Diverse Profiles Research Articles

Understanding bacterial diversity, infection dynamics, prevention of antibiotic resistance: an integrated study in an Algerian hospital context.

Bacterial infections, particularly bacteremia, urinary tract infections (UTIs), and pus infections, remain among hospitals' most worrying medical problems. This study aimed to explore bacterial diversity, infection dynamics, and antibiotic resistance profiles of bacterial isolates. We analyzed data from 1750 outpatients and 920 inpatients, of whom 1.6% and 8.47% respectively had various bacterial infections. The analysis revealed that UTIs were the most prevalent at 41.01%, particularly affecting women. UTIs also showed a distinct distribution across admission departments, notably in emergency (23.07%) and pediatric (14.10%) units. The most frequently isolated microorganisms were Escherichia coli (E. coli), followed by Klebsiella ornithinolytica. Skin infections followed UTIs, accounting for 35.88% of cases, more prevalent in men, with Staphylococcus aureus (S. aureus) being the primary pathogen (57%). Gram-negative bacteria (GNB) like E. coli and Pseudomonas aeruginosa contributed significantly to skin infections (43%). Bacteremia cases constituted 11.52% of bacterial infections, predominantly affecting women (67%) and linked to GNB (78%). A comparative study of antibiotic susceptibility profiles revealed more pronounced resistance in GNB strains isolated from inpatients, particularly to antibiotics such as Amoxicillin/clavulanic acid, Tetracyclin, Gentamicin, Chloramphenicol, and Ampicillin. In contrast, strains from ambulatory patients showed greater resistance to Colistin. Gram-positive bacteria from hospitalized patients showed higher resistance to quinolones and cephalosporins, while ambulatory strains showed high resistance to aminoglycosides, macrolides, fluoroquinolones, and penicillin. Furthermore, these analyses identified the most effective antibiotics for the empirical treatment of both community-acquired and nosocomial infections. Ciprofloxacin, aztreonam, and amikacin exhibited low resistance rates among GNB, with gentamicin and chloramphenicol being particularly effective for community-acquired strains. For S. aureus, ciprofloxacin, rifampicin, and cefoxitin were especially effective, with vancomycin showing high efficacy against community-acquired isolates and fosfomycin and chloramphenicol being effective for hospital-acquired strains. These results are essential for guiding antibiotic therapy and improving clinical outcomes, thus contributing to precision medicine and antimicrobial stewardship efforts.

Diverse calcium signaling profiles regulate migratory behavior in avascular wound healing and aberrant signal hierarchy occurs early in diabetes.

In avascular wound repair, calcium signaling events are the predominant mechanism cells use to transduce information about stressors in the environment into an effective and coordinated migratory response. Live cell imaging and computational analysis of corneal epithelial wound healing revealed that signal initiation and propagation at the wound edge are highly ordered, with groups of cells engaging in cyclical patterns of initiation and propagation. The cells in these groups exhibit a diverse range of signaling behavior, and dominant "conductor cells" drive activity in groups of lower-signaling neighbors. Ex vivo model systems reveal that conductor cells are present in wing cell layers of the corneal epithelium and that signaling propagates both within and between wing and basal layers. There are significant aberrations in conductor phenotype and interlayer propagation in type II diabetic murine models, indicating that signal hierarchy breakdown is an early indicator of disease. In vitro models reveal that signaling profile diversity and conductor cell phenotype is eliminated with P2X7 inhibition and is altered in Pannexin-1 or P2Y2 but not Connexin-43 inhibition. Conductor cells express significantly less P2X7 than their lower-signaling neighbors and exhibit significantly less migratory behavior after injury. Together, our results show that the postinjury calcium signaling cascade exhibits significantly more ordered and hierarchical behavior than previously thought, that proteins previously shown to be essential for regulating motility are also essential for determining signaling phenotype, and that loss of signal hierarchy integrity is an early indicator of disease state. NEW & NOTEWORTHY Calcium signaling in corneal epithelial cells after injury is highly ordered, with groups of cells engaged in cyclical patterns of event initiation and propagation driven by high-signaling cells. Signaling behavior is determined by P2X7, Pannexin-1, and P2Y2 and influences migratory behavior. Signal hierarchy is observed in healthy ex vivo models after injury and becomes aberrant in diabetes. This represents a paradigm shift, as signaling was thought to be random and determined by factors in the environment.

