The Role of Corporate Social Responsibility in the Nexus between Green HR Practices and Sustainable HR Management: Evidence from Health-Care Sectors of Pakistan

The global evolvement of green human resource management practices within organizations has significantly influenced the retention of personnel and sustainable growth of the firms. It is very imperative to examine the strengthening relationship between green human resource management (GHRM) and sustainable human resource management (SHRM) practices. Hence, the purpose of this study is to bridge the knowledge gap to examine the moderating effect of corporate social responsibility (CSR) on the GHRM and the SHRM practices link. The study collected a total of 300 respondents engaged in the human resource management practices of health care units in Punjab using random stratified sampling data. The data was analyzed using the PLS-SEM approach along with the descriptive statistics of the variables. The existing research studies have already provided the mediating effects of many other variables on the GHRM and sustainable HRM practices in the healthcare industry of Pakistan

Fetomaternal Effects of Obesity in Postdate and Induced Pregnancies

Background : To study the fetomaternal effects of obesity in post date and induced pregnancies. Methods: In this case control study 210 postdate patients were included. They were divided into obese and non-obese groups according to BMI. Patient’s age, parity, and duration of gestation was recorded. Induction was done, mode of delivery, PPH, perinatal outcome i.e. macrosomia, birth outcome, and shoulder dystocia was noted. Results;The mean age was 23.05±3.61 years. All patients were postdate and underwent induction. BMI showed an increase with increase in age.Fifty seven percent of obese compared to 32% of non-obese needed low segment caesarean section (LCSC). Shoulder dystocia occurred in 2% of obese and 1% in non-obese while PPH occurred in 23% and 9.6% in obese and non-obese females respectively. Macrocosmia was encountered in 25% of obese versus 5% non-obese while stillbirth was observed in 3% of obese group.  Clavicle fracture 1% was noticed only in obese females. Conclusion:  Maternal obesity is associated with adverse maternal and fetal outcomes in pregnancy including operative deliveries, PPH with fetal macrosomia, birth anoxia, and stillbirth. So these women should be treated as high risk pregnancie

Integrated omics and machine learning-assisted profiling of cysteine-rich-receptor-like kinases from three peanut spp. revealed their role in multiple stresses

Arachis hypogaea (peanut) is a leading oil and protein-providing crop with a major food source in many countries. It is mostly grown in tropical regions and is largely affected by abiotic and biotic stresses. Cysteine-rich receptor-like kinases (CRKs) is a family of transmembrane proteins that play important roles in regulating stress-signaling and defense mechanisms, enabling plants to tolerate stress conditions. However, almost no information is available regarding this gene family in Arachis hypogaea and its progenitors. This study conducts a pangenome-wide investigation of A. hypogaea and its two progenitors, A. duranensis and A. ipaensis CRK genes (AhCRKs, AdCRKs, and AiCRKs). The gene structure, conserved motif patterns, phylogenetic history, chromosomal distribution, and duplication were studied in detail, showing the intraspecies structural conservation and evolutionary patterns. Promoter cis-elements, protein–protein interactions, GO enrichment, and miRNA targets were also predicted, showing their potential functional conservation. Their expression in salt and drought stresses was also comprehensively studied. The CRKs identified were divided into three groups, phylogenetically. The expansion of this gene family in peanuts was caused by both types of duplication: tandem and segmental. Furthermore, positive as well as negative selection pressure directed the duplication process. The peanut CRK genes were also enriched in hormones, light, development, and stress-related elements. MicroRNA (miRNA) also targeted the AhCRK genes, which suggests the regulatory association of miRNAs in the expression of these genes. Transcriptome datasets showed that AhCRKs have varying expression levels under different abiotic stress conditions. Furthermore, the multi-stress responsiveness of the AhCRK genes was evaluated using a machine learning-based method, Random Forest (RF) classifier. The 3D structures of AhCRKs were also predicted. Our study can be utilized in developing a detailed understanding of the stress regulatory mechanisms of the CRK gene family in peanuts and its further studies to improve the genetic makeup of peanuts to thrive better under stress conditions

