Miracle-dz/UniFAR-FTUs huggingface dataset:
Population pharmacokinetic model of cefepime for critically ill adults: a comparative assessment of eGFR equations

ABSTRACT Cefepime exhibits highly variable pharmacokinetics in critically ill patients. The purpose of this study was to develop and qualify a population pharmacokinetic model for use in the critically ill and investigate the impact of various estimated glomerular filtration rate (eGFR) equations using creatinine, cystatin C, or both on model parameters. This was a prospective study of critically ill adults hospitalized at an academic medical center treated with intravenous cefepime. Individuals with acute kidney injury or on kidney replacement therapy or extracorporeal membrane oxygenation were excluded. A nonlinear mixed-effects population pharmacokinetic model was developed using data collected from 2018 to 2022. The 120 included individuals contributed 379 serum samples for analysis. A two-compartment pharmacokinetic model with first-order elimination best described the data. The population mean parameters (standard error) in the final model were 7.84 (0.24) L/h for CL1 and 15.6 (1.45) L for V1. Q was fixed at 7.09 L/h and V2 was fixed at 10.6 L, due to low observed interindividual variation in these parameters. The final model included weight as a covariate for volume of distribution and the eGFRcr-cysC (mL/min) as a predictor of drug clearance. In summary, a population pharmacokinetic model for cefepime was created for critically ill adults. The study demonstrated the importance of cystatin C to prediction of cefepime clearance. Cefepime dosing models which use an eGFR equation inclusive of cystatin C are likely to exhibit improved accuracy and precision compared to dosing models which incorporate an eGFR equation with only creatinine.
Association between the ratio of serum creatinine to cystatin C and bone mineral density in middle-aged and older adults: a cross-sectional study from NHANES database

Objective To investigate the association between creatinine to cystatin C ratio (CCR) and bone mineral density (BMD) in middle-aged and older adults. Methods This cross-sectional study investigated participants aged 50–85, using National Health and Nutrition Examination Survey (NHANES) data from 1999 to 2002. The correlation between CCR and total BMD was assessed by multivariate linear regression models, using stratified analysis by age, sex and race (Mexican American, other Hispanic, non-Hispanic White, non-Hispanic Black, and other race) to distinguish various special populations. Results Among 2992 patients, multiple regression models revealed a significant positive correlation between CCR and total BMD: model 1, 0.030 (95% confidence interval [CI] 0.029, 0.031); model 2, 0.009 (95% CI 0.008, 0.010); model 3, 0.010 (95% CI 0.009, 0.013). After controlling for all covariates, a positive correlation was observed between CCR and total BMD in both men and women, and was further strengthened in older age groups. When stratifying by race, the positive correlation was most significant among ‘other Hispanic’ participants; there was no significant correlation among those of ‘other race’. Conclusions A positive correlation was demonstrated between CCR and total BMD in middle-aged and older adults aged 50–85 years, with the most significant positive correlation in the older ‘other Hispanic’ population. No significant correlation was observed among participants of ‘other race’.
Efficacy and safety of monoclonal antibodies targeting CGRP in migraine prevention. GRADE tables elaborated by the ad hoc working group of the International Headache Society

Abstract Objectives Grading of Recommendations, Assessment Development and Evaluation (GRADE) tables were created using a standardized and independent assessment of the efficacy and side effects of treatments with monoclonal antibodies (mAb) against calcitonin gene-related peptide (CGRP) or the CGRP receptor for the prevention of migraine. We hope to provide support for author groups writing national or regional treatment or management guidelines for migraine prevention. Methods We formulated patient/population, intervention, comparison and outcomes (PICO) questions for the efficacy and safety of mAb against CGRP or the CGRP-receptor for the prevention of migraine attacks. We performed a systematic literature research for randomized studies with eptinezumab, erenumab, fremanezumab and galcanezumab and a pooled analysis was done, using RevMan 5.4 software. For dichotomous outcomes we used risk ratio, and for continuous outcomes we used the mean difference to compare and summarize the evidence between groups. The evidence across studies, for each outcome, except serious adverse events, was assessed using GRADE evidence tables. Additionally, we report the serious adverse effects in the tables of the characteristics of the studies. Results All mAb are superior to placebo for the reduction in monthly migraine days (days in which a headache consistent with migraine occurred) in participants with episodic and chronic migraine. There are no major differences between the mAb. Conclusions The GRADE evidence summary tables provided will support author groups to write treatment guidelines for the prevention of migraine with mAb.
Pharmacokinetic Models Scaled Up from Humanized Liver Mouse Data Can Account for Drug Monitoring Results of Atomoxetine and Its 4-Hydroxylated and N-Demethylated Metabolites in Pediatric Patients Genotyped for Cytochrome P450 2D6

