Isolation and Identification of Bacterial Pathogens from Blood Cultures in a Tertiary Care Hospital and Their Clinical Correlation

Objective: This study aimed to isolate and identify bacterial pathogens from blood cultures of patients with suspected bloodstream infections (BSIs) in a tertiary care hospital, analyze their antimicrobial susceptibility patterns, and establish clinical correlations. Methods: A cross-sectional study was conducted in the Microbiology Department of a tertiary care hospital. Blood samples from 60 patients were collected aseptically, processed using BACTEC, and cultured on blood and MacConkey agar. Bacterial isolates were identified based on colonial morphology, Gram staining, and biochemical tests. Antibiotic susceptibility testing was performed using the modified Kirby-Bauer disk diffusion method according to Clinical and Laboratory Standards Institute (CLSI) guidelines. Results: The overall culture positivity rate was 26%, with higher positivity among female patients (31.57%) and neonates or infants under six months (26%). Klebsiella pneumoniae was the most frequently isolated pathogen (53.33%), followed by Staphylococcus aureus (20.00%), Escherichia coli (13.33%), and Citrobacter species (13.33%). Klebsiella pneumoniae showed high resistance to ceftazidime and piperacillin, while remaining sensitive to cefoperazone and tobramycin. Staphylococcus aureus isolates were resistant to penicillin and erythromycin but sensitive to vancomycin and cefazolin. The prevalence of multidrug resistance among isolates underscores the need for targeted empirical therapy. Conclusion: Klebsiella pneumoniae emerged as the primary pathogen in BSIs, with significant resistance to commonly prescribed antibiotics. These findings highlight the necessity for enhanced infection control measures, especially in NICUs, and the implementation of local antibiograms to guide effective antibiotic therapy and mitigate resistance trends. Further research across multiple centers is recommended to validate these findings and inform broader clinical guidelines

A Structural Equation Model on Work Design in Relation to Authentic Leadership, Workplace Spirituality, and Practical Emotional Intelligence of Public Elementary Teachers

The study determined the best fit model for the work design based on authentic leadership, workplace spirituality, and practical emotional intelligence of public elementary teachers. Using e-survey through Google Forms, data was collected from the teachers using a set of modified survey questionnaires that were tested for content validity and reliability. This study used a quantitative descriptive and causal method of research. The statistical tools employed in analyzing the data includes the mean, Pearson-r, and structural equation model (SEM). Results of the study revealed the following: the level of authentic leadership was very high; the level of workplace spirituality was high; the level of practical emotional intelligence was high; and, the level of work design for teachers was high. Moreover, a significant relationship was established between the exogenous and endogenous variables. In addition, authentic leadership, workplace spirituality, and practical emotional intelligence significantly influence work design for teachers. Of the five (5) generated models, Model 5 best fits work design among public elementary teachers with practical emotional intelligence bringing the biggest impact. The model successfully passed all the conventions of a reasonable fit; hence, it is deemed the most parsimonious model

Exploring the Role of HR Analytics in Enhancing Talent Acquisition Strategies

Hiring and selecting the right candidate is a critical business process in today’s cutthroat competition. HR Analytics, also known as Human Resource Analytics, provides unique insights into talent acquisition and helps organisations to improve their strategies based on fact. This research paper aims to establish the use of the HR Analytics in improving the talent acquisition practices since this will help in identifying the different candidates sourcing, screening, selection, and onboarding processes. In doing so, the work employs the study of different techniques of HR Analytics including but not limited to the predictive analytics, data mining, and talent market analysis with the main view of understanding how different techniques can be used to give the organizations competitive advantage in talent management and attraction. The research will focus on a few real-world solutions such as the use of HR Analytics for social media talent acquisition, the use of prediction models for screening and the use of data analytics for selection. Also, the paper will discuss the problems and drawbacks that may be encountered while adopting HR Analytics in recruiting. In it, we will highlight the data quality issue, the privacy issue, and the need that HR professionals must have skills and knowledge to use the HR Analytics tools. Lastly, this research aims at contributing to the existing body of knowledge that seeks to help organizations that aim at increasing on their Strategic Human Resources Management Talent Acquisition approach based on the design and use of HR Analytics. Day by day organizations are becoming more rational and by using this technique organizations can arrive to better decisions about employer branding and, consequently, about attracting and retaining the best talent in today’s job market

Community based Sustainable Tourism Development - A tool for fostering and promoting peace: A case study of Odisha, India.

