Resistance pattern of methicillin resistant Staphylococcus aureus among nasal isolates of HIV infected patients in a tertiary care hospital

Background: Patients infected with HIV have an increased risk of nasal Staphylococcus aureus carriage as well as consecutive staphylococcal infections and is a major reservoir for MRSA which is potential risk factors for community acquired MRSA. Knowing the Nasal carriage status of Staphylococcus aureus and their Antibiogram will be beneficial for effective management of these patients.Methods: Nasal swab sample were collected from all the participants and processed for culture and identification of Staphylococcus aureus and their antimicrobial sensitivity. All the Staphylococcus aureus isolates were tested for Methicillin resistance by Oxacillin screen agar test, cefoxitin disc diffusion test and further confirmed by mecA gene PCR.Results: In this study out of 220 HIV seropositive patients, 43.64% isolates were confirmed to be S. aureus, 18.75% MRSA and 81.25% were MSSA. Cefoxitin disc diffusion showed 100% specificity (95% CI; 97.05%-100.00%), 100% sensitivity (95% CI; 83.89-100.00%) and 100% accuracy (95% CI; 97.47% to 100.00%) while comparing with gold standard mecA gene PCR. Among the nasal carriers; males (60%) ware dominant on females (40%). 31-50 years age group was strongly associated with MRSA nasal carriage. None of the isolates were resistant against lenozolid, teicoplanin and vancomycin while ampicillin (75%), ciprofloxacin (62.5%), clindamycin (59.38%) and cotrimoxazole (53.13%) showed increased resistance against S. aureus nasal carriage.Conclusions: Resistance among HIV positive persons for all antibiotics showed statistically significant while compared to control group. Cefoxitin disc diffusion can be used as surrogate agent for mecA gene detection

Bacteriological Profile and Antibiotic Resistance Pattern of Pathogens Causing Pyogenic Infections At A Tertiary Care Hospital in Central India

Background: Pyogenic infection is a bacterial infection that leads to the formation of pus. Antibiotics are routinely prescribed to treat these pyogenic bacterial infections, but their toxicity poses a severe threat. It is important to know the antimicrobial resistance profile of such pathogens for proper management of the patients. Objectives: To determine the bacteriological profile and antibiotic resistance pattern of pyogens. Patients and Methods: In this cross sectional study, a total of 678 pus samples were received and processed for aerobic culture from various departments. Standard techniques were used to identify isolates from positive pus cultures, and CLSI standards were used to identify antimicrobial susceptibility patterns. Results: Out of the 678 samples, 347 (51.18%) showed growth of pathogenic bacteria. Two hundred seventeen two (40.11%) Gram positive cocci and 75 (11.06%) Gram negative bacilli isolates were identified. Staphylococcus aureus was the most common isolate (57.5%). Most of the isolates were highly resistant to commonly prescribed antimicrobial drugs like Amoxycillin clavulanate. Most of the gram positive isolates were susceptible to vancomycin, linezolid, and teicoplanin. Most of the Gram-negative isolates were sensitive to imipenem. Conclusion: Microbiological profile findings of pus culture isolates as well as their pattern of antimicrobial resistant may aid in the formulation of antibiotic policies for pyogenic infections

Cooperative federalism VIS-À-VIS government policies in India

This study is an assessment to understand the current nature of Indian Federalism. The country has various forms of government and works in their respective fields and powers. This article explores the concept and meaning of federalism. Further, it also expresses the policies related to federalism followed by respected governments within the purview of India. The study considers the works of governments, governing powers, and the overall implementation of Central Sponsored Schemes regarding the administration of policy on the part of state governments. It is important to research as there is limited information about the same and it also includes the survey within the country. The object of this research is to determine the actual condition of federalism in the country with special reference to central sponsored schemes. And what else it requires to be better in the same components. The research might help for the betterment of working of the government policies mentioned therein

A nomadic multi-agent based privacy metrics for e-health care : a deep learning approach

In recent years, there has been a surge in the use of deep learning systems for e-healthcare applications. While these systems can provide significant benefits regarding improved diagnosis and treatment, they also pose substantial privacy risks to patients' sensitive data. Privacy is a crucial issue in e-healthcare, and it is essential to keep patient information secure. A new approach based on multi-agent-based privacy metrics for e-healthcare deep learning systems has been proposed to address this issue. This approach uses a combination of deep learning and multi-agent systems to provide a more robust and secure method for e-healthcare applications. The multi-agent system is designed to monitor and control the access to patients' data by different agents in the system. Each agent is assigned a specific role and has specific data access permissions. The system employs a set of privacy metrics to a substantial privacy level of the data accessed by each agent. These metrics include confidentiality, integrity, and availability, evaluated in real-time and used to identify potential privacy violations. In addition to the multi-agent system, the deep learning component is also integrated into the system to improve the accuracy of diagnoses and treatment plans. The deep learning model is trained on a large dataset of medical records and can accurately predict the diagnosis and treatment plan based on the patient's symptoms and medical history. The multi-agent-based privacy metrics for the e-healthcare deep learning system approach have several advantages. It provides a more secure system for e-healthcare applications by ensuring only authorized agents can access patients' data. Privacy metrics enable the system to identify potential privacy violations in real-time, thereby reducing the risk of data breaches. Finally, integrating deep learning improves the accuracy of diagnoses and treatment plans, leading to better patient outcomes. [Abstract copyright: © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Comparative Study of Different Approaches for Islanding Detection of Distributed Generation Systems

The issue of unintentional islanding in grid interconnection still remains a challenge in grid-connected, Distributed Generation System (DGS). This study discusses the general overview of popular islanding detection methods. Because of the various Distributed Generation (DG) types, their sizes connected to the distribution networks, and, due to the concern associated with out-of-phase reclosing, anti-islanding continues to be an issue, where no clear solution exists. The passive islanding detection technique is the simplest method to detect the islanding condition which compares the existing parameters of the system having some threshold values. This study first presents an auto-ground approach, which is based on the application of three-phase, short-circuit to the islanded distribution system just to reclose and re-energize the system. After that, the data mining-decision tree algorithm is implemented on a typical distribution system with multiple DGs. The results from both of the techniques have been accomplished and verified by determining the Non-Detection Zone (NDZ), which satisfies the IEEE standards of 2 s execution time. From the analysis, it is concluded that the decision tree approach is effective and highly accurate to detect the islanding state in DGs. These simulations in detail compare the old and new methods, clearly highlighting the progress in the field of islanding detection

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Not AvailableThe study was conducted in Haidergarh block District Barabanki, to identify the training needs of the mushroom cultivators. Seven Villages were selected randomly under Haidergarh block and finally 90 households were selected based on proportionate random sampling produced. A list of 10 major areas of training needs in relation to improved package of practices of mushroom cultivation was prepared. The training areas were ranked based o Training Importance. Sores were measured on three point continuum as Most Essential, Essential and Not Essential by giving scores of 3, 2 and 1 respectively. The primary data were collected using a pre-tested structured interview schedule by conducting personal interview. Findings revealed that majority of the farmers had medium level of training needs. Mushroom cultivation, subject matter relating to loan and intercultural operation were the top most training needs of the farmers and the least training need was identified in the subject related to nursery raising. The variable age and cultivation experience had negative and significant relationship with the training needs. The present study suggested that young having less exposure in requisite training related to improved package of practices of paddy and wheat cultivation may be given preference for imparting training in the prioritized areas of training as identified.Not Availabl