Hydrothermal Synthesis and Characterization of One-dimensional Ceria Nanorod for Chromium Ion Removal from Wastewater

Remediation of wastewater contaminated with Cr(VI) species by ceria particles has received considerable attention in recent years. The main objectives of the present study were to investigate the adsorption of Cr(VI) species on the one-dimensional (1-D) ceria nanorod (CeNR). In where, CeNR has 20–40 nm in diameter and 200–300 nm in length, as confirmed through FE-SEM and TEM images. Higher surface area of CeNR is insisted to the remediation of Cr(VI)-contaminated wastewaters. This work exemplifies the utilization of XAS and BET to reveal the speciation of CeNR for further understands of the very complex adsorption process. It is also very clear that decontamination of Cr species in wastewater via the in-situ remediation with CeNR permeable reactive barriers would be environmentally attractive in the near future. Keywords: Cr(VI)-contaminant, One-dimensional Ceria, Wastewater treatment; XANES/EXAFS

Deep Convolutional Neural Networks Model-based Brain Tumor Detection in Brain MRI Images

Diagnosing Brain Tumor with the aid of Magnetic Resonance Imaging (MRI) has gained enormous prominence over the years, primarily in the field of medical science. Detection and/or partitioning of brain tumors solely with the aid of MR imaging is achieved at the cost of immense time and effort and demands a lot of expertise from engaged personnel. This substantiates the necessity of fabricating an autonomous model brain tumor diagnosis. Our work involves implementing a deep convolutional neural network (DCNN) for diagnosing brain tumors from MR images. The dataset used in this paper consists of 253 brain MR images where 155 images are reported to have tumors. Our model can single out the MR images with tumors with an overall accuracy of 96%. The model outperformed the existing conventional methods for the diagnosis of brain tumor in the test dataset (Precision = 0.93, Sensitivity = 1.00, and F1-score = 0.97). Moreover, the proposed model's average precision-recall score is 0.93, Cohen's Kappa 0.91, and AUC 0.95. Therefore, the proposed model can help clinical experts verify whether the patient has a brain tumor and, consequently, accelerate the treatment procedure.Comment: 4th International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC 2020), IEEE, 7-9 October 2020, TamilNadu, INDI

Nucleotide identity and variability among different Pakistani hepatitis C virus isolates

<p>Abstract</p> <p>Background</p> <p>The variability within the hepatitis C virus (HCV) genome has formed the basis for several genotyping methods and used widely for HCV genotyping worldwide.</p> <p>Aim</p> <p>The aim of the present study was to determine percent nucleotide identity and variability in HCV isolates prevalent in different geographical regions of Pakistan.</p> <p>Methods</p> <p>Sequencing analysis of the 5'noncoding region (5'-NCR) of 100 HCV RNA-positive patients representing all the four provinces of Pakistan were carried out using ABI PRISM 3100 Genetic Analyzer.</p> <p>Results</p> <p>The results showed that type 3 is the predominant genotypes circulating in Pakistan, with an overall prevalence of 50%. Types 1 and 4 viruses were 9% and 6% respectively. The overall nucleotide similarity among different Pakistani isolates was 92.50% ± 0.50%. Pakistani isolates from different areas showed 7.5% ± 0.50% nucleotide variability in 5'NCR region. The percent nucleotide identity (PNI) was 98.11% ± 0.50% within Pakistani type 1 sequences, 98.10% ± 0.60% for type 3 sequences, and 99.80% ± 0.20% for type 4 sequences. The PNI between different genotypes was 93.90% ± 0.20% for type 1 and type 3, 94.80% ± 0.12% for type 1 and type 4, and 94.40% ± 0.22% for type 3 and type 4.</p> <p>Conclusion</p> <p>Genotype 3 is the most prevalent HCV genotype in Pakistan. Minimum and maximum percent nucleotide divergences were noted between genotype 1 and 4 and 1 and 3 respectively.</p

Cardiovascular risk factors in secondary progressive multiple sclerosis: A cross-sectional analysis from the MS-STAT2 randomized controlled trial

