Optimizing Vancomycin Dosing in Chronic Kidney Disease by Deriving and Implementing a Web-Based Tool Using a Population Pharmacokinetics Analysis.

Background: Chronic kidney disease (CKD) patients requiring intravenous vancomycin bear considerable risks of adverse outcomes both from the infection and vancomycin therapy itself, necessitating especially precise dosing to avoid sub- and supratherapeutic vancomycin exposure. Methods: In this retrospective study, we performed a population pharmacokinetic analysis to construct a vancomycin dose prediction model for CKD patients who do not require renal replacement therapy. The model was externally validated on an independent cohort of patients to assess its prediction accuracy. The pharmacokinetic parameter estimates and the equations were productized into a Web application (VancApp) subsequently implemented in routine care. The association between VancApp-based dosing and time-to-target concentration attainment, 30-day mortality, and nephrotoxicity were assessed postimplementation. Results: The model constructed from an initial cohort (n = 80) revealed a population clearance and volume of distribution of 1.30 L/h and 1.23 L/kg, respectively. External model validation (n = 112) demonstrated a mean absolute prediction error of 1.25 mg/L. Following 4 months of clinical implementation of VancApp as an optional alternative to usual care [VancApp (n = 22) vs. usual care (n = 21)], patients who had received VancApp-based dosing took a shorter time to reach target concentrations (median: 66 vs. 102 h, p = 0.187) and had fewer 30-day mortalities (14% vs. 24%, p = 0.457) compared to usual care. While statistical significance was not achieved, the clinical significance of these findings appear promising. Conclusion: Clinical implementation of a population pharmacokinetic model for vancomycin in CKD can potentially improve dosing precision in CKD and could serve as a practical means to improve vital clinical outcomes

Data driven surrogate model-based optimization of the process parameters in electric discharge machining of D2 steel using Cu-SiC composite tool for the machined surface roughness and the tool wear

Electrical discharge machining (EDM) is mainly utilized for the die manufacturing and also used to machine the hard materials. Pure Copper, Copper based alloys, brass, graphite, steel are the conventional electrode materials for EDM process. While machining with the conventional electrode materials, tool wear becomes the main bottleneck which led to increased machining cost. In the present work, the composite tool tip comprises 80% Copper and 20% silicon carbide was used for the machining of hardened D2 steel. The powder metallurgy route was used to fabricate the composite tool tip. Electrode wear rate and surface roughness were assessed with respect to the different process parameters like input current, gap voltage, pulse on time, pulse off time and dielectric flushing pressure. During the analysis it was found that Input current (I p ), Pulse on time (T on ) and Pulse off time (T off ) were the significant parameters which were affecting the tool wear rate (TWR) while the I p , T on and flushing pressure affected more the surface roughness (SR). SEM micrograph reveals that increase in I p leads to increase in the wear rate of the tool. The data obtained from experiments were used to develop machine learning based surrogate models. Three machine learning (ML) models are random forest, polynomial regression and gradient boosted tree. The predictive capability of ML based surrogate models was assessed by contrasting the R 2 and mean square error (MSE) of prediction of responses. The best surrogate model was used to develop a complex objective function for use in firefly algorithm-based optimization of input machining parameters for minimization of the output responses

Waning of specific antibodies against Delta and Omicron variants five months after a third dose of BNT162b2 SARS-CoV-2 vaccine in elderly individuals.

The emergence of new SARS-CoV-2 variants, such as the more transmissible Delta and Omicron variants, has raised concerns on efficacy of the COVID-19 vaccines. Here, we examined the waning of antibody responses against different variants following primary and booster vaccination. We found that antibody responses against variants were low following primary vaccination. The antibody response against Omicron was almost non-existent. Efficient boosting of antibody response against all variants, including Omicron, was observed following a third dose. The antibody response against the variants tested was significantly higher at one month following booster vaccination, compared with two months following primary vaccination, for all individuals, including the low antibody responders identified at two months following primary vaccination. The antibody response, for all variants tested, was significantly higher at four months post booster than at five months post primary vaccination, and the proportion of low responders remained low (6-11%). However, there was significant waning of antibody response in more than 95% of individuals at four months, compared to one month following booster. We also observed a robust memory B cell response following booster, which remained higher at four months post booster than prior to booster. However, the memory B cell responses were on the decline for 50% of individuals at four months following booster. Similarly, while the T cell response is sustained, at cohort level, at four months post booster, a substantial proportion of individuals (18.8 - 53.8%) exhibited T cell response at four months post booster that has waned to levels below their corresponding levels before booster. The findings show an efficient induction of immune response against SARS-CoV-2 variants following booster vaccination. However, the induced immunity by the third BNT162b2 vaccine dose was transient. The findings suggest that elderly individuals may require a fourth dose to provide protection against SARS-CoV-2

Synthesis And Characterization Of Nanocrystalline Barium Strontium Titanate Powder Via Sol-Gel Processing

