Individual Variation Research Articles

Mining and Expression Pattern Analysis of Genes Related to the Regulation of Flowering in Korean Pine (Pinus koraiensis)

Korean pine (Pinus koraiensis Siebold & Zucc.) is an important timber and economic tree species in northeast China. Its seeds serve as both a primary means of propagation and a significant economic product. In this study, we identified 12 full-length MADS-box genes based on the Korean pine flower-induced transcriptome data available in our laboratory. These genes were identified through multiple sequence alignment and screening for conserved structural domains. We analyzed the genetic relationships of these genes and predicted their physicochemical properties. Additionally, we examined the expression patterns of three SHORT VEGETATIVE PHASE (SVP) genes across different tissues and developmental stages of Korean pine. The results indicate that the amino acid composition, molecular weight, isoelectric point, and other physicochemical properties of the MADS-box gene family in Pinus koraiensis are generally similar, though some individual variations are observed. A total of 12 MADS-box family genes were identified from the Korean pine transcriptome, distributed across five subfamilies. Conserved motif analysis revealed that these genes share similar conserved sequences. Structural and physicochemical analyses showed that genes with similar sequences exhibited comparable characteristics. Expression levels of the SVP genes varied significantly across different developmental stages and tissues, with the expression of the three SVP genes in leaves being markedly higher than in buds (approximately 200-fold). The expression levels of these genes in leaves were not only higher than in buds but also exceeded those in other tissues. Based on these findings, we conclude that these three SVP genes primarily play a suppressive role in the process of flower bud formation, helping Korean pine maintain a juvenile state under certain conditions, and are also involved in the growth and development of its leaves. This research provides a basis for future studies on the flowering induction mechanism in Korean pine.

Performing whole-genome association analysis of winter wheat plant height using the 55K chip

Plant height is a critical agronomic that affects both plant architecture and yield. To decipher the genetic mechanisms underlying winter wheat plant height and identify candidate genes associated with this trait, we conducted phenotypic analysis on 239 wheat varieties (lines) collected from around the world. This analysis was complemented by genotyping using the wheat 55K SNP chip. A Wholegenome association analysis (GWAS) of wheat plant height was conducted utilizing the MLM (Q+K) model within TASSLE software. The results revealed significant phenotypic variation in wheat plant height across different years, with coefficients of variation ranging from 0.96% to 1.97%. Additionally, there was a strong correlation in plant height measurements between different years. GWAS identified 44 SNP markers significantly associated with wheat plant height across various environments (P ≤ 0.00001), predominantly distributed on chromosomes 1B, 1D, 2A, 2B, 2D, 3B, 3D, 4A, 4B, 6B, 6D, and 7D, explaining individual phenotypic variance rates ranging from 5.00% to 11.11%. Further, by mining association loci with substantial phenotypic effects and stability across multiple environments, seven candidate genes related to wheat plant height have been identified. This study provides new genetic markers and resources for improving wheat plant height.

Precision data-driven modeling of cortical dynamics reveals person-specific mechanisms underpinning brain electrophysiology

Task-free brain activity affords unique insight into the functional structure of brain network dynamics and has been used to identify neural markers of individual differences. In this work, we present an algorithmic optimization framework that directly inverts and parameterizes brain-wide dynamical-systems models involving hundreds of interacting neural populations, from single-subject M/EEG time-series recordings. This technique provides a powerful neurocomputational tool for interrogating mechanisms underlying individual brain dynamics ("precision brain models") and making quantitative predictions. We extensively validate the models' performance in forecasting future brain activity and predicting individual variability in key M/EEG metrics. Last, we demonstrate the power of our technique in resolving individual differences in the generation of alpha and beta-frequency oscillations. We characterize subjects based upon model attractor topology and a dynamical-systems mechanism by which these topologies generate individual variation in the expression of alpha vs. beta rhythms. We trace these phenomena back to global variation in excitatory-inhibitory balance, highlighting the explanatory power of our framework to generate mechanistic insights.

