[18F]FDG- PET/CT in Diagnosis, Staging, and Management of Patients with Langerhans Cell Histiocytosis.

Background: Langerhans cell histiocytosis (LCH), a rare hematological disorder, presents significant diagnostic challenges due to its varied clinical manifestations. This study aims to analyse the use of F-18 fluoro-deoxy-glucose positron emission tomography computed tomography (F-18 FDG PET/CT) in diagnosis, staging, and management of LCH.

Materials And Methods: Fifty-nine patients with LCH were included, who underwent a total of ninety-three F-18 FDG PET/CT scans (including follow-up scans in 19 patients).

Sustainable organic waste management using vermicomposting: a critical review on the prevailing research gaps and opportunities.

Logistic growth of human population, exponential rate in agronomic industries and feeble waste management practices have resulted in the massive generation of organic wastes. Vermicomposting is one of the eco-biotechnological practices to efficiently transform them into stable and nutrient-rich organic manure with the synergetic actions of earthworms and soil microbiota. Vermicompost, a derivative product has the desirable physicochemical traits such as excellent porosity, buffering actions, aeration and water holding capacity.

Comparison of chorion allograft and subepithelial connective tissue autograft in the treatment of gingival recession- A randomized controlled clinical trial.

Background: To compare the clinical outcomes of subepithelial connective tissue graft and chorion membrane along with coronally advanced flap in the treatment of gingival recession.

Methods: A total of 12 patients with 24 sites showing isolated bilateral Miller's class I and II gingival recessions were randomly allocated into two treatment sites. One site, connective tissue graft, (n = 12 sites) while on the contra-lateral site, chorion membrane (n = 12 sites) was used with coronally advanced flap.

Multimodal covid network: Multimodal bespoke convolutional neural network architectures for COVID-19 detection from chest X-ray's and computerized tomography scans.

AI-based tools were developed in the existing works, which focused on one type of image data; either CXR's or computerized tomography (CT) scans for COVID-19 prediction. There is a need for an AI-based tool that predicts COVID-19 detection from chest images such as Chest X-ray (CXR) and CT scans given as inputs. This research gap is considered the core objective of the proposed work.