The Association between Statin Use and Reduced Migraine Likelihood: A Comprehensive Analysis of Migraine Subtypes and Statin Types in a Nationwide Korean Cohort.

Despite growing interest in the preventive effects of statins, as lipid-lowering agents, on migraine attacks, comprehensive nationwide studies comparing migraine likelihood between statin users and controls are lacking. Our nested case-control study within the Korean National Health Insurance Service-Health Screening Cohort (2002-2019) investigated this association using 38,957 migraine patients and 155,828 controls, considering migraine subtypes (with/without aura) and statin types (lipophilic vs. hydrophilic). Using propensity score matching and adjusting for confounders, statin use was linked to reduced migraine likelihood overall (odds ratio (OR) 0.93), particularly for migraines with aura (OR 0.75) and without aura (OR 0.94). Lipophilic statins were effective for both subtypes, while hydrophilic statins mainly reduced the likelihood of migraines without aura. Subgroup analyses showed consistent benefits across demographics, but varied effectiveness based on weight, smoking, alcohol use, hemoglobin levels, and dyslipidemia history. In summary, this nationwide cohort study suggests that statin use may reduce migraine likelihood among Korean adults across diverse demographics and clinical profiles, but varied effectiveness based on certain lifestyle and comorbidity factors underscores the importance of considering individual patient profiles when assessing the potential benefits of statin therapy for migraine prevention.

Integrative single-cell RNA-seq and spatial transcriptomics analyses reveal diverse apoptosis-related gene expression profiles in EGFR-mutated lung cancer

In EGFR-mutated lung cancer, the duration of response to tyrosine kinase inhibitors (TKIs) is limited by the development of acquired drug resistance. Despite the crucial role played by apoptosis-related genes in tumor cell survival, how their expression changes as resistance to EGFR-TKIs emerges remains unclear. Here, we conduct a comprehensive analysis of apoptosis-related genes, including BCL-2 and IAP family members, using single-cell RNA sequence (scRNA-seq) and spatial transcriptomics (ST). scRNA-seq of EGFR-mutated lung cancer cell lines captures changes in apoptosis-related gene expression following EGFR-TKI treatment, most notably BCL2L1 upregulation. scRNA-seq of EGFR-mutated lung cancer patient samples also reveals high BCL2L1 expression, specifically in tumor cells, while MCL1 expression is lower in tumors compared to non-tumor cells. ST analysis of specimens from transgenic mice with EGFR-driven lung cancer indicates spatial heterogeneity of tumors and corroborates scRNA-seq findings. Genetic ablation and pharmacological inhibition of BCL2L1/BCL-XL overcome or delay EGFR-TKI resistance. Overall, our findings indicate that BCL2L1/BCL-XL expression is important for tumor cell survival as EGFR-TKI resistance emerges.

Identification of Rocaglate Acyl Sulfamides as Selective Inhibitors of Glioblastoma Stem Cells.

Glioblastoma (GBM) is the most aggressive and frequently occurring type of malignant brain tumor in adults. The initiation, progression, and recurrence of malignant tumors are known to be driven by a small subpopulation of cells known as tumor-initiating cells or cancer stem cells (CSCs). GBM CSCs play a pivotal role in orchestrating drug resistance and tumor relapse. As a prospective avenue for GBM intervention, the targeted suppression of GBM CSCs holds considerable promise. In this study, we found that rocaglates, compounds which are known to inhibit translation via targeting of the DEAD-box helicase eIF4A, exert a robust, dose-dependent cytotoxic impact on GBM CSCs with minimal killing of nonstem GBM cells. Subsequent optimization identified novel rocaglate derivatives (rocaglate acyl sulfamides or Roc ASFs) that selectively inhibit GBM CSCs with nanomolar EC50 values. Furthermore, comparative evaluation of a lead CSC-optimized Roc ASF across diverse mechanistic and target profiling assays revealed suppressed translation inhibition relative to that of other CSC-selective rocaglates, with enhanced targeting of the DEAD-box helicase DDX3X, a recently identified secondary target of rocaglates. Overall, these findings suggest a promising therapeutic strategy for targeting GBM CSCs.