Diet and trophic structure of fishes in the Barents Sea: between empty and full stomachs - large individual variability follows a common pattern.

More than 27,000 stomachs from 70 species of fish were collected from the Barents Sea in 2015. Quantitative stomach content expressed relative to the body weight of the predator fish (g g-1 as %) varied by four to five orders of magnitude for six species with the largest sample size (Atlantic cod Gadus morhua, haddock Melanogrammus aeglefinus, Greenland halibut Reinhardtius hippoglossoides, long rough dab Hippoglossoides platessoides, polar cod Boreogadus saida, and Atlantic capelin Mallotus villosus). The quantitative stomach contents of individual fish followed a common and strict statistical relationship for predator species or groups of species (by families), and for prey categories across predator species. The common pattern was log-normal-like and was modelled with good fit by different types of right-skewed distributions, that is, variants of the Box-Cox, generalized inverse Gaussian, inverse gamma, or gamma distributions. The long tail in the high end reflects high variation with no clear sign of a plateau, as could be expected from the concept of a "full stomach". This is interpreted to reflect that high stomach contents are rare events that are sampled at low frequencies. The maximum recorded stomach content varied from 1% to 34% of body weight for 55 species of fish, being positively correlated (R2 = 0.45) with sample size. About a third of the stomachs were empty, and the low tail of the log-normal-like distribution represents the transition to empty stomachs. The amount of food in the stomachs was overall low compared to maximum values, with mean and median of 2.0% and 1.1%, respectively, for the 17,873 stomachs containing food. Supported by bioenergetic considerations, this suggests relatively low feeding rates of the various fish predators but sufficient to meet their energy demands.

Multi-omics dataset of individual variations in growth performance of large yellow croaker

Large yellow croaker (Larimichthys crocea) is a highly economically important marine fish species in China. However, substantial individual variations in growth performance have emerged as a limiting factor for the sustainable development of the large yellow croaker industry. Gut microbiota plays a crucial role in fish growth and development by regulating metabolic processes. To explore these dynamics, we employed metagenomics, transcriptomics, and untargeted metabolomics to comprehensively analyze the structure of the intestinal microbiome and its relationship with intestinal metabolism and host gene expression. We constructed association models for “gut microbiota–differentially expressed genes”, “differentially expressed genes–metabolites,” and “gut microbiota–metabolites.” Sequencing data and LC–MS/MS raw data have been deposited in NCBI and MetaboLights databases for public access. Our findings offer critical insights into the molecular mechanisms underlying growth variations in L. crocea and provide valuable data for the selective breeding of improved strains.

What is transformed, resists, or is strengthened in physical education in school contexts? Analyzing the dispositional plasticity of a female migrant student

This article presents the socializing effects of PE, and more broadly school contexts, on the set of dispositions of a Somali migrant girl, recently arrived in France. Shaped from various agents of socialization and according to her gender, her social class, her religion and her migratory background, this portrait shows how PE allows, through individual variations, to (trans)form or reinforce her ways of being, acting and thinking at school. Based on an ethnographic survey carried out in a French secondary school, our findings highlight Sarah’s taste for PE and for sport, is gradually taking shape, thanks to the support of her teacher. Moreover, while dispositional transformations have been observed in her investment in PE thanks to the persistence of her docility, an inertia to change remains concerning the acquisition of fine motor skills. Also, in practice, a triple division of gender, migration and language still persists in class.