Atomoxetine is a cytochrome P450 (P450) 2D6 probe substrate and an approved medicine for attention deficit/hyperactivity disorder. In this humanized liver mouse study, interactions between atomoxetine and the P450 2D6 probe drug paroxetine were observed. Human physiologically based pharmacokinetic (PBPK) models were established by scaling up humanized liver mouse data obtained in the absence or presence of paroxetine. These models could explain the drug monitoring results of atomoxetine and its primary 4-hydroxylated and N-demethylated metabolites in Japanese children aged 8–14 years and could be used to help establish the correct dosage and for the evaluation of clinical outcomes. The results of simple PBPK models (using input parameters that reflected the subjects’ small body size and normal or reduced P450 2D6–dependent clearance) were in general agreement with one-point measured plasma concentrations of atomoxetine and its 4-hydroxylated and N-demethylated metabolites in 13 pediatric participants. Unexpectedly high hepatic exposure, possibly in intermediate-metabolizer patients harboring CYP2D6*10 or 2D6*36 alleles, might in part explain the adverse effects of atomoxetine prescribed alone recorded in a Japanese adverse-event database. The steady-state, one-point drug monitoring data from the participants indicated extensive biotransformation of atomoxetine to 4-hydroxyatomoxetine under individually prescribed doses of atomoxetine. These results also suggest that a relatively narrow range of 4-hydroxyatomoxetine and N-desmethylatomoxetine concentration ratios in spot urine and/or plasma samples from pediatric patients could be a simple semiquantitative determinant factor for P450 2D6 intermediate metabolizers compared with the wide range of concentrations of the two primary metabolites and substrate in extensive metabolizers. SIGNIFICANCE STATEMENT Validated simple pharmacokinetic models can predict steady-state plasma concentrations of the approved medicine atomoxetine and its primary metabolites in the majority of pediatric patients. The package insert advises careful dose escalation, especially for poor metabolizers; however, no simple way exists to determine cytochrome P450 (P450) 2D6 phenotypes. A relatively narrow range ratio of 4-hydroxyatomoxetine and N-desmethylatomoxetine in spot urine/plasma samples could be a simple semiquantitative determinant factor for P450 2D6 intermediate metabolizers to optimize or confirm the correct dosage.
Emerging pharmacotherapies for the treatment of pulmonary arterial hypertension

ABSTRACT Introduction Pulmonary arterial hypertension (PAH) is a progressive and life-threatening disease. Approved treatment options currently primarily target abnormal cell signaling pathways involved in vasoconstriction and proliferation, such as those mediated by prostacyclin, cyclic guanosine monophosphate, and endothelin. Areas covered Recent advancements have led to new applications and modes of delivery of currently approved PAH medications. At the same time, novel drugs targeting specific molecular pathways involved in PAH pathogenesis have been developed and are being investigated in clinical trials. This review summarizes investigational drug trials for PAH gathered from a comprehensive search using PubMed and ClinicalTrials.gov between 2003 and 2023. It includes both currently approved medications studied at different doses or new administration forms and experimental drugs that have not yet been approved. Expert opinion Approved treatments for PAH target imbalances in pulmonary vasoactive pathways that work primarily on enhancing pulmonary vasodilation with less salient effects on pulmonary vascular remodeling. The advent of more locally acting inhaled medications offers additional therapeutic options that may improve the ease of drug delivery and reduce adverse systemic effects. The more recent emphasis on developing and applying therapeutics that directly impact the aberrant signaling pathways implicated in PAH appears more likely to advance the treatment of this devastating disease.
Feasibility of Different Exercise Modalities for Community-Dwelling Residents With Physical Inactivity: A Randomized Controlled Trial

