Development of Acceptable Quality Dose (AQD) and image quality-related diagnostic reference levels for common computed tomography investigations in a tertiary care public sector hospital of Khyber Pakhtunkhwa, Pakistan.

PURPOSE: To describe the first experience of patient dose optimization in developing AQD, SSDE and image quality-related DRLs for common CT examinations in the adult age group using the concept of AQD. MATERIALS AND METHODS: The recent published IQSC from 0 to 4 were used by radiologists for the assessment of image quality. The entire data were collected for five types (brain CT, chest CT, chest HRCT, abdomen KUB CT and abdomen + pelvic CT) CT investigations based on anatomic region (head, chest and abdomen + pelvic). The entire datasets of 264 patients were categorized into three groups based on their weights: group-1 (41-60 kg), group-2 (61-80 kg) and group-3 (81-100 kg). Only score-3 images were considered to assess median and 75th percentile values of CTDIvol and DLP to obtain AQDs and DRLs, respectively. RESULTS: Following the practical training of four radiologists on image quality scoring criteria for CT images, 264 (92%) out of 288 patient images were clinically acceptable as per IQSC for the study. The AQD (median) values in terms of CTDIvol for the mentioned weight groups were 25.8, 2.7, and 30.6 mGy, while the median DLP values for these groups were 496, 510 and 557 mGycm, respectively, for brain CT. The 75th percentile values in terms of CTDIvol were 30.2, 35.3 and 36.2 mGy, while in terms of DLP, they were 583, 619 and 781 mGycm for brain CT, respectively. Similar results are presented for the above-mentioned procedures, as well as in terms of SSDE. CONCLUSION: The first ever experience in obtaining AQD, SSDE and DRLs values for specific CT procedures couples image quality with dose indices, showing comparable values with other relevant studies. Hence, it will provide a baseline for comparison within the facility for future studies and facilitate dose optimization for other facilities aiming for improvement.

Predicting inmate suicidal behavior with an interpretable ensemble machine learning approach in smart prisons.

The convergence of smart technologies and predictive modelling in prisons presents an exciting opportunity to revolutionize the monitoring of inmate behaviour, allowing for the early detection of signs of distress and the effective mitigation of suicide risks. While machine learning algorithms have been extensively employed in predicting suicidal behaviour, a critical aspect that has often been overlooked is the interoperability of these models. Most of the work done on model interpretations for suicide predictions often limits itself to feature reduction and highlighting important contributing features only. To address this research gap, we used Anchor explanations for creating human-readable statements based on simple rules, which, to our knowledge, have never been used before for suicide prediction models. We also overcome the limitation of anchor explanations, which create weak rules on high-dimensionality datasets, by first reducing data features with the help of SHapley Additive exPlanations (SHAP). We further reduce data features through anchor interpretations for the final ensemble model of XGBoost and random forest. Our results indicate significant improvement when compared with state-of-the-art models, having an accuracy and precision of 98.6% and 98.9%, respectively. The F1-score for the best suicide ideation model appeared to be 96.7%.

Model simplification and sensitivity analysis of chemical species for oxidation behavior in multi route complex chemical mechanism.

This study employs a Model Reduction Technique (MRT) to simplify the four-step catalytic carbon monoxide (CO) oxidation reaction. The C-matrix method identifies key elements, key/non key components, and key reactions, while the Intrinsic Low-Dimensional Manifold (ILDM) pinpoints a Slow-Invariant Manifold (SIM) important for understanding key species behavior. Sensitivity analysis can be considered for measuring the efficiency of the chemical species in detailed mechanism. This systematic approach contributes to optimizing and controlling complex reactions offering broad application potential. In addition to the mathematical proof, the validation of the given chemical model is rectified. The comparison between the slow invariant manifold of both reaction routes is reported and the computational based results performed in this study are obtained through MATLAB.

Effect of supplementing epinephrine in maturation media on in-vitro developmental competence of cattle and buffalo oocytes.

