Trends and disparities in heart failure and heart failure with obesity mortality among U.S. adults: A 1999-2020 analysis of geographic, gender, and racial variations using CDC WONDER data.

Background: Heart failure (HF) is a leading cause of hospitalization and mortality, and it poses a significant burden on healthcare systems globally. Obesity is a considerable risk factor for HF and contributes to increased cardiac stress and metabolic demands.

Methods: Data from the CDC WONDER database were examined from 1999-2020 for HF and HF with obesity-related mortality in adults aged 25 years and older at the time of death, using ICD-10 codes.

Integrating GANs, Contrastive Learning, and Transformers for Robust Medical Image Analysis.

Despite the widespread success of convolutional neural networks (CNNs) in general computer vision tasks, their application to complex medical image analysis faces persistent challenges. These include limited labeled data availability, which restricts model generalization; class imbalance, where minority classes are underrepresented and lead to biased predictions; and inadequate feature representation, since conventional CNNs often struggle to capture subtle patterns and intricate dependencies characteristic of medical imaging. To address these limitations, we propose CTNGAN, a unified framework that integrates generative modeling with Generative Adversarial Networks (GANs), contrastive learning, and Transformer architectures to enhance the robustness and accuracy of medical image analysis.

Alkyl Chain-Tuned Fluorescent Sensors: Phenanthroimidazole Derivatives for Selective Detection of Nitroaromatic Compounds Containing Phenolic Group.

In this paper, a series of phenanthroimidazole derivatives 2-(1 H-indol-3-yl)-3a,11b-dihydro-1 H-phenanthro[9,10-d]imidazole(NZ1), 1-hexyl-2-(1 H-indol-3-yl)-3a,11b-dihydro-1 H-phnanthro[9,10-d] imidazole (NZ2) and 1-hexyl-2-(1-hexyl-1 H-indol-3-yl)-1 H-phenanthro[9,10-d] imidazole (NZ3) were synthesized for selective sensing of nitroaromatic compounds used in explosives. The structure was confirmed through nuclear magnetic resonance (NMR) spectroscopy, infrared and single crystal x-ray diffraction data. To ensure the molecules suitability for sensing application, several photophysical characterization were performed.

Dual-model approach for accurate chest disease detection using GViT and swin transformer V2.

The precise detection and localization of abnormalities in radiological images are very crucial for clinical diagnosis and treatment planning. To build reliable models, large and annotated datasets are required that contain disease labels and abnormality locations. Most of the time, radiologists face challenges in identifying and segmenting thoracic diseases such as COVID-19, Pneumonia, Tuberculosis, and lung cancer due to overlapping visual patterns in X-ray images.

MediGuard: Protecting Sensitive Healthcare Data with Privacy-Preserving Language Models.

The integration of large language models (LLMs) into digital healthcare has the potential to significantly improve access to accurate and timely medical advice, especially in underserved areas. However, serious privacy concerns hinder the widespread adoption of LLM-based medical consultation systems, as they often require users to disclose private health information, risking unauthorized exposure and non-compliance with regulations. To address these issues, we introduce MediGuard, a new privacy-preserving LLM framework that dynamically protects sensitive healthcare data throughout the consultation process.

Fluorescence quenching aptitude of carbazole for the detection of nitro-aromatics: a comprehensive experimental analysis and computational studies validation.

Fluorescence quenching studies of carbazole with nitroaromatics were studied and compared with 2-phenyl-1-phenanthro[9,10-]imidazole (M1). Carbazole (CBz) can sense all nitroaromatics, in particular picric acid (PA), whereas M1 responds to the ones having acidic hydrogen. The complex formation constant ( ) and limit of detection (LOD) were measured using the Stern-Volmer plot.

Optimizing ensemble learning for satellite-based multi-hazard monitoring and susceptibility assessment of landslides, land subsidence, floods, and wildfires.

The preparation of accurate multi-hazard susceptibility maps is essential to effective disaster risk management. Past studies have relied mainly on traditional machine learning models, but these models do not perform well for complex spatial patterns. To address this gap, this study uses two meta-heuristic algorithms (Genetic Algorithm (GA) and Particle Swarm Optimization (PSO)) to provide an optimized Random Forest (RF) model with better predictive ability.