ABSTRACT Background Exercise interventions can promote health, but they can be difficult to implement. Moreover, no consensus has been reached regarding which exercise modality promotes the most significant improvement in metabolic health. Purpose This feasibility study was conducted to (a) determine the implementation efficacy of supervised and home-based exercise interventions by investigating their respective rates of intervention adherence, adherence to targeted intensity, attrition, and adverse events and (b) explore the preliminary efficacy of 12-week exercise programs among aerobic exercise, aerobic exercise combined with resistance exercise, and high-intensity interval training on body composition, anthropometric parameters, and lipid profiles for community-dwelling residents with physical inactivity. Methods This randomized controlled trial was conducted from April to October 2020. Seventy-two sedentary participants aged 40–70 years were enrolled and randomized into one of four groups: 12-week aerobic exercise, aerobic exercise combined with resistance exercise, high-intensity interval training, and control. The three exercise groups performed at least moderate-intensity supervised exercise twice a week and home-based exercise once a week, whereas the control group maintained their usual daily activities. The target variables, including body composition, anthropometric parameters, and lipid profiles, were measured before and after the 12-week intervention. Results The intervention adherence rates were 74.01%–87.54% for the supervised exercise group, 64.98%–83.90% for the home-based exercise group, and 82.65%–92.65% for the target exercise intensity group. The attrition rate ranged from 12.50% to 17.65%, and no adverse events were reported in any of the exercise groups. Preliminary efficacy data show the reductions in body weight (95% CI [0.01, 1.20], p = .048) and low-density lipoprotein (95% CI [2.76, 30.32], p = .02) were greater in the exercise groups than the control group, although the intergroup differences were not significant. Conclusions/Implications for Practice Body weight and low-density lipoprotein may be efficiently reduced in a 12-week period using any of the three exercise modalities with at least 82.65% adherence to moderate-intensity exercise and 70.84% adherence to exercising 3 times a week.
Memory error speed predicts subsequent accuracy for recognition misses but not false alarms

ABSTRACT The current study aims to test whether faster recognition memory errors tend to result from stronger misleading retrieval, making them harder to correct in subsequent decisions than slower errors, and whether this pattern holds for both miss and false-alarm errors. We used a paradigm in which each single-item Old/New recognition decision was followed by a two-alternative forced-choice (2AFC) test between a target and a lure. Each 2AFC trial had one item that had just been tested for an Old/New judgment and one item that had not been previously tested. Across 183 participants, the RTs for single-item recognition errors were used to predict accuracy in the 2AFC test using a hierarchical logistic regression model. The results showed a relationship between error RT and subsequent 2AFC accuracy that was qualified by an interaction with error type. Slower miss responses were more likely to be corrected than faster misses, but no accuracy differences were observed between slower and faster false alarms. The implications of these findings are discussed as they relate to assumptions about memory processes underlying inaccurate retrieval, using the diffusion model and the two-high-threshold model as examples of accounts that explain errors in terms of misleading retrieval and failed retrieval, respectively.
Temporal Generalizability of Machine Learning Models for Predicting Postoperative Delirium Using Electronic Health Record Data: Model Development and Validation Study