TEC-Q: A tool to sort out teacher emotions in the classroom

This article introduces the Teacher Emotions in the Classroom Q-sort (TEC-Q) as a systematic means to identify different combinations of teacher emotions within the classroom settings. Reflecting six discrete emotions, the TEC-Q was implemented using a sample of 40 secondary school teachers who performed a card-sorting task. The participants were divided into three groups based on their shared emotional profiles, namely bridging engagement and enjoyment, from misbehavior to the mix of anxiety and anger, and pride with tempered enjoyment. The findings revealed diverse emotional profiles which highlight the complex interplay between teacher emotions and classroom events.

Virulence and Antimicrobial Resistance Characterization of Glaesserella parasuis Isolates Recovered from Spanish Swine Farms.

Glaesserella (Haemophilus) parasuis, the causative agent of Glässer's disease, is present in most pig farms as an early colonizer of the upper respiratory tract. It exhibits remarkable variability in virulence and antimicrobial resistance (AMR), with virulent strains capable of inducing respiratory or systemic disease. This study aimed to characterize the virulence and the AMR profiles in 65 G. parasuis isolates recovered from Spanish swine farms. Virulence was assessed using multiplex leader sequence (LS)-PCR targeting vtaA genes, with all isolates identified as clinical (presumed virulent). Pathotyping based on ten pangenome genes revealed the virulent HPS_22970 as the most frequent (83.1%). Diverse pathotype profiles were observed, with 29 unique gene combinations and two isolates carrying only potentially non-virulent pangenome genes. AMR phenotyping showed widespread resistance, with 63.3% classified as multidrug resistant, and high resistance to clindamycin (98.3%) and tylosin (93.3%). A very strong association was found between certain pathotype genes and AMR phenotypes, notably between the virulent HPS_22970 and tetracycline resistance (p < 0.001; Φ = 0.58). This study reveals the wide diversity and complexity of G. parasuis pathogenicity and AMR phenotype, emphasizing the need for the targeted characterization of clinical isolates to ensure appropriate antimicrobial treatments and the implementation of prophylactic measures against virulent strains.

Is Mild Really Mild?: Generating Longitudinal Profiles of Stroke Survivor Impairment and Impact Using Unsupervised Machine Learning

The National Institute of Health Stroke Scale (NIHSS) is used worldwide to classify stroke severity as ‘mild’, ‘moderate’, or ‘severe’ based on neurological impairment. Yet, stroke survivors argue that the classification of ‘mild’ does not represent the holistic experience and impact of stroke on their daily lives. In this observational cohort study, we aimed to identify different types of impairment profiles among stroke survivors classified as ‘mild’. We used survivors of mild stroke’ data from the START longitudinal stroke cohort (n = 73), with measures related to sensorimotor, cognition, depression, functional disability, physical activity, work, and social adjustment over 12 months. Given the multisource, multigranular, and unlabeled nature of the data, we utilized a structure-adapting, unsupervised machine learning approach, the growing self-organizing map (GSOM) algorithm, to generate distinct clinical profiles. These diverse impairment profiles revealed that survivors of mild stroke experience varying degrees of impairment and impact (cognitive, depression, physical activity, work/social adjustment) at different time points, despite the uniformity implied by their NIHSS-classified ‘mild’ stroke. This emphasizes the necessity of creating a holistic and more comprehensive representation of survivors of mild stroke’ needs over the first year after stroke to improve rehabilitation and poststroke care.

