OBJECTIVE To investigate the causal relationships between gut microbiota， blood metabolites and antidepressant treatment response from a genetic perspective， and to assess the potential mediating role of blood metabolites. METHODS This study utilized a two-sample Mendelian randomization （MR） design. Exposure data were derived from four large-scale gut microbiome genome-wide association study （GWAS） datasets and two blood metabolite GWAS datasets. The inverse variance weighted method was used as the primary method to evaluate the causal relationships between gut microbiota， blood metabolites and antidepressant effects. The robustness， heterogeneity and horizontal pleiotropy of the results were evaluated through various sensitivity analyses. Additionally， the false discovery rate （FDR） was applied to correct type Ⅰ errors caused by multiple hypothesis testing. Finally， MR mediation analysis was conducted to test the potential mediating effect of blood metabolites. RESULTS The s_ Bilophila was negatively associated with the effectiveness of antidepressant treatment （ P ＝8.030×10 －5 ， then P ＝0.033 after FDR correction）， and the f_Bacteroidales was positively associated with the effectiveness of antidepressant treatment （ P ＝3.275×10 －4 ， then P ＝0.034 after FDR correction）. Over a hundred blood metabolites were also screened out as being associated with antidepressant response， but after FDR correction， no significant causal relationship was observed. The P value of the mediation effect proportion of blood metabolites in the “gut microbiota-blood metabolites-antidepressant efficacy” pathway was greater than 0.05. CONCLUSIONS The s_ Bilophila may represent a risk factor for antidepressant effects， whereas the f_Bacteroidales may serve as a protective factor for antidepressant effects. The correlation between blood metabolites and antidepressant efficacy is not strong， and no genetic evidence is found to support that the investigated blood metabolites play a key mediating role between the gut microbiota and antidepressant response.

ObjectiveTo evaluate the efficacy and possible mechanism of Wei's Huoxue Tongluo Formula （韦氏活血通络方，WHTF） in treating atrophic-stage non-arteritic anterior ischemic optic neuropathy （NAION） with qi deficiency and blood stasis. MethodsA total of 82 atrophic-stage NAION patients with qi deficiency and blood stasis were randomly divided into a treatment group and a control group， with 41 cases in each group. The treatment group was given oral administration of WHTF twice a day plus acupoint injection of distilled water 2 ml at Taiyang （EX-HN5） once daily， while the control group received injection of compound anisodine injection 2 ml at Taiyang （EX-HN5） once daily and oral administration of WHTF placebo twice a day. Both groups received treatment for a course of 14 days. The best-corrected visual acuity （BCVA）， optic disc perfusion density （PD）， flux index （FI）， macular superficial PD， vascular density （VD）， and traditional Chinese medicine （TCM） syndrome scores were compared between groups before treatment and on day 7 and day 14 of treatment. Additionally， mean defect （MD） and mean sensitivity （MS） of visual fields were measured before treatment and on day 14， along with safety evaluation. ResultsAfter treatment， both groups showed significant improvement in BCVA， visual field MD and MS， and TCM syndrome scores （P＜0.05 or P＜0.01）. On day 14 of treatment， the TCM syndrome score in the treatment group was significantly lower than that in the control group （P＜0.05）. There was no significant improvement in optic disc PD and FI， and macular superficial PD and VD after treatment in either group （P＞0.05） except that on day 7 the macular superficial foveal PD in the control group was significantly better than that in the treatment group （P＜0.05）. During the treatment period， no serious adverse events occurred in either group. ConclusionWHTF can improve the visual function indicators including visual acuity and visual field， as well as TCM syndrome scores in atrophic-stage NAION patients with qi deficiency and blood stasis. It shows clinical safety， although it does not appear to have a significant effect on optic disc or macular blood flow.

