Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

In this study, the pharmacokinetic characteristics and tissue distribution of cannabidiol(CBD)/γ-polyglutamic acid-g-cholesterol(γ-PGA-g-CHOL) nanomicelles [CBD/(γ-PGA-g-CHOL)NMs] were investigated by pharmacokinetic experiments, and the effect of CBD/(γ-PGA-g-CHOL)NMs on the lipopolysaccharide(LPS)-induced inflammatory damage of cells was evaluated by cell experiments. CBD/(γ-PGA-g-CHOL)NMs were prepared by dialysis. The CBD concentrations in the plasma samples of male SD rats treated with CBD and CBD/(γ-PGA-g-CHOL)NMs were investigated, and the pharmacokinetic parameters were calculated and compared. UPLC-MS/MS was employed to determine the concentration of CBD in tissue samples. The heart, liver, spleen, lung, kidney, and muscle samples were collected at different time points to explore the tissue distribution of CBD and CBD/(γ-PGA-g-CHOL)NMs. The Caco-2 cell model of LPS-induced inflammation was established, and the cell viability, transepithelial electrical resistance(TEER), and secretion levels of inflammatory cytokines were determined to compare the anti-inflammatory activity between the two groups. The results showed that CBD/(γ-PGA-g-CHOL)NMs had the average particle size of(163.1±2.3)nm, drug loading of 8.78%±0.28%, and encapsulation rate of 84.46%±0.35%. Compared with CBD, CBD/(γ-PGA-g-CHOL)NMs showed increased peak concentration(C_(max)) and prolonged peak time(t_(max)) and mean residence time(MRT_(0-t)). Within 24 h, the tissue distribution concentration of CBD/(γ-PGA-g-CHOL)NMs was higher than that of CBD. In addition, both CBD and CBD/(γ-PGA-g-CHOL)NMs significantly enhanced Caco-2 cell viability and TEER, lowered the secretion levels of inflammatory cytokines, and alleviated inflammation. Moreover, CBD/(γ-PGA-g-CHOL)NMs demonstrated stronger anti-inflammatory effect. It can be inferred that γ-PGA-g-CHOL blank nanomicelles are good carriers of CBD, being capable of prolonging the circulation time of CBD in the blood, improving the bioavailability and tissue distribution concentration of CBD, and protecting against LPS-induced inflammatory injury. The findings can provide an experimental basis for the development and clinical application of oral CBD preparations.
Animals ; Cannabidiol/administration & dosage* ; Polyglutamic Acid/analogs & derivatives* ; Humans ; Male ; Rats ; Rats, Sprague-Dawley ; Anti-Inflammatory Agents/administration & dosage* ; Micelles ; Caco-2 Cells ; Cholesterol/pharmacokinetics* ; Tissue Distribution ; Nanoparticles/chemistry*

OBJECTIVE: Humans are exposed to complex mixtures of environmental chemicals and other factors that can affect their health. Analysis of these mixture exposures presents several key challenges for environmental epidemiology and risk assessment, including high dimensionality, correlated exposure, and subtle individual effects. METHODS: We proposed a novel statistical approach, the generalized functional linear model (GFLM), to analyze the health effects of exposure mixtures. GFLM treats the effect of mixture exposures as a smooth function by reordering exposures based on specific mechanisms and capturing internal correlations to provide a meaningful estimation and interpretation. The robustness and efficiency was evaluated under various scenarios through extensive simulation studies. RESULTS: We applied the GFLM to two datasets from the National Health and Nutrition Examination Survey (NHANES). In the first application, we examined the effects of 37 nutrients on BMI (2011-2016 cycles). The GFLM identified a significant mixture effect, with fiber and fat emerging as the nutrients with the greatest negative and positive effects on BMI, respectively. For the second application, we investigated the association between four pre- and perfluoroalkyl substances (PFAS) and gout risk (2007-2018 cycles). Unlike traditional methods, the GFLM indicated no significant association, demonstrating its robustness to multicollinearity. CONCLUSION GFLM framework is a powerful tool for mixture exposure analysis, offering improved handling of correlated exposures and interpretable results. It demonstrates robust performance across various scenarios and real-world applications, advancing our understanding of complex environmental exposures and their health impacts on environmental epidemiology and toxicology.
Humans ; Environmental Exposure/analysis* ; Linear Models ; Nutrition Surveys ; Environmental Pollutants ; Body Mass Index

