Guideline-Concordant Antibiotic Treatment for Hospitalised Patients with Community-Acquired Pneumonia and Clinical Outcomes at a Tertiary Hospital in Australia.

Community-acquired pneumonia (CAP) remains a major cause of hospitalisation and death, particularly among older and frail adults. Although treatment guidelines exist, adherence to empiric antibiotic recommendations is variable. This study examined whether receiving guideline-concordant antibiotics for CAP was associated with better short- and long-term clinical outcomes.

Comparative analysis of tuberculosis drug consumption data in public and private sectors across selected districts of Madhya Pradesh.

Objectives: This study aimed to compare drug consumption rates in public and private healthcare sectors between 2018 and 2022 in the Tikamgarh, Datia, and Niwari districts of Madhya Pradesh.

Design: A community-based survey methodology was employed, alongside an analysis of program data and evaluation of anti-TB drug sales and utilization from both healthcare sectors.

Materials And Methods: Data were collected from district hospitals in both the public and private sectors.

Estimate of TB incidence and a critical analysis of programmatic data of TB score from Sub national Certification survey of district Niwari, M.P., India.

Background: India accounted for 26% of the global tuberculosis (TB) burden in 2023, with 27 lakh cases reported and 89% treatment coverage. Madhya Pradesh, a high-burden state, reported 28,299 cases in 2023. The Government of India aims to eliminate TB by 2025 through the Strategic National Campaign (SNC), emphasizing surveillance, early diagnosis, and comprehensive care.

Clinical Instability at Discharge and Post-Discharge Outcomes in Patients with Community-Acquired Pneumonia: An Observational Study.

: Clinical stability within 24 h prior to discharge is a key metric for safe care transitions in hospitalised patients with community-acquired pneumonia (CAP). However, its association with post-discharge outcomes, particularly readmissions, remains underexplored. This study assessed whether clinical instability before discharge is associated with 30-day mortality, readmissions, or a composite of both in hospitalised CAP patients.

A novel adaptive multi-scale wavelet Galerkin method for solving fuzzy hybrid differential equations.

Complex dynamical systems are represented by fuzzy hybrid differential equations (FHDEs), which describe systems that have mixed discrete and continuous behaviours with uncertainty. These equations are indispensable for control engineering, biology, and economic forecasting, as they model real-world phenomena. Nevertheless, it is intrinsically challenging to solve FHDEs because the dynamics, discontinuities, and uncertainties in parameters and conditions are all nonlinear and fuzzy.

Geochemical characterization of heavy metal bearing phases in the sediments of Ganges, India: analyzing the toxicity status of sedimentary environment.

The present study characterizes the heavy metal contamination in the bottom sediments of the Ganga River and the toxicity status of the associated aquatic environment. Cd was identified as a heavy metal of substantial concern, with levels surpassing baseline values, showing the effect of anthropogenic factors such as untreated urban-industrial wastewater and runoff from agricultural regions, among other local causes. The grain size distribution reveals that sediments contain dominant sand fractions (up to 60%), followed by silt and a small percentage of clay fractions.

Active Case Finding (ACF) of Tuberculosis Among School Students: Insights From a Tribal District in Seoni, Madhya Pradesh, India.

Background:  Tuberculosis (TB) remains a major public health concern in India, particularly among tribal populations who face structural and socioeconomic barriers to healthcare access. Despite ongoing efforts by the National Tuberculosis Elimination Program (NTEP), many tribal districts report persistently high TB burdens. Active case finding (ACF) has demonstrated effectiveness in improving early TB detection and reducing transmission.

Deciphering the role of monoacylglycerol lipases (MAGL) under abiotic stress and lipid metabolism in soybean (Glycine max L.).

Monoacylglycerol lipase (MAGL) is involved in the last step of triacylglycerol breakdown by hydrolysing the monoacylglycerol (MAG) to free fatty acid and glycerol. In the present study, 21 and 38 MAGL genes were identified in Glycine max (cultivated soybean) and Glycine soja (wild) genomes, respectively. Gene-specific association performed using whole genome resequencing data by mixed linear model showed a significant association with total seed oil, linolenic, and oleic acid content.