During in-vitro maturation, the oocyte experiences stressful conditions that likely compromise its development. Epinephrine is a catecholamine that plays a vital role during cellular stress by scavenging free radicals. The hypothesis is that epinephrine addition in maturation media improves the developmental competence of oocytes in cattle and buffalo. The objectives of the experiments were to investigate the effect of epinephrine addition in maturation media on nuclear maturation, developmental competence, and oocyte mRNA abundance of genes related to antioxidants and growth pathways in cattle and buffalo. In experiment 1, cattle oocytes were matured for 24 h in maturation media supplemented with increasing concentrations of epinephrine 0, 0.01, 1.0, and 100 µM. Oocytes were cultured to assess cleavage at 48 h and blastocyst on day 7 of the culture. The cumulus-oocyte complexes (COCs) expansion, nuclear maturation, and oocyte mRNA abundance of genes (SOD1, GPX4, GDF9, CASP9) were evaluated. In experiment 2, buffalo oocytes were matured and assessed for development and mRNA abundance as described for cattle. In addition, the blastomere number was counted in the hatched blastocyst. The data were analyzed using GLIMMIX and MIXED procedures of SAS. Results revealed that the supplementation of epinephrine increased (P ≤ 0.03) the COCs expansion, nuclear maturation, and developmental competence of oocytes in cattle. Interestingly, all the responses were maximized (quadratic effect; P ≤ 0.08) at 1 µM concentrations. The mRNA abundance of genes in cattle oocytes was not affected by the treatment. The experiment in buffalo revealed that epinephrine increased blastocyst formation without affecting COCs expansion, and nuclear maturation. The higher blastocyst was achieved at 0.01 µM concentrations of epinephrine. Interestingly, the addition of epinephrine increased the mRNA abundance of genes related to antioxidant pathways (SOD1, GPX4). Moreover, supplementation of epinephrine increased the blastomere count of the hatched blastocyst in buffalo. In conclusion, epinephrine addition in maturation media benefited oocyte development in cattle and blastocyst yield in buffalo at 1 and 0.01 µM concentrations, respectively. It appears that the addition of epinephrine affected different cellular pathways, COCs expansion, and nuclear maturation in cattle and increased antioxidant genes for buffalo.

Exploring the Therapeutic Potential of Petiveria alliacea L. Phytochemicals: A Computational Study on Inhibiting SARS-CoV-2's Main Protease (Mpro).

The outbreak of SARS-CoV-2, also known as the COVID-19 pandemic, is still a critical risk factor for both human life and the global economy. Although, several promising therapies have been introduced in the literature to inhibit SARS-CoV-2, most of them are synthetic drugs that may have some adverse effects on the human body. Therefore, the main objective of this study was to carry out an in-silico investigation into the medicinal properties of Petiveria alliacea L. (P. alliacea L.)-mediated phytocompounds for the treatment of SARS-CoV-2 infections since phytochemicals have fewer adverse effects compared to synthetic drugs. To explore potential phytocompounds from P. alliacea L. as candidate drug molecules, we selected the infection-causing main protease (Mpro) of SARS-CoV-2 as the receptor protein. The molecular docking analysis of these receptor proteins with the different phytocompounds of P. alliacea L. was performed using AutoDock Vina. Then, we selected the three top-ranked phytocompounds (myricitrin, engeletin, and astilbin) as the candidate drug molecules based on their highest binding affinity scores of -8.9, -8.7 and -8.3 (Kcal/mol), respectively. Then, a 100 ns molecular dynamics (MD) simulation study was performed for their complexes with Mpro using YASARA software, computed RMSD, RMSF, PCA, DCCM, MM/PBSA, and free energy landscape (FEL), and found their almost stable binding performance. In addition, biological activity, ADME/T, DFT, and drug-likeness analyses exhibited the suitable pharmacokinetics properties of the selected phytocompounds. Therefore, the results of this study might be a useful resource for formulating a safe treatment plan for SARS-CoV-2 infections after experimental validation in wet-lab and clinical trials.

Computational Insight into the Physical Properties of Bulk MP (M = Li, Na, K) for Energy Applications.

In this study, we applied density functional theory to compute the electronic, optical, and thermal properties of MP (M = Li, Na, K). We find that the materials under consideration are stable, owing to the lack of negative frequencies in the phonon spectra. LiP exhibits an indirect band gap of 1.43 eV. NaP and KP have direct band gaps of 1.67 and 1.76 eV, respectively. The family of these composites shows strong absorption, observed by their very sharp absorption edges and confirmed by their direct transition from the valence to conduction band. They exhibit strong absorption below 4.0 eV in the optical spectra, which could serve in a solar cell device. The thermal calculations show high zT values of 0.74, 0.78, and 0.64 at 300 K for LiP, NaP, and KP, respectively. Thus, our results could be promising for electronic and thermal devices.