Objective The relationship between blood pressure variability(BPV)and short-term neurological prognosis in patients with aneurysmal subarachnoid hemorrhage(aSAH)was investigated.Methods The study conducted a retrospective analysis of clinical data from aSAH patients who underwent surgical treatment and were admitted to the ICU at Beijing Tiantan Hospital,Capital Medical University,from January 2023 to April 2024.BPV was quantitively assessed by calculating the standard deviation(SD),successive variation(SV),coefficient of variation(CV),and range of mean blood pressure(MBP).Patients were divided into two group based on discharge GOS scores:good prognosis[Glasgow Outcome Scale(GOS)4-5]and poor prognosis(GOS 1-3)groups.Comparative analyses were performed to evaluate differences in BPV metrics between the two groups,followed by multivariable logistic regression modeling to adjust for potential confounding factors and elucidate the association between BPV and clinical prognosis.Results A total of 150 patients were included,with 59 in the poor prognosis group and 91 in the good prognosis group.The poor prognosis group exhibited significantly elevated levels of MBP-SD[(9.85±3.20)mmHg vs.(8.04±2.31)mmHg,P<0.001],MBP-SV[(10.37±3.85)mmHg vs.(8.07±2.33)mmHg,P<0.001],MBP-CV(10.00±3.30%vs.8.19±2.33%,P<0.001),and MBP-range[(39.60±13.56)mmHg vs.(32.44±9.78)mmHg,P<0.05]compared to the good prognosis group.Cohen’s d values indicated moderate effect sizes for BPV differences(0.65,0.72,0.63,and 0.61,respectively).Multivariable logistic regression showed that MBP-SD(OR=1.22,95%CI:1.08-1.39,P=0.002)and MBP-SV(OR=1.19,95%CI:1.05-1.35,P=0.007)were independently associated with poor prognosis.Conclusion Elevated MBP-SD and MBP-SV within the first 24 hours postoperative period are independent predictors of unfavorable short-term neurological outcomes in aSAH patients.

Objective:To explore the risk fall death associated with compound hot extremes.Methods:This study collected data on fall deaths in Guangdong, Hunan, and Zhejiang Provinces from 2013 to 2018 and matched their exposure to meteorological data. Based on a time-stratified case-crossover design, a conditional logistic regression model embedded with a cross-basis function of the distributed lag nonlinear model was applied to estimate the risk of fall to death due to compound hot extremes.Results:Compared with regular days, compound hot extremes significantly increased the risk of death from falls ( OR=1.19, 95% CI: 1.09-1.30), and women ( OR=1.27, 95% CI: 1.11-1.45) and the elderly age 65 and above ( OR=1.24, 95% CI: 1.12-1.39) were more sensitive to compound hot extremes. The maximum duration of compound hot extremes was 7 days, and the maximum intensity was 6.2 ℃, and the duration and intensity were proportional to the risk of death from falls. The risk of death from falls increased by 12% ( OR=1.12, 95% CI: 1.06-1.18) each day, increasing in duration after linearization. The risk of death from falls increased by 16% ( OR=1.16, 95% CI: 1.10-1.22) for each 1 ℃ increase in linearized intensity. Conclusion:Compound hot extremes increase the risk of death cases from falls.

Objective To investigate the effect of Lianpu Yin on duodenal microinflammation in rats with functional dyspepsia(FD)by regulating NLRP3 activation.Methods Wistar rats were randomly divided into blank group and model group.FD rats were reconstructed by iodoacetamide method(2%sucrose solution containing 0.1%iodoacetamide),and the model was verified.FD model rats were randomly divided into model group,Lianpu Yin group and Moxapride group by random number expression method.After a period of two weeks of administration,measurements were taken to determine the body mass,three-hour food consumption,as well as the rates of gastric emptying and intestinal propulsion.The pathological structure of duodenal tissue was observed by HE staining.The serum levels of IL-1β and IL-18 were quantified using the enzyme-linked immunosorbent assay(ELISA)method.The expression levels of NLRP3 and Caspase-1 in each group were detected by Western blot.Expression levels of NLRP3 and Caspase-1 proteins were detected by immunofluorescence.Results Compared with the blank group,body weight,food intake at 3 h,gastric emptyand intestinal propulsion rate in model group were significantly decreased(P<0.01),and inflammatory infiltration of duodenum tissue appeared in the model group.Meanwhile,the expressions of NLRP3 and Caspase-1 proteins,as well as the levels of IL-1β and IL-18 in the duodenal tissue of the model group,showed significant increasing(P<0.05).Compared with the model group,rats in the Lianpu Yin and Moxapride groups displayed significant increasing in body weight,gastric emptying rate,and intestinal propulsion rate(P<0.01).Additionally,inflammatory infiltration of duodenum tissue reduced in these groups.Furthermore,NLRP3 and Caspase-1 protein expressions,as well as IL-1β and IL-18 levels,significantly decreased in the Lianpu Yin and Moxapride groups compared to the model group(P<0.05).Conclusion Lianpu Yin can treat FD rats by inhibiting duodenal microinflammation and then restoring gastrointestinal motility,which may be related to the abnormal activation of NLRP3 inflammasome.