Barium Strontium Titanate (BST) solid solution is a strong candidate material for application in tunable ferroelectric devices. In this research, we have synthesized and characterized nanocrystalline BST (Ba0.7Sr 0.3TiO3) powder with average particle-diameter of 15 nm through a simple sol-gel process, using barium acetate, strontium acetate and titanium isopropoxide as the precursors. In this process, stoichiometric proportions of barium acetate and strontium acetate were dissolved in acetic acid followed by refluxing, and addition of titanium (IV) isopropoxide to form BST gel. The gel was analyzed using Differential Scanning Calorimetry (DSC) and Thermal Gravimetric Analysis (TGA). The as-formed gel was dried at 200 °C and then calcined in the temperature range of 400 to 800 °C for crystallization. Phase evolution during calcination was studied using X-ray diffraction (XRD) technique. Particle size, morphology and the lattice fringes of the calcined powder were characterized by high-resolution transmission electron microscopy (HR-TEM). To study the effects of sintering on BST nanopowder, green ceramic specimens were prepared by uniaxial compaction and then sintered at 950-1,100 °C under atmospheric conditions. Sintered specimens were analyzed for phase composition, grain size and geometric bulk density. © Springer Science+Business Media, LLC 2007

Al2Tio5-Al2O3-Tio2 Nanocomposite: Structure, Mechanical Property And Bioactivity Studies

Novel biomaterials are of prime importance in tissue engineering. Here, we developed novel nanostructured Al2TiO5-Al 2O3-TiO2 composite as a biomaterial for bone repair. Initially, nanocrystalline Al2O3-TiO2 composite powder was synthesized by a sol-gel process. The powder was cold compacted and sintered at 1300-1500 °C to develop nanostructured Al 2TiO5-Al2O3-TiO2 composite. Nano features were retained in the sintered structures while the grains showed irregular morphology. The grain-growth and microcracking were prominent at higher sintering temperatures. X-ray diffraction peak intensity of β-Al2TiO5 increased with increasing temperature. β-Al2TiO5 content increased from 91.67% at 1300 °C to 98.83% at 1500 °C, according to Rietveld refinement. The density of β-Al2TiO5 sintered at 1300 °C, 1400 °C and 1500 °C were computed to be 3.668 g cm-3, 3.685 g cm -3 and 3.664 g cm-3, respectively. Nanocrystalline grains enhanced the flexural strength. The highest flexural strength of 43.2 MPa was achieved. Bioactivity and biomechanical properties were assessed in simulated body fluid. Electron microscopy confirmed the formation of apatite crystals on the surface of the nanocomposite. Spectroscopic analysis established the presence of Ca and P ions in the crystals. Results throw light on biocompatibility and bioactivity of β-Al2TiO5 phase, which has not been reported previously. © 2010 Elsevier Ltd. All rights reserved

Synthesis, Densification, And Phase Evolution Studies Of Al2O3-Al2Tio5-Tio2 Nanocomposites And Measurement Of Their Electrical Properties

Alumina-aluminum titanate-titania (Al2O3-Al2TiO5-TiO2) nanocomposites were synthesized using alkoxide precursor solutions. Thermal analysis provided information on phase evolution from the as-synthesized gel with an increase in temperature. Calcination at 700°C led to the formation of an Al2O3-TiO2 nanocomposite, while at a higher temperature (1300°C) an Al2O3-Al2TiO5-TiO2 nanocomposite was formed. The nanocomposites were uniaxially compacted and sintered in a pressureless environment in air to study the densification behavior, grain growth, and phase evolution. The effects of nanosize particles on the crystal structure and densification of the nanocomposite have been discussed. The sintered nanocomposite structures were also characterized for dielectric properties. © 2007 The American Ceramic Society

Carditis following COVID-19 vaccination: balancing the risks and benefits

10.1016/j.lanwpc.2023.100765LANCET REGIONAL HEALTH-WESTERN PACIFIC3

Depression in systemic sclerosis: Review of the neuro-immunologic link and pharmacological management

Depression is a common neuropsychiatric condition associated with systemic sclerosis. The association of depression and systemic sclerosis is the result of multiple mechanisms such as autoimmune, significant morbidity due to multi-system involvement, distorted self-image due to disfigurement, chronic disability, and iatrogenic. The prevalence of depression in systemic sclerosis is as high as 65% as found in several clinical studies. Early diagnosis and appropriate intervention of depression in systemic sclerosis through integrated multidisciplinary team approach is more likely to improve the global outcome of illness. Hence, multidisciplinary management approach is highly recommended for the management of depression in systemic sclerosis

Mass COVID-19 testing of asymptomatic health-care workers in a tertiary hospital during an outbreak in another hospital in Singapore: an effective strategy?

10.5365/wpsar.2022.13.4.951WESTERN PACIFIC SURVEILLANCE AND RESPONSE13

Stress Cardiomyopathy with Transient Biventricular Dysfunction Following Recent COVID-19 Infection

10.6515/ACS.202103_37(2).20201221AACTA CARDIOLOGICA SINICA372204-20