In Silico-Based Identification of Natural Inhibitors from Traditionally Used Medicinal Plants that can Inhibit Dengue Infection.

Dengue fever (DF) is an endemic disease that has become a public health concern around the globe. The NS3 protease-helicase enzyme is an important target for the development of antiviral drugs against DENV (dengue virus) due to its impact on viral replication. Inhibition of the activity of the NS3 protease-helicase enzyme complex significantly inhibits the infection associated with DENV. Unfortunately, there are no scientifically approved antiviral drugs for its prevention. However, this study has been developed to find natural bioactive molecules that can block the activity of the NS3 protease-helicase enzyme complex associated with DENV infection through molecular docking, MM-GBSA (molecular mechanics-generalized born surface area), and molecular dynamics (MD) simulations. Three hundred forty-two (342) compounds selected from twenty traditional medicinal plants were retrieved and screened against the NS3 protease-helicase protein by molecular docking and MM-GBSA studies, where the top six phytochemicals have been identified based on binding affinities. The six compounds were then subjected to pharmacokinetics and toxicity analysis, and we conducted molecular dynamics simulations on three protein-ligand complexes to validate their stability. Through computational analysis, this study revealed the potential of the two selected natural bioactive inhibitors (CID-440015 and CID-7424) as novel anti-dengue agents.

Dietary supplementation of protease and organic acid in poultry by-product meal-based diet in broilers.

Objective: This study investigated the impact of supplementation of protease and organic acid on growth performance and other biological parameters in broilers fed poultry by-product meal (PBM) based diet. Methods: Five hundred-day-old broiler chicks (Ross 308) were distributed into five treatments with 5 replicates, each pen having 20 birds, and fed each group one of five isocaloric and isonitrogenous diets in two phases: stater phase (1-21 days) ME 3000 kcal/kg; CP 22%, and a finisher phase (22-35 days) ME 3200 kcal/kg; CP 19.5%. The dietary treatments were: 1) standard broiler ration (Cont); 2) The control diet with 25% of the soybean meal replaced by poultry by-product meal (PBM) on an equivalent protein basis (PBM); 3) PBM diet supplemented with 0.5 g/kg of protease (PBMP); 4) PBM diet supplemented with 1 g/kg organic acid (PBMO); and 5) PBM diet addition with 0.5 g/kg protease and 1 g/kg organic acid (PBMPO). Results: The overall data showed that FCR was improved (P<0.05) in the PBMP group. Apparent crude protein digestibility was higher (P<0.05) in both Cont and PBMP groups. Jejunal villus height (VH) increased (P<0.05) in PBMP and PBMPO groups, while only the PBMO group exhibited a higher (P<0.05) crypt depth (CD). Lipase activity was increased (P<0.05) in the PBMP, PBMO and PBMPO dietary treatments. However, trypsin activity showed a significant increase (P<0.05) in the PBMP and PBMO groups. Serum biochemistry increased (P<0.05) globulin and total protein levels in the PBMP group. Conclusion: PBM could partially replace the soybean meal with supplementation of either protease or organic acid in broiler diets without impairing overall growth performance. Furthermore, careful optimization must be considered when combining protease and organic acids.

Effective Removal of Nile Blue Dye from Wastewater using Silver-Decorated Reduced Graphene Oxide.

Nile blue (NB) dye is a highly toxic substance that when discharged into sewage presents a significant risk to the environment and human health. Carbon-based nanomaterials, such as graphene oxide (GO), reduced graphene oxide (rGO), and their nanocomposites, offer considerable potential for eliminating hazardous pollutants from aqueous systems. In this study, we have successfully fabricated bare GO and rGO, and then, the rGO was decorated with silver (Ag) nanoparticles to develop the Ag-rGO composite. The as-prepared materials were characterized by various techniques, such as UV-visible (UV-vis) and Fourier transform infrared (FTIR) spectroscopies, X-ray diffraction (XRD), energy-dispersive X-ray (EDX), and scanning electron microscopy (SEM) to elucidate their structure, morphology, and chemical composition. The pollutant removal performance of the as-prepared materials was evaluated through a batch approach under the effect of various experimental variables for removal of NB dye from wastewater. As obvious, the Ag-rGO composite revealed exceptional performance for NB dye removal from wastewater, with a maximum removal percentage of 94% within 60 min, which is remarkably higher than those of the rGO (i.e., 59%) and GO (i.e., 22%), under the same experimental conditions. The adsorption data was analyzed with thermodynamics, isotherms, and kinetics models to better understand the physicochemical mechanisms driving the effective removal of the NB dye. The results reveal that Ag-rGO nanocomposite exhibit excellent adsorption ability as well as favorable thermodynamic and kinetic parameters for NB dye removal. It was also found that the presence of light enhanced the adsorptive removal of NB while using Ag-rGO as an adsorbent. The present study noted significant reusability of the Ag-rGO nanocomposite, likely due to minimal Ag leaching and/or the robust stability of the Ag-rGO. It is suggested that Ag-rGO-based hybrid materials could serve as promising candidates for efficiently adsorbing and catalytically removing various toxic pollutants from wastewater.

