BC-QNet: A quantum-infused ELM model for breast cancer diagnosis

The timely and accurate diagnosis of breast cancer is pivotal for effective treatment, but current automated mammography classification methods have their constraints. In this study, we introduce an innovative hybrid model that marries the power of the Extreme Learning Machine (ELM) with FuNet transfer learning, harnessing the potential of the MIAS dataset. This novel approach leverages an Enhanced Quantum-Genetic Binary Grey Wolf Optimizer (Q-GBGWO) within the ELM framework, elevating its performance. Our contributions are twofold: firstly, we employ a feature fusion strategy to optimize feature extraction, significantly enhancing breast cancer classification accuracy. The proposed methodological motivation stems from optimizing feature extraction for improved breast cancer classification accuracy. The Q-GBGWO optimizes ELM parameters, demonstrating its efficacy within the ELM classifier. This innovation marks a considerable advancement beyond traditional methods. Through comparative evaluations against various optimization techniques, the exceptional performance of our Q-GBGWO-ELM model becomes evident. The classification accuracy of the model is exceptionally high, with rates of 96.54 % for Normal, 97.24 % for Benign, and 98.01 % for Malignant classes. Additionally, the model demonstrates a high sensitivity with rates of 96.02 % for Normal, 96.54 % for Benign, and 97.75 % for Malignant classes, and it exhibits impressive specificity with rates of 96.69 % for Normal, 97.38 % for Benign, and 98.16 % for Malignant classes. These metrics are reflected in its ability to classify three different types of breast cancer accurately. Our approach highlights the innovative integration of image data, deep feature extraction, and optimized ELM classification, marking a transformative step in advancing early breast cancer detection and enhancing patient outcomes.

Uncovering PPAR-γ agonists: An integrated computational approach driven by machine learning

Peroxisome proliferator-activated receptor gamma (PPAR-γ) serves as a nuclear receptor with a pivotal function in governing diverse facets of metabolic processes. In diabetes, the prime physiological role of PPAR-γ is to enhance insulin sensitivity and regulate glucose metabolism. Although PPAR-γ agonists such as Thiazolidinediones are effective in addressing diabetes complications, it is vital to be mindful that they are associated with substantial side effects that could potentially give rise to health challenges. The recent surge in the discovery of selective modulators of PPAR-γ inspired us to formulate an integrated computational strategy by leveraging the promising capabilities of both machine learning and in silico drug design approaches. In pursuit of our objectives, the initial stage of our work involved constructing an advanced machine learning classification model, which was trained utilizing chemical information and physicochemical descriptors obtained from known PPAR-γ modulators. The subsequent application of machine learning-based virtual screening, using a library of 31,750 compounds, allowed us to identify 68 compounds having suitable characteristics for further investigation. A total of four compounds were identified and the most favorable configurations were complemented with docking scores ranging from -8.0 to -9.1 kcal/mol. Additionally, the compounds engaged in hydrogen bond interactions with essential conserved residues including His323, Leu330, Phe363, His449 and Tyr473 that describe the ligand binding site. The stability indices investigated herein for instance root-mean-square fluctuations in the backbone atoms indicated higher mobility in the region of orthosteric site in the presence of agonist with the deviation peaks in the range of 0.07-0.69 nm, signifying moderate conformational changes. The deviations at global level revealed that the average values lie in the range of 0.25-0.32 nm. In conclusion, our identified hits particularly, CHEMBL-3185642 and CHEMBL-3554847 presented outstanding results and highlighted the stable conformation within the orthosteric site of PPAR-γ to positively modulate the activity.

Exploring the mechanism of action of spirooxindoles as a class of CDK2 inhibitors: a structure-based computational approach

Cyclin-dependent kinase 2 (CDK2) regulates cell cycle checkpoints in the synthesis and mitosis phases and plays a pivotal role in cancerous cell proliferation. The activation of CDK2, influenced by various protein signaling pathways, initiates the phosphorylation process. Due to its crucial role in carcinogenesis, CDK2 is a druggable hotspot target to suppress cancer cell proliferation. In this context, several studies have identified spirooxindoles as an effective class of CDK2 inhibitors. In the present study, three spirooxindoles (SOI1, SOI2, and SOI3) were studied to understand their inhibitory mechanism against CDK2 through a structure-based approach. Molecular docking and molecular dynamics (MD) simulations were performed to explore their interactions with CDK2 at the molecular level. The calculated binding free energy for the spirooxindole-based CDK2 inhibitors aligned well with experimental results regarding CDK2 inhibition. Energy decomposition (ED) analysis identified key binding residues, including I10, G11, T14, R36, F82, K89, L134, P155, T158, Y159, and T160, in the CDK2 active site and T-loop phosphorylation. Molecular mechanics (MM) energy was identified as the primary contributor to stabilizing inhibitor binding in the CDK2 protein structure. Furthermore, the analysis of binding affinity revealed that the inhibitor SOI1 binds more strongly to CDK2 compared to the other inhibitors under investigation. It demonstrated a robust interaction with the crucial residue T160 in the T-loop phosphorylation site, responsible for kinase activation. These insights into the inhibitory mechanism are anticipated to contribute to the development of potential CDK2 inhibitors using the spirooxindole scaffold.

Composite Aerogel Scaffolds Containing Flexible Silica Nanofiber and Tricalcium Phosphate Enable Skin Regeneration

Poor hemostatic ability and less vascularization at the injury site could hinder wound healing as well as adversely affect the quality of life (QOL). An ideal wound dressing should exhibit certain characteristics: (a) good hemostatic ability, (b) rapid wound healing, and (c) skin appendage formation. This necessitates the advent of innovative dressings to facilitate skin regeneration. Therapeutic ions, such as silicon ions (Si4+) and calcium ions (Ca2+), have been shown to assist in wound repair. The Si4+ released from silica (SiO2) can upregulate the expression of proteins, including the vascular endothelial growth factor (VEGF) and alpha smooth muscle actin (α-SMA), which is conducive to vascularization; Ca2+ released from tricalcium phosphate (TCP) can promote the coagulation alongside upregulating the expression of cell migration and cell differentiation related proteins, thereby facilitating the wound repair. The overarching objective of this study was to exploit short SiO2 nanofibers along with the TCP to prepare TCPx@SSF aerogels and assess their wound healing ability. Short SiO2 nanofibers were prepared by electrospinning and blended with varying proportions of TCP to afford TCPx@SSF aerogel scaffolds. The TCPx@SSF aerogels exhibited good cytocompatibility in a subcutaneous implantation model and manifested a rapid hemostatic effect (hemostatic time 75 s) in a liver trauma model in the rabbit. These aerogel scaffolds also promoted skin regeneration and exhibited rapid wound closure, epithelial tissue regeneration, and collagen deposition. Taken together, TCPx@SSF aerogels may be valuable for wound healing.

Genome wide analysis of carotenoid cleavage oxygenases (CCO) gene family in Arachis hypogaea (peanut) under biotic stress

Carotenoid cleavage oxygenases (CCOs) enzymes play a vital role in plant growth and development through the synthesis of apocarotenoids and their derivative. These chemicals are necessary for flower and fruit coloration, as well as the manufacture of plant hormones such as abscisic acid (ABA) and strigolactones, which control a variety of physiological processes. The CCOs gene family has not been characterized in Arachis hypogaea. Genome mining of A. hypogaea identifies 24 AhCCO gene members. The AhCCO gene family was divided into two subgroups based on the recent study of the Arabidopsis thaliana CCO gene family classification system. Twenty-three AhCCO genes, constituting 95.8% of the total, were regulated by 29 miRNAs, underscoring the significance of microRNAs (miRNAs) in governing gene expression in peanuts. AhCCD19 is the only gene that lacks a miRNA target site. The physicochemical characteristics of CCO genes and their molecular weights and isoelectric points were studied further. The genes were then characterized regarding chromosomal distribution, structure, and promoter cis-elements. Light, stress development, drought stress, and hormone responsiveness were discovered to be associated with AhCCO genes, which can be utilized in developing more resilient crops. The investigation also showed the cellular location of the encoded proteins and discovered that the peanut carotenoid oxygenase gene family's expansion was most likely the result of tandem, segmental, and whole-genome duplication events. The localization expresses the abundance of genes mostly in the cytoplasm and chloroplast. Expression analysis shows that AhCCD7 and AhCCD14 genes show the maximum expression in the apical meristem, lateral leaf, and pentafoliate leaf development, while AhNCED9 and AhNCED13 express in response to Aspergillus flavus resistance. This knowledge throws light on the evolutionary history of the AhCCO gene family and may help researchers better understand the molecular processes behind gene duplication occurrences in plants. An integrated synteny study was used to find orthologous carotenoid oxygenase genes in A. hypogaea, whereas Arabidopsis thaliana and Beta vulgaris were used as references for the functional characterization of peanut CCO genes. These studies provide a foundation for future research on the regulation and functions of this gene family. This information provides valuable insights into the genetic regulation of AhCCO genes. This technology could create molecular markers for breeding programs to develop new peanut lines.

Coupling of phycoremediation and phytoremediation technologies to treat tannery effluents with rainwater dilutions

From tannery effluent (TE) severely polluted with heavy metals (HMs viz., Cr, Cu, Cd, and Pb), hydrophytic phytoextraction remains a challenge as transplanted plants succumb to death on facing acclimatization shock. Current study was aimed at diluting TE with harvested rainwater (HR) for improving HM phytoextraction potential of Phragmites australis (a hydrophyte) assisted with phycoremediation of coupled algae (viz., Oedogonium sp. and Pithophora sp.). The TE:HR dilutions (TEDs) 0, 25, 50, 75, and 100% (v/v) included three sets: set-1 included algae only, set-2 included P. australis only and set-3 included P. australis coupled with combined algal inoculum. Results showed that P. australis assisted with HR dilution and combined algal inoculum showed significantly greater uptake of HMs from each of the TEDs than respective control treatments. Combined algal application in the TEDs proved phycoremediation assistants based on their bioaccumulation factor (BF). The dry biomass of P. australis in TEDs applied with phycoremediation assistants remained greater than uninoculated ones. Overall, HM translocation factor (TF) of P. australis for Cr, Cu, Cd, and Pb remained ≥ 1. The study concludes that HM phytoextraction is substantially increased when concentrated TE is diluted with HR and assisted with phycoremediation of HM tolerant algae.