Acceptance and adoption determinants of telemedicine in public healthcare institutions

Background: One of the challenges facing the usage of telemedicine technology in South Africa, particularly in the North West province (NWP), is lack of user acceptance by health care professionals which prevents piloted project to produce the desired outcomes.Objectives: The purpose of this study was to investigate the influential factors for the adoption of telemedicine by health care professionals from three selected hospitals (Bophelong, Taung and Klerksdorp) in the NWP.Method: The study adopted a case study approach and gathered data through questionnaires, which were distributed to the health care professionals of the three selected hospitals. In order to ensure that the instrument was accurate, a pilot study was carried out prior to the main investigation. Both the alpha and power values were set at 0.05 for the statistical analysis. The statistical tool used for the data analysis was SPSS v. 23.0.Results: Attitude towards the use of telemedicine technology (ATUTT), perceived usefulness (PU) and acceptance of telemedicine technology (ATT) were considered to be the influential factors in the adoption of telemedicine technology. The association between perceived ease of use (PEOU) and perceived usefulness (PU) (0.150, p = 0.034), PEOU and Attitude towards the use of telemedicine technology (ATUTT) (0.211, p = 0.002), PEOU and Acceptance of telemedicine technology (ATT) (0.245, p = 0.000), PU and (ATT) (0.212, p = 0.002), ATUTT and (ATT) (0.189, p = 0.005). However, PEOU was found to have an insignificant relationship with (0.048, p = 0.093). Hypotheses 1, 3, 4, 5, and 6 are supported while H2 was not supported.Conclusion: The study aims to fill the knowledge vacuum identified, helping poor countries effectively implement telemedicine technology to modernise the health care sector. In addition, results from this study shed insight on the varied impacts of individual, technical, clinical and multidimensional social influence variables on health care providers’ decisions to use telemedicine.Contribution: This study contributes to the body of knowledge by investigating the success factors for telemedicine technology adoption in South African public hospitals. These results have important implications for the public health care system in South Africa, both for the direction of future research and for the methods used to promote the use of telemedicine.

Predictive modeling of transverse cracking in continuously reinforced concrete pavement: a machine learning approach

Abstract Accurate prediction of transverse cracking in Continuously Reinforced Concrete Pavement (CRCP) is critical for improving infrastructure management procedures and preserving the road network's long-term durability and safety. This paper conducts a thorough analysis into predicting transverse cracking in CRCP using machine learning approaches. The research involved meticulous data preparation, feature selection, and evaluation of various machine learning models to identify the most effective predictor. Key variables such as pavement age, total thickness, temperature, freeze index, traffic volume, precipitation, and initial International Roughness Index (IRI) were analyzed for their impact on transverse cracking occurrences. Sensitivity analysis was conducted to assess the influence of individual input variables on model predictions. Results indicated that the cubic Support Vector Machine (SVM) model outperformed other models, demonstrating exceptional predictive accuracy. Furthermore, sensitivity analysis revealed significant correlations between input variables and transverse cracking occurrences, emphasizing the importance of considering a holistic range of factors in pavement engineering and maintenance strategies. Our findings, which provide insights into the intricate interactions between input factors and pavement distress, help to create tailored treatments and methods for minimizing transverse cracking and enhancing CRCP performance.

Effectiveness of the handgrip test for assessing readiness in national level basketball players: a cohort study.

Assessing player readiness is crucial in elite basketball. This study aims to provide a practical method for monitoring player readiness through the handgrip test and identify associations with wellness scales. Fifteen players (age: 25.3±3.3 years; weight: 92.2±11.8 kg; height: 1.94±0.09 m; BMI: 24.3±1.8 kg/m2; experience: 6.5±3.4 years) from an elite basketball team participated in this cohort study, which was conducted over 9 weeks of training and official competitions. All players were medically cleared and injury-free for three months prior. Daily psychometric questionnaires assessed different aspects of wellness using analog scales, combined with a handgrip test. Training cycles were developed according to the Game-Day method. All parameters investigated, except the handgrip test, (means ranging from 53.43±8.06 kg to 54.03±7.79 kg) showed significant variations in the weekly training cycle (P<0.05). The linear regression results indicate that while the overall model is statistically significant (P=0.039), the predictive power of the individual independent variables is not strong, with the model able to explain approximately 4.13% of the variability in the dependent variable "Handgrip." The calculation of the minimal detectable change (MDC) confirmed that for this variable, on average, significant changes (approximately 6.77 kg) are generally required to be noteworthy. This study demonstrates that the handgrip test is not an effective tool for objectively assessing player readiness in elite basketball. Regular monitoring using this method cannot help in making informed decisions about training and competition readiness. Conversely, psychometric have shown stronger sensitivity in determining player status during the weekly training cycle.