Much has been analyzed, discussed and written about tourism, its interdisciplinary approach and multidimensional concepts, but one of the most significant roles that the tourism has been playing for a while now and which has not come into the limelight is the fostering and promotion of peace. Tourism is regarded as one of the most pioneering sectors, and has not only made socio economic contributions but also created a harmonious platform for all to exchange, share, and understand each other better in order to gain co-operation, mutual understanding, a sense of belonging, and integrity. In the backdrop of a peaceful society where justice, equality, human rights and prosperity stand firm, this is in part due to the remarkable contributions of tourism in assimilating people into a common platform of thought. Society and its people have witnessed socio economic development, the creation of equal opportunities for everyone to live in, and sustainability which to a greater extent has been achieved due to the catalytic nature of tourism which in turn fosters and promotes a peaceful existence. This paper emphasizes and explores the role of tourism in enhancing peace through community based sustainable tourism development by interconnecting the environment, the local community, the tourists, and other important aspects .The paper cites some of the key examples of Odisha in terms of its community participation and their involvement in sustainable development initiatives leading to the harmonious inter-existence between locals and visitors

Challenges and Solution for Identification of Plant Disease Using Machine Learning & IoT

Internet of Thing (IoT) is a groundbreaking technology that has been introduced in the field of agriculture to improve the quality and quantity of food production. As agriculture plays a vital role in feeding most of the world\u27s population, the increasing demand for food has led to a rise in food grain production. The identification of plant diseases is a critical task for farmers and agronomists as it enables them to take proactive measures to prevent the spread of diseases, protect crops, and maximize yields. Traditional methods of plant disease detection involve visual inspections by experts, which can be time-consuming and often subject to human error. However, with technological advancements, IoT and Machine Learning (ML) has emerged as promising solution for automating and improving plant disease identification. This paper explores the challenges and solutions for identifying plant diseases using IoT and ML. The challenges discussed include data collection, quality, scalability, and interpretability. The proposed solutions include using sensor networks, data pre-processing techniques, transfer learning, and explainable AI

Antiinflammatory Therapy with Canakinumab for Atherosclerotic Disease

Background: Experimental and clinical data suggest that reducing inflammation without affecting lipid levels may reduce the risk of cardiovascular disease. Yet, the inflammatory hypothesis of atherothrombosis has remained unproved. Methods: We conducted a randomized, double-blind trial of canakinumab, a therapeutic monoclonal antibody targeting interleukin-1β, involving 10,061 patients with previous myocardial infarction and a high-sensitivity C-reactive protein level of 2 mg or more per liter. The trial compared three doses of canakinumab (50 mg, 150 mg, and 300 mg, administered subcutaneously every 3 months) with placebo. The primary efficacy end point was nonfatal myocardial infarction, nonfatal stroke, or cardiovascular death. RESULTS: At 48 months, the median reduction from baseline in the high-sensitivity C-reactive protein level was 26 percentage points greater in the group that received the 50-mg dose of canakinumab, 37 percentage points greater in the 150-mg group, and 41 percentage points greater in the 300-mg group than in the placebo group. Canakinumab did not reduce lipid levels from baseline. At a median follow-up of 3.7 years, the incidence rate for the primary end point was 4.50 events per 100 person-years in the placebo group, 4.11 events per 100 person-years in the 50-mg group, 3.86 events per 100 person-years in the 150-mg group, and 3.90 events per 100 person-years in the 300-mg group. The hazard ratios as compared with placebo were as follows: in the 50-mg group, 0.93 (95% confidence interval [CI], 0.80 to 1.07; P = 0.30); in the 150-mg group, 0.85 (95% CI, 0.74 to 0.98; P = 0.021); and in the 300-mg group, 0.86 (95% CI, 0.75 to 0.99; P = 0.031). The 150-mg dose, but not the other doses, met the prespecified multiplicity-adjusted threshold for statistical significance for the primary end point and the secondary end point that additionally included hospitalization for unstable angina that led to urgent revascularization (hazard ratio vs. placebo, 0.83; 95% CI, 0.73 to 0.95; P = 0.005). Canakinumab was associated with a higher incidence of fatal infection than was placebo. There was no significant difference in all-cause mortality (hazard ratio for all canakinumab doses vs. placebo, 0.94; 95% CI, 0.83 to 1.06; P = 0.31). Conclusions: Antiinflammatory therapy targeting the interleukin-1β innate immunity pathway with canakinumab at a dose of 150 mg every 3 months led to a significantly lower rate of recurrent cardiovascular events than placebo, independent of lipid-level lowering. (Funded by Novartis; CANTOS ClinicalTrials.gov number, NCT01327846.