Population exposure to emerging perfluoroalkyl acids (PFAAs) via drinking water resources: Application of multivariate statistics and risk assessment models.

This study assessed the occurrence, origins, and potential risks of emerging perfluoroalkyl acids (PFAAs) for the first time in drinking water resources of Khyber Pakhtunkhwa, Pakistan. In total, 13 perfluoroalkyl carboxylic acids (PFCAs) with carbon (C) chains C4-C18 and 4 perfluoroalkyl sulfonates (PFSAs) with C chains C4-C10 were tested in both surface and ground drinking water samples using a high-performance liquid chromatography system (HPLC) equipped with an Agilent 6460 Triple Quadrupole liquid chromatography-mass spectrometry (LC-MS) system. The concentrations of ∑PFCAs, ∑PFSAs, and ∑PFAAs in drinking water ranged from 1.46 to 72.85, 0.30-8.03, and 1.76-80.88 ng/L, respectively. Perfluorobutanoic acid (PFBA), perfluorohexanoic acid (PFHxA), and perfluoropentanoic acid (PFPeA) were the dominant analytes in surface water followed by ground water, while the concentration of perfluorobutane sulfonate (PFBS), perfluorooctanoic acid (PFOA), perfluoroheptanoic acid (PFHpA), perfluorooctane sulfonate (PFOS), perfluorohexane sulfonate (PFHxS), perfluorononanoic acid (PFNA), perfluorodecanoic acid (PFDA), perfluoroundecanoic acid (PFUnDA), and perfluorododecanoic acid (PFDoDA) were greater than long-chain PFOA and PFOS. The correlation statistics, which showed a strong correlation (p < 0.05) between the PFAA analytes, potentially indicated the fate of PFAAs in the area's drinking water sources, whereas the hierarchical cluster analysis (HCA) and principal component analysis (PCA) statistics identified industrial, domestic, agricultural, and commercial applications as potential point and non-point sources of PFAA contamination in the area. From risk perspectives, the overall PFAA toxicity in water resources was within the ecological health risk thresholds, where for the human population the hazard quotient (HQ) values of individual PFAAs were < 1, indicating no risk from the drinking water sources; however, the hazard index (HI) from the ∑PFAAs should not be underestimated, as it may significantly result in potential chronic toxicity to exposed adults, followed by children.

Discovery of Bacterial Key Genes from 16S rRNA-Seq Profiles That Are Associated with the Complications of SARS-CoV-2 Infections and Provide Therapeutic Indications.

SARS-CoV-2 infections, commonly referred to as COVID-19, remain a critical risk to both human life and global economies. Particularly, COVID-19 patients with weak immunity may suffer from different complications due to the bacterial co-infections/super-infections/secondary infections. Therefore, different variants of alternative antibacterial therapeutic agents are required to inhibit those infection-causing drug-resistant pathogenic bacteria. This study attempted to explore these bacterial pathogens and their inhibitors by using integrated statistical and bioinformatics approaches. By analyzing bacterial 16S rRNA sequence profiles, at first, we detected five bacterial genera and taxa (Bacteroides, Parabacteroides, Prevotella Clostridium, Atopobium, and Peptostreptococcus) based on differentially abundant bacteria between SARS-CoV-2 infection and control samples that are significantly enriched in 23 metabolic pathways. A total of 183 bacterial genes were found in the enriched pathways. Then, the top-ranked 10 bacterial genes (accB, ftsB, glyQ, hldD, lpxC, lptD, mlaA, ppsA, ppc, and tamB) were selected as the pathogenic bacterial key genes (bKGs) by their protein-protein interaction (PPI) network analysis. Then, we detected bKG-guided top-ranked eight drug molecules (Bemcentinib, Ledipasvir, Velpatasvir, Tirilazad, Acetyldigitoxin, Entreatinib, Digitoxin, and Elbasvir) by molecular docking. Finally, the binding stability of the top-ranked three drug molecules (Bemcentinib, Ledipasvir, and Velpatasvir) against three receptors (hldD, mlaA, and lptD) was investigated by computing their binding free energies with molecular dynamic (MD) simulation-based MM-PBSA techniques, respectively, and was found to be stable. Therefore, the findings of this study could be useful resources for developing a proper treatment plan against bacterial co-/super-/secondary-infection in SARS-CoV-2 infections.