OBJECTIVE: The investigation of the correlation between ecological factors and the genetic characteristics or metabolites of plants offers valuable insights into the regional causes of genetic and metabolic diversity. Here, Gastrodia elata, a medicinal plant, is employed as a model to explore the environmental factors that influence its genetic characteristics and metabolic accumulations. METHODS: A total of 23 G. elata populations from six cultispecies and 11 cultivated regions were selected based on the predictions of the global geographic information system. The genetic characteristics of these populations were evaluated using highly polymorphic simple sequence repeat markers. Additionally, the metabolic accumulations and antioxidant capacity of mature tubers were measured employing colorimetry and high performance liquid chromatography (HPLC). Ecological data of each region were obtained from the WorldClim-global climate database and harmonized world soil database. To assess the influence of ecological factors on the genetic characteristics and metabolic profiles of G. elata, Pearson's correlation analysis was conducted. RESULTS: Genetic variation among G. elata populations exceeded that within populations. Genetic diverisity, distance and structure manifested regional and species-specific patterns. Metabolic profiling and antioxidant capacity exhibited regional variations. Notably, the Lueyang region demonstrated that a content range of total polysaccharide, total protein, and phenolic glycosides was 9.34%-189.67% higher than the average. Similarly, in the Hubei region, total phenolic content, p-hydroxybenzyl alcohol content, and antioxidant indicators were observed to be higher than the average levels, by 106.57%, 136.47% and 12.50%-91.14%, respectively. Furthermore, ecological factors had a significant comprehensive impact on G. elata genetic characteristics (r > 0.256 and P < 0.05). Multivariate metabolite accumulations in G. elata were influenced by dominant ecological factors. Temperature notably impacted the accumulation of total protein (|r| > 0.528 and P < 0.05). Moisture, encompassing precipitation and soil content, significantly affected the production of phenolic glycosides (|r| > 0.503 and P < 0.05). CONCLUSION The genetic characteristics of G. elata manifested regional and species-specific patterns, with the metabolic accumulations and antioxidant capacity of mature tubers exhibited regional variations. Specifically, multivariate ecological factors comprehensively influenced genetic characteristics. Temperature and moisture played pivotal roles in regulating the accumulations of proteins and phenolic glycosides, respectively. These findings underscore the significant impact of ecological factors on the shaping of G. elata, highlighting their crucial role in enhancing the quality of Chinese medicinal materials.