Aquibium pacificus sp. nov., a Novel Mixotrophic Bacterium from Bathypelagic Seawater in the Western Pacific Ocean.

A novel Gram-stain-negative, facultatively anaerobic, and mixotrophic bacterium, designated as strain LZ166T, was isolated from the bathypelagic seawater in the western Pacific Ocean. The cells were short rod-shaped, oxidase- and catalase-positive, and motile by means of lateral flagella. The growth of strain LZ166T was observed at 10-45 °C (optimum 34-37 °C), at pH 5-10 (optimum 6-8), and in the presence of 0-5% NaCl (optimum 1-3%). A phylogenetic analysis based on the 16S rRNA gene showed that strain LZ166T shared the highest similarity (98.58%) with Aquibium oceanicum B7T and formed a distinct branch within the Aquibium genus. The genomic characterization, including average nucleotide identity (ANI, 90.73-76.79%), average amino identity (AAI, 88.50-79.03%), and digital DNA-DNA hybridization (dDDH, 36.1-22.2%) values between LZ166T and other species within the Aquibium genus, further substantiated its novelty. The genome of strain LZ166T was 6,119,659 bp in size with a 64.7 mol% DNA G+C content. The predominant fatty acid was summed feature 8 (C18:1ω7c and/or C18:1ω6c). The major polar lipids identified were diphosphatidylglycerol (DPG), phosphatidylethanolamine (PE), glycolipid (GL), and phosphatidylglycerol (PG), with ubiquinone-10 (Q-10) as the predominant respiratory quinone. The genomic annotation indicated the presence of genes for a diverse metabolic profile, including pathways for carbon fixation via the Calvin-Benson-Bassham cycle and inorganic sulfur oxidation. Based on the polyphasic taxonomic results, strain LZ166T represented a novel species of the genus Aquibium, for which the name Aquibium pacificus sp. nov. is proposed, with the type strain LZ166T (=MCCC M28807T = KACC 23148T = KCTC 82889T).

Optimal Brassicaceae family microgreens from a phytochemical and sensory perspective

Microgreens, also called superfoods, emerge because of their high levels of nutrients, diverse flavour profiles, and sustainable cultivation methods, which make them culinary delights and valuable to a healthy and flavorful diet. The present study investigated Brassicaceae family microgreens, proposing a novel system (quality indices) that allows scoring among them. Fourteen Brassica microgreen species were morphological, phytochemical, and sensorial investigated. The morphological assessment revealed that radish microgreens exhibited the highest leaf area (p < 0.05), while red mizuna demonstrated superior yield. Cauliflower microgreens contained the highest concentrations of ascorbic acid (HPLC-DAD) and total phenolic content (p < 0.05). Phytochemical analysis using HPLC-MS/MS identified over 18 glucosinolates and phenolic compounds. Red mustard and red cabbage showed the highest glucosinolate content (p < 0.05). Watercress exhibited the highest phenolic compound content (p < 0.05), primarily flavonoids, while broccoli and radish contained the highest isothiocyanate levels. Cauliflower microgreens resulted in the most consumer-accepted variety. Appling quality indices scoring system identified radish, cauliflower, and broccoli microgreens as the most promising species. This study underscores the potential of Brassica microgreens as an excellent source of health-promoting phytochemicals with favorable market acceptance, providing valuable insights for both nutritional research and commercial applications.

Approximating Rayleigh Scattering in Exoplanetary Atmospheres using Physics-informed Neural Networks (PINNs)

