• A cross-sectional study assesses the level of the job satisfaction among dieticians in Jordan. • This study aims to find the factors that influence job satisfaction status among dieticians in Jordan. • Assessments are based on using reliable and valid international job satisfaction survey (JSS). • The association between the job satisfaction and intend to stay was assessed too. • The survey is very generic and can be easily adapted in international future studies.

Background: Sepsis reaction is a response to an infection composed of genetic elements. This research aims to better understand how sepsis affects the molecular pathways in whole blood samples. Methods: Whole blood samples from healthy controls (n = 18), sepsis nonsurvivors (n = 9), and sepsis survivors (n = 26) were retrieved from the gene expression omnibus (GEO) collection of the national center for biotechnology information (NCBI) (accession number GSE54514). The NCBI's GEO2R program was used to determine differential expression, and the ingenuity pathway analysis (IPA) software was utilized to do a pathway analysis. Results: In sepsis patients, 2672 genes were substantially differently expressed (p value 0.05). One thousand three hundred four genes were overexpressed, and one thousand three hundred sixty-eight were under-expressed. The inhibition of ARE-mediated mRNA degradation pathway and the Pl3K/AKT signaling spliceosomal cycle were the most significant canonical pathways identified by ingenuity pathway analysis (IPA). The IPA upstream analysis predicted the ESR1, SIRT1, and PTPRR proteins, and the drugs filgrastim and fluticasone were top transcriptional regulators. Conclusions: The inhibition of ARE-mediated mRNA degradation pathway and the Pl3K/AKT signaling spliceosomal cycle were highlighted as essential pathways of inflammation by IPA, indicating widespread cancer owing to sepsis. Our data imply that sepsis considerably influences gene pathways in whole blood samples, pointing to possible targets for sepsis treatment.

Background/Objectives: Polycystic ovary syndrome (PCOS) is a common endocrine–metabolic disorder in which skeletal muscle insulin resistance contributes substantially to cardiometabolic risk. Pioglitazone improves insulin sensitivity in women with PCOS, yet the underlying transcriptional changes and their potential as treatment-response biomarkers remain incompletely defined. We aimed to reanalyse skeletal muscle gene expression from pioglitazone-treated PCOS patients using modern machine learning and network approaches to identify candidate biomarkers and regulatory hubs that may support precision therapy. Methods: Public microarray data (GSE8157) from skeletal muscle of obese women with PCOS and healthy controls were reprocessed. Differentially expressed genes (DEGs) were identified and submitted to Ingenuity Pathway Analysis to infer canonical pathways, upstream regulators, and disease functions. Four supervised machine learning algorithms (logistic regression, random forest, support vector machines, and gradient boosting) were trained using multi-step feature selection and 3-fold stratified cross-validation to provide superior Exploratory Gene Analysis. Gene co-expression networks were constructed from the most informative genes to characterize network topology and hub genes. A simulated multi-omics framework combined selected transcripts with representative clinical variables to explore the potential of integrated signatures. Results: We identified 1459 DEGs in PCOS skeletal muscle following pioglitazone, highlighting immune and fibrotic signalling, interferon and epigenetic regulators (including IFNB1 and DNMT3A), and pathways linked to mitochondrial function and extracellular matrix remodelling. Within this dataset, all four machine learning models showed excellent cross-validated discrimination between PCOS and controls, based on a compact gene panel. Random forest feature importance scoring and network centrality consistently prioritized ITK, WT1, BRD1-linked loci and several long non-coding RNAs as key nodes in the co-expression network. Simulated integration of these transcripts with clinical features further stabilized discovery performance, supporting the feasibility of multi-omics biomarker signatures. Conclusions: Reanalysis of skeletal muscle transcriptomes from pioglitazone-treated women with PCOS using integrative machine learning and network methods revealed a focused set of candidate genes and regulatory hubs that robustly separate PCOS from controls in this dataset. These findings generate testable hypotheses about the immunometabolism and epigenetic mechanisms of pioglitazone action and nominate ITK, WT1, BRD1-associated loci and related network genes as promising biomarkers for future validation in larger, independent PCOS cohorts.