BACKGROUND AND PURPOSE: There is increasing evidence that cardiovascular risk (CVR) contributes to disability progression in multiple sclerosis (MS). CVR is particularly prevalent in secondary progressive MS (SPMS) and can be quantified through validated composite CVR scores. The aim was to examine the cross-sectional relationships between excess modifiable CVR, whole and regional brain atrophy on magnetic resonance imaging, and disability in patients with SPMS. METHODS: Participants had SPMS, and data were collected at enrolment into the MS-STAT2 trial. Composite CVR scores were calculated using the QRISK3 software. Prematurely achieved CVR due to modifiable risk factors was expressed as QRISK3 premature CVR, derived through reference to the normative QRISK3 dataset and expressed in years. Associations were determined with multiple linear regressions. RESULTS: For the 218 participants, mean age was 54 years and median Expanded Disability Status Scale was 6.0. Each additional year of prematurely achieved CVR was associated with a 2.7 mL (beta coefficient; 95% confidence interval 0.8-4.7; p = 0.006) smaller normalized whole brain volume. The strongest relationship was seen for the cortical grey matter (beta coefficient 1.6 mL per year; 95% confidence interval 0.5-2.7; p = 0.003), and associations were also found with poorer verbal working memory performance. Body mass index demonstrated the strongest relationships with normalized brain volumes, whilst serum lipid ratios demonstrated strong relationships with verbal and visuospatial working memory performance. CONCLUSIONS: Prematurely achieved CVR is associated with lower normalized brain volumes in SPMS. Future longitudinal analyses of this clinical trial dataset will be important to determine whether CVR predicts future disease worsening

Effects of antibiotic resistance, drug target attainment, bacterial pathogenicity and virulence, and antibiotic access and affordability on outcomes in neonatal sepsis: an international microbiology and drug evaluation prospective substudy (BARNARDS)

Background Sepsis is a major contributor to neonatal mortality, particularly in low-income and middle-income countries (LMICs). WHO advocates ampicillin–gentamicin as first-line therapy for the management of neonatal sepsis. In the BARNARDS observational cohort study of neonatal sepsis and antimicrobial resistance in LMICs, common sepsis pathogens were characterised via whole genome sequencing (WGS) and antimicrobial resistance profiles. In this substudy of BARNARDS, we aimed to assess the use and efficacy of empirical antibiotic therapies commonly used in LMICs for neonatal sepsis. Methods In BARNARDS, consenting mother–neonates aged 0–60 days dyads were enrolled on delivery or neonatal presentation with suspected sepsis at 12 BARNARDS clinical sites in Bangladesh, Ethiopia, India, Pakistan, Nigeria, Rwanda, and South Africa. Stillborn babies were excluded from the study. Blood samples were collected from neonates presenting with clinical signs of sepsis, and WGS and minimum inhibitory concentrations for antibiotic treatment were determined for bacterial isolates from culture-confirmed sepsis. Neonatal outcome data were collected following enrolment until 60 days of life. Antibiotic usage and neonatal outcome data were assessed. Survival analyses were adjusted to take into account potential clinical confounding variables related to the birth and pathogen. Additionally, resistance profiles, pharmacokinetic–pharmacodynamic probability of target attainment, and frequency of resistance (ie, resistance defined by in-vitro growth of isolates when challenged by antibiotics) were assessed. Questionnaires on health structures and antibiotic costs evaluated accessibility and affordability. Findings Between Nov 12, 2015, and Feb 1, 2018, 36 285 neonates were enrolled into the main BARNARDS study, of whom 9874 had clinically diagnosed sepsis and 5749 had available antibiotic data. The four most commonly prescribed antibiotic combinations given to 4451 neonates (77·42%) of 5749 were ampicillin–gentamicin, ceftazidime–amikacin, piperacillin–tazobactam–amikacin, and amoxicillin clavulanate–amikacin. This dataset assessed 476 prescriptions for 442 neonates treated with one of these antibiotic combinations with WGS data (all BARNARDS countries were represented in this subset except India). Multiple pathogens were isolated, totalling 457 isolates. Reported mortality was lower for neonates treated with ceftazidime–amikacin than for neonates treated with ampicillin–gentamicin (hazard ratio [adjusted for clinical variables considered potential confounders to outcomes] 0·32, 95% CI 0·14–0·72; p=0·0060). Of 390 Gram-negative isolates, 379 (97·2%) were resistant to ampicillin and 274 (70·3%) were resistant to gentamicin. Susceptibility of Gram-negative isolates to at least one antibiotic in a treatment combination was noted in 111 (28·5%) to ampicillin–gentamicin; 286 (73·3%) to amoxicillin clavulanate–amikacin; 301 (77·2%) to ceftazidime–amikacin; and 312 (80·0%) to piperacillin–tazobactam–amikacin. A probability of target attainment of 80% or more was noted in 26 neonates (33·7% [SD 0·59]) of 78 with ampicillin–gentamicin; 15 (68·0% [3·84]) of 27 with amoxicillin clavulanate–amikacin; 93 (92·7% [0·24]) of 109 with ceftazidime–amikacin; and 70 (85·3% [0·47]) of 76 with piperacillin–tazobactam–amikacin. However, antibiotic and country effects could not be distinguished. Frequency of resistance was recorded most frequently with fosfomycin (in 78 isolates [68·4%] of 114), followed by colistin (55 isolates [57·3%] of 96), and gentamicin (62 isolates [53·0%] of 117). Sites in six of the seven countries (excluding South Africa) stated that the cost of antibiotics would influence treatment of neonatal sepsis

