Blood Biomarkers and Metabolomic Profiling for the Early Diagnosis of Vancomycin-Associated Acute Kidney Injury: A Systematic Review and Meta-Analysis of Experimental Studies

Background: several blood-based biomarkers have been proposed for predicting vancomycin-associated kidney injury (VIKI). However, no systematic analysis has compared their prognostic value. Objective: this systematic review and meta-analysis was designed to investigate the role of blood biomarkers and metabolomic profiling as diagnostic and prognostic predictors in pre-clinical studies of VIKI. Methods: a systematic search of PubMed was conducted for relevant articles from January 2000 to May 2022. Animal studies that administered vancomycin and studied VIKI were eligible for inclusion. Clinical studies, reviews, and non-English literature were excluded. The primary outcome was to investigate the relationship between the extent of VIKI as measured by blood biomarkers and metabolomic profiling. Risk of bias was assessed with the CAMARADES checklist the SYRCLE's risk of bias tool. Standard meta-analysis methods (random-effects models) were used. Results: there were four studies for the same species, dosage, duration of vancomycin administration and measurement only for serum creatine and blood urea nitrogen in rats. A statistically significant increase was observed between serum creatinine in the vancomycin group compared to controls (pooled p = 0.037; Standardized Mean Difference: 2.93; 95% CI: 0.17 to 5.69; I-2 = 92.11%). Serum BUN levels were not significantly different between control and vancomycin groups (pooled p = 0.11; SMD: 3.05; 95% CI: 0.69 to 6.8; I-2 = 94.84%). We did not identify experimental studies using metabolomic analyses in animals with VIKI. Conclusions: a total of four studies in rodents only described outcomes of kidney injury as defined by blood biomarkers. Blood biomarkers represented included serum creatinine and BUN. Novel blood biomarkers have not been explored

Group descent algorithms for nonconvex penalized linear and logistic regression models with grouped predictors

Penalized regression is an attractive framework for variable selection problems. Often, variables possess a grouping structure, and the relevant selection problem is that of selecting groups, not individual variables. The group lasso has been proposed as a way of extending the ideas of the lasso to the problem of group selection. Nonconvex penalties such as SCAD and MCP have been proposed and shown to have several advantages over the lasso; these penalties may also be extended to the group selection problem, giving rise to group SCAD and group MCP methods. Here, we describe algorithms for fitting these models stably and efficiently. In addition, we present simulation results and real data examples comparing and contrasting the statistical properties of these methods

Heritability and impact of environmental effects during pregnancy on antral follicle count in cattle

peer-reviewedPrevious studies have documented that ovarian antral follicle count (AFC) is positively correlated with number of healthy follicles and oocytes in ovaries (ovarian reserve), as well as ovarian function and fertility in cattle. However, environmental factors (e.g., nutrition, steroids) during pregnancy in cattle and sheep can reduce AFC in offspring. The role that genetic and environmental factors play in influencing the variability in AFC and, correspondingly, the size of the ovarian reserve, ovarian function, and fertility, are, however, poorly understood. The present study tests the hypothesis that variability in AFC in offspring is influenced not only by genetic merit but also by the dam age and lactation status (lactating cows vs. nonlactating heifers) and milk production during pregnancy. Antral follicle count was assessed by ultrasonography in 445 Irish Holstein-Friesian dairy cows and 522 US Holstein-Friesian dairy heifers. Heritability estimates for AFC (± standard error) were 0.31 ± 0.14 and 0.25 ± 0.13 in dairy cows and heifers, respectively. Association analysis between both genotypic sire data and phenotypic dam data with AFC in their daughters was performed using regression and generalized linear models. Antral follicle count was negatively associated with genetic merit for milk fat concentration. Also, AFC was greater in offspring of dams that were lactating (n = 255) compared with nonlactating dams (n = 89) during pregnancy and was positively associated with dam milk fat concentration and milk fat-to-protein ratio. In conclusion, AFC in dairy cattle is a moderately heritable genetic trait affected by age or lactation status and milk quality but not by level of dam’s milk production during pregnancy

A Novel mRNA Level Subtraction Method for Quick Identification of Target-Orientated Uniquely Expressed Genes Between Peanut Immature Pod and Leaf

Subtraction technique has been broadly applied for target gene discovery. However, most current protocols apply relative differential subtraction and result in great amount clone mixtures of unique and differentially expressed genes. This makes it more difficult to identify unique or target-orientated expressed genes. In this study, we developed a novel method for subtraction at mRNA level by integrating magnetic particle technology into driver preparation and tester–driver hybridization to facilitate uniquely expressed gene discovery between peanut immature pod and leaf through a single round subtraction. The resulting target clones were further validated through polymerase chain reaction screening using peanut immature pod and leaf cDNA libraries as templates. This study has resulted in identifying several genes expressed uniquely in immature peanut pod. These target genes can be used for future peanut functional genome and genetic engineering research