OBJECTIVE: To investigate the frequency and related factors of ineffective triggering (IT) and double triggering (DT) in patients with acute brain injury undergoing invasive mechanical ventilation. METHODS: A retrospective cohort study was conducted using data from a single-center observational trial. Patients with acute brain injury [traumatic brain injury, stroke, and post-craniotomy for brain tumors] undergoing mechanical ventilation in the intensive care unit (ICU) of Beijing Tiantan Hospital, Capital Medical University between June 2017 and July 2019 were retrospectively analyzed. Demographic and clinical data were collected. Respiratory parameters and waveforms during the first 3 days of mechanical ventilation were recorded, with 15-minute waveform segments collected 4 times daily. Airway occlusion pressure (P_0.1) was measured via end-expiratory hold at the end of each recording. IT and DT were identified based on airway pressure, flow, and esophageal pressure waveforms, and the ineffective triggering index (ITI) and DT incidence were calculated. Multivariate Logistic regression was used to identify factors associated with IT and DT. RESULTS: A total of 94 patients with acute brain injury were ultimately enrolled, including 19 cases of traumatic brain injury (20.2%), 39 cases of stroke (41.5%), and 36 cases of post-craniotomy for brain tumor (38.3%). Supratentorial injury was observed in 49 patients (52.1%), while infratentorial injury was identified in 45 patients (47.9%). A total of 94 patients with 1 018 datasets were analyzed; 684 (67.2%) datasets were on pressure support ventilation (PSV), and 334 (32.8%) were on mandatory ventilation. IT was detected in 810 (79.6%) datasets, with a median incidence of 2.1% (0.3%, 12.0%). Datasets demonstrating IT were characterized by lower P_0.1, higher tidal volume (VT), reduced respiratory rate (RR), and decreased minute ventilation (MV) compared to those without IT. The proportion of datasets exhibiting IT was higher during PSV than in mandatory ventilation [83.8% (573/684) vs. 71.0% (237/334), P < 0.05], while, the prevalence of ITI ≥ 10% was lower [23.8% (163/684) vs. 33.5% (112/334), P < 0.05]. DT was detected in 305 datasets (30%), with a median incidence of 0.6% (0.4%, 1.3%). Datasets exhibiting DT were characterized by higher VT, reduced RR, and lower pressure support levels. The incidence of DT was lower in PSV compared to mandatory ventilation modes [0% (0%, 0.3%) vs. 0% (0%, 0.5%), P < 0.05]. The post-craniotomy for brain tumors group exhibited higher ITI, lower RR, reduced MV, and a greater proportion of infratentorial lesions, compared to the TBI group. The infratentorial lesion group demonstrated higher ITI and incidence of DT compared to the supratentorial lesion group [ITI: 3.1% (0.7%, 17.8%) vs. 1.5% (0%, 8.3%), incidence of DT: 0% (0%, 0.5%) vs. 0% (0%, 0%), both P < 0.05]. After adjusting for confounding factors through multivariate logistic regression analysis, infratentorial lesion [odds ratio (OR) = 2.029, 95% confidence interval (95%CI) was 1.465-2.811, P < 0.001], lower P_0.1 (OR = 0.714, 95%CI was 0.616-0.827, P < 0.001), and mandatory ventilation (OR = 1.613, 95%CI was 1.164-2.236, P = 0.004) were independently associated with IT. Additionally, infratentorial lesion (OR = 1.618, 95%CI was 1.213-2.157, P = 0.001), large tidal volume (OR = 1.222, 95%CI was 1.137-1.314, P < 0.001), lower pressure support levels (OR = 0.876, 95%CI was 0.829-0.925, P < 0.001), and mandatory ventilation (OR = 2.750, 95%CI was 1.983-3.814, P < 0.001) were independently associated with DT. CONCLUSION IT and DT were common in patients with acute brain injury. Infratentorial lesions and mandatory ventilation were independently associated with both IT and DT.
Humans ; Respiration, Artificial/methods* ; Retrospective Studies ; Brain Injuries/therapy* ; Intensive Care Units ; Male ; Female ; Middle Aged ; Brain Injuries, Traumatic/therapy* ; Logistic Models ; Aged ; Adult