The poly-omics of ageing through individual-based metabolic modelling

Abstract Background Ageing can be classified in two different ways, chronological ageing and biological ageing. While chronological age is a measure of the time that has passed since birth, biological (also known as transcriptomic) ageing is defined by how time and the environment affect an individual in comparison to other individuals of the same chronological age. Recent research studies have shown that transcriptomic age is associated with certain genes, and that each of those genes has an effect size. Using these effect sizes we can calculate the transcriptomic age of an individual from their age-associated gene expression levels. The limitation of this approach is that it does not consider how these changes in gene expression affect the metabolism of individuals and hence their observable cellular phenotype. Results We propose a method based on poly-omic constraint-based models and machine learning in order to further the understanding of transcriptomic ageing. We use normalised CD4 T-cell gene expression data from peripheral blood mononuclear cells in 499 healthy individuals to create individual metabolic models. These models are then combined with a transcriptomic age predictor and chronological age to provide new insights into the differences between transcriptomic and chronological ageing. As a result, we propose a novel metabolic age predictor. Conclusions We show that our poly-omic predictors provide a more detailed analysis of transcriptomic ageing compared to gene-based approaches, and represent a basis for furthering our knowledge of the ageing mechanisms in human cells

Semaglutide and cardiovascular outcomes in patients with obesity and prevalent heart failure: a prespecified analysis of the SELECT trial

Background: Semaglutide, a GLP-1 receptor agonist, reduces the risk of major adverse cardiovascular events (MACE) in people with overweight or obesity, but the effects of this drug on outcomes in patients with atherosclerotic cardiovascular disease and heart failure are unknown. We report a prespecified analysis of the effect of once-weekly subcutaneous semaglutide 2·4 mg on ischaemic and heart failure cardiovascular outcomes. We aimed to investigate if semaglutide was beneficial in patients with atherosclerotic cardiovascular disease with a history of heart failure compared with placebo; if there was a difference in outcome in patients designated as having heart failure with preserved ejection fraction compared with heart failure with reduced ejection fraction; and if the efficacy and safety of semaglutide in patients with heart failure was related to baseline characteristics or subtype of heart failure. Methods: The SELECT trial was a randomised, double-blind, multicentre, placebo-controlled, event-driven phase 3 trial in 41 countries. Adults aged 45 years and older, with a BMI of 27 kg/m2 or greater and established cardiovascular disease were eligible for the study. Patients were randomly assigned (1:1) with a block size of four using an interactive web response system in a double-blind manner to escalating doses of once-weekly subcutaneous semaglutide over 16 weeks to a target dose of 2·4 mg, or placebo. In a prespecified analysis, we examined the effect of semaglutide compared with placebo in patients with and without a history of heart failure at enrolment, subclassified as heart failure with preserved ejection fraction, heart failure with reduced ejection fraction, or unclassified heart failure. Endpoints comprised MACE (a composite of non-fatal myocardial infarction, non-fatal stroke, and cardiovascular death); a composite heart failure outcome (cardiovascular death or hospitalisation or urgent hospital visit for heart failure); cardiovascular death; and all-cause death. The study is registered with ClinicalTrials.gov, NCT03574597. Findings: Between Oct 31, 2018, and March 31, 2021, 17 604 patients with a mean age of 61·6 years (SD 8·9) and a mean BMI of 33·4 kg/m2 (5·0) were randomly assigned to receive semaglutide (8803 [50·0%] patients) or placebo (8801 [50·0%] patients). 4286 (24·3%) of 17 604 patients had a history of investigator-defined heart failure at enrolment: 2273 (53·0%) of 4286 patients had heart failure with preserved ejection fraction, 1347 (31·4%) had heart failure with reduced ejection fraction, and 666 (15·5%) had unclassified heart failure. Baseline characteristics were similar between patients with and without heart failure. Patients with heart failure had a higher incidence of clinical events. Semaglutide improved all outcome measures in patients with heart failure at random assignment compared with those without heart failure (hazard ratio [HR] 0·72, 95% CI 0·60-0·87 for MACE; 0·79, 0·64-0·98 for the heart failure composite endpoint; 0·76, 0·59-0·97 for cardiovascular death; and 0·81, 0·66-1·00 for all-cause death; all pinteraction>0·19). Treatment with semaglutide resulted in improved outcomes in both the heart failure with reduced ejection fraction (HR 0·65, 95% CI 0·49-0·87 for MACE; 0·79, 0·58-1·08 for the composite heart failure endpoint) and heart failure with preserved ejection fraction groups (0·69, 0·51-0·91 for MACE; 0·75, 0·52-1·07 for the composite heart failure endpoint), although patients with heart failure with reduced ejection fraction had higher absolute event rates than those with heart failure with preserved ejection fraction. For MACE and the heart failure composite, there were no significant differences in benefits across baseline age, sex, BMI, New York Heart Association status, and diuretic use. Serious adverse events were less frequent with semaglutide versus placebo, regardless of heart failure subtype. Interpretation: In patients with atherosclerotic cardiovascular diease and overweight or obesity, treatment with semaglutide 2·4 mg reduced MACE and composite heart failure endpoints compared with placebo in those with and without clinical heart failure, regardless of heart failure subtype. Our findings could facilitate prescribing and result in improved clinical outcomes for this patient group. Funding: Novo Nordisk