Unveiling diabetes onset: Optimized XGBoost with Bayesian optimization for enhanced prediction.

Diabetes, a chronic condition affecting millions worldwide, necessitates early intervention to prevent severe complications. While accurately predicting diabetes onset or progression remains challenging due to complex and imbalanced datasets, recent advancements in machine learning offer potential solutions. Traditional prediction models, often limited by default parameters, have been superseded by more sophisticated approaches.

Enhancing multiclass COVID-19 prediction with ESN-MDFS: Extreme smart network using mean dropout feature selection technique.

Deep learning and artificial intelligence offer promising tools for improving the accuracy and efficiency of diagnosing various lung conditions using portable chest x-rays (CXRs). This study explores this potential by leveraging a large dataset containing over 6,000 CXR images from publicly available sources. These images encompass COVID-19 cases, normal cases, and patients with viral or bacterial pneumonia.

Stacking based ensemble learning framework for identification of nitrotyrosine sites.

Protein nitrotyrosine is an essential post-translational modification that results from the nitration of tyrosine amino acid residues. This modification is known to be associated with the regulation and characterization of several biological functions and diseases. Therefore, accurate identification of nitrotyrosine sites plays a significant role in the elucidating progress of associated biological signs.

Unconventional Radical and Radical-Hole Site-Based Interactions in Halogen-Bearing Dimers and Trimers: A Comparative Study.

Radical (R) and R-hole site-based interactions are comparatively studied, for the first time, using methods. In this regard, R-bearing molecules XO (where X = Cl, Br, and I) were subjected to direct interaction with NH within dimeric and trimeric forms in the form of NH···XO/XO···NH and NH···XO···NH complexes, respectively. As confirmed by electrostatic potential analysis, the studied R-bearing molecules XO had the outstanding potentiality to interact as Lewis acid centers via two positive sites dubbed as R and R-hole sites.

σ-Hole, lone-pair-hole, and π-hole site-based interactions in aerogen-comprising complexes: a comparative study.

Herein, the potential of ZO and ZF aerogen-comprising molecules (where Z = Ar, Kr, and Xe) to engage in σ-, lp-, and π-hole site-based interactions was comparatively studied using various computations. For the first time, a premier in-depth elucidation of the external electric field (EEF) influence on the strength of the σ-, lp-, and π-hole site-based interactions within the ZO/ZF⋯NH and ⋯NCH complexes was addressed using oriented EEF with disparate magnitude. Upon the energetic features, σ-hole site-based interactions were noticed with the most prominent preferability in comparison to lp- and π-hole analogs.

Aluminium phosphide (AlP) nanocage as a potential sensor for volatile organic compounds: A DFT study.

The efficacy of aluminium phosphide (AlP) nanocage toward sensing methanol (MeOH) and ethanol (EtOH) volatile organic compounds (VOCs) was herein thoroughly elucidated utilizing various density functional theory (DFT) computations. In this perspective, MeOH⋯ and EtOH⋯AlP complexes were investigated within all plausible configurations. According to the energetic features, the EtOH⋯AlP complexes exhibited larger negative values of adsorption and interaction energies with values up to -27.

Hole interactions of aerogen oxides with Lewis bases: an insight into σ-hole and lone-pair-hole interactions.

σ-Hole and lone-pair (lp)-hole interactions of aerogen oxides with Lewis bases (LB) were comparatively inspected in terms of quantum mechanics calculations. The ZO ⋯ LB complexes (where Z = Kr and Xe, = 1, 2, 3 and 4, and LB = NH and NCH) showed favourable negative interaction energies. The complexation features were explained in light of σ-hole and lp-hole interactions within optimum distances lower than the sum of the respective van der Waals radii.

First identification of potato tuber rot caused by , its silver nanoparticles synthesis, characterization and use against harmful pathogens.

Potato is one of the highly consumed vegetable crop grown in different regions across Pakistan that is affected by fungal diseases. The current research was conducted to identify fungal pathogen causing mold-like disease of potato in Khyber Pakhtunkhwa (KP), Pakistan. For molecular identification and characterization of the fungal disease; potato tuber samples were collected followed by culturing on potato dextrose agar (PDA).

Sigma-Hole and Lone-Pair-Hole Site-Based Interactions of Seesaw Tetravalent Chalcogen-Bearing Molecules with Lewis Bases.

For the first time, sigma (σ)- and lone-pair (lp)-hole site-based interactions of SF and SeF molecules in seesaw geometry with NH and FH Lewis bases were herein comparatively investigated. The obtained findings from the electrostatic potential analysis outlined the emergence of sundry holes on the molecular entity of the SF and SeF molecules, dubbed the σ- and lp-holes. The energetic viewpoint announced splendid negative binding energy values for σ-hole site-based interactions succeeded by lp-hole analogues, which were found to be -9.