Background Although machine learning models demonstrate significant potential in predicting postoperative delirium, the advantages of their implementation in real-world settings remain unclear and require a comparison with conventional models in practical applications. Objective The objective of this study was to validate the temporal generalizability of decision tree ensemble and sparse linear regression models for predicting delirium after surgery compared with that of the traditional logistic regression model. Methods The health record data of patients hospitalized at an advanced emergency and critical care medical center in Kumamoto, Japan, were collected electronically. We developed a decision tree ensemble model using extreme gradient boosting (XGBoost) and a sparse linear regression model using least absolute shrinkage and selection operator (LASSO) regression. To evaluate the predictive performance of the model, we used the area under the receiver operating characteristic curve (AUROC) and the Matthews correlation coefficient (MCC) to measure discrimination and the slope and intercept of the regression between predicted and observed probabilities to measure calibration. The Brier score was evaluated as an overall performance metric. We included 11,863 consecutive patients who underwent surgery with general anesthesia between December 2017 and February 2022. The patients were divided into a derivation cohort before the COVID-19 pandemic and a validation cohort during the COVID-19 pandemic. Postoperative delirium was diagnosed according to the confusion assessment method. Results A total of 6497 patients (68.5, SD 14.4 years, women n=2627, 40.4%) were included in the derivation cohort, and 5366 patients (67.8, SD 14.6 years, women n=2105, 39.2%) were included in the validation cohort. Regarding discrimination, the XGBoost model (AUROC 0.87-0.90 and MCC 0.34-0.44) did not significantly outperform the LASSO model (AUROC 0.86-0.89 and MCC 0.34-0.41). The logistic regression model (AUROC 0.84-0.88, MCC 0.33-0.40, slope 1.01-1.19, intercept –0.16 to 0.06, and Brier score 0.06-0.07), with 8 predictors (age, intensive care unit, neurosurgery, emergency admission, anesthesia time, BMI, blood loss during surgery, and use of an ambulance) achieved good predictive performance. Conclusions The XGBoost model did not significantly outperform the LASSO model in predicting postoperative delirium. Furthermore, a parsimonious logistic model with a few important predictors achieved comparable performance to machine learning models in predicting postoperative delirium.
Burn injuries in KwaZulu-Natal Province, South Africa: Quantifying the healthcare burden.

BACKGROUND Most burn injuries occur in low- and middle-income countries (LMICs) and affect those of lower socioeconomic status disproportionally. A multifaceted approach is needed to improve burn outcomes. Healthcare strategies and reform should be data driven, but South Africa (SA) currently lacks sufficient baseline data related to burn injuries. The absence of local data is compounded by a global lack of published data from LMIC settings. The Pietermaritzburg Burn Service Registry (PBSR) is the only established registry for burn injuries in SA. OBJECTIVES To use the high-quality, detailed data from the PBSR to estimate the KwaZulu-Natal (KZN) provincial burden of burns in terms of length of stay, need for surgery and mortality. Our broader aim is to quantify the magnitude of the problem to highlight the need for specific burn care strategies in SA. METHODS We conducted an observational, retrospective review of burns data from two databases, the District Health Information System (DHIS) between 2013 and 2018, and the more detailed PBSR between 2016 and 2019. We compared the distribution of mild, moderate and severe injuries as well as the distribution of adult and paediatric admissions between the DHIS and PBSR data sets. We then assumed that outcomes for the province would follow similar patterns to the Pietermaritzburg Burn Service and applied the proportions to the DHIS data set to estimate the annual provincial burden. RESULTS In the DHIS, there was an annual mean (standard deviation (SD)) of 4 807 (760) children (age ≤12 years) and 3 622 (588) adults (age >12 years) admitted to hospitals in KZN with burn injuries. Annual average injury severity was 76.0% mild (mean (SD) n=5 539 (1 112.4)), 19.8% moderate (n=1 441 (148.8)) and 4.2% severe (n=312 (24.5)). These proportions were similar in the PBSR. Projections estimate that 2 967 patients would need surgery, with 212 500 hospital days required annually in the province. Additionally, provincial mortality would be 586 patients, including 84% with burns of mild and moderate severity. These deaths are potentially preventable. CONCLUSION There is a significant, unquantified burden of burn injury in KZN, highlighting the urgent need for development of specialised surgical services for burns. Collection of more robust national data to verify our projections is required to confirm the need and guide required healthcare reform.
Comparison between Weibull and gamma distributions to derive synthetic unit hydrograph using Horton ratios