Investigating Potential Cancer Therapeutics: Insight into Histone Deacetylases (HDACs) Inhibitions.

Histone deacetylases (HDACs) are enzymes that remove acetyl groups from ɛ-amino of histone, and their involvement in the development and progression of cancer disorders makes them an interesting therapeutic target. This study seeks to discover new inhibitors that selectively inhibit HDAC enzymes which are linked to deadly disorders like T-cell lymphoma, childhood neuroblastoma, and colon cancer. MOE was used to dock libraries of ZINC database molecules within the catalytic active pocket of target HDACs. The top three hits were submitted to MD simulations ranked on binding affinities and well-occupied interaction mechanisms determined from molecular docking studies. Inside the catalytic active site of HDACs, the two stable inhibitors LIG1 and LIG2 affect the protein flexibility, as evidenced by RMSD, RMSF, Rg, and PCA. MD simulations of HDACs complexes revealed an alteration from extended to bent motional changes within loop regions. The structural deviation following superimposition shows flexibility via a visual inspection of movable loops at different timeframes. According to PCA, the activity of HDACs inhibitors induces structural dynamics that might potentially be utilized to define the nature of protein inhibition. The findings suggest that this study offers solid proof to investigate LIG1 and LIG2 as potential HDAC inhibitors.

Strategies to alleviate distortive phase transformations in Li-ion intercalation reactions: an example with vanadium pentoxide.

Chemical and electrochemical Li-ion insertion in transition metal oxides, either via a phase transformation reaction (ions insert into specific crystallographic sites of the host lattice) or a solid solution insertion (ions distribute uniformly throughout the host lattice), enables high energy density electrochemical energy storage. Many phase transformation cathode materials, that undergo two-phase reactions, exhibit high theoretical capacities arising from multi-electron redox reactions. However, challenges in distortive phase transformations and uncontrolled phase nucleation, propagation, segregation, and co-existence continue to limit the energy density, (dis)charging rate performances, and cycling stability of available phase transformation cathode materials. Vanadium pentoxide (V2O5), a classical layered intercalation host material with high theoretical capacity, undergoes irreversible structural changes and capacity fading when intercalating more than one lithium ion per V2O5 unit in its thermodynamically stable phase. Here, we review recent synthetic strategies to alter the V-O connectivity, thereby alleviating distortive phase transformations and promoting solid solution-based Li-ion insertion in V2O5. We also summarize several widely accessible and classical molecular-based analytical tools that can provide local structural dynamics and phase transformation mechanism information on the lithiation of V2O5, including single-crystal X-ray diffraction, infrared and Raman spectroscopy, electron paramagnetic resonance, and nuclear magnetic resonance spectroscopy.

The emergence of highly resistant and hypervirulent Klebsiella pneumoniae CC14 clone in a tertiary hospital over 8 years.