Abstract This research introduces an innovative application of physics-informed neural networks (PINNs) to tackle the intricate challenges of radiative transfer (RT) modeling in exoplanetary atmospheres, with a special focus on efficiently handling scattering phenomena. Traditional RT models often simplify scattering as absorption, leading to inaccuracies. Our approach utilizes PINNs, noted for their ability to incorporate the governing differential equations of RT directly into their loss function, thus offering a more precise yet potentially fast modeling technique. The core of our method involves the development of a parameterized PINN tailored for a modified RT equation, enhancing its adaptability to various atmospheric scenarios. We focus on RT in transiting exoplanet atmospheres using a simplified 1D isothermal model with pressure-dependent coefficients for absorption and Rayleigh scattering. In scenarios of pure absorption, the PINN demonstrates its effectiveness in predicting transmission spectra for diverse absorption profiles. For Rayleigh scattering, the network successfully computes the RT equation, addressing both direct and diffuse stellar light components. While our preliminary results with simplified models are promising, indicating the potential of PINNs in improving RT calculations, we acknowledge the errors stemming from our approximations as well as the challenges in applying this technique to more complex atmospheric conditions. Specifically, extending our approach to atmospheres with intricate temperature-pressure profiles and varying scattering properties, such as those introduced by clouds and hazes, remains a significant area for future development.

Diversity in Irish and British avifauna assemblages: What can variation in diversity profiles reveal about the forces that drive assemblage composition and structure?

Ireland and Britain are two islands located at Europe's westernmost edge, both of which act as the final breeding outposts for many bird species within their European ranges. Despite their similar geographic locations and geological histories, Ireland and Britain host different breeding avifauna assemblages. Diversity profiles, which can serve as more robust alternatives to classic diversity indices, were employed in this study to explore disparities in the two islands' breeding avifauna assemblages. Variations in assemblages were explored, along with their potential drivers, through analyses at three levels: island-scale breeding bird assemblage compositions, island-scale diversity profiles considering 49 common breeding species, and habitat-specific diversity profiles considering assemblages in east/central Irish farmland and East Anglian farmland. Analysis of the two islands' breeding avifauna assemblages revealed that the Irish assemblage is a complete subset of the British assemblage. Analyses of Irish and British assemblages at both an island scale and a habitat scale revealed patterns linking land use to trends within the two islands' avifauna assemblages. Irish assemblages contained greater proportions of insectivorous farmland species by abundance, while British assemblages contained greater proportions of seed-eating farmland species; both trends appeared to be related to structural differences in agricultural land use on the two islands. The British and East Anglian assemblages exhibited higher diversity across all analyses, which appeared to be driven by the assemblages' higher relative abundances of species that were most genetically distinct. This study highlights the ability of diversity profiles to impart more information than classic diversity indices by incorporating species similarity data.

Proteomic Characterisation of Heart Failure Reveals a Unique Molecular Phenotype for Hypertrophic Cardiomyopathy.

Hypertrophic cardiomyopathy (HCM) is a disease, which is difficult to diagnose at an early stage and for which there is a pressing need for more effective treatment options. The purpose of this study was to compare the molecular profile of HCM to that of ischaemic cardiomyopathy (ISCM) and dilated cardiomyopathy (DCM) for identification of protein and pathway targets that could support the development of better diagnostic and treatment options for HCM. A high-throughput mass spectrometry workflow was applied to achieve deep quantitative coverage of left ventricular tissue from HCM, DCM, ISCM and non-heart-failure control patients. HCM had a diverse proteomic profile compared to that of DCM and ISCM. Differentially expressed proteins unique to HCM were identified based on an observed fold change of ≥1.5 or ≤0.67 and q-value ≤ 0.05. Candidate proteins of interest were found to be significantly associated with clinical features of HCM. The significant association between these proteins and HCM was validated in an independent dataset. This represents one of the largest and deepest proteomic datasets for myocardial tissue reported to date. The dataset highlights the diverse proteomic profile of HCM, relative to other cardiomyopathies, and reveals disease-relevant pathways and promising biomarker candidates that are uniquely associated with HCM.

Potential of Fasting C-peptide to Glucose Ratio and Triglyceride Glucose Index as Markers for β-Cell Dysfunction and Insulin Resistance in Patients With Type 2 Diabetes on Insulin Therapy.