Green synthesis of cobalt ferrite and Mn doped cobalt ferrite nanoparticles: Anticancer, antidiabetic and antibacterial studies.

Background: CoFeO are important magnetic NPs with high coercivity and moderate magnetization. These properties of CoFeO NPs show variation when doped with various metals. Recent studies explained that Cobalt ferrites doped with metal ion like Mn, have attracted increasing attention in many applications, particularly in biomedical applications.

Identification of novel homozygous missense and deletion mutations manifesting oligospermia infertility in Kashmiri population.

Background: Human male infertility has a lot of known molecular components that have an accurate diagnosis, such as Y chromosome deletion and monogenic causes. Only 4% of all infertile males are diagnosed with genetic causes, while 60-70% of infertile men remain without an accurate diagnosis and are classified as unexplained. Oligospermia is a major cause of human male infertility.

Process optimization, antioxidant, antibacterial, and drug adjuvant properties of bioactive keratin microparticles derived from porcupine () quills.

A structural protein called keratin is often employed in the medical industry to create medication carriers. Process improvement, antioxidant, antibacterial, and adjuvant drug studies of synthetic bioactive keratin microparticles made from lipids and keratin derived from porcupine () quills are the main objectives of this study. After coating the keratin microparticles with lipids which were obtained from the same porcupine quills, the bioactive keratin microparticles were produced.

Adsorption Features of Tetrahalomethanes (CX; X = F, Cl, and Br) on Borophene and Pristine Graphene Nanosheets: A Comparative DFT Study.

The potentiality of the borophene () and pristine graphene (GN) nanosheets to adsorb tetrahalomethanes (CX; X = F, Cl, and Br) were investigated using density functional theory (DFT) methods. To provide a thorough understanding of the adsorption process, tetrel (XC-X∙∙∙/GN)- and halogen (XC-X∙∙∙/GN)-oriented configurations were characterized at various adsorption sites. According to the energetic manifestations, the adsorption process of the CX∙∙∙/GN complexes within the tetrel-oriented configuration led to more desirable negative adsorption energy () values than that within the halogen-oriented analogs.

In-vitro high-throughput library screening-Kinetics and molecular docking studies of potent inhibitors of α-glucosidase.

High throughput screening of synthetic compounds against vital enzymes is the way forward for the determination of potent enzyme inhibitors. In-vitro high throughput library screening of 258 synthetic compounds (comp. 1-258), was performed against α-glucosidase.

Analysis and forecasting of road traffic mortalities in Azad Jammu and Kashmir.

Objective: To analyse road traffic accident mortalities in a geographical region.

Method: The retrospective study was conducted in Azad Jammu and Kashmir based on secondary data from 2004 to 2017 collected from the police department. Duncan's multiple range test was used to assess the trends in road traffic accident fatalities with respect to districts and divisions.

Exploring Probenecid Derived 1,3,4-Oxadiazole-Phthalimide Hybrid as α-Amylase Inhibitor: Synthesis, Structural Investigation, and Molecular Modeling.

1,3,4-Oxadiazole moiety is a crucial pharmacophore in many biologically active compounds. In a typical synthesis, probenecid was subjected to a sequence of reactions to obtain a 1,3,4-oxadiazole-phthalimide hybrid () in high yields. The NMR (H and C) spectroscopic analysis initially confirmed the structure of .

Radiogenomic classification for MGMT promoter methylation status using multi-omics fused feature space for least invasive diagnosis through mpMRI scans.

Accurate radiogenomic classification of brain tumors is important to improve the standard of diagnosis, prognosis, and treatment planning for patients with glioblastoma. In this study, we propose a novel two-stage MGMT Promoter Methylation Prediction (MGMT-PMP) system that extracts latent features fused with radiomic features predicting the genetic subtype of glioblastoma. A novel fine-tuned deep learning architecture, namely Deep Learning Radiomic Feature Extraction (DLRFE) module, is proposed for latent feature extraction that fuses the quantitative knowledge to the spatial distribution and the size of tumorous structure through radiomic features: (GLCM, HOG, and LBP).

Genetic engineering for enhanced biological nitrogen fixation in cereal crops.

Enhancing biological nitrogen (N) fixation in cereal crops has been a long-sought objective. Recently, Yan et al. identified plant compounds that induce biofilm production of diazotrophic bacteria and then performed genetic engineering in order to improve nitrogen fixation in rice plants.

On Suitability of Mixture of Generalized Exponential Models in Modeling Right-Censored Medical Datasets Using Conditional Expectations.

The exploration of suitable models for modeling censored medical datasets is of great importance. There are numerous studies dealing with modeling the censored medical datasets. However, majority of the earlier contributions have utilized the conventional models for modeling the said datasets.