BACKGROUND: Klebsiella pneumoniae is a major bacterial and opportunistic human pathogen, increasingly recognized as a healthcare burden globally. The convergence of resistance and virulence in K. pneumoniae strains has led to the formation of hypervirulent and multidrug-resistant strains with dual risk, limiting treatment options. K. pneumoniae clones are known to emerge locally and spread globally. Therefore, an understanding of the dynamics and evolution of the emerging strains in hospitals is warranted to prevent future outbreaks. METHODS: In this study, we conducted an in-depth genomic analysis on a large-scale collection of 328 multidrug-resistant (MDR) K. pneumoniae strains recovered from 239 patients from a single major hospital in the western coastal city of Jeddah in Saudi Arabia from 2014 through 2022. We employed a broad range of phylogenetic and phylodynamic methods to understand the evolution of the predominant clones on epidemiological time scales, virulence and resistance determinants, and their dynamics. We also integrated the genomic data with detailed electronic health record (EHR) data for the patients to understand the clinical implications of the resistance and virulence of different strains. RESULTS: We discovered a diverse population underlying the infections, with most strains belonging to Clonal Complex 14 (CC14) exhibiting dominance. Specifically, we observed the emergence and continuous expansion of strains belonging to the dominant ST2096 in the CC14 clade across hospital wards in recent years. These strains acquired resistance mutations against colistin and extended spectrum ß-lactamase (ESBL) and carbapenemase genes, namely blaOXA-48 and blaOXA-232, located on three distinct plasmids, on epidemiological time scales. Strains of ST2096 exhibited a high virulence level with the presence of the siderophore aerobactin (iuc) locus situated on the same mosaic plasmid as the ESBL gene. Integration of ST2096 with EHR data confirmed the significant link between colonization by ST2096 and the diagnosis of sepsis and elevated in-hospital mortality (p-value < 0.05). CONCLUSIONS: Overall, these results demonstrate the clinical significance of ST2096 clones and illustrate the rapid evolution of an emerging hypervirulent and MDR K. pneumoniae in a clinical setting.

Biochar imparted constructed wetlands (CWs) for enhanced biodegradation of organic and inorganic pollutants along with its limitation.

The remediation of polluted soil and water stands as a paramount task in safeguarding environmental sustainability and ensuring a dependable water source. Biochar, celebrated for its capacity to enhance soil quality, stimulate plant growth, and adsorb a wide spectrum of contaminants, including organic and inorganic pollutants, within constructed wetlands, emerges as a promising solution. This review article is dedicated to examining the effects of biochar amendments on the efficiency of wastewater purification within constructed wetlands. This comprehensive review entails an extensive investigation of biochar's feedstock selection, production processes, characterization methods, and its application within constructed wetlands. It also encompasses an exploration of the design criteria necessary for the integration of biochar into constructed wetland systems. Moreover, a comprehensive analysis of recent research findings pertains to the role of biochar-based wetlands in the removal of both organic and inorganic pollutants. The principal objectives of this review are to provide novel and thorough perspectives on the conceptualization and implementation of biochar-based constructed wetlands for the treatment of organic and inorganic pollutants. Additionally, it seeks to identify potential directions for future research and application while addressing prevailing gaps in knowledge and limitations. Furthermore, the study delves into the potential limitations and risks associated with employing biochar in environmental remediation. Nevertheless, it is crucial to highlight that there is a significant paucity of data regarding the influence of biochar on the efficiency of wastewater treatment in constructed wetlands, with particular regard to its impact on the removal of both organic and inorganic pollutants.

Effect of different concentrations of resveratrol on nuclear maturation and in-vitro development competence of oocytes of Nili Ravi buffalo.

Buffaloes are considered animals of the future with the ability to survive under unfavorable conditions. However, the lack of access to superior germplasm poses a significant challenge to increasing buffalo production. Resveratrol has been shown to improve oocyte quality and developmental competence in various animals during in vitro embryo development. However, limited information is available on the use of resveratrol to improve the in vitro maturation and development competence of Nili Ravi buffalo oocytes. Therefore, the current study aimed to investigate the influence of different concentrations of resveratrol on the maturation, fertilization, and development of buffalo oocytes under in vitro conditions. Oocytes were collected from ovaries and subjected to in vitro maturation (IVM) using varying concentrations of resveratrol (0 µM, 0.5 µM, 1 µM, 1.5 µM, and 2 µM), and the maturation process was assessed using a fluorescent staining technique. Results indicated no significant differences in oocyte maturation, morula rate, and blastocyst rate among the various resveratrol concentrations. However, the cleavage rate notably increased with 1 µM and 1.5 µM concentrations of resveratrol (p < 0.05). In conclusion, the study suggests that adding 1 µM of resveratrol into the maturation media may enhance the cleavage and blastocyst hatching of oocytes of Nili Ravi buffaloes. These findings hold promise for advancing buffalo genetics, reproductive performance, and overall productivity, offering potential benefits to the dairy industry, especially in Asian countries.

Temporal Trends of Age-Adjusted Mortality Rates for Rheumatic Heart Disease in Brazil From 2000 to 2021.