Current Trends and Future Approaches in Small-Molecule Therapeutics for COVID-19

The novel coronavirus (SARS-CoV-2) pandemic has created a global public health emergency. The pandemic is causing substantial morbidity, mortality and significant economic loss. Currently, no approved treatments for COVID-19 are available, and it is likely to take at least 12-18 months to develop a new vaccine. Therefore, there is an urgent need to find new therapeutics that can be progressed to clinical development as soon as possible. Repurposing regulatory agency-approved drugs and experimental drugs with known safety profiles can provide important repositories of compounds that can be fast-tracked to clinical development. Globally, over 500 clinical trials involving repurposed drugs have been registered, and over 150 have been initiated, including some backed by the World Health Organisation (WHO). This review is intended as a guide to research into small-molecule therapies to treat COVID-19; it discusses the SARS-CoV-2 infection cycle and identifies promising viral therapeutic targets, reports on a number of promising pre-approved small-molecule drugs with reference to over 150 clinical trials worldwide, and offers a perspective on the future of the field

Cardiovascular risk factors in secondary progressive multiple sclerosis: a cross-sectional analysis from the MS-STAT2 randomized controlled trial

Background and purpose: there is increasing evidence that cardiovascular risk (CVR) contributes to disability progression in multiple sclerosis (MS). CVR is particularly prevalent in secondary progressive MS (SPMS) and can be quantified through validated composite CVR scores. The aim was to examine the cross-sectional relationships between excess modifiable CVR, whole and regional brain atrophy on magnetic resonance imaging, and disability in patients with SPMS.Methods: participants had SPMS, and data were collected at enrolment into the MS-STAT2 trial. Composite CVR scores were calculated using the QRISK3 software. Prematurely achieved CVR due to modifiable risk factors was expressed as QRISK3 premature CVR, derived through reference to the normative QRISK3 dataset and expressed in years. Associations were determined with multiple linear regressions.Results: for the 218 participants, mean age was 54 years and median Expanded Disability Status Scale was 6.0. Each additional year of prematurely achieved CVR was associated with a 2.7 mL (beta coefficient; 95% confidence interval 0.8-4.7; p = 0.006) smaller normalized whole brain volume. The strongest relationship was seen for the cortical grey matter (beta coefficient 1.6 mL per year; 95% confidence interval 0.5-2.7; p = 0.003), and associations were also found with poorer verbal working memory performance. Body mass index demonstrated the strongest relationships with normalized brain volumes, whilst serum lipid ratios demonstrated strong relationships with verbal and visuospatial working memory performance.Conclusions: prematurely achieved CVR is associated with lower normalized brain volumes in SPMS. Future longitudinal analyses of this clinical trial dataset will be important to determine whether CVR predicts future disease worsening