Objective: To investigate the therapeutic effect of patchouli alcohol on mice with lung-heat syndrome based on the phosphoinositide 3-kinase(PI3K)/protein kinase B(Akt)/nuclear factor-kappa B(NF-κB) signaling pathway. Methods: First, network pharmacology was used to predict the potential targets of patchouli alcohol in the treatment of lung-heat syndrome, and a "component-disease-key target" network was constructed for pathway analysis. Then, 40 BALB/c mice were assigned to the normal, lung-heat model, honeysuckle, and low-dose and high-dose patchouli alcohol groups. All groups, except the blank group, were intranasally infected with 50 μL (103 TCID50) of influenza virus solution. After two hours of infection, mice were treated once a day for seven consecutive days. The therapeutic mechanism of patchouli alcohol was explored by measuring pulmonary inflammatory factors, the PI3K/Akt/NF-κB pathway, hypothalamic fever markers (PGE2, cAMP, cGMP levels), rectal temperature, and tissue energy metabolism. Results: Network pharmacology identified 135 target genes related to patchouli alcohol and lung-heat syndrome, with the key targets being STAT3, H1F1A, and NF-κB1. In animal experiments, patchouli alcohol significantly alleviated influenza virus-induced lung inflammatory damage in mice with lung-heat syndrome, inhibited the expression of TNF-α and IL-6 in lung tissues(P<0.01), and suppressed the activation of the PI3K/Akt/NF-κB pathway. It also reduced hypothalamic levels of PGE2 and cAMP(P<0.01), suppressed the increase in rectal temperature, significantly decreased liver glycogen and pyruvate levels(P<0.01), and increased the activities of SDH, LDH, and Na+ -K+ -ATPase in the liver(P<0.01) Conclusion Patchouli alcohol improves the symptoms of lung-heat syndrome in mice by inhibiting the activation of the PI3K/Akt/NF-κB pathway, reducing proinflammatory cytokines and inflammatory damage, and regulating hypothalamic fever markers and energy metabolism.

Circadian rhythms are core regulatory mechanisms that evolved to align biological functions with the Earth's rotation. These rhythms are conserved across organisms from unicellular life to multicellular species and play essential roles in metabolism, immune responses, and sleep-wake cycle. Circadian disruptions are strongly associated with various diseases. Over the past decades, genetic studies in Drosophila and mice have identified key conserved clock genes and uncovered transcription-translation feedback loops governing circadian regulation. Additionally, rhythmic neurons in the brain integrate complex neural circuits to precisely regulate physiological and behavioral rhythms. This review highlights recent advances in understanding the neuronal circuit mechanisms of rhythmic neurons in the Drosophila brain and discusses future directions for translating circadian rhythm research into chronomedicine and precision therapies.
Animals ; Circadian Rhythm/genetics* ; Neurons/physiology* ; Drosophila/physiology* ; Brain/physiology* ; Nerve Net/physiology*

OBJECTIVES: To identify potential plasma lipidomic biomarkers that distinguish non-metastatic medulloblastoma (nmMB) from metastatic medulloblastoma (mMB) in children. METHODS: In this prospective study, 17 children with mMB and 20 matched children with nmMB were enrolled. Plasma samples were analyzed using ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry. Lipid metabolites were evaluated for their associations and diagnostic performance. RESULTS: Orthogonal partial least squares discriminant analysis based on lipid profiles clearly separated nmMB from mMB, and 14 differential lipids were identified, including DG(18:2/20:4/0:0) and SM(d18:1/20:0). Receiver operating characteristic analysis showed nine metabolites with area under the curve greater than 0.7. Differential lipids were enriched in sphingolipid, glycerophospholipid, and arachidonic acid metabolism, suggesting an association with the metastatic phenotype. CONCLUSIONS Plasma lipidomics provides a new approach to identify mMB, and the identified lipid metabolites may support early diagnosis and treatment, prognostic assessment, and selection of therapeutic targets for metastatic medulloblastoma.
Humans ; Medulloblastoma/diagnosis* ; Lipidomics ; Child ; Male ; Female ; Child, Preschool ; Cerebellar Neoplasms/blood* ; Biomarkers, Tumor/blood* ; Neoplasm Metastasis ; Prospective Studies ; Adolescent ; Lipids/blood*