Peripartum hypertension and neonatal outcomes across races: 2016-2022.

Background: Maternal hypertension, a major pregnancy complication, can adversely affect newborn health. Our study investigated racial/ethnic disparities in neonatal outcomes among hypertensive pregnant women in the US.

Methods: Using data from the CDC WONDER Natality database, we conducted a retrospective cohort study focusing on live births to hypertensive mothers from 2016 to 2022.

Vagal Nerve Stimulation Device-Induced Second-Degree Heart Block and Sinus Pauses.

A 41-year-old male with a history of preterm birth, intellectual disability, and refractory epilepsy on multiple anti-seizure medications with an active vagus nerve stimulation device (VNS) presented for progressive lethargy and a global decline in health. The symptoms began two years after placement of a second VNS, as the first was removed years earlier due to infection complications. At the time of the lethargy and global decline presentation, the VNS was set at an output of 3.

Action unit based micro-expression recognition framework for driver emotional state detection.

Understanding a driver's emotional state is critical for ensuring road safety and public well-being. Emotions such as anger, fear, disgust, sadness, or happiness can significantly influence driving behavior and decision-making. Facial micro-expressions reveal genuine feelings that people attempt to mask or conceal, offering valuable cues for detecting these emotional states, as they tend to be universally expressed across cultures.

Biomonitoring and bioremediating potential of commonly grown tree species against trace elements with seasonal and site allocation: a region-based study.

Heavy metals-mediated environmental pollution and global warming are two emerging threats to plant and human health worldwide. Several anthropogenic and natural activities with a preference for industrialization and heavy transportation have accelerated heavy metals and CO emissions into aerial and soil environments. For a few decades, woody trees have been considered an effective bioaccumulator or bioindicator tool for pollution assessment processes of air-born pollutants.

Bifunctional Sr(II)-based coordination polymer for sensing of Ba(II)/nitroaromatic compounds and supercapacitor applications.

Main group element-based coordination polymers (CPs) are being widely studied for energy storage and sensing applications because of their structural versatility and electropositive properties. In this work, Sr(II)-CP, namely (SA2), was fabricated utilizing 3,5-pyridine dicarboxylic acid (PDC). The formation of SA2 was confirmed by single-crystal X-ray diffraction (SC-XRD).

Decentralized trust framework for smart cities: a blockchain-enabled cybersecurity and data integrity model.

The rapid evolution of smart cities has led to transformative advancements through the integration of IoT devices, sensors, and data-driven systems, yet has simultaneously exposed critical vulnerabilities in cybersecurity, data integrity, and trust management. This research proposes a Decentralized Trust Framework that leverages blockchain technology, AI-driven threat detection, and a Lightweight Adaptive Proof-of-Stake (LA-PoS) consensus mechanism to address these challenges. The framework integrates three key layers: a Blockchain Layer for decentralized trust and immutability, a Cybersecurity Layer employing cryptographic standards and AI-based anomaly detection, and a Data Integrity Protocol Layer for real-time synchronization and tamper-proof data validation.

Detecting malicious code variants using convolutional neural network (CNN) with transfer learning.

Malware presents a significant threat to computer networks and devices that lack robust defense mechanisms, despite the widespread use of anti-malware solutions. The rapid growth of the Internet has led to an increase in malicious code attacks, making them one of the most critical challenges in network security. Accurate identification and classification of malware variants are crucial for preventing data theft, security breaches, and other cyber risks.

Trifolin inhibits the calcium-driven contraction pathway in vascular smooth muscle.

Trifolin, a bioactive component of the Qingda granule, has demonstrated significant antihypertensive potential; however, its precise mechanisms of action remain largely unknown. This study aimed to investigate the antihypertensive effects of trifolin and unravel its underlying molecular mechanisms. The influence of trifolin on vascular contraction and relaxation and its regulatory effects on ion channels were evaluated through a vascular tension experiment.

A causality investigation into stock prices and macroeconomic indicators in the Indian stock market.

Background Of The Study: The systematic impact of macroeconomic variables on stock market returns makes it crucial to comprehend the link between macroeconomic variables and the stock market. Stock prices are closely linked to macroeconomic indicators, a crucial aspect for investors, policymakers, and researchers in emerging markets like India, influencing investment decisions and policy formulation.

