Comparative evaluation of two matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) systems for the identification of clinically significant yeasts

SummaryObjectivesTo prospectively evaluate the performance of two matrix-assisted laser desorption/ionization time-of-flight mass spectrometry systems (MALDI-TOF MS) for the identification of clinically significant yeast isolates compared to the VITEK 2 system.MethodsOne hundred and eighty-eight consecutive yeast isolates were analyzed by Bruker Biotyper and VITEK MS. The results were compared with the conventional VITEK 2 yeast identification system. Discrepant results were resolved by direct sequencing of rDNA.ResultsAccurate identification by VITEK 2, VITEK MS, and Bruker Biotyper MS was 94.1% (177/188), 93.0% (175/188), and 92.6% (174/188), respectively. Three isolates were not identified by VITEK MS, while nine Candida orthopsilosis were misidentified as Candida parapsilosis, as this species is not present in its database. Eleven isolates were not identified or were wrongly identified by Bruker Biotyper and although another 14 were correctly identified, the score was unreliable at <1.7.ConclusionThe overall accuracy of rapid MALDI-TOF MS systems was essentially comparable to that of the conventional VITEK 2 yeast identification system. However, future expansion of the databases may further improve the outcome and accuracy of identification of yeast species

Fabrication of Microbicidal Silver Nanoparticles: Green Synthesis and Implications in the Containment of Bacterial Biofilm on Orthodontal Appliances

Among various metal-based nanoparticles, silver nanoparticles (AgNPs) manifest superior inhibitory effects against several microorganisms. In fact, the AgNP-based treatment has been reported to inhibit both sensitive and resistant isolates of bacteria and other disease-causing microbes with equal propensity. Keeping this fact into consideration, we executed bio-mediated synthesis of AgNPs employing extract of flower and various other parts (such as bud and leaf) of the Hibiscus rosa-sinensis plant. The physicochemical characterization of as-synthesized AgNPs was executed employing transmission electron microscopy (TEM), dynamic light scattering (DLS), zeta potential, Fourier transform infrared (FTIR) spectroscopy, and UV-Vis spectroscopy, etc. The as-synthesized AgNPs demonstrated strong antimicrobial activity against both Gram-positive and Gram-negative bacteria with equal propensity. The as-synthesized AgNPs successfully inhibited Streptococcus mutans (S. mutans), one of the main causative bacteria responsible for dental caries. Considering the fact that orthodontic appliances facilitate infliction of the oral cavity with a range of microbes including S. mutans, we determined the growth inhibitory and anti-adherence activities of AgNPs on orthodontic appliances. We performed microbiological assays employing AgNPs adsorbed onto the surface of nickel–titanium (Ni-Ti) orthodontic wires. A topographic analysis of the decontaminated Ni-Ti orthodontic wires was performed by scanning electron microscopy. In addition to antimicrobial and anti-biofilm activities against oral S. mutans, the as-fabricated AgNPs demonstrated significant inhibitory and anti-biofilm properties against other biofilm-forming bacteria such as Escherichia coli and Listeria monocytogenes

Ransomware detection using deep learning based unsupervised feature extraction and a cost sensitive Pareto Ensemble classifier

Ransomware attacks pose a serious threat to Internet resources due to their far-reaching effects. It's Zero-day variants are even more hazardous, as less is known about them. In this regard, when used for ransomware attack detection, conventional machine learning approaches may become data-dependent, insensitive to error cost, and thus may not tackle zero-day ransomware attacks. Zero-day ransomware have normally unseen underlying data distribution. This paper presents a Cost-Sensitive Pareto Ensemble strategy, CSPE-R to detect novel Ransomware attacks. Initially, the proposed framework exploits the unsupervised deep Contractive Auto Encoder (CAE) to transform the underlying varying feature space to a more uniform and core semantic feature space. To learn the robust features, the proposed CSPE-R ensemble technique explores different semantic spaces at various levels of detail. Heterogeneous base estimators are then trained over these extracted subspaces to find the core relevance between the various families of the ransomware attacks. Then, a novel Pareto Ensemble-based estimator selection strategy is implemented to achieve a cost-sensitive compromise between false positives and false negatives. Finally, the decision of selected estimators are aggregated to improve the detection against unknown ransomware attacks. The experimental results show that the proposed CSPE-R framework performs well against zero-day ransomware attacks

Recent developments and perspectives in CdS-based photocatalysts for water splitting

Over the past few years, many approaches have been developed progressively to produce hydrogen (H2) from water under solar light irradiation. This process of fuel production is clean, potentially cost-effective, and environment-friendly. At present, however, current technologies are unable to meet the industrial requirements because of high cost, low photoresponse, and insufficient catalytic performance. Among water splitting photocatalysts, CdS is considered to be an interesting and important material owing to its low cost, prominent catalytic activity, high absorption in the visible spectrum, and the suitable positions of its conduction (CB) and valence (VB) bands. There are, however, some associated problems such as the rapid recombination of photogenerated electron–hole pairs and photocorrosion that have severely hampered its practical usage. The efficient conversion of water to H2 depends on the extent to which the charge carriers, especially the electrons, are first generated and then have sufficient life-time for their effective utilization. This review highlights work over the past several years to improve the photocatalytic efficiency and stability of CdS for H2 production from water