Maternal socialization and infant helping in Uganda and the United Kingdom.

Prosocial behavior, including instrumental helping, emerges early in development, but the role parental attitudes and practices take in shaping the emergence of early helping across different cultural contexts is not well understood. We took a longitudinal approach to investigate maternal socialization of early helping across two different cultural groups. Participants were mother-infant dyads from urban/suburban York, United Kingdom (43 infants: 21 females, 22 males) and the rural Masindi District, Uganda (39 infants: 22 females, 17 males). We examined cultural variations in mother's helping-related parenting practices toward 14- and 18-month-olds and infants' actual helping in experimental tasks at 18 months. We then asked whether maternal parenting practices and socialization goals predicted individual variation in infant helping. We found that U.K. mothers scaffolded infant helping using a larger range of strategies than Ugandan mothers, but expecting an infant to help was more common in Uganda than in the United Kingdom. Moreover, we found that the Ugandan infants were more likely and often quicker to help an adult in need than the U.K. infants. Finally, we found that maternal scaffolding behaviors positively predicted individual variation in infant helping at 18 months in the United Kingdom, but not in Uganda. By contrast, maternal alignment with relational socialization goals at 11 months positively predicted infant helping at 18 months in the Ugandan, but not in the U.K., sample. These results indicate that early instrumental helping behavior varies across societies and that maternal socialization goals and scaffolding behaviors can shape infant helping in culturally specific ways. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Longitudinal Improvement of Quality of Life in Children With Legg-Calve-Perthes Disease Treated With Proximal Femoral Varus Osteotomy.

Proximal femoral varus osteotomy (PFVO) is commonly performed to improve femoral head containment and decrease deformity in Legg-Calve-Perthes disease (LCPD). Little is known about how PFVO impacts the quality of life after surgery. The purpose of this study was to determine the longitudinal changes to patient-reported physical, mental, and social health measures after PFVO. This is a retrospective review of prospectively collected Patient-Reported Outcomes Measurement Information System (PROMIS) data from 20 patients with unilateral LCPD treated with a PFVO. We collected seven PROMIS measures (mobility, anxiety, fatigue, depressive symptoms, pain interference, anger, and peer relationships) before and approximately 1, 3, 8, 12, and 18 months after surgery. We compared PROMIS scores across different time points using repeated measures ANOVA and multiple pairwise comparisons with Tukey adjustment. The relationship between presurgery and postsurgery mental health scores was analyzed using a Spearman correlation. The mean age at PFVO was 8.2 ± 1.6 years. The mean length of follow-up was 17.0 ± 2.1 months. There was a significant improvement in the mobility score between preoperation and 12 months (P=0.0031) and 18 months postoperation (P<0.0001). Anxiety scores significantly improved from preoperation and 18 months postoperation (P=0.0014). A significant reduction in the pain interference score between preoperation and 12 and 18 months postoperation (P<0.0001) was observed. Peer relationships significantly improved from one month postoperatively to 18 months postoperation (P=0.0355). Individual variations were also observed with some patients having elevated depressive symptoms and anxiety scores. Moderate correlations between preoperative and postoperative anxiety and depressive symptoms scores were observed. PROMIS mobility, anxiety, pain interference, and peer relationship scores improved significantly after PFVO. While the mean anxiety, depressive symptoms, peer relationships, and anger scores were in normal ranges at each visit, individual variations with elevated anxiety and depressive symptom scores were observed. This new longitudinal PROMIS data will better inform patients and families about the quality of life and recovery experience after PFVO. Level IV-therapeutic study.

Exploring Brain Imaging and Genetic Risk Factors in Different Progression States of Alzheimer's Disease Through OSnetNMF-Based Methods.