Genetics aspect of vitamin C (Ascorbic Acid) biosynthesis and signaling pathways in fruits and vegetables crops

Vitamin C, also known as ascorbic acid, is an essential nutrient that plays a critical role in many physiological processes in plants and animals. In humans, vitamin C is an antioxidant, reducing agent, and cofactor in diverse chemical processes. The established role of vitamin C as an antioxidant in plants is well recognized. It neutralizes reactive oxygen species (ROS) that can cause damage to cells. Also, it plays an important role in recycling other antioxidants, such as vitamin E, which helps maintain the overall balance of the plant's antioxidant system. However, unlike plants, humans cannot synthesize ascorbic acid or vitamin C in their bodies due to the absence of an enzyme called gulonolactone oxidase. This is why humans need to obtain vitamin C through their diet. Different fruits and vegetables contain varying levels of vitamin C. The biosynthesis of vitamin C in plants occurs primarily in the chloroplasts and the endoplasmic reticulum (ER). The biosynthesis of vitamin C is a complex process regulated by various factors such as light, temperature, and plant hormones. Recent research has identified several key genes that regulate vitamin C biosynthesis, including the GLDH and GLDH genes. The expression of these genes is known to be regulated by various factors such as light, temperature, and plant hormones. Recent studies highlight vitamin C's crucial role in regulating plant stress response pathways, encompassing drought, high salinity, and oxidative stress. The key enzymes in vitamin C biosynthesis are L-galactose dehydrogenase (GLDH) and L-galactono-1, 4-lactone dehydrogenase (GLDH). Genetic studies reveal key genes like GLDH and GLDH in Vitamin C biosynthesis, offering potential for crop improvement. Genetic variations influence nutritional content through their impact on vitamin C levels. Investigating the roles of genes in stress responses provides insights for developing resilient techniques in crop growth. Some fruits and vegetables, such as oranges, lemons, and grapefruits, along with strawberries and kiwi, are rich in vitamin C. Guava. Papaya provides a boost of vitamin C and dietary fiber. At the same time, red and yellow bell peppers, broccoli, pineapple, mangoes, and kale are additional sources of this essential nutrient, promoting overall health. In this review, we will discuss a brief history of Vitamin C and its signaling and biosynthesis pathway and summarize the regulation of its content in various fruits and vegetables.

Genome-wide identification and in-silico expression analysis of CCO gene family in sunflower (Helianthus annnus) against abiotic stress

Carotenoid cleavage oxygenases (CCOs) enzymes play an important role in plant growth and development by producing a wide array of apocarotenoids and their derivatives. These compounds are vital for colouring flowers and fruits and synthesizing plant hormones such as abscisic acid and strigolactones. Despite their importance, the gene family responsible for CCO enzymes in sunflowers has not been identified. In this study, we identify the CCO genes of the sunflower plant to fill this knowledge gap. Phylogenetic and synteny analysis indicated that the Helianthus annnus CCO (HaCCO) genes were conserved in different plant species and they could be divided into three subgroups based on their conserved domains. Analysis using MEME tool and multiple sequence alignment identified conserved motifs in the HaCCO gene sequence. Cis-regulatory elements (CREs) analysis of the HaCCO genes indicated the presence of various responsive elements related to plant hormones, development, and responses to both biotic and abiotic stresses. This implies that these genes may respond to plant hormones, developmental cues, and drought stress, offering potential applications in the development of more resistant crops. Genes belonging to the 9-cis-epoxy carotenoid dioxygenases (NCED) subgroups predominantly exhibited chloroplast localization, whereas the genes found in other groups are primarily localized in the cytoplasm. These 21 identified HaCCOs were regulated by 60 miRNAs, indicating the crucial role of microRNAs in gene regulation in sunflowers. Gene expression analysis under drought stress revealed significant up-regulation of HaNCED16 and HaNCED19, genes that are pivotal in ABA hormone biosynthesis. During organ-specific gene expression analysis, HaCCD12 and HaCCD20 genes exhibit higher activity in leaves, indicating a potential role in leaf pigmentation. This study provides a foundation for future research on the regulation and functions of the CCO gene family in sunflower and beyond. There is potential for developing molecular markers that could be employed in breeding programs to create new sunflower lines resistant to biotic and abiotic stresses.

Genome-wide analysis of NPR1-like genes in citrus species and expression analysis in response to citrus canker (Xanthomonas axonopodis pv. citri)

Citrus fruits, revered for their nutritional value, face significant threats from diseases like citrus canker, particularly impacting global citrus cultivation, notably in Pakistan. This study delves into the critical role of NPR1-like genes, the true receptors for salicylic acid (SA), in the defense mechanisms of citrus against Xanthomonas axonopodis pv. citri (Xcc). By conducting a comprehensive genome-wide analysis and phylogenetic study, the evolutionary dynamics of Citrus limon genes across diverse citrus cultivars are elucidated. Structural predictions unveil conserved domains, such as the BTB domain and ankyrin repeat domains, crucial for the defense mechanism. Motif analysis reveals essential conserved patterns, while cis-regulatory elements indicate their involvement in transcription, growth, response to phytohormones, and stress. The predominantly cytoplasmic and nuclear localization of NPR1-like genes underscores their pivotal role in conferring resistance to various citrus species. Analysis of the Ks/Ka ratio indicates a purifying selection of NPR1-like genes, emphasizing their importance in different species. Synteny and chromosomal mapping provide insights into duplication events and orthologous links among citrus species. Notably, Xac infection stimulates the expression of NPR1-like genes, revealing their responsiveness to pathogenic challenges. Interestingly, qRT-PCR profiling post-Xac infection reveals cultivar-specific alterations in expression within susceptible and resistant citrus varieties. Beyond genetic factors, physiological parameters like peroxidase, total soluble protein, and secondary metabolites respond to SA-dependent PR genes, influencing plant characteristics. Examining the impact of defense genes (NPR1) and plant characteristics on disease resistance in citrus, this study marks the inaugural investigation into the correlation between NPR1-associated genes and various plant traits in both susceptible and resistant citrus varieties to citrus bacterial canker.

Assessing the efficacy of cinnamon compounds against H. pylori through molecular docking, MD Simulations and ADMET analyses

Antibiotics are the drugs that are used for the management of microbial diseases. However, these conventional synthetic drugs can harmfully affect the human health. Since phytochemicals are extracted from natural sources and, are hence relatively safer for human health, they are the enticing alternatives in this regard. Cinnamon is also one of those plants which is being employed as herbal medication for centuries against certain microbial infections due its significant therapeutic effectiveness. A well-known pathogenic bacterium called H. pylori causes a wide range of illnesses in human body. This pathogen's pathogenicity is determined by certain virulent proteins. In this study, some of such proteins, which included virB4, virB8, and virB9 were selected to evaluate the therapeutic efficiency of cinnamon compounds. These proteins were identified in different isolates of H. pylori. The structural modelling of all these proteins were performed initially in order to proceed them for molecular docking analysis. While, the docking studies illustrated that one of the cinnamon compounds, cinnamyl acetate, showed significant binding interactions with virB4 and virB9. However, benzyl benzoate which is another cinnamon compound, docked well with virB8. Afterwards, the MD simulations were incorporated to explore the interaction motions and structural stability of all the docked complexes. In this regard, the resultant maps of Bfactor, eigenvalues and elastic network model, among other factors ensured the structural stabilities of all the respective complexes. After these crucial estimations, benzyl benzoate and cinnamyl acetate underwent the ADMET investigation to assess their pharmacokinetic characteristics. SwissADME and ADMETLab 2.0 server were employed for this investigation. The compiled findings these servers revealed that both, benzyl benzoate and cinnamyl acetate, exhibited a significant level of pharmacokinetic and drug-likeness conformity.

Genome-wide analysis of plant specific YABBY transcription factor gene family in carrot (Dacus carota) and its comparison with Arabidopsis

YABBY gene family is a plant-specific transcription factor with DNA binding domain involved in various functions i.e. regulation of style, length of flowers, and polarity development of lateral organs in flowering plants. Computational methods were utilized to identify members of the YABBY gene family, with Carrot (Daucus carota) 's genome as a foundational reference. The structure of genes, location of the chromosomes, protein motifs and phylogenetic investigation, syntony and transcriptomic analysis, and miRNA targets were analyzed to unmask the hidden structural and functional characteristics YABBY gene family in Carrots. In the following research, it has been concluded that 11 specific YABBY genes irregularly dispersed on all 9 chromosomes and proteins assembled into five subgroups i.e. AtINO, AtCRC, AtYAB5, AtAFO, and AtYAB2, which were created on the well-known classification of Arabidopsis. The wide ranges of YABBY genes in carrots were dispersed due to segmental duplication, which was detected as prevalent when equated to tandem duplication. Transcriptomic analysis showed that one of the DcYABBY genes was highly expressed during anthocyanin pigmentation in carrot taproots. The cis-regulatory elements (CREs) analysis unveiled elements that particularly respond to light, cell cycle regulation, drought induce ability, ABA hormone, seed, and meristem expression. Furthermore, a relative study among Carrot and Arabidopsis genes of the YABBY family indicated 5 sub-families sharing common characteristics. The comprehensive evaluation of YABBY genes in the genome provides a direction for the cloning and understanding of their functional properties in carrots. Our investigations revealed genome-wide distribution and role of YABBY genes in the carrots with best-fit comparison to Arabidopsis thaliana.