Prevalence and characteristics of potentially avoidable unplanned readmissions: a retrospective cohort study.

ObjectiveUnplanned readmissions are key indicators of hospital care quality, yet research on potentially avoidable unplanned readmissions (PAURs) remains limited. This study aimed to assess the prevalence, causes, and predictors of PAURs in an Australian tertiary hospital.MethodsThis retrospective cohort study included all unplanned readmissions to a general medicine unit between 1 July and 30 September 2022, in South Australia.

Epidemiological Trends and Treatment Outcomes: Findings of a TB Survey From Selected Districts of Madhya Pradesh, India.

Background And Objective: Tuberculosis (TB) remains a significant public health challenge in India, particularly in Madhya Pradesh. In this study, we aimed to examine epidemiological trends and treatment outcomes in TB patients in the Datia and Tikamgarh districts of Madhya Pradesh, from 2018 to 2022, to inform targeted TB control strategies.

Methods: We conducted a retrospective observational study using data from the National TB Elimination Program (NTEP), accessed through the Nikshay portal (a Government of India initiative).

Refining Osmosensing Mechanisms for Crop Resilience: Insights From Glycophytes and Halophytes.

Salinity and drought are major global challenges threatening crop productivity and ecosystem diversity, causing annual losses exceeding US$100 billion. These stresses share a common factor: osmotic stress imposed on plants. While extensive research has explored plant osmotic adjustment mechanisms, the processes underlying osmosensing in plant roots and how this sensing translates into adaptive responses remain poorly understood.

Performance of Machine Learning Models in Predicting 30-Day General Medicine Readmissions Compared to Traditional Approaches in Australian Hospital Setting.

: Hospital readmissions are a key quality metric impacting both patient outcomes and healthcare costs. Traditional logistic regression models, including the LACE index (Length of stay, Admission type, Comorbidity index, and recent Emergency department visits), are commonly used for readmission risk stratification, though their accuracy may be limited by non-linear interactions with other clinical variables. This study compared the predictive performance of non-linear machine learning (ML) models with stepwise logistic regression (LR) and the LACE index for predicting 30-day general medicine readmissions.

Optimized Grasshopper Optimisation Algorithm enabled DETR (DEtection TRansformer) model for skin disease classification.

Skin disease classification is a choir cognate for early diagnosis and therapy. The novelty of this study lies in integrating the Grasshopper Optimisation Algorithm (GOA) with a DETR (DEtection TRansformer) model which is developed for the classification of skin disease. Hyperparameter tuning using GOA optimizes the critical parameters of the proposed model to improve classification accuracy.

Substrate-controlled regioselective C(sp)-H sulfonylation of -aminophenols.

Cu(II)-catalyzed highly regioselective C(sp)-H bond sulfonylation of -aminophenols with sulfonyl hydrazides to obtain arylsulfones is described. The sulfonyl radical generated from sulfonyl hydrazide single-electron transfer (SET) forms a C-S bond with the aminophenol a Cu(II)/Cu(III) catalytic cycle. The synthetic transformations and photophysical properties of the synthesized aryl sulfones have also been investigated.

SkinEHDLF a hybrid deep learning approach for accurate skin cancer classification in complex systems.

Skin cancer represents a significant global public health issue, and prompt and precise detection is essential for effective treatment. This study introduces SkinEHDLF, an innovative deep-learning model that enhances skin cancer classification. SkinEHDLF utilizes the advantages of several advanced models, i.

Investigation of green supply chain management practices and sustainability in Indian manufacturing enterprises using a structural equation modelling approach.

Green Supply Chain Management (GSCM) has gained increasing attention as a means of ensuring sustainable manufacturing and a sustainable society. This study examines the relationship between GSCM practices and top management performance to understand its effect on low-carbon performance, sustainable manufacturing, and sustainable society. Data were gathered from 389 top-, middle-, and lower-level managers working in bag-manufacturing firms in India.