Objective To establish the pharmacokinetic model of linezolid in neonates,and to optimize the administration regimen. Methods A prospective study was conducted among 64 neonates with sepsis who received linezolid as anti-infective therapy,and liquid chromatography-tandem mass spectrometry was used to measure the plasma concentration of the drug. Clinical data were collected,and nonlinear mixed effects modeling was used to establish a population pharmacokinetic (PPK) model. Monte Carlo simulation and evaluation was performed for the optimal administration regimen of children with different features. Results The pharmacokinetic properties of linezolid in neonates could be described by a single-compartment model with primary elimination,and the population typical values for apparent volume of distribution and clearance rate were 0.79 L and 0.34 L/h,respectively. The results of goodness of fit,visualization verification,and the Bootstrap method showed that the model was robust with reliable results of parameter estimation and prediction. Monte Carlo simulation results showed that the optimal administration regimen for linezolid in neonates was as follows:6 mg/kg,q8h,at 28 weeks of gestational age (GA);8 mg/kg,q8h,at 32 weeks of GA;9 mg/kg,q8h,at 34-37 weeks of GA;11 mg/kg,q8h,at 40 weeks of GA. Conclusions The PPK model established in this study can provide a reference for individual administration of linezolid in neonates. GA and body weight at the time of administration are significant influencing factors for the clearance rate of linezolid in neonates.

To address the issue of peak loss when applying variational mode decomposition(VMD)to denoise spectra with sharp peaks,in this study,a method for spectral signal denoising of complex samples called peak extraction variational mode decomposition(PE-VMD)was introduced.Firstly,the spectral signal was subjected to a process of denoising utilising the VMD algorithm.Next,the first order derivatives of the spectral signals were calculated to determine the peak center.Subsequently,the second order derivatives of the spectral signal was calculated to extract the sharp peaks with high signal-to-noise ratio(SNR).Finally,the peak intercepted that lose information after VMD denoising were removed,and the remaining spectrum was sequentially connected with the extracted sharp peaks to obtain the final denoised spectrum.The effectiveness of the method was evaluated by one of simulated signals and X-ray diffraction(XRD)spectrum of MnCo-ISAs/CN catalysts.Furthermore,the method was compared with other denoising techniques,including Savitzky-Golay(SG)smoothing,empirical mode decomposition(EMD)and VMD.The efficacy of the denoising process was then assessed by analyzing the spectrograms and signal-to-noise ratio before and after denoising.The results demonstrated that PE-VMD denoising achieved the greatest SNR and effectively preserved the essential information of the spectral signals.Consequently,PE-VMD exhibited superior denoising capability for spectra with sharp peaks.

Objective To compare the pharmacokinetic profiles of the two teriflunomide tablets in healthy Chinese subjects under fasting and fed conditions and to evaluate their bioequivalence and safety.Methods A randomized,open,single-dose,parallel trial design was used to enroll 31 and 32 healthy Chinese male subjects in the fasting and fed groups,who were randomized to a single oral dose of 14 mg of either reference or test preparation of teriflunomide tablets.The plasma concentrations of teriflunomide were determined using liquid chromatography-tandem mass spectrometry method,and Phoenix WinNonlin 8.1 software was used to calculate pharmacokinetic parameters and perform bioequivalence analysis.Results Subjects received a single oral dose of the reference and test formulations of teriflunomide.The main pharmacokinetic parameters of teriflunomide in the fasting group were as follows:Cmax were(2.14±0.27)and(2.27±0.33)μg·mL-1,AUC0-72h were(105.70±11.20)and(107.72±11.77)μg·mL-1·h,tmax was 1.49 and 0.99 h;the main pharmacokinetic parameters of teriflunomide in the fed group were as follows:Cmaxwere(1.83±0.17)and(1.75±0.22)μg·mL-1,AUC0-72h were(102.66±9.18)and(101.57±13.01)μg·mL-1·h,tmax was 4.01 and 4.99 h.The 90％confidence intervals for the geometric means of Cmax and AUC0-72h for reference and test preparations in the fasting and fed groups were in the range of 80％to 125％.Conclusion The pharmacokinetic characteristics of the 2 formulations were similar under fasting and fed administration conditions,with good bioequivalence and safety;Postprandial administration may delay the time to peak of the drug.