Patient Mortality Prediction and Analysis of Health Cloud Data Using a Deep Neural Network

Cloud computing plays a vital role in healthcare as it can store a large amount of data known as big data. In the current emerging era of computing technology, big data analysis and prediction is a challenging task in the healthcare industry. Healthcare data are very crucial for the patient as well as for the respective healthcare services provider. Several healthcare industries adopted cloud computing for data storage and analysis. Incredible progress has been achieved in making combined health records available to data scientists and clinicians for healthcare research. However, big data in health cloud informatics demand more robust and scalable solutions to accurately analyze it. The increasing number of patients is putting high pressure on healthcare services worldwide. At this stage, fast, accurate, and early clinical assessment of the disease severity is vital. Predicting mortality among patients with a variety of symptoms and complications is difficult, resulting inaccurate and slow prediction of the disease. This article presents a deep learning based model for the prediction of patient mortality using the Medical Information Mart for Intensive Care III (MIMIC-III) dataset. Different parameters are used to analyze the proposed model, i.e., accuracy, F1 score, recall, precision, and execution time. The results obtained are compared with state-of-the-art models to test and validate the proposed model. Moreover, this research suggests a simple and operable decision rule to quickly predict patients at the highest risk, allowing them to be prioritized and potentially reducing the mortality rate

Potential Use of Venom of Odontobuthus odonturus (Arachnida: Buthidae) as Bio-pesticide Against Rhopalosiphum erysimi (Homoptera: Aphididae)

Abstract.-Present study was designed to test the effectiveness of different concentrations of crude venom of Odontobuthus odonturus Pocock, 1897 (Scorpiones: Buthidae) against Rhopalosiphum erysimi (Hemiptera: Aphididae). Scorpions were collected from Sargodha district of Punjab (Pakistan) using portable ultra-violet (UV) lamps. The venom of the scorpions was collected in 1.5 ml plastic collection tubes and frozen at -20ºC. The bioassay tests were performed against 0.5, 0.75 and 1 dose of scorpion venom in the laboratory. The percent mortality after 12 h was 68.3, 71.65 and 83.3 against 0.5, 0.75 and 1 µl concentrations, respectively. The mortality was significantly higher in the treated groups compared to the control. The LT 50 and LT 95 values were decreased as the venom concentrations were increased. The calculated LD 50 and LD 95 values for R. erysimi were 0.44 µl and 1.31 µl, respectively. It is concluded that venom of O. odonturus contains toxins which could be used as potential bio-pesticide candidates

Comparative genomics and bioinformatics approaches revealed the role of CC-NBS-LRR genes under multiple stresses in passion fruit

Passion fruit is widely cultivated in tropical, subtropical regions of the world. The attack of bacterial and fungal diseases, and environmental factors heavily affect the yield and productivity of the passion fruit. The CC-NBS-LRR (CNL) gene family being a subclass of R-genes protects the plant against the attack of pathogens and plays a major role in effector-triggered immunity (ETI). However, no information is available regarding this gene family in passion fruit. To address the underlying problem a total of 25 and 21 CNL genes have been identified in the genome of purple (Passiflora edulis Sims.) and yellow (Passiflora edulis f. flavicarpa) passion fruit respectively. Phylogenetic tree was divided into four groups with PeCNLs present in 3 groups only. Gene structure analysis revealed that number of exons ranged from 1 to 9 with 1 being most common. Most of the PeCNL genes were clustered at the chromosome 3 and underwent strong purifying selection, expanded through segmental (17 gene pairs) and tandem duplications (17 gene pairs). PeCNL genes contained cis-elements involved in plant growth, hormones, and stress response. Transcriptome data indicated that PeCNL3, PeCNL13, and PeCNL14 were found to be differentially expressed under Cucumber mosaic virus and cold stress. Three genes were validated to be multi-stress responsive by applying Random Forest model of machine learning. To comprehend the biological functions of PeCNL proteins, their 3D structure and gene ontology (GO) enrichment analysis were done. Our research analyzed the CNL gene family in passion fruit to understand stress regulation and improve resilience. This study lays the groundwork for future investigations aimed at enhancing the genetic composition of passion fruit to ensure robust growth and productivity in challenging environments