Utility of the CHA2DS2-VASc score for predicting ischaemic stroke in patients with or without atrial fibrillation: a systematic review and meta-analysis

AIMS: Anticoagulants are the mainstay treatment for stroke prevention in patients with non-valvular atrial fibrillation (NVAF), and the CHA2DS2-VASc score is widely used to guide anticoagulation therapy in this cohort. However, utility of CHA2DS2-VASc in NVAF patients is debated, primarily because it is a vascular scoring system, which does not incorporate atrial fibrillation related parameters. Therefore, we conducted a meta-analysis to estimate the discrimination ability of CHA2DS2-VASc in predicting ischaemic stroke overall, and in subgroups of patients with or without NVAF. METHODS AND RESULTS: PubMed and Embase databases were searched till June 2020 for published articles that assessed the discrimination ability of CHA2DS2-VASc, as measured by C-statistics, during mid-term (2-5 years) and long-term (\u3e5 years) follow-up. Summary estimates were reported as random effects C-statistics with 95% confidence intervals (CIs). Seventeen articles were included in the analysis. Nine studies (n = 453 747 patients) reported the discrimination ability of CHA2DS2-VASc in NVAF patients, and 10 studies (n = 138 262 patients) in patients without NVAF. During mid-term follow-up, CHA2DS2-VASc predicted stroke with modest discrimination in the overall cohort [0.67 (0.65-0.69)], with similar discrimination ability in patients with NVAF [0.65 (0.63-0.68)] and in those without NVAF [0.69 (0.68-0.71)] (P-interaction = 0.08). Similarly, at long-term follow-up, CHA2DS2-VASc had modest discrimination [0.66 (0.63-0.69)], which was consistent among patients with NVAF [0.63 (0.54-0.71)] and those without NVAF [0.67 (0.64-0.70)] (P-interaction = 0.39). CONCLUSION: This meta-analysis suggests that the discrimination power of the CHA2DS2-VASc score in predicting ischaemic stroke is modest, and is similar in the presence or absence of NVAF. More accurate stroke prediction models are thus needed for the NVAF population

Integration of Large-Scale Electric Vehicles into Utility Grid: An Efficient Approach for Impact Analysis and Power Quality Assessment

Electric vehicles (EVs) have received massive consideration in the automotive industries due to their improved performance, efficiency and capability to minimize global warming and carbon emission impacts. The utilization of EVs has several potential benefits, such as increased use of renewable energy, less dependency on fossil-fuel-based power generations and energy-storage capability. Although EVs can significantly mitigate global carbon emissions, it is challenging to maintain power balance during charging on-peak hours. Thus, it mandates a comprehensive impact analysis of high-level electric vehicle penetration in utility grids. This paper investigates the impacts of large-scale EV penetration on low voltage distribution, considering the charging time, charging method and characteristics. Several charging scenarios are considered for EVs’ integration into the utility grid regarding power demand, voltage profile, power quality and system adequacy. A lookup-table-based charging approach for EVs is proposed for impact analysis, while considering a large-scale integration. It is observed that the bus voltage and line current are affected during high-level charging and discharging of the EVs. The residential grid voltage sag increases by about 1.96% to 1.77%, 2.21%, 1.96 to 1.521% and 1.93% in four EV-charging profiles, respectively. The finding of this work can be adopted in designing optimal charging/discharging of EVs to minimize the impacts on bus voltage and line current

TAT-peptide conjugated repurposing drug against SARS-CoV-2 main protease (3CLpro): potential therapeutic intervention to combat COVID-19

The Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that originated in Chinese city of Wuhan has caused around 906,092 deaths and 28,040,853 confirmed cases worldwide (WHO, 11 September, 2020). In a life-threatening situation, where there is no specific and licensed anti-COVID-19 vaccine or medicine available; the repurposed drug might act as a silver bullet. Currently, more than 211 vaccines, 80 antibodies, 31 antiviral drugs, 35 cell-based, 6 RNA-based and 131 other drugs are in clinical trials. It is therefore utter need of the hour to develop an effective drug that can be used for the treatment of COVID-19 before a vaccine can be developed. One of the best-characterized and attractive drug targets among coronaviruses is the main protease (3CL^{pro}). Therefore, the current study focuses on the molecular docking analysis of TAT-peptide^{47–57} (GRKKRRQRRRP)-conjugated repurposed drugs (i.e., lopinavir, ritonavir, favipiravir, and hydroxychloroquine) with SARS-CoV-2 main protease (3CL^{pro} to discover potential efficacy of TAT-peptide (TP) - conjugated repurposing drugs against SARS-CoV-2. The molecular docking results validated that TP-conjugated ritonavir, lopinavir, favipiravir, and hydroxychloroquine have superior and significantly enhanced interactions with the target SARS-CoV-2 main protease. In-silico approach employed in this study suggests that the combination of the drug with TP is an excelling alternative to develop a novel drug for the treatment of SARS-CoV-2 infected patients. The development of TP based delivery of repurposing drugs might be an excellent approach to enhance the efficacy of the existing drugs for the treatment of COVID-19. The predictions from the results obtained provide invaluable information that can be utilized for the choice of candidate drugs for in vitro, in vivo and clinical trials. The outcome from this work prove crucial for exploring and developing novel cost-effective and biocompatible TP conjugated anti-SARS-CoV-2 therapeutic agents in immediate future