Nuclear Stopping in Au+Au Collisions at sqrt(sNN) = 200 GeV

Transverse momentum spectra and rapidity densities, dN/dy, of protons, anti-protons, and net--protons (p-pbar) from central (0-5%) Au+Au collisions at sqrt(sNN) = 200 GeV were measured with the BRAHMS experiment within the rapidity range 0 < y < 3. The proton and anti-proton dN/dy decrease from mid-rapidity to y=3. The net-proton yield is roughly constant for y<1 at dN/dy~7, and increases to dN/dy~12 at y~3. The data show that collisions at this energy exhibit a high degree of transparency and that the linear scaling of rapidity loss with rapidity observed at lower energies is broken. The energy loss per participant nucleon is estimated to be 73 +- 6 GeV.Comment: 5 pages, 4 figure

Evolution of the nuclear modification factors with rapidity and centrality in d+Au collisions at $\sqrt{s_{NN}} = 200 GeV

We report on a study of the transverse momentum dependence of nuclear modification factors $R_{dAu}$ for charged hadrons produced in deuteron + gold collisions at $\sqrt{s_{NN}}= 200$GeV, as a function of collision centrality and of the pseudorapidity ($\eta = 0,1,2.2,3.2$) of the produced hadrons. We find significant and systematic decrease of $R_{dAu}$ with increasing rapidity. The midrapidity enhancement and the forward rapidity suppression are more pronounced in central collisions relative to peripheral collisions. These results are relevant to the study of the possible onset of gluon saturation at RHIC energies.Comment: Four pages, four figures. Published in PRL. Figures 1 and 2 have been updated, and several changes made to the tex

Quark Gluon Plasma an Color Glass Condensate at RHIC? The perspective from the BRAHMS experiment

We review the main results obtained by the BRAHMS collaboration on the properties of hot and dense hadronic and partonic matter produced in ultrarelativistic heavy ion collisions at RHIC. A particular focus of this paper is to discuss to what extent the results collected so far by BRAHMS, and by the other three experiments at RHIC, can be taken as evidence for the formation of a state of deconfined partonic matter, the so called quark-gluon-plasma (QGP). We also discuss evidence for a possible precursor state to the QGP, i.e. the proposed Color Glass Condensate.Comment: 32 pages, 18 figure

Assessing the predictive performance of population pharmacokinetic models for intravenous polymyxin B in critically ill patients

Polymyxin B (PMB) has reemerged as a last-line therapy for infections caused by multidrug-resistant gram-negative pathogens, but dosing is challenging because of its narrow therapeutic window and pharmacokinetic (PK) variability. Population PK (POPPK) models based on suitably powered clinical studies with appropriate sampling strategies that take variability into consideration can inform PMB dosing to maximize efficacy and minimize toxicity and resistance. Here we reviewed published PMB POPPK models and evaluated them using an external validation data set (EVD) of patients who are critically ill and enrolled in an ongoing clinical study to assess their utility. Seven published POPPK models were employed using the reported model equations, parameter values, covariate relationships, interpatient variability, parameter covariance, and unexplained residual variability in NONMEM (Version 7.4.3). The predictive ability of the models was assessed using prediction-based and simulation-based diagnostics. Patient characteristics and treatment information were comparable across studies and with the EVD (n = 40), but the sampling strategy was a main source of PK variability across studies. All models visually and statistically underpredicted EVD plasma concentrations, but the two-compartment models more accurately described the external data set. As current POPPK models were inadequately predictive of the EVD, creation of a new POPPK model based on an appropriately powered clinical study with an informed PK sampling strategy would be expected to improve characterization of PMB PK and identify covariates to explain interpatient variability. Such a model would support model-informed precision dosing frameworks, which are urgently needed to improve PMB treatment efficacy, limit resistance, and reduce toxicity in patients who are critically ill

Centrality dependence of charged-particle pseudorapidity distributions from d+Au collisions at sqrt(s_{NN})=200 GeV

Charged-particle pseudorapidity densities are presented for the d+Au reaction at sqrt{s_{NN}}=200 GeV with -4.2 <= eta <= 4.2$. The results, from the BRAHMS experiment at RHIC, are shown for minimum-bias events and 0-30%, 30-60%, and 60-80% centrality classes. Models incorporating both soft physics and hard, perturbative QCD-based scattering physics agree well with the experimental results. The data do not support predictions based on strong-coupling, semi-classical QCD. In the deuteron-fragmentation region the central 200 GeV data show behavior similar to full-overlap d+Au results at sqrt{s_{NN}}=19.4 GeV.Comment: 4 pages, 3figures; expanded discussion of uncertainties; added 60-80% centrality range; added additional discussion on centrality selection bia