Methacrylated gelatin and platelet-rich plasma based hydrogels promote regeneration of critical-sized bone defects

Physiological repair of large-sized bone defects requires instructive scaffolds with appropriate mechanical properties, biocompatibility, biodegradability, vasculogenic ability and osteo-inductivity. The objective of this study was to fabricate in situ injectable hydrogels using platelet-rich plasma (PRP)-loaded gelatin methacrylate (GM) and employ them for the regeneration of large-sized bone defects. We performed various biological assays as well as assessed the mechanical properties of GM@PRP hydrogels alongside evaluating the release kinetics of growth factors (GFs) from hydrogels. The GM@PRP hydrogels manifested sufficient mechanical properties to support the filling of the tissue defects. For biofunction assay, the GM@PRP hydrogels significantly improved cell migration and angiogenesis. Especially, transcriptome RNA sequencing of human umbilical vein endothelial cells and bone marrow-derived stem cells were performed to delineate vascularization and biomineralization abilities of GM@PRP hydrogels. The GM@PRP hydrogels were subcutaneously implanted in rats for up to 4 weeks for preliminary biocompatibility followed by their transplantation into a tibial defect model for up to 8 weeks in rats. Tibial defects treated with GM@PRP hydrogels manifested significant bone regeneration as well as angiogenesis, biomineralization, and collagen deposition. Based on the biocompatibility and biological function of GM@PRP hydrogels, a new strategy is provided for the regenerative repair of large-size bone defects.

Evaluation of chalcones as new glycogen phosphorylase inhibitors - an in-vitro and in-silico approach

Diabetes mellitus (DM) remains one of the pivotal diseases that have drawn the attention of researchers recently and during the last few decades. Due to its devastating symptoms, attempts to develop new drugs with mild side effects have resulted in a number of drugs that are functioning through various mechanisms. Among these, Glycogen phosphorylase (GP) inhibitors emerged as a new strategy for combating DM. GP is an enzyme that regulates blood glucose levels; it catalyses the breakdown of glycogen to glucose-1-phosphate in the liver and tissues with high and fluctuating energy demands. In the present research, we evaluate the possibility of type 2 diabetes therapy with the help of chalcones which are known to have antidiabetic activities. For this purpose, 29 chalcones were modelled, synthesised and investigated for their inhibitory activity against GP using in-vitro methods. Compounds 1, 2, and 3 were found to be the most potent compounds with IC50 values 26.6, 57.1 and 75.6 µM respectively. The observed results were further validated using in-silico methods. Molecular docking simulation revealed interaction patterns that explain the structure-activity relationships of the compounds with GP. Molecular dynamic (MD) simulation demonstrated a stable complex formation between compound 1 and GP through lower value and uniformity in root mean square deviation (RMSD) of the complex and root mean square fluctuation (RMSF) of the protein Cα.

NIMEQ-SACNet: A novel self-attention precision medicine model for vision-threatening diabetic retinopathy using image data

In the realm of precision medicine, the potential of deep learning is progressively harnessed to facilitate intricate clinical decision-making, especially when navigating multifaceted datasets encompassing Omics, Clinical, image, device, social, and environmental dimensions. This study accentuates the criticality of image data, given its instrumental role in detecting and classifying vision-threatening diabetic retinopathy (VTDR) - a predominant global contributor to vision impairment. The timely identification of VTDR is a linchpin for efficacious interventions and the mitigation of vision loss. Addressing this, This study introduces "NIMEQ-SACNet," a novel hybrid model by the prowess of the Enhanced Quantum-Inspired Binary Grey Wolf Optimizer (EQI-BGWO) with a self-attention capsule network. The proposed approach is characterized by two pivotal advancements: firstly, the augmentation of the Binary Grey Wolf Optimization through Quantum Computing methodologies, and secondly, the deployment of the enhanced EQI-BGWO to adeptly calibrate the SACNet's parameters, culminating in a notable uplift in VTDR classification accuracy. The proposed model's ability to handle binary, 5-stage, and 7-stage VTDR classifications adroitly is noteworthy. Rigorous assessments on the fundus image dataset, underscored by metrics such as Accuracy, Sensitivity, Specificity, Precision, F1-Score, and MCC, bear testament to NIMEQ-SACNet's pre-eminence over prevailing algorithms and classification frameworks.

The least sample size essential for detecting changes in clustering solutions of streaming datasets

The clustering analysis approach treats multivariate data tuples as objects and groups them into clusters based on their similarities or dissimilarities within the dataset. However, in modern world, a significant volume of data is continuously generated from diverse sources over time. In these dynamic scenarios, the data is not static but continually evolves. Consequently, the interesting patterns and inherent subgroups within the datasets also change and develop over time. The researchers have paid special attention to monitoring changes in cluster solutions of evolving streams. For this matter, several algorithms have been proposed in the literature. However, to date, no study has examined the effect of variability in cluster sizes on the evolution of cluster solutions. Moreover, no guidance is available on determining the impact of cluster sizes on the type of changes they experience in the streams. In the present simulation study using artificial datasets, the evolution of clusters is examined concerning the variability in cluster sizes. The findings are substantial because tracing and monitoring the changes in clustering solutions have a wide range of applications in every field of research. This study determines the minimum sample size required in the clustering of time-stamped datasets.

A deep learning-based theoretical protocol to identify potentially isoform-selective PI3Kα inhibitors

Phosphoinositide 3-kinase alpha (PI3Kα) is one of the most frequently dysregulated kinases known for their pivotal role in many oncogenic diseases. While the side effects linked to existing drugs against PI3Kα-induced cancers provide an avenue for further research, the significant structural conservation among PI3Ks makes it extremely difficult to develop new isoform-selective PI3Kα inhibitors. Embracing this challenge, we herein designed a hybrid protocol by integrating machine learning (ML) with in silico drug-designing strategies. A deep learning classification model was developed and trained on the physicochemical descriptors data of known PI3Kα inhibitors and used as a screening filter for a database of small molecules. This approach led us to the prediction of 662 compounds showcasing appropriate features to be considered as PI3Kα inhibitors. Subsequently, a multiphase molecular docking was applied to further characterize the predicted hits in terms of their binding affinities and binding modes in the targeted cavity of the PI3Kα. As a result, a total of 12 compounds were identified whereas the best poses highlighted the efficiency of these ligands in maintaining interactions with the crucial residues of the protein to be targeted for the inhibition of associated activity. Notably, potential activity of compound 12 in counteracting PI3Kα function was found in a previous in vitro study. Following the drug-likeness and pharmacokinetic characterizations, six compounds (compounds 1, 2, 3, 6, 7, and 11) with suitable ADME-T profiles and promising bioavailability were selected. The mechanistic studies in dynamic mode further endorsed the potential of identified hits in blocking the ATP-binding site of the receptor with higher binding affinities than the native inhibitor, alpelisib (BYL-719), particularly the compounds 1, 2, and 11. These outcomes support the reliability of the developed classification model and the devised computational strategy for identifying new isoform-selective drug candidates for PI3Kα inhibition.

The antibiogram of pus cultures in federal tertiary care hospital, Islamabad and its utility in antimicrobial stewardship

Background and Objectives

Antimicrobial resistance has emerged as a significant global health threat. Infections caused by Multi Drug-Resistant (MDR) bacteria pose formidable challenges in terms of treatment options and patient outcomes. Pus cultures serve as crucial diagnostic tools in identifying the agents responsible for various infections, and their antimicrobial susceptibility patterns which help in establishment of empirical therapy guidelines. This study was conducted to determine the pathogen and its susceptibility pattern from pus cultures and to generate antibiogram in our tertiary care setting.

Materials and Methods

It was a cross-sectional study, conducted for a period of six months, from July 2022 to December 2022, in the Pathology Department of Pakistan Institute of Medical Sciences (PIMS).

Results

Out of total 2507 samples received, 1242 (49.5%) showed positive culture. Among the 1242 positive samples, 364 were Gram positive cocci (GPCs) and 878 were Gram negative rods (GNRs). Methicillin resistant Staphylococcus aureus (MRSA) was the most common isolate (23%) followed by Klebsiella pneumoniae (22.6%), Pseudomonas aeruginosa (16.9%), Enterobacter spp. (15.5%) and Escherichia coli (14.2%). Vancomycin was found to be highly effective (100%) against MRSA. GPCs were highly susceptible to linezolid (98%) while GNRs showed high level of sensitivity to colistin (96%) and tigecycline (92%).

Conclusion

The generation of a local antibiogram specific to the hospital setting is essential to effectively manage infections empirically and preserve the efficacy of existing antibiotics. By implementing antimicrobial stewardship practices based on a better understanding of antibiotic susceptibility patterns, we can contribute to the mitigation of antibiotic resistance and improve patient outcomes.

Genome-wide in-silico analysis of ethylene biosynthesis gene family in Musa acuminata L. and their response under nutrient stress

Ethylene is a gaseous phytohormone involved in plants' growth and developmental processes, including seed germination, root initiation, fruit ripening, flower and leaf senescence, abscission, and stress responses. Ethylene biosynthesis (EB) gene analysis in response to nitrogen (N) and potassium (K) stress has not yet been conducted in Musa acuminata (banana) roots. The genome mining of banana (Musa acuminata L.) revealed 14 putative 1-aminocyclopropane-1-carboxylate synthase (ACS), 10 1-aminocyclopropane-1-carboxylate oxidase (ACO), and 3 Ethylene overproducer 1 (ETO1) genes. ACS, ACO, and ETO1 proteins possessed amino acid residues ranging from 422-684, 636-2670, and 893-969, respectively, with molecular weight (Mw) ranging from 4.93-7.55 kD, 10.1-8.3 kD and 10.1-10.78 kD. The number of introns present in ACS, ACO, and ETO1 gene sequences ranges from 0-14, 1-6, and 0-6, respectively. The cis-regulatory element analysis revealed the presence of light-responsive, abscisic acid, seed regulation, auxin-responsive, gibberellin element, endosperm-specific, anoxic inducibility, low-temperature responsiveness, salicylic acid responsiveness, meristem-specific and stress-responsive elements. Comprehensive phylogenetic analyses ACS, ACO, and ETO1 genes of Banana with Arabidopsis thaliana revealed several orthologs and paralogs assisting in understanding the putative functions of these genes. The expression profile of Musa acuminata genes in root under normal and low levels of nitrogen and potassium shows that MaACS14 and MaACO6 expressed highly at normal nitrogen supply. MaACS1 expression was significantly upregulated at low potassium levels, whereas, MaACO6 gene expression was significantly downregulated. The functional divergence and site-specific selective pressures on specific gene sequences of banana have been investigated. The bioinformatics-based genome-wide assessment of the family of banana attempted in the present study could be a significant step for deciphering novel ACS, ACO, and ETO1 genes based on genome-wide expression profiling.