Seed germination and early seedling development are critical determinants of crop establishment, stress tolerance, and yield stability, yet these stages remain insufficiently integrated into contemporary crop improvement strategies. Recent advances across genome editing, microbiome-assisted seed treatments, nanotechnology-enabled priming, and artificial intelligence-guided phenotyping have generated substantial but fragmented insights into early developmental regulation. This review synthesizes recent advances across early plant development research. It demonstrates that seemingly diverse technologies converge on a limited set of regulatory control nodes, including abscisic acid–gibberellin balance, redox homeostasis, and root system architectural plasticity. By integrating evidence from molecular, microbial, physicochemical, and computational studies, early plant ontogeny is presented as a tunable regulatory state governed by quantitative thresholds rather than as a strictly predetermined genetic process. Advances in deep learning, reinforcement learning, and high-throughput phenotyping further enable the modeling and optimization of early developmental trajectories across genotype by environment contexts. Together, these insights establish early development as a programmable target for crop improvement and provide a mechanistic foundation for designing integrated interventions that enhance developmental uniformity, stress resilience, and yield stability across diverse agroecological systems.

Background/Objectives: Antimicrobial resistance (AMR) is a major global health issue. Since community pharmacists are frontline health officials regarding the provision and management of antibiotics, it is of great importance to study the knowledge, attitudes, and practices (KAPs) of pharmacists with respect to antimicrobial stewardship (AMS) to formulate specific interventions. In Jordan, where dispensing antibiotics without a prescription is a common situation, this study was designed to assess the KAPs of community pharmacists in southern Jordan on AMR and AMS, the gap in the knowledge base and the practice, and the effect of other variables on antimicrobial education and responsible dispensing. Results: Participant pharmacists (n = 383) confirmed a moderate or lack of knowledge in antibiotic choice, resistance mechanisms, and the basis of stewardship. Despite positive attitudes for AMS, important practice gaps occurred: 38.6% infrequently dispensed antibiotics without prescriptions, 67.4% mistakenly believed that antibiotics may cure viral infections (flu/common cold), and only 33.4% firmly rejected non-prescription antibiotic requests. Knowledge scores were significantly higher among bachelor’s degree pharmacists, public university pharmacists, and urban-working pharmacists. Practice scores were better among master’s degree holders and urban practitioners. Conclusions: This work indicates that the AMS knowledge and practices of pharmacists in the southern Jordanian community are lacking in a severe way, with almost 4 out of 10 having poor behaviors including dispensing non-prescription antibiotics.

Background: The zoonotic pathogen Escherichia coli O157: H7, known as enterohemorrhagic E. coli (EHEC), is a public health concern associated with acute gastrointestinal diseases and hemolytic uremic syndrome (HUS). The primary reservoirs of EHEC are ruminants, including cattle and, potentially, sheep. However, data on EHEC prevalence and antimicrobial resistance in Jordanian sheep are scarce. Aim: This study aimed to examine the prevalence of EHEC and to assess antibacterial resistance patterns in non-EHEC E. coli isolates from Awasi sheep in Central Jordan. Methods: Rectal swabs from 198 sheep were collected and analyzed using conventional bacteriological methods and polymerase chain reaction (PCR) for genotypic confirmation of EHEC. The sample size was calculated using an anticipated prevalence of 5%, a confidence level of 95%, and a precision of 3%. Antimicrobial susceptibility testing was performed using the disc diffusion method for ciprofloxacin, ampicillin, and erythromycin, with findings interpreted according to standards. Results: None of the 198 EHEC isolates were identified among the 198 samples. However, 18 samples (9%) contained non-EHEC E. coli isolates, all of which exhibited resistance to at least one antibiotic. Notably, all isolates (100%) showed resistance to ampicillin, 94.4% to erythromycin, and 5.6% were ciprofloxacin-resistant. No significant variations in prevalence were found between sampling sites (p=0.78). Conclusion: The absence of EHEC in local sheep suggests that they are not a primary source of this pathogen in Jordan. However, the observed antimicrobial resistance in non-EHEC isolates highlights the need for stringent sanitary practices and antimicrobial stewardship to mitigate public health risks. Seasonal and age-related variations should be explored in future longitudinal studies.