Background Rheumatic heart disease (RHD) is a chronic cardiovascular condition stemming from an infectious origin, posing a substantial health burden, particularly in economically disadvantaged regions. It starts with acute rheumatic fever (ARF), a complication following group A Streptococcus infection, leading to heart valve damage and, over time, structural heart abnormalities. RHD contributes to premature deaths, especially in low-middle-income countries. Although the incidence and prevalence have generally reduced globally due to antibiotics and improved healthcare, it remains a significant public health concern in Brazil, echoing its prevalence in many developing nations around the world. RHD stands as a poignant testament to the intersection of socio-economic disparities and healthcare challenges within Brazil's diverse population. In Brazil, despite advancements in healthcare, RHD continues to impact communities, highlighting the urgent need for enhanced prevention strategies, access to quality healthcare services, and heightened awareness to combat this preventable, yet persistent, cardiac condition. Understanding the epidemiological landscape and socio-cultural factors influencing RHD in Brazil is crucial for developing targeted interventions aimed at mitigating its burden on individuals, families, and the healthcare system at large. Thus, our study focuses on analyzing age-related mortality rates linked to ARF and chronic RHD (ARHD) in Brazil from 2000 to 2021, particularly examining gender disparities. Materials and methods This retrospective cohort study employed a descriptive time-series approach, utilizing comprehensive nationwide data from Brazil spanning from 2000 to 2021 to assess trends in diverse age groups, among both sexes, enabling a detailed analysis of temporal patterns. Mortality data, extracted and categorized meticulously, were subjected to Joinpoint statistical analyses enabling comparative assessments, with average annual percent change (AAPC) and annual percent change (APC) serving as key metrics to quantify and interpret trends over the analyzed period. Results The acute RHD (ARHD)-related mortality declined over the analyzed years supported by AAPC, with higher mortality reduction in females. The age-adjusted mortality rate for "males and females" decreased from 78 to 67 deaths/100,000 from 2000 to 2021. Female mortality dropped from 85 to 69/100,000, and male mortality decreased from 73 to 63/100,000 over the same period. For ARHD, male age groups (20-29, 60-69, 70-79, 80+) showed declining mortality, while the 30-59 age group exhibited an upward. Females AAMR for chronic RHD (CRHD) decreased across all age groups, with significant reductions in the 80 years and above age group from 2000-2002 (APC: -11.94*) and steadily from 2002 onwards (APC: -1.33). Conclusions Our study revealed an overall decline in mortality rates for both acute and CRHD across both sexes. Females consistently exhibited higher mortality rates and a more pronounced reduction compared to males in both acute and CRHD. In ARHD, males experience the highest mortality in the 50-59 age group, while females have a peak in the 40-49 age group. The 60-69 age group had the highest mortality in CRHD for both sexes. Conversely, the 20-29 age group displayed the lowest mortality in CRHD, and the 80-89 age group had the lowest mortality in ARHD.

Exploring Potentilla nepalensis Phytoconstituents: Integrated Strategies of Network Pharmacology, Molecular Docking, Dynamic Simulations, and MMGBSA Analysis for Cancer Therapeutic Targets Discovery.

Potentilla nepalensis belongs to the Rosaceae family and has numerous therapeutic applications as potent plant-based medicine. Forty phytoconstituents (PCs) from the root and stem through n-hexane (NR and NS) and methanolic (MR and MS) extracts were identified in earlier studies. However, the PCs affecting human genes and their roles in the body have not previously been disclosed. In this study, we employed network pharmacology, molecular docking, molecular dynamics simulations (MDSs), and MMGBSA methodologies. The SMILES format of PCs from the PubChem was used as input to DIGEP-Pred, with 764 identified as the inducing genes. Their enrichment studies have shown inducing genes' gene ontology descriptions, involved pathways, associated diseases, and drugs. PPI networks constructed in String DB and network topological analyzing parameters performed in Cytoscape v3.10 revealed three therapeutic targets: TP53 from MS-, NR-, and NS-induced genes; HSPCB and Nf-kB1 from MR-induced genes. From 40 PCs, two PCs, 1b (MR) and 2a (MS), showed better binding scores (kcal/mol) with p53 protein of -8.6 and -8.0, and three PCs, 3a, (NR) 4a, and 4c (NS), with HSP protein of -9.6, -8.7, and -8.2. MDS and MMGBSA revealed these complexes are stable without higher deviations with better free energy values. Therapeutic targets identified in this study have a prominent role in numerous cancers. Thus, further investigations such as in vivo and in vitro studies should be carried out to find the molecular functions and interlaying mechanism of the identified therapeutic targets on numerous cancer cell lines in considering the PCs of P. nepalensis.