Improved Support Vector Machine based on CNN-SVD for vision-threatening diabetic retinopathy detection and classification

The integration of artificial intelligence (AI) in diagnosing diabetic retinopathy, a major contributor to global vision impairment, is becoming increasingly pronounced. Notably, the detection of vision-threatening diabetic retinopathy (VTDR) has been significantly fortified through automated techniques. Traditionally, the reliance on manual analysis of retinal images, albeit slow and error-prone, constituted the conventional approach. Addressing this, our study introduces a novel methodology that amplifies the robustness and precision of the detection process. This is complemented by the groundbreaking Hierarchical Block Attention (HBA) and HBA-U-Net architecture, which notably propel attention mechanisms in image segmentation. This innovative model refines image processing without imposing excessive computational demands by honing in on individual pixel intricacies, spatial relationships, and channel-specific attention. Building upon this innovation, our proposed method employs a multi-stage strategy encompassing data pre-processing, feature extraction via a hybrid CNN-SVD model, and classification employing an amalgamation of Improved Support Vector Machine-Radial Basis Function (ISVM-RBF), DT, and KNN techniques. Rigorously tested on the IDRiD dataset classified into five severity tiers, the hybrid model yields remarkable performance, achieving a 99.18% accuracy, 98.15% sensitivity, and 100% specificity in VTDR detection, thus surpassing existing methods. These results underscore a more potent avenue for diagnosing and addressing this crucial ocular condition while underscoring AI's transformative potential in medical care, particularly in ophthalmology.

Variability in Reproductive Choices: A Comprehensive Analysis of Women's Working Status and Fertility Behavior in Pakistan

The relationship between women's working status and fertility behavior has been a topic of interest for researchers and policymakers. The societal shifts over time, particularly the increasing participation of women in the workforce, have transformed traditional roles. Women, once primarily perceived as caregivers, are now assuming roles of economic independence. This transformation prompts a re-evaluation of the traditional association between women's working status and fertility behavior. This study aims to investigate the impact of women's working status on fertility behavior using a multistage stratified sampling design. A total of 408 women aged 15 to 49 years were recruited from 2 strata: working and non-working women. The data were collected through face-to-face interviews using a structured questionnaire. Descriptive statistics, cluster analysis, and generalized additive models were used for in-depth analysis of the dataset. An examination of fertility patterns indicates that, on average, working women bear 2.90 live children, while their non-working counterparts have an average of 3.52 children. Stillbirth was reported in 13% of housewives and 15.1% of working women. However, further analysis revealed that the relationship between women's employment status and fertility behavior varied depending on Social and Cultural Norms, Reproductive Rights, Workplace Policies, Economic Independence, Age, and Life Stage. Our findings suggest that promoting access to family-friendly policies and services, as well as challenging gender norms and cultural values, could help address the impact of women's employment on fertility behavior.

Cotton leaf curl Multan betasatellite impaired ToLCNDV ability to maintain cotton leaf curl Multan alphasatellite

Abstract Alphasatellites (family Alphasatellitidae) are circular, single-stranded (ss) DNA molecules of ~1350 nucleotide in size that have been characterized in both the Old and New Worlds. Alphasatellites have inherent ability to self-replicate, which is accomplished by a single protein, replication-associated protein (Rep). Although the precise function of alphasatellite is yet unknown, and these consider dispensable for infectivity, however, their Rep protein functions as a suppressor of host defence. While alphasatellites are most frequently associated with begomoviruses, particularly with monopartite than bipartite begomoviruses, they have recently been found associated with mastreviruses. The in planta maintenance of alphasatellites by helper geminivirus is still an enigma, with no available study on the topic. This study aimed to investigate whether a widely distributed bipartite begomovirus, tomato leaf curl New Delhi virus (ToLCNDV), can maintain cotton leaf curl Multan alphasatellite (CLCuMuA) in the presence or absence of cotton leaf curl Multan betasatellite (CLCuMuB). The findings of this study demonstrated that ToLCNDV or its DNA A could maintain CLCuMuA in Nicotiana benthamiana plants. However, the presence of CLCuMuB interferes with the maintenance of CLCuMuA, and mutations in the CP of ToLCNDV further reduces it. Our study highlighted that the maintenance of alphasatellites is impaired in the presence of a betasatellite by ToLCNDV. Further investigation is needed to unravel all the interactions between a helper virus and an alphasatellites.

Advances in IoMT for Healthcare Systems

Nowadays, the demand for healthcare to transform from traditional hospital and disease-centered services to smart healthcare and patient-centered services, including the health management, biomedical diagnosis, and remote monitoring of patients with chronic diseases, is growing tremendously [...].

Enhanced lead phytoextraction and soil health restoration through exogenous supply of organic ligands: Geochemical modeling"

Phytoremediation of lead (Pb) contaminated soil is a green technology to reduce Pb exposure and root exudates-derived organic acids play a vital role in this treatment process. In this study, Pb hyperaccumulator Pelargonium hortorum was chosen to investigate root-induced organic acid secretions and their subsequent role in Pb phytoextraction. In the first step, root exudation of P. hortorum was investigated in hydroponic experiments (0.2X Hoagland solution) under control and Pb stress conditions. Possible chemical interactions between Pb and the observed root exudates were then analyzed using Visual MINTEQ modeling. In the next step, the effects of the exogenous application of organic acids on Pb phytoextraction and soil enzymatic activities were studied in a pot experimental setup. Results indicated significant exudation of malic acid > citric acid > oxalic acid > tartaric acid in root exudates of P. hortorum under 50 mg L-1 Pb. Visual MINTEQ modeling results revealed that organic acids directly affect Pb dissolution in the nutrient solution by modulation of solution pH. Experimental results revealed that malic acid and citric acid significantly increased available Pb contents (7.2- and 6.7-folds) in the soil with 1500 mg kg-1 Pb contamination. Whereas, in shoot and root, the highest increase in Pb concentration was observed with citric acid (2.01-fold) and malic (3.75-fold) supplements, respectively. Overall, Pb uptake was notably higher when malic acid was applied (2.8-fold) compared to other organic acids, followed by citric acid (2.7-fold). In the case of soil enzymatic activities, oxalic acid significantly improved dehydrogenase, alkaline phosphatase, and microbial biomass by 1.6-, 1.4- and 1.3-folds, respectively. The organic acids were successful in reviving enzyme activity in Pb-contaminated soil, and might thus be used for long-term soil regeneration.

Genome-wide identification of CCO gene family in cucumber (Cucumis sativus) and its comparative analysis with A. thaliana

Carotenoid cleavage oxygenase (CCO) is an enzyme capable of converting carotenoids into volatile, aromatic compounds and it plays an important role in the production of two significant plant hormones, i.e., abscisic acid (ABA) and strigolactone (SL). The cucumber plant genome has not been mined for genomewide identification of the CCO gene family. In the present study, we conducted a comprehensive genome-wide analysis to identify and thoroughly examine the CCO gene family within the genomic sequence of Cucumis sativus L. A Total of 10 CCO genes were identified and mostly localized in the cytoplasm and chloroplast. The CCO gene is divided into seven subfamilies i.e. 3 NCED, 3 CCD, and 1 CCD-like (CCDL) subfamily according to phylogenetic analysis. Cis-regulatory elements (CREs) analysis revealed the elements associated with growth and development as well as reactions to phytohormonal, biotic, and abiotic stress conditions. CCOs were involved in a variety of physiological and metabolic processes, according to Gene Ontology annotation. Additionally, 10 CCO genes were regulated by 84 miRNA. The CsCCO genes had substantial purifying selection acting upon them, according to the synteny block. In addition, RNAseq analysis indicated that CsCCO genes were expressed in response to phloem transportation and treatment of chitosan oligosaccharides. CsCCD7 and CsNCED2 showed the highest gene expression in response to the exogenous application of chitosan oligosaccharides to improve cold stress in cucumbers. We also found that these genes CsCCD4a and CsCCDL-a showed the highest expression in different plant organs with respect to phloem content. The cucumber CCO gene family was the subject of the first genome-wide report in this study, which may help us better understand cucumber CCO proteins and lay the groundwork for the gene family's future cloning and functional investigations.

Molecular Signature of a Novel Alternanthera Yellow Vein Virus Variant Infecting the Ageratum conyzoides Weed in Oman

Alternanthera yellow vein virus (AlYVV), a monopartite begomovirus, has been identified infecting a diverse range of crops and native plants in Pakistan, India, and China. However, distinctive yellow vein symptoms, characteristic of begomovirus infection, were observed on the Ageratum conyzoides weed in Oman, prompting a thorough genomic characterization in this study. The results unveiled a complete genome sequence of 2745 base pairs and an associated betasatellite spanning 1345 base pairs. In addition, Sequence Demarcation Tool analyses indicated the highest nucleotide identity of 92.8% with a previously reported AlYVV-[IN_abalpur_A_17:LC316182] strain, whereas the betasatellite exhibited a 99.8% nucleotide identity with isolates of tomato leaf curl betasatellite. Thus, our findings propose a novel AlYVV Oman virus (AlYVV-OM) variant, emphasizing the need for additional epidemiological surveillance to understand its prevalence and significance in Oman and the broader region. To effectively manage the spread of AlYVV-OM and minimize its potential harm to (agro)ecosystems, future research should focus on elucidating the genetic diversity of AlYVV-OM and its interactions with other begomoviruses.

