Serum Ferritin in Dengue Infection.

Dengue fever (DF), a significant global health issue, particularly impacts tropical and subtropical regions. Elevated serum ferritin levels are increasingly recognized as a biomarker for severe dengue infection. This review examines the role of serum ferritin in diagnosing and prognosticating dengue severity.

Disruptive multiple cell death pathways of bisphenol-A.

Endocrine-disrupting chemicals (EDCs) significantly contribute to health issues by interfering with hormonal functions. Bisphenol A (BPA), a prominent EDC, is extensively utilized as a monomer and plasticizer in producing polycarbonate plastic and epoxy resins, making it one of the highest-demanded chemicals in commercial use. This is the major component used in plastic products, including bottles, containers, storage items, and food serving ware.

Enhanced diabetic retinopathy detection using U-shaped network and capsule network-driven deep learning.

Glaucoma, a severe eye disease leading to irreversible vision loss if untreated, remains a significant challenge in healthcare due to the complexity of its detection. Traditional methods rely on clinical examinations of fundus images, assessing features like optic cup and disc sizes, rim thickness, and other ocular deformities. Recent advancements in artificial intelligence have introduced new opportunities for enhancing glaucoma detection.

Sensorless vector-controlled induction motor drives: Boosting performance with Adaptive Neuro-Fuzzy Inference System integrated augmented Model Reference Adaptive System.

The Model Reference Adaptive System (MRAS) is effective for speed control in sensorless Induction Motor (IM) drives, particularly at zero and very low speeds. This study enhances MRAS's resilience and dynamic performance by integrating an Adaptive Neuro-Fuzzy Inference System (ANFIS) controller into sensorless vector-controlled IM drives. The research addresses challenges related to parameter uncertainties, load variations, and external disturbances through the combination of MRAS and ANFIS.

A comparison of super-resolution microscopy techniques for imaging tightly packed microcolonies of an obligate intracellular bacterium.

Conventional optical microscopy imaging of obligate intracellular bacteria is hampered by the small size of bacterial cells, tight clustering exhibited by some bacterial species and challenges relating to labelling such as background from host cells, a lack of validated reagents, and a lack of tools for genetic manipulation. In this study, we imaged intracellular bacteria from the species Orientia tsutsugamushi (Ot) using five different fluorescence microscopy techniques: standard confocal, Airyscan confocal, instant Structured Illumination Microscopy (iSIM), three-dimensional Structured Illumination Microscopy (3D-SIM) and Stimulated Emission Depletion Microscopy (STED). We compared the ability of each to resolve bacterial cells in intracellular clumps in the lateral (xy) axis, using full width half-maximum (FWHM) measurements of a labelled outer membrane protein (ScaA) and the ability to detect small, outer membrane vesicles external to the cells.