QSAR-driven screening uncovers and designs novel pyrimidine-4,6-diamine derivatives as potent JAK3 inhibitors.

This study presents a robust and integrated methodology that harnesses a range of computational techniques to facilitate the design and prediction of new inhibitors targeting the JAK3/STAT pathway. This methodology encompasses several strategies, including QSAR analysis, pharmacophore modeling, ADMET prediction, covalent docking, molecular dynamics (MD) simulations, and the calculation of binding free energies (MM/GBSA). An efficacious QSAR model was meticulously crafted through the employment of multiple linear regression (MLR). The initial MLR model underwent further refinement employing an artificial neural network (ANN) methodology aimed at minimizing predictive errors. Notably, both MLR and ANN exhibited commendable performance, showcasing R2 values of 0.89 and 0.95, respectively. The model's precision was assessed via leave-one-out cross-validation (CV) yielding a Q2 value of 0.65, supplemented by rigorous Y-randomization. , The pharmacophore model effectively differentiated between active and inactive drugs, identifying potential JAK3 inhibitors, and demonstrated validity with an ROC value of 0.86. The newly discovered and designed inhibitors exhibited high inhibitory potency, ranging from 6 to 8, as accurately predicted by the QSAR models. Comparative analysis with FDA-approved Tofacitinib revealed that the new compounds exhibited promising ADMET properties and strong covalent docking (CovDock) interactions. The stability of the new discovered and designed inhibitors within the JAK3 binding site was confirmed through 500 ns MD simulations, while MM/GBSA calculations supported their binding affinity. Additionally, a retrosynthetic study was conducted to facilitate the synthesis of these potential JAK3/STAT inhibitors. The overall integrated approach demonstrates the feasibility of designing novel JAK3/STAT inhibitors with robust efficacy and excellent ADMET characteristics that surpass Tofacitinib by a significant margin.Communicated by Ramaswamy H. Sarma.

In Silico, In Vitro, and In Vivo Evaluation of Caffeine-Coated Nanoparticles as a Promising Therapeutic Avenue for AML through NF-Kappa B and TRAIL Pathways Modulation.

BACKGROUND: Advancements in nanoscience have led to a profound paradigm shift in the therapeutic applications of medicinally important natural drugs. The goal of this research is to develop a nano-natural product for efficient cancer treatment. METHODS AND RESULTS: For this purpose, mesoporous silica nanoparticles (MSNPs) were formulated, characterized, and loaded with caffeine to develop a targeted drug delivery system, i.e., caffeine-coated nanoparticles (CcNPs). In silico docking studies were conducted to examine the binding efficiency of the CcNPs with different apoptotic targets followed by in vitro and in vivo bioassays in respective animal models. Caffeine, administered both as a free drug and in nanomedicine form, along with doxorubicin, was delivered intravenously to a benzene-induced AML model. The anti-leukemic potential was assessed through hematological profiling, enzymatic biomarker analysis, and RT-PCR examination of genetic alterations in leukemia markers. Docking studies show strong inter-molecular interactions between CcNPs and apoptotic markers. In vitro analysis exhibits statistically significant antioxidant activity, whereas in vivo analysis exhibits normalization of the genetic expression of leukemia biomarkers STMN1 and S1009A, accompanied by the restoration of the hematological and morphological traits of leukemic blood cells in nanomedicine-treated rats. Likewise, a substantial improvement in hepatic and renal biomarkers is also observed. In addition to these findings, the nanomedicine successfully normalizes the elevated expression of GAPDH and mTOR induced by exposure to benzene. Further, the nanomedicine downregulates pro-survival components of the NF-kappa B pathway and upregulated P53 expression. Additionally, in the TRAIL pathway, it enhances the expression of pro-apoptotic players TRAIL and DR5 and downregulates the anti-apoptotic protein cFLIP. CONCLUSIONS: Our data suggest that MSNPs loaded with caffeine, i.e., CcNP/nanomedicine, can potentially inhibit transformed cell proliferation and induce pro-apoptotic TRAIL machinery to counter benzene-induced leukemia. These results render our nanomedicine as a potentially excellent therapeutic agent against AML.