Rare presentation of pneumothorax in a young woman with underlying congenital pulmonary airway malformation

Congenital pulmonary airway malformation (CPAM) is the most common among a rare group of congenital anomalies of the lower respiratory tract. It has variable presentation depending on its subtype and the patient's age. It may lead to respiratory distress in neonates. It can be a particularly challenging diagnosis in children born asymptomatic but present with complications later in life such as haemoptysis, recurrent chest infections, breathlessness and pneumothorax. Prenatal ultrasound, chest X-ray, CT scan and MRI are helpful in making a radiological diagnosis.A woman in her late teens presented with shortness of breath and right pleuritic chest pain. CT's chest showed a number of bullae of varying sizes on the right, including one huge bulla compressing all three lobes. She underwent lung volume reduction surgery via video-assisted thoracoscopy, and the histology specimen confirmed the diagnosis of CPAM type 1.

Entropy-based grid approach for handling outliers: a case study to environmental monitoring data

Grid-based approaches render an efficient framework for data clustering in the presence of incomplete, inexplicit, and uncertain data. This paper proposes an entropy-based grid approach (EGO) for outlier detection in clustered data. The given hard clusters obtained from a hard clustering algorithm, EGO uses entropy on the dataset as a whole or on an individual cluster to detect outliers. EGO works in two steps: explicit outlier detection and implicit outlier detection. Explicit outlier detection is concerned with those data points that are isolated in the grid cells. They are either far from the dense region or maybe a nearby isolated data point and therefore declared as an explicit outlier. Implicit outlier detection is associated with the detection of outliers that are perplexedly deviated from the normal pattern. The determination of such outliers is achieved using entropy change of the dataset or a specific cluster for each deviation. The elbow based on the trade-off between entropy and object geometries optimizes the outlier detection process. Experimental results on CHAMELEON datasets and other similar datasets suggested that the proposed approach(es) detect the outliers more precisely and extend the capability of outliers detection to an additional 4.5% to 8.6%. Moreover, the resultant clusters became more precise and compact when the entropy-based gridding approach is applied on top of hard clustering algorithms. The performance of the proposed algorithms is compared with well-known outlier detection algorithms, including DBSCAN, HDBSCAN, RE3WC, LOF, LoOP, ABOD, CBLOF and HBOS. Finally, a case study for detecting outliers in environmental data has been carried out using the proposed approach and results are generated on our synthetically prepared datasets. The performance shows that the proposed approach may be an industrial-oriented solution to outlier detection in environmental monitoring data.

Genetic Diversity, Evolutionary Dynamics, and Ongoing Spread of Pedilanthus Leaf Curl Virus

Pedilanthus leaf curl virus (PeLCV) is a monopartite begomovirus (family Geminiviridae) discovered just a few decades ago. Since then, it has become a widely encountered virus, with reports from ca. 25 plant species across Pakistan and India, indicative of its notable evolutionary success. Viruses mutate at such a swift rate that their ecological and evolutionary behaviors are inextricably linked, and all of these behaviors are imprinted on their genomes as genetic diversity. So, all these imprints can be mapped by computational methods. This study was designed to map the sequence variation dynamics, genetic heterogeneity, regional diversity, phylogeny, and recombination events imprinted on the PeLCV genome. Phylogenetic and network analysis grouped the full-length genome sequences of 52 PeLCV isolates into 7 major clades, displaying some regional delineation but lacking host-specific demarcation. The progenitor of PeLCV was found to have originated in Multan, Pakistan, in 1977, from where it spread concurrently to India and various regions of Pakistan. A high proportion of recombination events, distributed unevenly throughout the genome and involving both inter- and intraspecies recombinants, were inferred. The findings of this study highlight that the PeLCV population is expanding under a high degree of genetic diversity (π = 0.073%), a high rate of mean nucleotide substitution (1.54 × 10-3), demographic selection, and a high rate of recombination. This sets PeLCV apart as a distinctive begomovirus among other begomoviruses. These factors could further exacerbate the PeLCV divergence and adaptation to new hosts. The insights of this study that pinpoint the emergence of PeLCV are outlined.

Identification and characterization of Glycolate oxidase gene family in garden lettuce (Lactuca sativa cv. 'Salinas') and its response under various biotic, abiotic, and developmental stresses

Glycolate oxidase (GLO) is an FMN-containing enzyme localized in peroxisomes and performs in various molecular and biochemical mechanisms. It is a key player in plant glycolate and glyoxylate accumulation pathways. The role of GLO in disease and stress resistance is well-documented in various plant species. Although studies have been conducted regarding the role of GLO genes from spinach on a microbial level, the direct response of GLO genes to various stresses in short-season and leafy plants like lettuce has not been published yet. The genome of Lactuca sativa cultivar 'Salinas' (v8) was used to identify GLO gene members in lettuce by performing various computational analysis. Dual synteny, protein-protein interactions, and targeted miRNA analyses were conducted to understand the function of GLO genes. The identified GLO genes showed further clustering into two groups i.e., glycolate oxidase (GOX) and hydroxyacid oxidase (HAOX). Genes were observed to be distributed unevenly on three chromosomes, and syntenic analysis revealed that segmental duplication was prevalent. Thus, it might be the main reason for GLO gene diversity in lettuce. Almost all LsGLO genes showed syntenic blocks in respective plant genomes under study. Protein-protein interactions of LsGLO genes revealed various functional enrichments, mainly photorespiration, and lactate oxidation, and among biological processes oxidative photosynthetic carbon pathway was highly significant. Results of in-depth analyses disclosed the interaction of GLO genes with other members of the glycolate pathway and the activity of GLO genes in various organs and developmental stages in lettuce. The extensive genome evaluation of GLO gene family in garden lettuce is believed to be a reference for cloning and studying functional analyses of GLO genes and characterizing other members of glycolate/glyoxylate biosynthesis pathway in various plant species.

Genome-wide identification and in-silico expression analysis of carotenoid cleavage oxygenases gene family in Oryza sativa (rice) in response to abiotic stress

Rice constitutes a foundational cereal and plays a vital role in the culinary sector. However, the detriments of abiotic stress on rice quality and productivity are noteworthy. Carotenoid cleavage oxygenases (CCO) hold vital importance as they enable the particular breakdown of carotenoids and significantly contribute towards the growth and response to abiotic stress in rice. Due to the insufficient information regarding rice CCOs and their potential role in abiotic stress, their utilization in stress-resistant genetic breeding remains limited. The current research identified 16 CCO genes within the Oryza sativa japonica group. These OsCCO genes can be bifurcated into three categories based on their conserved sequences: NCEDs (9-Cis-epoxycarotenoid dioxygenases), CCDs (Carotenoid cleavage dioxygenases) and CCD-like (Carotenoid cleavage dioxygenases-like). Conserved motifs were found in the OsCCO gene sequence via MEME analysis and multiple sequence alignment. Stress-related cis-elements were detected in the promoter regions of OsCCOs genes, indicating their involvement in stress response. Additionally, the promoters of these genes had various components related to plant light, development, and hormone responsiveness, suggesting they may be responsive to plant hormones and involved in developmental processes. MicroRNAs play a pivotal role in the regulation of these 16 genes, underscoring their significance in rice gene regulation. Transcriptome data analysis suggests a tissue-specific expression pattern for rice CCOs. Only OsNCED6 and OsNCED10 significantly up-regulated during salt stress, as per RNA seq analyses. CCD7 and CCD8 levels were also higher in the CCD group during the inflorescence growth stage. This provides insight into the function of rice CCOs in abiotic stress response and identifies possible genes that could be beneficial for stress-resistant breeding.

Medical Specialty Classification Based on Semiadversarial Data Augmentation

Rapidly increasing adoption of electronic health record (EHR) systems has caused automated medical specialty classification to become an important research field. Medical specialty classification not only improves EHR system retrieval efficiency and helps general practitioners identify urgent patient issues but also is useful in studying the practice and validity of clinical referral patterns. However, currently available medical note data are imbalanced and insufficient. In addition, medical specialty classification is a multicategory problem, and it is not easy to remove sensitive information from numerous medical notes and tag them. To solve those problems, we propose a data augmentation method based on adversarial attacks. The semiadversarial examples generated during the dynamic process of adversarial attacking are added to the training set as augmented examples, which can effectively expand the coverage of the training data on the decision space. Besides, as nouns in medical notes are critical information, we design a classification framework incorporating probabilistic information of nouns, with confidence recalculation after the softmax layer. We validate our proposed method on an 18-class dataset with extremely unbalanced data, and comparison experiments with four benchmarks show that our method improves accuracy and F1 score to the optimal level, by an average of 14.9%.

Epidemiology and antifungal susceptibilities of clinically isolated Aspergillus species in South China

Aspergillosis is a rising concern worldwide; however, its prevalence is not well documented in China. This retrospective study determined Aspergillus's epidemiology and antifungal susceptibilities at Meizhou People's Hospital, South China. From 2017 to 2022, the demographic, clinical, and laboratory data about aspergillosis were collected from the hospital's records and analysed using descriptive statistics, chi-square test, and ANOVA. Of 474 aspergillosis cases, A. fumigatus (75.32%) was the most common, followed by A. niger (9.92%), A. flavus (8.86%), and A. terreus (5.91%). A 5.94-fold increase in aspergillosis occurred during the study duration, with the highest cases reported from the intensive care unit (52.74%) - chronic pulmonary aspergillosis (79.1%) and isolated from sputum (62.93%). Only 38 (8.02%) patients used immunosuppressant drugs, while gastroenteritis (5.7%), haematologic malignancy (4.22%), and cardiovascular disease (4.22%) were the most prevalent underlying illnesses. In A. fumigatus, the wild-type (WT) isolates against amphotericin B (99.1%) were higher than triazoles (97-98%), whereas, in non-fumigatus Aspergillus species, the triazole (95-100%) WT proportion was greater than amphotericin B (91-95%). Additionally, there were significantly fewer WT A. fumigatus isolates for itraconazole and posaconazole in outpatients than inpatients. These findings may aid in better understanding and management of aspergillosis in the region.