Current Management Strategies in Breast Cancer by Targeting Key Altered Molecular Players

Breast Cancer is second largest disease affecting women worldwide. It remains the most frequently reported and leading cause of death among women in both developed and developing countries. Chemoprevention is one the promising approaches which reduces breast cancer. Tamoxifen and raloxifene are commonly used for treatment of breast cancer in women with high risk, although resistance occurs by tamoxifen after five years of therapy and both drugs cause uterine cancer and thromboembolic events. Aromatase inhibitors are coming up as potential option for prevention in treatment with adjuvant trials in practice. The combination of aromatase inhibitors along with tamoxifen can also be beneficial. For this, clinical trials based on large number of patients with optimal dose and lesser side effects have to be more in practice. Despite the clinical trials going on, there is need of better molecular models which can identify high risk population and new agents with better benefit having less side effects and improved biomarkers for treating breast cancer

Effects of EDTA and aqueous plants extract on the developmental and stress tolerance attributes of Spinacia oleracea and Brassica rapa under sewage water regime

Sewage water is causing a potential threat to agriculture sector due to industrial effluents having heavy metals. Present investigation was carried to study the role of ethylenediaminetetraacetic acid (EDTA) or aqueous extracts of Hyacinth and Hedychium on soil quality and growth of spinach and turnip plants irrigated with sewage water (SW). Treatment of plants with SW resulted in an increment of catalase (CAT), peroxidase (POD) and polyphenol oxidase (PPO) activities. However, EDTA or plant extracts further enhanced their activities. At both stages of development of the tested crops, a substantial increase was found in the content of proline and total phenols, indicating the strengthening of the antioxidant protection mechanism to boost the oxidative effects of SW stress. Sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE) studies revealed considerable variation in the protein profile among the different treatments, with an expression of some unique proteins obvious with other treatments. SW treatments increased heavy metals (HM) content in soil and plants; however, EDTA or plant extracts greatly decreased the levels of HMs in both shoots and roots and soils. The present study results suggest that the application of EDTA or aqueous plant extracts can be a useful strategy for phytoextraction in areas irrigated with sewage water

Heterogeneous trends in burden of heart disease mortality by subtypes in the United States, 1999-2018: observational analysis of vital statistics

Abstract Objective To describe trends in the burden of mortality due to subtypes of heart disease from 1999 to 2018 to inform targeted prevention strategies and reduce disparities. Design Serial cross sectional analysis of cause specific heart disease mortality rates using national death certificate data in the overall population as well as stratified by race-sex, age, and geography. Setting United States, 1999-2018. Participants 12.9 million decedents from total heart disease (49% women, 12% black, and 19% &lt;65 years old). Main outcome measures Age adjusted mortality rates (AAMR) and years of potential life lost (YPLL) for each heart disease subtype, and respective mean annual percentage change. Results Deaths from total heart disease fell from 752 192 to 596 577 between 1999 and 2011, and then increased to 655 381 in 2018. From 1999 to 2018, the proportion of total deaths from heart disease attributed to ischemic heart disease decreased from 73% to 56%, while the proportion attributed to heart failure increased from 8% to 13% and the proportion attributed to hypertensive heart disease increased from 4% to 9%. Among heart disease subtypes, AAMR was consistently highest for ischemic heart disease in all subgroups (race-sex, age, and region). After 2011, AAMR for heart failure and hypertensive heart disease increased at a faster rate than for other subtypes. The fastest increases in heart failure mortality were in black men (mean annual percentage change 4.9%, 95% confidence interval 4.0% to 5.8%), whereas the fastest increases in hypertensive heart disease occurred in white men (6.3%, 4.9% to 9.4%). The burden of years of potential life lost was greatest from ischemic heart disease, but black-white disparities were driven by heart failure and hypertensive heart disease. Deaths from heart disease in 2018 resulted in approximately 3.8 million potential years of life lost. Conclusions Trends in AAMR and years of potential life lost for ischemic heart disease have decelerated since 2011. For almost all other subtypes of heart disease, AAMR and years of potential life lost became stagnant or increased. Heart failure and hypertensive heart disease account for the greatest increases in premature deaths and the largest black-white disparities and have offset declines in ischemic heart disease. Early and targeted primary and secondary prevention and control of risk factors for heart disease, with a focus on groups at high risk, are needed to avoid these suboptimal trends beginning earlier in life. </jats:sec