C. pilosula.

ObjectiveTo study the effects of applying different microbial fertilizers on the growth and rhizosphere soil environment of Codonopsis pilosula and provide a theoretical basis for ecological cultivation of this medicinal plant. MethodsSeven groups were designed， including CK （no application of microbial fertilizer）， T1 （Trichoderma longibrachiatum fertilizer）， T2 （Bacillus subtilis fertilizer）， T3 （Trichoderma viride fertilizer）， T4 （compound microbial fertilizer）， T5 （C. pilosula stems and leaves fermented with compound microbial fertilizer）， and T6 （Scutellaria baicalensis stems and leaves fermented with T. viride fertilizer）. The physiological indicators， yield， and quality of C. pilosula and the physicochemical properties， enzyme activities， and microbial diversity in the rhizosphere soil of different fertilizer treatments were measured. ResultsGroup T1 showed slight decreases in soluble protein content （SPC） and superoxide dismutase （SOD）. Groups T2-T6 showed increases in physiological indicators such as proline （Pro）， soluble solids content （SSC）， SPC， catalase （CAT）， and peroxidase （POD） and a decrease in malondialdehyde （MDA） in C. pilosula leaves. All the fertilizer treatments increased the yield of C. pilosula and the total polysaccharide content in the roots. T1， T2， T3， T4， and T5 increased the total flavonoid content in the roots. Meanwhile， T4 increased the total saponin content in the roots. All the fertilizer treatments reduced the pH and increased the electric conductivity （EC）， soil organic matter （SOM）， and alkaline nitrogen （AN） in the soil. T2 and T5 increased the available phosphorus （AP）， and T3， T4， T5， and T6 increased the available potassium （AK） in the soil. All the fertilizer treatments increased the activities of urease， sucrase， and CAT in the soil. Except that T1 decreased the bacterial diversity in the soil， other fertilizer treatments significantly increased bacterial and fungal diversity in the soil. Different fertilizer treatments significantly affected the composition of bacterial and fungal communities in the soil. At the phylum level， the dominant bacterial phyla included Proteobacteria， Acidobacteriota， and Bacteroideta， and the dominant fungal phyla were Ascomycota， Mortierellomycota， and unclassified_fungi in the rhizosphere soil of C. pilosula after bacterial fertilizer treatment. At the genus level， unclassified Gemmatimonadaceae， Sphingomonas， and unclassified Vicinamibacteraceae were the dominant bacterial genera， while unidentified， unclassified Fungi， and unclassified Sordariomycetes were the dominant fungal genera in the rhizosphere soil. The results of redundancy analysis indicated that the main physicochemical factors affecting changes of microbial communities in the rhizosphere soil of C. pilosula were pH， EC， AK， AN， AP， and soil organic matter （SOM） in the soil. The correlation heatmap showed that Bryobacter had significantly positive correlations with EC， AK， and AN. There was a significantly negative correlation between Fusarium and SOM. In summary， applying an appropriate amount of microbial fertilizer can promote the growth and improve the rhizosphere soil environment of C. pilosula. ConclusionThe compound microbial fertilizer and the C. pilosula stems and leaves fermented with compound microbial fertilizer can improve the soil nutrients， growth， development， yield， and quality of C. pilosula， and thus they can be applied to the artificial cultivation of C. pilosula.

OBJECTIVE: To explore the genetic testing outcomes of a fetal family with Thyroid dyshormonogenesis type 5 (TDH5) and familial Neurofibromatosis type 1 (NF1), and to clarify the association between clinical manifestations and genetic variations. METHODS: One case of a TDH5 combined with familiar NF1 fetus treated at Gansu Maternal and Child Health Hospital in January 2024 was selected as the research subject. The clinical and family history data of the fetus were collected by retrospective research method. 10-15 mL of fetal amniotic fluid, and 2-3 mL of peripheral blood from the parents, sister, and grandfather of the fetus were collected, and genomic DNA was extracted for trio whole-exome sequencing (trio-WES). The Sanger sequencing was utilized to validate candidate variants for family verification. According to the Standards and Guidelines for the Interpretation and Reporting of Sequence Variants of the American Society of Medical Genetics and Genomics (ACMG) (hereafter referred to as the ACMG guidelines), the pathogenicity of the detected variants was classified. This study has been approved by the Medical Ethics Committee of Gansu Maternal and Child Health Hospital [Ethics No.（2021）GSFY（65）]. RESULTS: The fetal ultrasound indicated the nuchal translucency (NT) thickening, and the thyroid function test results of the sister showed an increase in thyroid stimulating hormone and a decrease in free thyroid hormone. Simultaneously, there were cafe-au-lait macules of various sizes in multiple parts of the body of the sister, and the mother had a similar cafe-au-lait macules phenotype. The trio-WES results revealed that there was a c.413dupA (p.Tyr138*) frameshift mutation in exon4 and c.573G>A (p.Trp191*) nonsense mutation in exon5 of the fetal DUOXA2, which were inherited from the mother and father, respectively. In accordance with the ACMG guidelines, they were classified as pathogenic variant (PVS1+PM2_Supporting+PM3) and likely pathogenic variant (PVS1+PM2_Supporting), respectively. And the nonsense mutation c.6972C>A (p.Tyr2264*) was detected in exon46 of the NF1 in the fetus, inherited from the mother maternal grandfather. The genetic testing results of the first sister and proband in this case were consistent, and the DUOXA2 and NF1 of the second sister were both wild-type. According to the ACMG guidelines, c.6972C>A (p.Tyr2264 *) was classified as pathogenic variant (PVS1+PS4_Supporting+PP4+PM2_Supporting). CONCLUSION The mutations in the DUOXA2 gene c.413dupA (p.Tyr138*) and c.573G>A (p.Trp191*), and the NF1 gene c.6972C>A (p.Tyr2264*) might be the genetic causes of TDH5 combined with familiar NF1 in proband. The discovery of the DUOXA2 gene c.573G>A (p.Trp191*) enriches the spectrum of pathogenic gene variations.
Humans ; Female ; Pedigree ; Pregnancy ; Neurofibromatosis 1/complications* ; Male ; Genetic Testing ; Adult ; Thyroid Dysgenesis/genetics* ; Fetus ; Exome Sequencing ; Mutation