In silico and computational analysis of zinc finger motif-associated homeodomain (ZF-HD) family genes in chilli (Capsicum annuum L)

Zinc finger-homeodomain (ZHD) proteins are mostly expressed in plants and are involved in proper growth and development and minimizing biotic and abiotic stress. A recent study identified and characterized the ZHD gene family in chilli (Capsicum annuum L.) to determine their probable molecular function. ZHD genes with various physicochemical characteristics were discovered on twelve chromosomes in chilli. We separated ZHD proteins into two major groups using sequence alignment and phylogenetic analysis. These groups differ in gene structure, motif distribution, and a conserved ZHD and micro-zinc finger ZF domain. The majority of the CaZHDs genes are preserved, early duplication occurred recently, and significant pure selection took place throughout evolution, according to evolutionary study. According to expression profiling, the genes were found to be equally expressed in tissues above the ground, contribute to plant growth and development and provide tolerance to biotic and abiotic stress. This in silico analysis, taken as a whole, hypothesized that these genes perform distinct roles in molecular and phytohormone signaling processes, which may serve as a foundation for subsequent research into the roles of these genes in other crops.

An insight on ophthalmic drug delivery systems: Focus on polymeric biomaterials-based carriers

Presently, different types of eye diseases, such as glaucoma, myopia, infection, and dry eyes are treated with topical eye drops. However, due to ocular surface barriers, eye drops require multiple administrations, which may cause several risks, thereby necessitating additional strategies. Some of the key characteristics of an ideal ocular drug delivery system are as follows: (a) good penetration into cornea, (b) high drug retention in the ocular tissues, (c) targetability to the desired regions of the eye, and (d) good bioavailability. It is worthy to note that the corneal epithelial tight junctions hinder the permeation of therapeutics through the cornea. Therefore, it is necessary to design nanocarriers that can overcome these barriers and enhance drug penetration into the inner parts of the eye. Moreover, intelligent multifunctional nanocarriers can be designed to include cavities, which may help encapsulate sufficient amount of the drug. In addition, nanocarriers can be modified with the targeting moieties. Different types of nanocarriers have been developed for ocular drug delivery applications, including emulsions, liposomes, micelles, and nanoparticles. However, these formulations may be rapidly cleared from the eye. The therapeutic use of the nanoparticles (NPs) is also hindered by the non-specific adsorption of proteins on NPs, which may limit their interaction with the cellular moieties or other targeted biological factors. Functional drug delivery systems (DDS), which can offer targeted ocular drug delivery while avoiding the non-specific protein adsorption could exhibit great potential. This could be further realized by the on-demand DDS, which can respond to the stimuli in a spatio-temporal fashion. The cell-mediated DDS offer another valuable platform for ophthalmological drug delivery.

Decellularized Scaffolds with Double-Layer Aligned Microchannels Induce the Oriented Growth of Bladder Smooth Muscle Cells: Toward Urethral and Ureteral Reconstruction

There is a great clinical need for regenerating urinary tissue. Native urethras and ureters have bidirectional aligned smooth muscle cells (SMCs) layers, which plays a pivotal role in micturition and transporting urine and inhibiting reflux. Thus far, urinary scaffolds have not been designed to induce the native-mimicking aligned arrangement of SMCs. In this study, a tubular decellularized extracellular matrix (dECM) with an intact internal layer and bidirectional aligned microchannels in the tubular wall, which is realized by the subcutaneous implantation of a template, followed by the removal of the template, and decellularization, is engineered. The dense and intact internal layer effectively increases the leakage pressure of the tubular dECM scaffolds. Rat-derived dECM scaffolds with three different sizes of microchannels are fabricated by tailoring the fiber diameter of the templates. The rat-derived dECM scaffolds exhibiting microchannels of ≈65 µm show suitable mechanical properties, good ability to induce the bidirectional alignment and growth of human bladder SMCs, and elevated higher functional protein expression in vitro. These data indicate that rat-derived tubular dECM scaffolds manifesting double-layer aligned microchannels may be promising candidates to induce the native-mimicking regeneration of SMCs in urethra and ureter reconstruction.

Exploring the role of ranking systems towards university performance improvement: A focus group-based study

The development of multiple university ranking systems at national and global levels has been driven by increasing interest in improving efficiency in the national educational sector without compromising the demand for international standards. Global university ranking systems play an important role by providing the foundation for competing in this global era. One approach could be developing and evaluating criteria to reduce the unnecessary use of standard, less productive indicators. This study aims to systematically exploit national and global university ranking systems in terms of their indicators and relevance to national educational needs. This study uses two online qualitative focus groups with 10 participants each. The participants were purposively sampled, and the transcribed data from the focus group were thematically analyzed. Findings indicate that university ranking should include indicators like governance and digital presence, as these are missing in global ranking indicators. These findings will guide the development of a university ranking framework that policymakers and universities can implement to improve institutional performance.

Multi-Resolution Wavelet Fractal Analysis and Subtask Training for Enhancing Few-Shot Noisy Brainwave Recognition

The integration of healthcare monitoring with Internet of Things (IoT) networks radically transforms the management and monitoring of human well-being. Portable and lightweight electroencephalography (EEG) systems with fewer electrodes have improved convenience and flexibility while retaining adequate accuracy. However, challenges emerge when dealing with real-time EEG data from IoT devices due to the presence of noisy samples, which impedes improvements in brainwave detection accuracy. Moreover, high inter-subject variability and substantial variability in EEG signals present difficulties for conventional data augmentation and subtask learning techniques, leading to poor generalizability. To address these issues, we present a novel framework for enhancing EEG-based recognition through multi-resolution data analysis, capturing features at different scales using wavelet fractals. The original data can be expanded many times after continuous wavelet transform (CWT) and recombination, alleviating insufficient training samples. In the transfer stage of deep learning (DL) models, we adopt a subtask learning approach to train the recognition model to generalize efficiently. This incorporates wavelets at various scales instead of exclusively considering average prediction performance across scales and paradigms. Through extensive experiments, we demonstrate that our proposed DL-based method excels at extracting features from small-scale and noisy EEG data. This significantly improves healthcare monitoring performance by mitigating the impact of noise introduced by the external environment.

Bacterial and Fungal Biocontrol Agents for Plant Disease Protection: Journey from Lab to Field, Current Status, Challenges, and Global Perspectives

Plants are constantly exposed to various phytopathogens such as fungi, Oomycetes, nematodes, bacteria, and viruses. These pathogens can significantly reduce the productivity of important crops worldwide, with annual crop yield losses ranging from 20% to 40% caused by various pathogenic diseases. While the use of chemical pesticides has been effective at controlling multiple diseases in major crops, excessive use of synthetic chemicals has detrimental effects on the environment and human health, which discourages pesticide application in the agriculture sector. As a result, researchers worldwide have shifted their focus towards alternative eco-friendly strategies to prevent plant diseases. Biocontrol of phytopathogens is a less toxic and safer method that reduces the severity of various crop diseases. A variety of biological control agents (BCAs) are available for use, but further research is needed to identify potential microbes and their natural products with a broad-spectrum antagonistic activity to control crop diseases. This review aims to highlight the importance of biocontrol strategies for managing crop diseases. Furthermore, the role of beneficial microbes in controlling plant diseases and the current status of their biocontrol mechanisms will be summarized. The review will also cover the challenges and the need for the future development of biocontrol methods to ensure efficient crop disease management for sustainable agriculture.

Six-Year Retrospective Analysis of Epidemiology, Risk Factors, and Antifungal Susceptibilities of Candidiasis from a Tertiary Care Hospital in South China

Candidiasis is a life-threatening disease that increases mortality in critically ill patients. However, such epidemiological data are still lacking in underdeveloped regions of China. A retrospective analysis (2016 to 2021) was conducted in Meizhou People's Hospital, China to study the burden of candidiasis, particularly candidemia, and antifungal susceptibilities of the species among hospitalized patients. Of the 7,864 candidiasis cases, 461 (5.86%) were candidemia cases. Candida albicans (64.25%) was the most identified species, followed by C. tropicalis (12.61%), C. glabrata (10.79%), and C. parapsilosis (9.79%). In non-C. albicans (NCA) candidemia cases, the number of C. glabrata cases was higher (102/461, 22.37%) than C. tropicalis (64/461, 14.04%). Gastrointestinal pathology, respiratory dysfunctions, septic shock, and malignancies were common underlying comorbidities, respectively. A central venous catheter was an independent risk factor for both C. albicans and NCA candidemia. The mortality rate was not statistically significant for either C. albicans or NCA. Amphotericin B and 5-flucytosine were highly effective (98 to 100%), while azoles were least effective (67.74 to 95.66%). Candidemia cases caused by C. tropicalis and C. glabrata had significantly lower azole susceptibility than non-candidemia-causing isolates. This study provides valuable information for prescribers to choose the right empirical therapy, for researchers to explore different resistance mechanisms, and for health care managers to control candidiasis better. IMPORTANCE This study provides important information on the burden of candidiasis, particularly candidemia, and the antifungal susceptibility of Candida species among hospitalized patients in an underdeveloped region of China. First, the finding that azoles were least effective against Candida species causing candidemia is particularly noteworthy, as it suggests the possibility of resistance to this class of antifungal agents. This information can guide the choice of empirical therapy and help in the selection of appropriate antifungal agents for the treatment of candidemia, thereby reducing the risk of resistance development. Second, the study provides important information for researchers to explore different resistance mechanisms in Candida species. Finally, the study has important implications for health care managers in controlling the spread of candidiasis. The high prevalence of candidemia cases in the study highlights the need for appropriate infection control measures to prevent the spread of the disease.