Pathogenesis of type 2 diabetes mellitus (T2DM) is combined from initial insulin resistance (IR) and subsequent β-cell dysfunction. Insulin therapy can replace β-cell function in advanced stages. However excessive insulin therapy increases IR and may expose the patients to risk of cardiovascular disease. We aim to assess β-cell function and IR in patients with type 2 diabetes on insulin therapy by fasting C-peptide to glucose ratio (FCPGR), and triglyceride glucose (TyG) index respectively to support treatment plans. A cross-sectional study was conducted at the Galiawa Diabetes and Endocrinology Teaching Center in Erbil City, Iraq,from June 2023 to January 2024. A convenient sample of 100 patients with T2DM on insulin-based therapy were included after obtaining informed written consent and excluding conditions such as acute illness,uncertain type of diabetes, etc. Each patient was evaluated for anthropometric parameters and current treatment details. Biochemical tests were then carried out to calculate metabolic syndrome (MetS) index score, FCPGR, and TyG index. Finally, patients were divided into four subgroups according to their FCPGR and TyG index and the data were analyzed statistically. The data showed those patients with sufficient β-cell function were 60(60%), and patients withhigh TyG index were 95 (95%). There was a significant negative correlation betweenFCPGR and hemoglobin A1c (HbA1c) (p-value=0.001), while there was a positive correlation between TyG index and HbA1C (p-value=0.001). None of these markers were correlated with BMI (p-value=0.297, and 0.976), duration of T2DM (p-value=0.258, and 0.458), and dose of insulin therapy (p-value=0.901, and 0.477). Patients with sufficient β-cell function and high TyG index had the lowest HbA1C. The study provides valuable insights into the utility of FCPGR and TyG index as biomarkers for β-cell function and insulin resistance in T2DM patients on insulin therapy. The significant correlation with HbA1C underscores their potential in clinical practice. However, the lack of correlation with BMI, disease duration, and insulin dose suggests that further investigation is needed to fully understand these biomarkers' implications across diverse patient profiles.

Development of algorithmic thinking skills in K-12 education: A comparative study of unplugged and digital assessment instruments

In the rapidly evolving landscape of digital competencies, the need for a robust and universal method to assess students’ algorithmic thinking (AT) skills has become increasingly pronounced. Algorithmic thinking refers to the ability to analyse a problem and develop a step-by-step process to solve it.This research investigates the efficacy of the Cross Array Task (CAT) as an assessment tool for AT skills within Switzerland’s compulsory education system. Originally conceptualised as an unplugged activity, where students performed the task without digital technologies (e.g., by using gestures on paper) and an administrator manually assessed them, the CAT evolved into a digital activity that runs on an iPad. The CAT’s digital transformation has automated the scoring of student responses and data collection, streamlining the assessment processes and facilitating efficient large-scale assessments. It has also enhanced scalability, making the CAT suitable for widespread use in educational settings. Furthermore, it provides immediate feedback to students and educators, supporting timely interventions and personalised learning experiences.Our study aims to comprehensively investigate algorithmic competencies in compulsory education, examining their variations and influencing factors. This research examines key variables, such as age, sex, educational environment and school characteristics (e.g., the level and grade of education), and regional factors (e.g., the canton of the school) in Switzerland, and characteristics related to the specific assessment tool, including the type of artefact used, the complexity of the algorithms generated, and the level of autonomy. Additionally, it seeks to analyse the effectiveness of the unplugged and digital approaches in assessing AT skills, specifically comparing the unplugged and virtual CAT versions, aiming to provide insights into their advantages and potential synergies.This investigation delineates the developmental progression of AT skills across compulsory education, emphasising the influence of age on algorithm development and problem-solving strategies. Furthermore, we reveal the impact of artefacts and the potential of digital tools to facilitate advanced AT skill development across diverse age groups. Finally, our investigation delves into the influence of school environments and sex disparities on AT performance, alongside the significant individual variability influenced by personal abilities and external circumstances.These findings underscore the importance of tailored educational interventions and equitable practices to accommodate diverse learning profiles and optimise student outcomes in AT across educational settings.