OBJECTIVE: To determine the carrier rate for thalassemia mutations in the ethnic Miao population of Qianxinan Prefecture. METHODS: Ethnic Miao people suspected for thalassemia trait at the People's Hospital of Qianxinan Prefecture, Guizhou Province between November 2020 to September 2024 were selected as the study subjects. Gap-PCR technology combined with high-throughput sequencing was used to screen a total of 666 individuals. ArcMap v10.8.2 was used to create a spatial distribution map of thalassemia based on the screening results. This study was approved by the Medical Ethics Committee of the hospital (Ethics No.: 2016-01). RESULTS: In total 254 positive cases were detected, with an overall positive rate of 38.14%. Among these, 173 cases were α-thalassemia (25.98%), 77 cases were β-thalassemia (11.56%), and 4 cases were αβ compound thalassemia (0.60%). The most common genotypes for α-thalassemia were αα/--^SEA (positive rate = 10.06%, accounting for 38.73%), αα/-α^3.7 (positive rate = 8.86%, accounting for 34.10%), and α^CSα/αα (positive rate = 4.95%, accounting for 19.08%). The most common genotypes for β-thalassemia were β^41/42(-TTCT)/β^A (positive rate = 5.11%, accounting for 44.16%) and β^{17 (A>T)}/β^A(positive rate = 4.20%, accounting for 36.36%), with these two genotypes accounting for as much as 80.52%. The spatial distribution map indicated that the highest overall detection rate of thalassemia and α-thalassemia in the Miao population of Qianxinan Prefecture was in Xingyi City. The highest detection rate of β-thalassemia was in Zhenfeng County, and the highest detection rate of αβ compound thalassemia was in Wangmo County. CONCLUSION The detection rate of thalassemia among the ethnic Miaos from Qianxinan Prefecture is relatively high, which primarily consisted of α-thalassemia. Regular monitoring and educational outreach should be conducted.
Humans ; China/ethnology* ; Female ; Male ; Genetic Testing ; Adult ; alpha-Thalassemia/genetics* ; Thalassemia/ethnology* ; Ethnicity/genetics* ; Genotype ; beta-Thalassemia/ethnology* ; Adolescent ; Mutation ; Middle Aged ; Child ; Asian People/genetics* ; Young Adult

PURPOSE: Early mortality in major trauma has decreased, but MODS remains a leading cause of poor outcomes, driven by trauma-induced cytokine storms that exacerbate injuries and organ damage. METHODS: This prospective cohort study included 79 major trauma patients (ISS >15) treated in the National Center for Trauma Medicine, Peking University People's Hospital, from September 1, 2021, to July 31, 2023. Patients (1) with ISS >15 (according to AIS 2015), (2) aged 15-80 years, (3) admitted within 6 h of injury, (4) having no prior treatment before admission, were included. Exclusion criteria were (1) GCS score <9 or AIS score ≥3 for TBI, (2) confirmed infection, infectious disease, or high infection risk, (3) pregnancy, (4) severe primary diseases affecting survival, (5) recent use of immunosuppressive or cytotoxic drugs within the past 6 months, (6) psychiatric patients, (7) participation in other clinical trials within the past 30 days, (8) patients with incomplete data or missing blood samples. Admission serum inflammatory cytokines and pathophysiological data were analyzed to develop machine learning models predicting MODS within 7 days. LR, DR, RF, SVM, NB, and XGBoost were evaluated based on the area under the AUROC. The SHAP method was used to interpret results. RESULTS: This study enrolled 79 patients with major trauma, and the median (Q₁, Q₃) age was 51 (35, 59) years (52 males, 65.8%). The inflammatory cytokine data were collected for all participants. Among these patients, 35 (44.3%) developed MODS, and 44 (55.7%) did not. Additionally, 2 patients (2.5%) from the MODS group succumbed. The logistic regression model showed strong performance in predicting MODS. Ten key cytokines, IL-18, Eotaxin, MCP-4, IP-10, CXCL12, MIP-3α, MCP-1, IL-1RA, Cystatin C, and MRP8/14 were identified as critical to the trauma-induced cytokine storm and MODS development. Early elevation of these cytokines achieved high predictive accuracy, with an AUROC of 0.887 (95% CI 0.813-0.976). CONCLUSION Trauma-induced cytokine storms are strongly associated with MODS. Early identification of inflammatory cytokine changes enables better prediction and timely interventions to improve outcomes.
Humans ; Prospective Studies ; Middle Aged ; Male ; Female ; Adult ; Aged ; Cytokine Release Syndrome/etiology* ; Adolescent ; Young Adult ; Aged, 80 and over ; Wounds and Injuries/complications* ; Cytokines/blood* ; Multiple Organ Failure/diagnosis* ; Machine Learning