The two‐parameter Weibull distribution (2PWD), similar to an instantaneous unit hydrograph (IUH), is parameterized in terms of Horton catchment ratios on the basis of a geomorphologic model of catchment response. For this the shape and scale parameters of the Weibull distribution are expressed analytically in terms of Horton's catchment ratios. The two parameters of the IUH derived using Nash's model, which is a two‐parameter gamma distribution (2PGD), are also expressed analytically in terms of Horton ratios. The performance of the proposed methods is tested for describing a synthetic unit hydrograph (SUH) under limited data conditions. A comparison is made with the unit hydrographs derived from the event data of two real catchments, and with the existing geomorphological based 2PGD for developing SUH given by Rosso (1984). The sensitivity analysis of the 2PWD to the nondimensional parameter β of the UH (a product of peak discharge and time to peak) shows β to be more sensitive to the shape parameter a than the scale parameter b. Further examination to find any similarity between the behavior of 2PWD and 2PGD showed that a in 2PWD corresponds to the shape parameter n in the 2PGD, and b behaves similar to the scale parameter k in the 2PGD. Finally, practical applicability of the proposed approach to ungauged catchments is tested using field data.
Toll‐like receptor 9 signaling in chronic lymphocytic leukemia cell lines

Chronic lymphocytic leukemia (CLL) is a prototypic neoplasia in which malignant cells strongly depend on microenvironmental stimulations in the lymphoid tissues where they accumulate; leukemic cells are exposed to interaction with bystander and accessory cells, as well as inflammatory soluble mediators. Cell lines are frequently used to model the pathobiology of this disease; however, they do not always recapitulate leukemic cell growth and response to stimulation, and no data are available on Toll‐like receptors (TLR) signaling in CLL cell lines. To address this gap, we analyzed HG3, MEC2, and PCL12 cell lines, before and after CpG stimulation, by RNA‐sequencing followed by bioinformatic analyses and validation experiments. We identified NFKBIZ mRNA and the corresponding IkBz protein as robust markers of TLR9 activation in both MEC2 and PCL12, but not in HG3 cells. Next, we compared our current results with previous results obtained with primary CLL patient samples and were able to conclude that MEC2 is most similar to the patients' cells in terms of global responsiveness to TLR stimulation; in particular, MEC2 better resembles the samples of patients, as it is characterized by high expression levels of IkBz, but with a lower number of genes regulated.
Elevated 4R tau contributes to endolysosomal dysfunction and neurodegeneration in VCP-related frontotemporal dementia

Abstract Frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS) are two incurable neurodegenerative diseases that exist on a clinical, genetic and pathological spectrum. The VCP gene is highly relevant, being directly implicated in both FTD and ALS. Here, we investigate the effects of VCP mutations on the cellular homoeostasis of human induced pluripotent stem cell-derived cortical neurons, focusing on endolysosomal biology and tau pathology. We found that VCP mutations cause abnormal accumulation of enlarged endolysosomes accompanied by impaired interaction between two nuclear RNA binding proteins: fused in sarcoma (FUS) and splicing factor, proline- and glutamine-rich (SFPQ) in human cortical neurons. The spatial dissociation of intranuclear FUS and SFPQ correlates with alternative splicing of the MAPT pre-mRNA and increased tau phosphorylation. Importantly, we show that inducing 4R tau expression using antisense oligonucleotide technology is sufficient to drive neurodegeneration in control human neurons, which phenocopies VCP-mutant neurons. In summary, our findings demonstrate that tau hyperphosphorylation, endolysosomal dysfunction, lysosomal membrane rupture, endoplasmic reticulum stress and apoptosis are driven by a pathogenic increase in 4R tau.
Blockchain Data Mining With Graph Learning: A Survey

Blockchain data mining has the potential to reveal the operational status and behavioral patterns of anonymous participants in blockchain systems, thus providing valuable insights into system operation and participant behavior. However, traditional blockchain analysis methods suffer from the problems of being unable to handle the data due to its large volume and complex structure. With powerful computing and analysis capabilities, graph learning can solve the current problems through handling each node's features and linkage relationships separately and exploring the implicit properties of data from a graph perspective. This paper systematically reviews the blockchain data mining tasks based on graph learning approaches. First, we investigate the blockchain data acquisition method, integrate the currently available data analysis tools, and divide the sampling method into rule-based and cluster-based techniques. Second, we classify the graph construction into transaction-based blockchain and account-based methods, and comprehensively analyze the existing blockchain feature extraction methods. Third, we compare the existing graph learning algorithms on blockchain and classify them into traditional machine learning-based, graph representation-based, and graph deep learning-based methods. Finally, we propose future research directions and open issues which are promising to address.