Enhancement of combustion effect leading to improved performance and exhaust emissions of an SI engine with ferrous oxide and graphite nanoparticles

The present study was conducted to investigate the effectiveness of new, less toxic, less harmful, and nonmetallic graphite (G) and metallic iron oxide (Fe2O3) nanofuel additives by analyzing experimentally their consequences on exhaust emissions and performance of an air cooled, single cylinder, 4-stroke gasoline engine. Fe2O3 and graphite nanoparticles at 40, 80, and 120 mg/l of gasoline concentrations were mixed with gasoline by means of a magnetic stirrer. Brake power (BP), brake-specific fuel consumption (BSFC), torque (T), brake thermal efficiency (BTE), nitrogen oxides (NOx), carbon monoxide (CO), hydrocarbons (HC), and carbon dioxide (CO2) emissions were the investigated parameters. Experimental results indicated that G-blends showed a higher rise in brake power, brake thermal efficiency and torque and a greater reduction in the brake-specific fuel consumption as compared to that of Fe2O3 fuel blends. Moreover, the G-blends produced less NOx and CO2 than Fe2O3 blends but produced more emissions of CO and HC than that of Fe2O3 blends. On average, G-blends produced 0.46%, 0.71%, and 1.71% more torque, power, and BTE and 2.43%, 1.87%, and 13.39% less brake-specific fuel consumption (BSFC), NOx, and CO2 than Fe2O3 blends, respectively. So, in terms of the eight parameters, four performance parameters (i.e., T, BP, BSFC, BTE), and four engine emission exhaust indicators (i.e., CO, NOx, HC, CO2), graphite nanoparticles showed more positive results for 6 parameters (T, BP, BSFC, BTE, NOx, CO2), while two parameters HC and CO showed negative results with graphite as compared to that of Fe2O3 nanoparticles. So, overall, we conclude that nanoparticles of graphite are more engine and environment friendly than that of iron oxide fuel additives.

Genome-Wide Identification and Characterization of the Biosynthesis of the Polyamine Gene Family in Citrus unshiu

Polyamines (PAs) contribute to diverse plant processes, environmental interaction, and stress responses. In citrus, the mechanism underlying the biosynthesis of polyamines is poorly understood. The present study aims to identify the biosynthesis of PA gene family members in satsuma mandarin (Citrus unshiu) and investigate their response against various stresses. The identified biosynthesis of PA genes in C. unshiu showed clustering in six groups, i.e., SPMS, SPDS, ACL5, ADC, ODC, and SAMDC. Syntenic analysis revealed that segmental duplication was prevalent among the biosynthesis of PA genes compared to tandem duplication. Thus, it might be the main reason for diversity in the gene family in C. unshiu. Almost all biosynthesis of PA gene family members in C. unshiu showed syntenic blocks in the genome of Arabidopsis, Citrus sinensis, Poncirus trifoliata, and Citrus reticulata. Analysis of Cis-regulatory elements (CREs) indicated the occurrence of hormones, light, defense, and environmental stress responses as well as the development and other plant mechanisms-related elements in the upstream sequence of the biosynthesis of PA genes. Expression profiling revealed that the biosynthesis of PA gene expression modulates in different organs during various developmental stages and stress in C. unshiu. This information will provide a deep understanding of genomic information and its expression in multiple tissues to better understand its potential application in functional genomics.

qPCR Assay as a Tool for Examining Cotton Resistance to the Virus Complex Causing CLCuD: Yield Loss Inversely Correlates with Betasatellite, Not Virus, DNA Titer

Cotton leaf curl disease (CLCuD) is a significant constraint to the economies of Pakistan and India. The disease is caused by different begomoviruses (genus Begomovirus, family Geminiviridae) in association with a disease-specific betasatellite. However, another satellite-like molecule, alphasatellite, is occasionally found associated with this disease complex. A quantitative real-time PCR assay for the virus/satellite components causing CLCuD was used to investigate the performance of selected cotton varieties in the 2014-2015 National Coordinated Varietal Trials (NCVT) in Pakistan. The DNA levels of virus and satellites in cotton plants were determined for five cotton varieties across three geographic locations and compared with seed cotton yield (SCY) as a measure of the plant performance. The highest virus titer was detected in B-10 (0.972 ng·µg^-1) from Vehari and the lowest in B-3 (0.006 ng·µg^-1) from Faisalabad. Likewise, the highest alphasatellite titer was found in B-1 (0.055 ng·µg^-1) from Vehari and the lowest in B-1 and B-2 (0.001 ng·µg^-1) from Faisalabad. The highest betasatellite titer was found in B-23 (1.156 ng·µg^-1) from Faisalabad and the lowest in B-12 (0.072 ng·µg^-1) from Multan. Virus/satellite DNA levels, symptoms, and SCY were found to be highly variable between the varieties and between the locations. Nevertheless, statistical analysis of the results suggested that betasatellite DNA levels, rather than virus or alphasatellite DNA levels, were the important variable in plant performance, having an inverse relationship with SCY (-0.447). This quantitative assay will be useful in breeding programs for development of virus resistant plants and varietal trials, such as the NCVT, to select suitable varieties of cotton with mild (preferably no) symptoms and low (preferably no) virus/satellite. At present, no such molecular techniques are used in resistance breeding programs or varietal trials in Pakistan.

The impact of partner's behaviour on pregnancy related outcomes and safe child-birth in Pakistan

BACKGROUND

Pakistan is one of the nations with the worst statistics for pregnancy-related outcomes. Health programmes in underdeveloped nations frequently ignore the role of partners in maternal health, which is a crucial contributing factor in these worst situations. This research study aims to explore the role of husbands in maternity care and safe childbirth in Pakistan.

METHODS

The data for this study comes from the Pakistan Maternal Mortality Survey 2019. The k-Modes clustering algorithm was implemented to generate clusters from the dataset. Cluster profiling was used to identify the problems in pregnancy-related outcomes in cases where women live away from their partners. The chi-square test and logistic regression model were fitted to identify the significant factors associated with women's health and safe childbirth.

RESULTS

The finding of the study reveals that the partner's support during and after pregnancy plays a vital role in maternal health and safe child-birth. It was revealed that the women living away from their partners have certain health problems during pregnancy. These problems include Vaginal bleeding, Excessive vomiting, Chest pain, Cough, High B.P, Excessive weight gain, Body aches, Swelling of feet, and Swelling of the face. This also leads to complications and health problems in the postpartum period. Due to a lack of antenatal care from the spouse during pregnancy, the women who lived away from their partners lost their pregnancies.

CONCLUSION

The study concludes that the husband's emotional and financial support substantially impacts the overall health of expecting mothers and the safety of delivery in Pakistan. Given its potential advantages for mother and child health outcomes, male engagement in health education must be acknowledged and addressed. The finding of the study is of immense importance, as it guides the policymakers to arrange various awareness programs for the male partners to support their pregnant spouse and provide proper antenatal care.

Cryptococcosis in Southern China: Insights from a Six-Year Retrospective Study in Eastern Guangdong

Objective

Cryptococcosis is a fatal infection that can affect both immunocompetent and immunocompromised patients, and it is little understood in China's various regions. This research aimed to look at the epidemiology, risk factors, and antifungal susceptibility pattern of Cryptococcus neoformans in eastern Guangdong, China.

Methods

A six-year (2016-2022) retrospective study was conducted at Meizhou People's Hospital, China. Demographical, clinical, and laboratory data of cryptococcal patients were collected from hospital records and statistically analyzed using the chi-square and ANOVA tests.

Results

Overall, 170 cryptococcal infections were recorded, of which meningitis accounted for 78 (45.88%), cryptococcemia for 50 (29.41%), and pneumonia for 42 (24.7%). The number of cases increased 8-fold during the study duration. The median age of patients was 58 years (Inter quartile range: 47-66), and the high proportion of cases was from the male population (n = 121, 71.17%). The underlying diseases were identified only in 60 (35.29%) patients, of which 26 (15.29%) were severely immunocompromised, and 26 (15.29%) others were mildly immunocompromised. A statistically significant difference was reported for chronic renal failure, and anemia (p < 0.05) persisted in cases of three infection types. A high number of non-wild type (NWT) isolates were found against amphotericin B (n=13/145, 8.96%), followed by itraconazole (n=7/136, 5.15%) and voriconazole (n=4/158, 2.53%). Only six isolates (3.79%) were multidrug-resistant, four of which were from cryptococcemia patients. Compared to meningitis and pneumonia, cryptococcemia revealed a higher percentage of NWT isolates (p < 0.05).

Conclusion

In high-risk populations, cryptococcal infections require ongoing monitoring and management.

Characterization of antibiotic resistance genes and mobile elements in extended-spectrum β-lactamase-producing Escherichia coli strains isolated from hospitalized patients in Guangdong, China

AIM

This study aimed to investigate the high-resolution phenotypic and genotypic characterization of extended-spectrum β-lactamase (ESBL)-producing E. coli strains isolated from hospitalized patients to explore the resistance genes and mobile genetic elements (MGEs) involved in horizontal dissemination.

METHODS

Between May and September 2021, a total of 216 ESBL-producing E. coli isolates were recovered from multiple departments. The identification of strains was performed using MALDI-TOF mass spectrometry and PCR, while antibiotic susceptibility testing was carried out using the Vitek 2 COMPACT system to determine resistance patterns, while PCR was used to detect different resistance genes and MGEs. In addition, a conjugation assay was performed to investigate the horizontal gene transfer of resistance genes. Selected isolates underwent whole-genome sequencing using the Illumina MiSeq platform.