Table1_Integrated omics and machine learning-assisted profiling of cysteine-rich-receptor-like kinases from three peanut spp. revealed their role in multiple stresses.DOCX

Arachis hypogaea (peanut) is a leading oil and protein-providing crop with a major food source in many countries. It is mostly grown in tropical regions and is largely affected by abiotic and biotic stresses. Cysteine-rich receptor-like kinases (CRKs) is a family of transmembrane proteins that play important roles in regulating stress-signaling and defense mechanisms, enabling plants to tolerate stress conditions. However, almost no information is available regarding this gene family in Arachis hypogaea and its progenitors. This study conducts a pangenome-wide investigation of A. hypogaea and its two progenitors, A. duranensis and A. ipaensis CRK genes (AhCRKs, AdCRKs, and AiCRKs). The gene structure, conserved motif patterns, phylogenetic history, chromosomal distribution, and duplication were studied in detail, showing the intraspecies structural conservation and evolutionary patterns. Promoter cis-elements, protein–protein interactions, GO enrichment, and miRNA targets were also predicted, showing their potential functional conservation. Their expression in salt and drought stresses was also comprehensively studied. The CRKs identified were divided into three groups, phylogenetically. The expansion of this gene family in peanuts was caused by both types of duplication: tandem and segmental. Furthermore, positive as well as negative selection pressure directed the duplication process. The peanut CRK genes were also enriched in hormones, light, development, and stress-related elements. MicroRNA (miRNA) also targeted the AhCRK genes, which suggests the regulatory association of miRNAs in the expression of these genes. Transcriptome datasets showed that AhCRKs have varying expression levels under different abiotic stress conditions. Furthermore, the multi-stress responsiveness of the AhCRK genes was evaluated using a machine learning-based method, Random Forest (RF) classifier. The 3D structures of AhCRKs were also predicted. Our study can be utilized in developing a detailed understanding of the stress regulatory mechanisms of the CRK gene family in peanuts and its further studies to improve the genetic makeup of peanuts to thrive better under stress conditions.</p

Table2_Integrated omics and machine learning-assisted profiling of cysteine-rich-receptor-like kinases from three peanut spp. revealed their role in multiple stresses.XLSX

Arachis hypogaea (peanut) is a leading oil and protein-providing crop with a major food source in many countries. It is mostly grown in tropical regions and is largely affected by abiotic and biotic stresses. Cysteine-rich receptor-like kinases (CRKs) is a family of transmembrane proteins that play important roles in regulating stress-signaling and defense mechanisms, enabling plants to tolerate stress conditions. However, almost no information is available regarding this gene family in Arachis hypogaea and its progenitors. This study conducts a pangenome-wide investigation of A. hypogaea and its two progenitors, A. duranensis and A. ipaensis CRK genes (AhCRKs, AdCRKs, and AiCRKs). The gene structure, conserved motif patterns, phylogenetic history, chromosomal distribution, and duplication were studied in detail, showing the intraspecies structural conservation and evolutionary patterns. Promoter cis-elements, protein–protein interactions, GO enrichment, and miRNA targets were also predicted, showing their potential functional conservation. Their expression in salt and drought stresses was also comprehensively studied. The CRKs identified were divided into three groups, phylogenetically. The expansion of this gene family in peanuts was caused by both types of duplication: tandem and segmental. Furthermore, positive as well as negative selection pressure directed the duplication process. The peanut CRK genes were also enriched in hormones, light, development, and stress-related elements. MicroRNA (miRNA) also targeted the AhCRK genes, which suggests the regulatory association of miRNAs in the expression of these genes. Transcriptome datasets showed that AhCRKs have varying expression levels under different abiotic stress conditions. Furthermore, the multi-stress responsiveness of the AhCRK genes was evaluated using a machine learning-based method, Random Forest (RF) classifier. The 3D structures of AhCRKs were also predicted. Our study can be utilized in developing a detailed understanding of the stress regulatory mechanisms of the CRK gene family in peanuts and its further studies to improve the genetic makeup of peanuts to thrive better under stress conditions.</p