Hybrid convolutional neural network and bi-LSTM model with EfficientNet-B0 for high-accuracy breast cancer detection and classification.

Breast cancer detection remains one of the most challenging problems in medical imaging. We propose a novel hybrid model that integrates Convolutional Neural Networks (CNNs), Bidirectional Long Short-Term Memory (Bi-LSTM) networks, and EfficientNet-B0, a pre-trained model. By leveraging EfficientNet-B0, which has been trained on the large and diverse ImageNet dataset, our approach benefits from transfer learning, enabling more efficient feature extraction from mammographic images compared to traditional methods that require CNNs to be trained from scratch.

A novel hybrid framework for efficient higher order ODE solvers using neural networks and block methods.

In this paper, the author introduces the Neural-ODE Hybrid Block Method, which serves as a direct solution for solving higher-order ODEs. Many single and multi-step methods employed in numerical approximations lose their stability when applied in the solution of higher-order ODEs with oscillatory and/or exponential features, as in this case. A new hybrid approach is formulated and implemented, which incorporates both the approximate power of neural networks and the stability and robustness of block numerical methods.

Hybrid parking space prediction model: integrating ARIMA, Long short-term memory (LSTM), and backpropagation neural network (BPNN) for smart city development.

Parking space prediction is a significant aspect of smart cities. It is essential for addressing traffic congestion challenges and low parking availability in urban areas. The present research mainly focuses on proposing a novel scalable hybrid model for accurately predicting parking space.

A Clinical Practice-Based Comparison of Conventional and Individualized Dosing Strategies for Therapeutic Enoxaparin.

To understand differences in anti-factor-Xa levels produced by two different dosing strategies (conventional and individualized) for therapeutic enoxaparin in a cohort of hospital inpatients. A multicenter, retrospective cohort study over a two- and a half-year period for inpatients with stable renal function and on therapeutic enoxaparin. Anti-factor-Xa levels were taken 3-5 h after enoxaparin administration and a minimum of 48 h of dosing.

Significance of the Powder Metallurgy Approach and Its Processing Parameters on the Mechanical Behavior of Magnesium-Based Materials.

Magnesium-based materials, which are known for their light weight and exceptional strength-to-weight ratio, hold immense promise in the biomedical, automotive, aerospace, and military sectors. However, their inherent limitations, including low wear resistance and poor mechanical properties, have driven the development of magnesium-based metal matrix composites (Mg-MMCs). The pivotal role of powder metallurgy (PM) in fabricating Mg-MMCs was explored, enhancing their mechanical and corrosion resistance characteristics.

Potential Role of TIP3 Aquaporins in the Transport of HO and Boric Acid During Seed Development and Germination in Soybean (Glycine max L.).

Tonoplast intrinsic proteins (TIPs) are the channel-forming proteins predominantly found in the tonoplast of plant cells. Despite the identification of TIPs in numerous plant species, very less is known about the precise role of different TIP subgroups. In the present study, two genes belonging to the TIP3 subgroup were studied to understand tissue-specific role and solute transport activity.

Gait-based Parkinson's disease diagnosis and severity classification using force sensors and machine learning.

A dual-stage model for classifying Parkinson's disease severity, through a detailed analysis of Gait signals using force sensors and machine learning approaches, is proposed in this study. Parkinson's disease is the primary neurodegenerative disorder that results in a gradual reduction in motor function. Early detection and monitoring of the disease progression is highly challenging due to the gradual progression of symptoms and the inadequacy of conventional methods in identifying subtle changes in mobility.

Palladium-Catalyzed Intramolecular C-H Amination via Oxidative Coupling on Indole Derivatives: Access to 11-Benzo[4,5]imidazo[1,2-]indoles.

A novel palladium-catalyzed intramolecular C-H amination via oxidative coupling exploiting inactivated N-substituted aryl amines on indoles for the one-pot synthesis of novel 11-benzo[4,5]imidazo[1,2-]indole derivatives is reported. The optimized reaction conditions accommodated a wide range of electronic variations on both the indole and the pendant aryl amine ring, resulting in products with good to excellent yields.