Parmelia perlata mediated microwave-assisted one-pot green synthesis of NiO nanoparticles a noble approach: Antibacterial and photocatalytic activity evaluation

This study reports a green-mediated fabrication of NiO nanoparticles (NiO NPs) using Parmelia Perlata lichen extract as a sustainable source. The Physical, chemical, optical, and morphological behavior of the fabricated NiO NPs were analyzed by employing diverse analytical profiles like XRD, FTIR, UV, and SEM. FTIR spectrum demonstrates the involvement of various phytochemicals in the bio-fabrication of NiO NPs. Furthermore, the appearance of a band at 668 cm−1 indicates the successful formation of NiO NPs. The observations of the SEM analysis depicted that the average particle size was in the range of 40–50 nm. The result of the antibacterial study indicates that the NiO NPs significantly reduce the growth of Staphylococcus aureus (19 mm). The result of the photocatalytic research illustrated that the bio-fabricated NiO NPs exhibited superior photocatalytic activity in the degradation of acridine orange dye achieving 84 % degradation efficiency.

Epididymal mRNA expression profiles for the protein disulfide isomerase gene family: Modulation by development and androgens.

The endoplasmic reticulum (ER) is the central hub for protein quality control, where the protein disulfide isomerases (PDIs), encoded by at least 21 genes, play a pivotal role. These multifunctional proteins contribute to disulfide bond formation, proper folding, and protein modifications, and may act as hormone-binding proteins (e.g., steroids), influencing hormone biology. The interplay between ER proteostasis, PDIs, and epididymis-a crucial site for sperm maturation-remains largely understudied. This study characterizes transcriptional signatures of Pdi genes in the epididymis. Transcriptional profiles of selected Pdi genes were assessed in adult Wistar rat tissues, and epididymis under different experimental conditions (developmental stages, surgical castration, and efferent ductules ligation [EDL]). In silico bioinformatic analyses identified expression trends of this gene family in human epididymal segments. P4hb, Pdia3, Pdia5, Pdia6, Erp44, Erp29, and Casq1 transcripts were detected in both reproductive and non-reproductive tissues, while Casq2 exhibited higher abundance in vas deferens, prostate, and heart. Pdilt, highly expressed in testis, and Pdia2, highly expressed in heart, showed minimal mRNA levels in the epididymis. In the mesonephric duct, epididymal embryonic precursor, P4hb, Pdia3, Pdia5, Pdia6, and Erp29 mRNAs were found at gestational day (GD) 17.5. Except for Erp29, which remained stable, these Pdi transcript levels increased from GD17.5 to GD20.5, when epididymal morphogenesis occurs, and were maintained to varying degrees in the epididymis during postnatal development. Surgical castration downregulated P4hb, Pdia3, Pdia5, Pdia6, Pdilt and Erp29 transcripts, an effect reversed by testosterone replacement. Conversely, transcript levels remained unaffected by EDL, except P4hb, which was reduced in caput epididymis. All 21 PDI genes exhibited diverse transcriptional profiles across the human epididymis. The findings lay the foundations to explore Pdi genes in epididymal biology. As a considerable proportion of male infertility cases are idiopathic, targeting hormonal regulation of protein quality control in epididymis represents a route to address male infertility and advance therapeutic interventions in this domain.

Custo-Efetividade da Oxigenação por Membrana Extracorpórea Venoarterial no Choque Cardiogênico Refratário: Um Estudo na Perspectiva Brasileira