RESULTS

A total of 216 out of 409 E. coli isolates recovered from a tertiary hospital were observed to be ESBL-producing, giving a carriage rate of 52.8%, as determined by phenotypic screening. The most frequent sources of ESBL-producing E. coli isolates were urine (129/216, 59.72%,) and blood (50/216, 23.14%). The most prevalent ESBL genes identified were blaCTX-M (60.18%), blaTEM (40.27%), and blaSHV (18.05%). Three E. coli isolates were found to carry the genes blaNDM, mcr-1, and fosA3 genes. The most prevalent MGEs were IS26 (95.37%), Int (87.03%), and IncFIB (76.85%). Whole-genome sequencing analysis of eight MDR E. coli strains revealed that these isolates belonged to eight different sequence types (STs) and serotypes and were found to harbor multiple plasmid replicons and virulence factors.

CONCLUSION

This study highlights a high incidence of antibiotic resistance genes and MGEs associated with the dissemination of ESBLs and other resistance genes.

Metagenomic evidence for antibiotics-driven co-evolution of microbial community, resistome and mobilome in hospital sewage

Overconsumption of antibiotics is an immediate cause for the emergence of antimicrobial resistance (AMR) and antibiotic resistant bacteria (ARB), though its environmental impact remains inadequately clarified. There is an urgent need to dissect the complex links underpinning the dynamic co-evolution of ARB and their resistome and mobilome in hospital sewage. Metagenomic and bioinformatic methods were employed to analyze the microbial community, resistome and mobilome in hospital sewage, in relation to data on clinical antibiotic use collected from a tertiary-care hospital. In this study, resistome (1,568 antibiotic resistance genes, ARGs, corresponding to 29 antibiotic types/subtypes) and mobilome (247 types of mobile genetic elements, MGEs) were identified. Networks connecting co-occurring ARGs with MGEs encompass 176 nodes and 578 edges, in which over 19 types of ARGs had significant correlations with MGEs. Prescribed dosage and time-dependent antibiotic consumption were associated with the abundance and distributions of ARGs, and conjugative transfer of ARGs via MGEs. Variation partitioning analyses show that effects of conjugative transfer were most likely the main contributors to transient propagation and persistence of AMR. We have presented the first evidence supporting idea that use of clinical antibiotics is a potent driving force for the development of co-evolving resistome and mobilome, which in turn supports the growth and evolution of ARB in hospital sewage. The use of clinical antibiotics calls for greater attention in antibiotic stewardship and management.

Maternal High Fat Diet and its expressions in the Heart and Liver in the Mice Embryogenesis

BACKGROUND

The developmental biology for the nonalcoholic fatty liver disease and coronary heart disease are known but elaborative ideas of triglycerides phenomenon in the embryo-genesis of the liver and the heart are still not clear.

OBJECTIVE

The aim of the study was to relate different triglycerides like LXRα, LPL, LDL R, PPARG-, and SREBP-1C expression in the high fat-fed mice with the normal-fed diet mice in the process of developmen-tal and embryo-genesis biology.

METHODS

Tissue preparation was done by RIPA lysis. Different protein content was obtained via western blot for the 6 samples namely A.3 months embryo B.4 months embryo C.Birth day embryo D.3 days infant E. 2 weeks infant F. 4 weeks infant. Protein lysates from the heart tissues of the mice were obtained via ho-mogenization and centrifugation. Hematoxylin and Eosin staining (H and E) were done to see the fat droplets in the liver tissues at the different developmental stages.

RESULT

LXRα,SREBP-1C expression in 3 months embryo and 4 months embryo is highly expressed in the high-fat diet. LDL-R in the high-fat diet mice is increased in 3 days infant heart but in 3 months and 4 months embryo it has low expression but from the 0th day to the 4 weeks the expression is in a decreasing trend. Similarly, LPL is highly expressed in 3 months embryo and 0th day(Birthday) and thus low expression indecreasing order until 4 weeks infant. Thus, these results collectively show that a maternal HF diet in-creases the expression of proteins such as LPL, and LDLr in the embryo phase and thus getting normal ex-pressions in the adult phase that facilitate Triglycerides (TAG) hydrolysis across the liver and the heart. Also, maternal high-fat diet increases the SREBP1c expression, leading to stimulation of LPL Expression.

CONCLUSION

In summary, using a pregnant mice model, we found that a maternal high-fat diet increases fe-tal fat accumulation. Elevated placental LPL activity and expression of genes that facilitate placental lipid transport suggest that enhanced placental lipid transport may play a key role in maternal nutrition and obesi-ty-induced fetal fat accumulation.

Insight on Oxygen-Supplying Biomaterials Used to Enhance Cell Survival, Retention, and Engraftment for Tissue Repair

Oxygen is one of the essential requirements for cell survival, retention, and proliferation. The field of regenerative medicine and tissue engineering (TE) has realized considerable achievements for the regeneration of tissues. However, tissue regeneration still lacks the full functionality of solid organ implantations; limited cell survival and retention due to oxidative stress and hypoxia in the deeper parts of tissues remains a perpetual challenge. Especially prior to neovascularization, hypoxia is a major limiting factor, since oxygen delivery becomes crucial for cell survival throughout the tissue-engineered construct. Oxygen diffusion is generally limited in the range 100-200 μm of the thickness of a scaffold, and the cells located beyond this distance face oxygen deprivation, which ultimately leads to hypoxia. Furthermore, before achieving functional anastomosis, implanted tissues will be depleted of oxygen, resulting in hypoxia (<5% dissolved oxygen) followed by anoxic (<0.5% dissolved oxygen) microenvironments. Different types of approaches have been adopted to establish a sustained oxygen supply both in vitro and in vivo. In this review, we have summarized the recent developments in oxygen-generating and/or releasing biomaterials for enhancing cell survival in vitro, as well as for promoting soft and hard tissue repair, including skin, heart, nerve, pancreas, muscle, and bone tissues in vivo. In addition, redox-scavenging biomaterials and oxygenated scaffolds have also been highlighted. The surveyed results have shown significant promise in oxygen-producing biomaterials and oxygen carriers for enhancing cell functionality for regenerative medicine and TE applications. Taken together, this review provides a detailed overview of newer approaches and technologies for oxygen production, as well as their applications for bio-related disciplines.

Supplementation of PUFA extracted from microalgae for the development of chicken patties

In recent years, there has been a growing interest in development of a diverse range of foods that are enriched with omega-3 fatty acids. It is widely recognized that through dietary interventions, the lipid fraction of food can be modified to enhance its nutritional content. This study is aimed to develop chicken patties enriched with poly unstaurated fatty acids (PUFAs) extracted from microalgae aurintricarboxylic acid (ATA) concentration of 0% (T0), 1% (T1), 2% (T2), and 3% (T3). All treatments were stored at -18 °C for one month and analysed at an interval of 0, 10, 20, and 30 days to assess the effect of PUFAs supplementation on physicochemical, oxidative, microbiological and organoleptic properties of chicken patties. The results revealed that moisture content was significantly increased during the storage; the maximum moisture was observed in T0 (67.25% ± 0.03) on day 0, while the minimun was found in T3 (64.69% ± 0.04) on day 30. Supplemenatation of PUFAs in chicken patties significantly enhanced the fat content of the product the highest fat content was observed for T3 (9.7% ± 0.06. An increase in PUFAs concentration led to a significant increase in thiobarbituric acid reactive substances (TBARS). TBARS were increased from 1.22 ± 0.43 at 0 days to 1.48 ± 0.39 at 30 days of storage. The PUFAs incorporation negatively effected sensory acceptance of the product ranging from (8.41 ± 0.17 to 7.28 ± 0.12). However, the sensory scores were in acceptable range for supplemented patties as compared to control sample. Treatment T3 depicted the highest nutritional content. The sensory and physiochemical analysis of supplemented patties suggested that PUFAs extracted from microalgae can be used as a functional ingredient in the preparation various meat products particularly chicken meta patties. However, antioxidants should be added to to prevent lipid oxidation in the product.

SEC24D gene as a biomarker in human cancers and its association with CD8+ T cell immune cell infiltration

OBJECTIVE

The SEC24D (SEC24 Homolog D, COPII Coat Complex Component) gene belongs to the SEC24 subfamily of genes. The protein encoded by this gene, along with its other binding partners, mediates the transport of newly-synthesized proteins from the endoplasmic reticulum to the Golgi apparatus.

METHODS

A pan-cancer analysis of this gene, as well as its diagnostic and prognostic implications, are lacking in the medical literature. First, we analyzed SEC24D gene expression, its prognostic effect, promoter methylation level, genetic alteration landscape, pathways, CD8+ T immune cell infiltration, and gene-drug network in various types of cancer through various online databases and bioinformatic tools. Then, we performed the expression and methylation validation analysis of the SEC24D gene on cell lines using RNA sequencing (RNA-seq) and targeted bisulfite sequencing (bisulfite-seq) techniques.

RESULTS

Bioinformatic analysis showed that the SEC24D gene was overexpressed in metastasis across Kidney Renal Clear Cell Carcinoma (KIRC), Lung Squamous Cell Carcinoma (LUSC), and Stomach Adenocarcinoma (STAD) patients and was a prognostic risk factor. Then, using RNA sequencing and targeted bisulfite sequencing analysis, it was validated in cell lines that SEC24D was overexpressed and hypomethylated in KIRC patients. Mutational analysis revealed that SEC24D was mutated less frequently in KIRC, LUSC, and STAD patients. It was further observed that CD8+ T cell infiltration levels were increased in SEC24D-overexpressed KIRC, LUSC, and STAD samples. Pathway enrichment analysis of SEC24D-associated genes revealed their participation in two important pathways. Moreover, we suggested a few valuable drugs for treating KIRC, LUSC, and STAD patients with respect to overexpressed SEC24D.

CONCLUSION

This is the first pan-cancer study that details the oncogenic roles of SEC24D among different cancers.