Objective This study aimed to investigate the potential relationship between urinary metals copper (Cu), arsenic (As), strontium (Sr), barium (Ba), iron (Fe), lead (Pb) and manganese (Mn) and grip strength. Methods We used linear regression models, quantile g-computation and Bayesian kernel machine regression (BKMR) to assess the relationship between metals and grip strength.Results In the multimetal linear regression, Cu (β=-2.119), As (β=-1.318), Sr (β=-2.480), Ba (β=0.781), Fe (β= 1.130) and Mn (β=-0.404) were significantly correlated with grip strength (P < 0.05). The results of the quantile g-computation showed that the risk of occurrence of grip strength reduction was -1.007 (95％ confidence interval:-1.362, -0.652; P < 0.001) when each quartile of the mixture of the seven metals was increased. Bayesian kernel function regression model analysis showed that mixtures of the seven metals had a negative overall effect on grip strength, with Cu, As and Sr being negatively associated with grip strength levels. In the total population, potential interactions were observed between As and Mn and between Cu and Mn (Pinteractions of 0.003 and 0.018, respectively).Conclusion In summary, this study suggests that combined exposure to metal mixtures is negatively associated with grip strength. Cu, Sr and As were negatively correlated with grip strength levels, and there were potential interactions between As and Mn and between Cu and Mn.

Objective:To investigate the spectrum and antimicrobial resistance of major pathogens causing nosocomial infections in China during 2020-2021.Methods:A total of 1 311 non-duplicated nosocomial pathogens causing bloodstream infections (BSI, n=670), hospital-acquired pneumonia (HAP, n=394) and intra-abdominal infections (IAI, n=297) were collected from 10 teaching hospitals across China. The minimum inhibitory concentrations (MICs) of clinical common strains were determined using agar dilution or broth microdilution method. Interpretation of reults followed the CLSI M100-Ed33 criteria, with data analysis conducted using WHONET-5.6 software. The Chi-square test was used to compare rates. Results:The most prevalent pathogens causing BSI were Escherichia coli (21.2%, 142/670), Klebsiella pneumoniae (14.9%, 100/670) and Staphylococcus aureus (11.5%, 77/670); the most prevalent pathogens causing HAP were K. pneumoniae (27.7%, 109/394), Acinetobacter baumanii (22.1%, 87/394) and Pseudomonas aeruginosa (18.3%, 72/394). IN IAI, E. coli (24.3%, 60/247), Enterococcus faecium and K. pneumoniae (both 14.6%, 36/247) were dominated. All S. aureus strains were susceptible to tigecycline, linezolid, daptomycin and glycopeptides. Rates of methicillin-resistant S. aureus (MRSA) and coagulase-negative Staphylococcus (MRCNS) were 36.5% (42/115) and 74.5% (38/51), respectively. The rate of vancomycin-resistant E. faecium and E. faecalis was 3.3% (3/90) and 1.9% (1/53), respectively. The prevalence of extended-spectrum β-lactamase (ESBL) was 23.7% (58/245) in K. pneumonia and 60.5% (130/215) in E. coli.The rate of carbapenem-resistant K. pneumonia and E. coli was 29.8% (73/245) and 4.2% (9/215), respectively; the percentage of tigecycline-resistant K. pneumonia and E. coli was 1.6% (4/245) and 0, respectively; the rate of colistin-resistant K. pneumonia and E. coli was 1.6% (4/245) and 2.8% (6/215), respectively; the percentage of ceftazidime/avibactam-resistant K. pneumonia and E. coli was 2.0% (5/245) and 2.3% (5/215), respectively. The rate of carbapenem-resistant A. baumanii and P. aeruginosa was 76.7% (125/163) and 28.4% (33/116), respectively. A. baumanii showed low susceptibility to most antimicrobial agents except colistin (98.8%, 161/163) and tigecycline (89.6%, 146/163). Colistin, amikacin and ceftazidime/avibactam demonstrated high antibacterial activity against P. aeruginosa with susceptility rates of 99.1% (115/116), 94.0% (109/116) and 83.6% (97/116), respectively. Conclusions:The major pathogens of nosocomial infections were K. pneumonia, E. coli, A. baumanii, P. aeruginosa and S. aureus. Nosocomial Gram-negative pathogens exhibited high susceptibilities to tigecycline, colistin and ceftazidime/avibactam. Antimicrobial resistance in A. baumannii remains a significant challenge. The increasing prevalence of carbapenem-resistant Enterobacterales underscores the urgency of antibiotics rational applications and hospital infection controls.