OBJECTIVE: To analyze the distribution characteristics of glucose-6-phosphate-dehydrogenase (G6PD) mutations and their enzyme activity in newborns patients with G6PD deficiency in Guilin region. METHODS: From July 2022 to July 2024, umbilical cord blood samples from 4 554 newborns in Guilin were analyzed for G6PD mutations using fluorescence PCR melting curve analysis. Enzyme activity was detected in 4 467 cases using the rate assay. RESULTS: Among 4 467 newborns who underwent G6PD activity testing, 162 newborns (3.63%) were identified as G6PD-deficient, including 142 males (6.04%) and 20 females (0.94%), the prevalence of G6PD deficiency was significantly higher in males than in females (P < 0.001). Genetic analysis of 4 554 newborns detected G6PD mutations in 410 cases (9%), including 171 males (7.13%) and 239 females (11.09%), with a significantly higher mutation detection rate in females than in males (P < 0.001). A total of nine single mutations and four compound heterozygous mutations were identified. The most common mutations were c.1388G>A (33.66%), c.1376G>T (23.66%) and c.95A>G (16.34%). Among newborns who underwent both enzyme activity and genetic mutation testing, males with G6PD mutations had significantly lower enzyme activity than that of females with G6PD mutations(P < 0.001). Specifically, among newborns carrying the mutations c.1388G>A, c.1376G>T, c.95A>G, c.1024C>T or c.871G>A, males consistently exhibited lower enzymatic activity than females with the same mutations (P < 0.001). Furthermore, in male G6PD-deficient newborns, the enzyme activity levels in those carrying c.1388G>A, c.1376G>T, c.95A>G, c.1024C>T, or c.871G>A were lower than those in both the control group and the c.519C>T group (P < 0.05). CONCLUSION This study provides a comprehensive profile of G6PD deficiency incidence and mutation spectrum in the Guilin region. By analyzing enzyme activity and genetic mutation results, this study provides insights into potential intervention strategies and personalized management approaches for the prevention and treatment of neonatal G6PD deficiency in the region.
Humans ; Infant, Newborn ; Glucosephosphate Dehydrogenase Deficiency/epidemiology* ; Glucosephosphate Dehydrogenase/genetics* ; Female ; Male ; Mutation ; China/epidemiology*

OBJECTIVE: To investigate the associations between eight serum per- and polyfluoroalkyl substances (PFASs) and regional fat depots, we analyzed the data from the National Health and Nutrition Examination Survey (NHANES) 2011-2018 cycles. METHODS: Multiple linear regression models were developed to explore the associations between serum PFAS concentrations and six fat compositions along with a fat distribution score created by summing the concentrations of the six fat compositions. The associations between structurally grouped PFASs and fat distribution were assessed, and a prediction model was developed to estimate the ability of PFAS exposure to predict obesity risk. RESULTS: Among females aged 39-59 years, trunk fat mass was positively associated with perfluorooctane sulfonate (PFOS). Higher concentrations of PFOS, perfluorohexane sulfonate (PFHxS), perfluorodecanoate (PFDeA), perfluorononanoate (PFNA), and n-perfluorooctanoate (n-PFOA) were linked to greater visceral adipose tissue in this group. In men, exposure to total perfluoroalkane sulfonates (PFSAs) and long-chain PFSAs was associated with reductions in abdominal fat, while higher abdominal fat in women aged 39-59 years was associated with short-chain PFSAs. The prediction model demonstrated high accuracy, with an area under the curve (AUC) of 0.9925 for predicting obesity risk. CONCLUSION PFAS exposure is associated with regional fat distribution, with varying effects based on age, sex, and PFAS structure. The findings highlight the potential role of PFAS exposure in influencing fat depots and obesity risk, with significant implications for public health. The prediction model provides a highly accurate tool for assessing obesity risk related to PFAS exposure.
Humans ; Fluorocarbons/blood* ; Female ; Adult ; Middle Aged ; Male ; Environmental Pollutants/blood* ; Abdominal Fat ; Nutrition Surveys ; Alkanesulfonic Acids/blood* ; Obesity ; Environmental Exposure

OBJECTIVE: Blood culture remains the gold standard for diagnosing bloodstream infections. Clinical laboratories must ensure the quality of blood culture processes from receipt to obtaining definitive results. We examined laboratory analytical indicators associated with positive blood culture results. METHODS: Blood cultures collected from Peking Union Medical College Hospital between January 1, 2020, and December 31, 2022, were retrospectively analyzed. The mode of transportation (piping logistics delivery vs. staff), source of blood cultures (outpatient/emergency department vs. inpatient department), rotation of personnel, and time of reception (8:00-19:59 vs. 20:00-07:59) were compared between blood culture-positive and -negative results. RESULTS: Between 2020 and 2022, the total positive rate of blood culture was 8.07%. The positive rate of blood cultures in the outpatient/emergency department was significantly higher than that in the inpatient department (12.46% vs. 5.83%; P < 0.0001). The time-to-detection of blood cultures was significantly affected by the delivery mode and personnel rotation. The blood culture positive rate of the total pre-analytical time within 1 h was significantly higher than that within 1-2 h or > 2 h ( P < 0.0170). CONCLUSION Laboratory analytical indicators such as patient source, transportation mode, and personnel rotation significantly impacted the positive detection rate or time of blood culture.
Blood Culture/statistics & numerical data* ; Humans ; Retrospective Studies ; Emergency Service, Hospital/statistics & numerical data*