Methods: The autoregressive distributed lag (ARDL) model was used in this study to examine the causal links between specific macroeconomic factors and Indian stock prices from April 2009 to March 2023.

Identification of potential therapeutic targets and epithelial cell signaling pathway for Helicobacter pylori infection using biosurfactants as a novel green antimicrobials: A network pharmacology approach.

The global prevalence of Helicobacter pylori (H. pylori) infection has led to the practice of multiple treatments with antibiotics as the standard treatment strategy. However, antibiotic resistance has led to a decline in therapeutic effectiveness, prompting the exploration of innovative and eco-friendly antimicrobial agents.

Factors Influencing Organisational Politics and their Relationship with Emotional Intelligence and Employee Behavior: A PLS-SEM Modelling.

Background: This study explores the complex relationship between organizational politics, emotional intelligence and employee behavior in contemporary settings. Organizational politics, which is widespread in organizational settings, has a substantial impact on different aspects of employee behavior. Emotional Intelligence has become a vital factor in individuals' capacity to successfully traverse the complexities of an organization.

Enhanced ultrafast cubic nonlinearity in the carbazole-picric acid complex for potential applications in photonic devices: Kerr nonlinearity with two-photon absorption.

Carbazole-based complexes have garnered attention in ultrafast nonlinear optics due to their distinct molecular structures, which facilitate robust nonlinear interactions for promising photonic devices. In this context, we have synthesized a donor-acceptor-based carbazole-picric acid (Cz-PA) complex. Herein, the structure of the complex was confirmed by X-ray crystallography and infrared (IR) spectroscopy.

Decoding Investor Sentiments in the Indian Stock Market: A Structural Equation Modelling Approach.

Background Of The Study: This research examines how psychological and social biases affect individual investors' investing decisions. Investor sentiment significantly influences financial markets, frequently causing stock prices to deviate from their intrinsic values. In rising economies such as India, where retail investors are significantly affected by psychological factors, comprehending these attitudes is crucial.

Isoliensinine promotes vasorelaxation and inhibits constriction by regulating the calcium channel in hypertension: In vitro and in vivo approaches.

Isoliensinine, a bioactive alkaloid derived from Nelumbo nucifera Gaertn, has antihypertension effects. This study investigated its antihypertensive effect and molecular mechanism. Spontaneously hypertensive rats (SHRs) and Wistar Kyoto rats (n = 6 per group) were treated with 2.

The Biological and Agronomic Nexus Behind Protoporphyrinogen IX Oxidase (PPO)-Inhibiting Herbicide Resistance in Crops.

The repeated use of a single herbicide over many years results in the emergence of resistant weeds, posing a significant danger to food security. Current attempts to prevent herbicide-resistant weeds from evolving and spreading rely mostly on the creation of genetically engineered herbicide-resistant crops and the implementation of herbicide rotation strategies with varied modes of action. In recent years, protoporphyrinogen oxidase (PPO)-inhibiting herbicides have gained popularity for weed management in fields as a result of the slow evolution of PPO-inhibitor resistance and the widespread emergence of weed resistance to acetolactate synthase-inhibitor and glyphosate.

Where Adults With Heart Failure Die: Insights From the CDC-WONDER Database.

Background: Heart failure (HF) is associated with high mortality rates and substantial health care costs. While there is growing emphasis on integrating palliative care for patients with HF, limited data exist on the locations where adults with HF spend their final days. The study aimed to analyze the location and circumstances of death among adults with HF in the United States using Centers for Disease Control and Prevention's Wide-ranging Online Data for epidemiological Research data.

Effects and mechanisms of trifolin on attenuating hypertension-induced vascular smooth muscle cell proliferation and collagen deposition in vivo and in vitro.

Trifolin exhibits anti-tumor activities; however, its effect on hypertension remains unknown. This study was performed to investigate trifolin's potential therapeutic effects and underlying mechanisms of action on angiotensin II (Ang II)-induced hypertension in mice and Ang II stimulated A7R5 cells. Mice were randomly allocated into six groups: control, Ang II, Ang II + Trifolin (0.