OBJECTIVE: To investigate the potential mechanisms of sepsis pathogenesis in intensive care unit (ICU), with a specific focus on the role of skin microbiota, and to evaluate the causal relationships between skin microbiota and ICU sepsis using Mendelian randomization (MR). METHODS: A two-sample MR analysis was performed using skin microbiota genome-wide association study (GWAS) summary data from German population cohorts as exposures, combined with ICU sepsis susceptibility and 28-day mortality GWAS summary data from the IEU OpenGWAS database as outcomes. The primary causal effect estimates were generated using the inverse variance weighted (IVW) method, supplemented by validation through MR-Egger and weighted median approaches. Heterogeneity and pleiotropy tests, along with sensitivity analyses, were conducted to evaluate the robustness of the results. RESULTS: Regarding risk of ICU sepsis, IVW analysis showed that order Pseudomonadales [odds ratio (OR) = 0.93, 95% confidence interval (95%CI) was 0.88-0.98], family Flavobacteriaceae (OR = 0.93, 95%CI was 0.90-0.96), and genus Acinetobacter (OR = 0.96, 95%CI was 0.93-0.99) were significantly negatively correlated with the risk of ICU sepsis (all P < 0.05). There was a significant positive correlation between the risk of ICU sepsis and the presence of β-Proteobacteria (OR = 1.05, 95%CI was 1.00-1.11) and Actinobacteria (OR = 1.05, 95%CI was 1.00-1.11), both P < 0.05. Regarding 28-day mortality of ICU sepsis, IVW analysis showed that phylum Bacteroidetes (OR = 0.92, 95%CI was 0.86-0.99), family Streptococcaceae (OR = 0.92, 95%CI was 0.85-0.98), family Flavobacteriaceae (OR = 0.90, 95%CI was 0.83-0.97), genus Streptococcus (OR = 0.92, 95%CI was 0.86-0.99), ASV016 [Enhydrobacter] (OR = 0.92, 95%CI was 0.87-0.98), and ASV042 [Acinetobacter] (OR = 0.92, 95%CI was 0.88-0.97) were significantly negatively correlated with the 28-day mortality of ICU sepsis (all P < 0.05); family Moraxellaceae (OR = 1.09, 95%CI was 1.00-1.18) and ASV008 [Staphylococcus] (OR = 1.08, 95%CI was 1.03-1.14) was significantly positively correlated with the 28-day mortality of ICU sepsis (both P < 0.05). Sensitivity analysis and MR-PRESSO showed no heterogeneity, pleiotropy, or horizontal pleiotropy between skin microbiota and ICU sepsis risk and 28-day mortality rate. Analysis of confounding factors showed that single nucleotide polymorphisms (SNPs) associated with relevant skin bacteria could independently and causally affect the risk of ICU sepsis or ICU sepsis related mortality rate, independent of other confounding factors. The Steiger test results indicated that the established causal relationship was not due to reverse causality. CONCLUSIONS Skin microbiota composition may influence both sepsis susceptibility and 28-day mortality in ICU settings. Family Flavobacteriaceae demonstrated protective effects against sepsis onset and mortality. These findings provide new perspectives for early detection and management strategies.
Humans ; Sepsis/mortality* ; Intensive Care Units ; Mendelian Randomization Analysis ; Microbiota ; Skin/microbiology* ; Genome-Wide Association Study ; Risk Factors ; Skin Microbiome

Objective: To analyze the temporal variation patterns of sickness absenteeism among primary and secondary school students in Shanghai, so as to explore models suitable for predicting peaks and intensity of absenteeism rates. Methods: The seasonal and trend decomposition using loess (STL) method was used to analyze the seasonal and long term trend changes in sickness absenteeism among primary and secondary school students from September 1 in 2010 to June 30 in 2018, in Shanghai. A hierarchical clustering method based on Dynamic Time Warping (DTW) was employed to classify absenteeism symptoms with similar temporal patterns. Based on historical data, the study constructed and evaluated different time series algorithms and machine learning models to optimize the accuracy of predicting the trend of sickness absenteeism. Results: During the research period, the average new absenteeism rate due to illness was 16.86 per 10 000 person day for every academic year, and the trend of sickness absenteeism exhibited both seasonality and a long term upward trend, reaching its highest point in the 2017 academic year (22.47 per 10 000 person day). The symptoms of absenteeism were divided into three categories: high incidence in winter and spring (respiratory symptoms, fever and general discomfort, etc.), high incidence in summer (eye symptoms, nosebleeds, etc.) and those without obvious seasonality (skin symptoms, accidental injuries, etc.).The constructed time series models effectively predicted the trend of absenteeism due to illness, although the accuracy of predicting peak intensity was relatively low. Among them, the multi layer perceptron (MLP) model performed the best, with an root mean squared error (RMSE) of 8.96 and an mean absolute error (MAE) of 4.37, reducing 36.51% and 39.02% compared to the baseline model. Conclusion Time series models and machine learning algorithms could effectively predict the trend of sickness absenteeism, and corresponding prevention and control measures can be taken for absenteeism caused by different symptoms during peak periods.