Objective To investigate the impact of silymarin(SM)on the malignant growth of glioma cells and the regulatory mechanism on the miR-124-3p/WEE1 axis.Methods Glioma U87 cells were grouped into control,SM low,medium,and high concentration groups,and SM high concentration + miR-124-3p inhibitor group(SM high + miR-124-3p inhibitor group).CCK-8 was used to measure the proli-feration rate of cells;Transwell? assay was applied to assay the migration and invasion of cells;cell cycle progression was detected by flow cytometry;Western blotting was applied to measure the expression of cyclin D1 and apoptosis-related proteins;the levels of miR-124-3p and WEE1 mRNA were determined by qRT-PCR;and a luciferase activity test was applied to verify the targeting relationship between miR-124-3p and WEE1;in addition,the establishment,administration,and analysis of a NOD/SCID mouse model of intracranial trans-planted tumor were conducted.Results Compared with the control group,the cell proliferation,the numbers of migrating and invading cells,the expression of cyclin D1,and the level of WEE1 mRNA in the various SM treatment groups decreased,the number of cells in G0/G1 phase,the expression of cleaved caspase-8,cleaved caspase-9,cleaved caspase-3 and miR-124-3p increased(P＜0.05);furthermore,transfection of miR-124-3p inhibitor reversed the inhibitory effect of SM on the malignant behavior of glioma cells.In vivo experiments with mice showed that the weights and volumes of tumors in the SM treatment group were lower than those in the model group(P＜0.05),and there was no discernible change in the weight of the mice(P＞0.05).Conclusion SM can inhibit the malignant growth of glioma cells by upregulating miR-124-3p and downregulating WEE1.

Objective To explore the molecular mechanism of chronic osteomyelitis and to clarify the role of MAPK signal pathway in the pathogenesis of chronic osteomyelitis,by collecting and analyzing the transcriptional information of bone tissue in patients with chronic osteomyelitis.Methods Four cases of traumatic osteomyelitis in limbs from June 2019 to June 2020 were selected,and the samples of necrotic osteonecrosis from chronic osteomyelitis(necrotic group),and normal bone tissue(control group)were collected.Transcriptome information was collected by Illumina Hiseq Xten high throughput sequencing platform,and the gene expression in bone tissue was calculated by FPKM.The differentially expressed genes were screened by comparing the transcripts of the Necrotic group and control group.Genes were enriched by GO and KEGG.MAP3K7 and NFATC1 were selected as differential targets in the verification experiments,by using rat osteomyelitis animal model and im-munohistochemical analysis.Results A total of 5548 differentially expressed genes were obtained by high throughput sequenc-ing by comparing the necrotic group and control group,including 2701 up-regulated and 2847 down-regulated genes.The genes enriched in MAPK pathway and osteoclast differentiation pathway were screened,the common genes expressed in both MAPK and osteoclast differentiation pathway were(inhibitor of nuclear factor κ subunit Beta,IκBKβ),(mitogen-activated protein ki-nase 7,MAP3K7),(nuclear factor of activated t cells 1,NFATC1)and(nuclear factor Kappa B subunit 2,NFκB2).In rat os-teomyelitis model,MAP3K7 and NFATC1 were highly expressed in bone marrow and injured bone tissue.Conclusion Based on the transcriptome analysis,the MAPK signaling and osteoclast differentiation pathways were closely related to chronic os-teomyelitis,and the key genes IκBKβ,MAP3K7,NFATC1,NFκB2 might be new targets for clinical diagnosis and therapy of chronic osteomyelitis.

Objective To establish a dynamic prediction model of fatal massive hemorrhage in trauma based on the vital signs time series data and machine learning algorithms.Methods Retrospectively analyze the vital signs time series data of 7522 patients with trauma in the Medical Information Mart for Intensive Care-Ⅳ(MIMIC-Ⅳ)database from 2008 to 2019.According to the occurrence of posttraumatic fatal massive hemorrhage,the patients were divided into two groups:fatal massive hemorrhage group(n=283)and non-fatal massive hemorrhage group(n=7239).Six machine learning algorithms,including logistic regression(LR),support vector machine(SVM),random forests(RF),adaptive boosting(AdaBoost),gated recurrent unit(GRU),and GRU-D were used to develop a dynamic prediction models of fatal massive hemorrhage in trauma.The probability of fatal massive hemorrhage in the following 1,2,and 3 h was dynamically predicted.The performance of the models was evaluated by accuracy,sensitivity,specificity,positive predictive value,negative predictive value,Youden index,and area under receiver operating characteristic curve(AUC).The models were externally validated based on the trauma database of the Chinese PLA General Hospital.Results In the MIMIC-Ⅳ database,the set of dynamic prediction models based on the GRU-D algorithm was the best.The AUC for predicting fatal major bleeding in the next 1,2,and 3 h were 0.946±0.029,0.940±0.032,and 0.943±0.034,respectively,and there was no significant difference(P=0.905).In the trauma dataset,GRU-D model achieved the best external validation effect.The AUC for predicting fatal major bleeding in the next 1,2,and 3 h were 0.779±0.013,0.780±0.008,and 0.778±0.009,respectively,and there was no significant difference(P=0.181).This set of models was deployed in a public web calculator and hospital emergency department information system,which is convenient for the public and medical staff to use and validate the model.Conclusion A set of dynamic prediction models has been successfully developed and validated,which is greatly significant for the early diagnosis and dynamic prediction of fatal massive hemorrhage in trauma.

Humans ; Leukemia, Myeloid, Acute ; Molecular Chaperones ; Tumor Suppressor Proteins