Abstract Background Refractory cardiogenic shock (CS) is associated with high mortality rates, and the use of venoarterial extracorporeal membrane oxygenation (VA-ECMO) as a therapeutic option has generated discussions. Therefore, its cost-effectiveness, especially in low- and middle-income countries like Brazil, remains uncertain.Objectives: To conduct a cost-utility analysis from the Brazilian Unified Health System perspective to assess the cost-effectiveness of VA-ECMO combined with standard care compared to standard care alone in adult refractory CS patients. Methods We followed a cohort of refractory CS patients treated with VA-ECMO in tertiary care centers located in Southern Brazilian. We collected data on hospital outcomes and costs. We conducted a systematic review to supplement our data and utilized a Markov model to estimate incremental cost-effectiveness ratios (ICERs) per quality-adjusted life year (QALY) and per life-year gained. Results In the base-case analysis, VA-ECMO yielded an ICER of Int$ 37,491 per QALY. Sensitivity analyses identified hospitalization cost, relative risk of survival, and VA-ECMO group survival as key drivers of results. Probabilistic sensitivity analysis favored VA-ECMO, with a 78% probability of cost-effectiveness at the recommended willingness-to-pay threshold. Conclusions Our study suggests that, within the Brazilian Health System framework, VA-ECMO may be a cost-effective therapy for refractory CS. However, limited efficacy data and recent trials questioning its benefit in specific patient subsets highlight the need for further research. Rigorous clinical trials, encompassing diverse patient profiles, are essential to confirm cost-effectiveness and ensure equitable access to advanced medical interventions within healthcare systems, particularly in socio-economically diverse countries like Brazil.

Discrepancies in Mate Preferences among Chinese Families between Fathers, Mothers, and Children: A Latent Profile Analysis.

Parents develop their own preferences regarding prospective in-laws, which influence their children's mate selection processes and outcomes. From an evolutionary perspective, fathers, mothers, and their offspring have partially divergent genetic interests, potentially leading to conflicts in mate preferences. Currently, the characteristics of discrepancy profiles in mate preferences within Chinese families and their influencing factors remain unclear. Adopting an individual-centered perspective, this study examined the profiles of discrepancies in mate preferences between fathers, mothers, and children across a diverse set of Chinese families, along with their associations with family relations and evaluations of children. This study recruited 337 complete families. The results revealed three distinct profiles of father-mother mate preference discrepancies in families with sons and four profiles in families with daughters. Additionally, both families with sons and daughters displayed three profiles of discrepancies in parent-child mate preferences. Parental perceptions of marital relationships and their evaluations of children were linked to diverse father-mother discrepancy profiles in both families with sons and daughters. The father-son relationship was associated with the profiles of parent-child discrepancies in families with sons, while maternal evaluations of children and daughters' self-evaluations were related to the profiles of parent-child discrepancies in families with daughters. This study provides insights into understanding the conflict patterns and underlying reasons regarding mate preference between Chinese parents and their children within family settings.

Exploring protein relative relations in skeletal muscle proteomic analysis for insights into insulin resistance and type 2 diabetes

The escalating prevalence of insulin resistance (IR) and type 2 diabetes mellitus (T2D) underscores the urgent need for improved early detection techniques and effective treatment strategies. In this context, our study presents a proteomic analysis of post-exercise skeletal muscle biopsies from individuals across a spectrum of glucose metabolism states: normal, prediabetes, and T2D. This enabled the identification of significant protein relationships indicative of each specific glycemic condition. Our investigation primarily leveraged the machine learning approach, employing the white-box algorithm relative evolutionary hierarchical analysis (REHA), to explore the impact of regulated, mixed mode exercise on skeletal muscle proteome in subjects with diverse glycemic status. This method aimed to advance the diagnosis of IR and T2D and elucidate the molecular pathways involved in its development and the response to exercise. Additionally, we used proteomics-specific statistical analysis to provide a comparative perspective, highlighting the nuanced differences identified by REHA. Validation of the REHA model with a comparable external dataset further demonstrated its efficacy in distinguishing between diverse proteomic profiles. Key metrics such as accuracy and the area under the ROC curve confirmed REHA’s capability to uncover novel molecular pathways and significant protein interactions, offering fresh insights into the effects of exercise on IR and T2D pathophysiology of skeletal muscle. The visualizations not only underscored significant proteins and their interactions but also showcased decision trees that effectively differentiate between various glycemic states, thereby enhancing our understanding of the biomolecular landscape of T2D.