Alzheimer's disease (AD) is a neurodegenerative disease with no effective treatment, often preceded by mild cognitive impairment (MCI). Multimodal imaging genetics integrates imaging and genetic data to gain a deeper understanding of disease progression and individual variations. This study focuses on exploring the mechanisms that drive the transition from normal cognition to MCI and ultimately to AD. As an effective joint feature extraction and dimensionality reduction method, non-negative matrix factorization (NMF) and its improved variants, particularly the network-based non-negative matrix factorization (netNMF), have been widely used in multimodal analysis to mine brain imaging and genetic data by considering the interactions between different features. However, many of these methods overlook the importance of the coefficient matrix and do not address issues related to data accuracy and feature redundancy. To address these limitations, we propose an orthogonal sparse network non-negative matrix factorization (OSnetNMF) algorithm, which introduces orthogonal and sparse constraints based on netNMF. By establishing linear relationships between structural magnetic resonance imaging (sMRI) and corresponding gene expression data, OSnetNMF reduces feature redundancy and decreases correlation between data, resulting in more accurate and reliable biomarker extraction. Experiments demonstrate that the OSnetNMF algorithm can accurately identify risk regions of interest (ROIs) and key genes that characterize AD progression, revealing significant trends in ROI pairs such as l4thVen-HIF1A, rBst-MPO, and rBst-PTK2B. Comparative experiments show that the improved algorithm outperforms traditional methods, identifying more disease-related biomarkers and achieving better reconstruction performance.

A distributed subcortical circuit linked to instrumental information-seeking about threat

Daily life for humans and other animals requires switching between periods of threat- and reward-oriented behavior. We investigated neural activity associated with spontaneous switching, in a naturalistic task, between foraging for rewards and seeking information about potential threats with 7T fMRI in healthy humans. Switching was driven by estimates of likelihood of threat and reward. Both tracking of threat and switching to a vigilant mode in which people sought more information about potential threats were associated with specific but distributed patterns of activity spanning habenula, dorsal raphe nucleus (DRN), anterior cingulate cortex, and anterior insula cortex. Different aspects of the distributed activity patterns were linked to monitoring the threat level, seeking information about the threat, and actual threat detection. A distinct pattern of activity in the same circuit and elsewhere occurred during returns to reward-oriented behavior. Individual variation in DRN activity reflected individual variation in the seeking of information about threats.

Rightward brain structural asymmetry in young children with autism.

To understand the neural mechanism of autism spectrum disorder (ASD) and developmental delay/intellectual disability (DD/ID) that can be associated with ASD, it is important to investigate individuals at an early stage with brain, behavioural and also genetic measures, but such research is still lacking. Here, using the cross-sectional sMRI data of 1030 children under 8 years old, we employed developmental normative models to investigate the atypical development of gray matter volume (GMV) asymmetry in individuals with ASD without DD/ID, ASD with DD/ID and individuals with only DD/ID, and their associations with behavioral and clinical measures and transcription profiles. By extracting the individual deviations of patients from the typical controls with normative models, we found a commonly abnormal pattern of GMV asymmetry across all ASD children: more rightward laterality in the inferior parietal lobe and precentral gyrus, and higher individual variability in the temporal pole. Specifically, ASD with DD/ID children showed a severer and more extensive abnormal pattern in GMV asymmetry deviation values, which was linked with both ASD symptoms and verbal IQ. The abnormal pattern of ASD without DD/ID children showed higher and more extensive individual variability, which was linked with ASD symptoms only. DD/ID children showed no significant differences from healthy population in asymmetry. Lastly, the GMV laterality patterns of all patient groups were significantly associated with both shared and unique gene expression profiles. Our findings provide evidence for rightward GMV asymmetry of some cortical regions in young ASD children (1-7 years) in a large sample (1030 cases), show that these asymmetries are related to ASD symptoms, and identify genes that are significantly associated with these differences.

Anterior-temporal network hyperconnectivity is key to Alzheimer's disease: from ageing to dementia.

Curing Alzheimer's disease remains hampered by an incomplete understanding of its pathophysiology and progression. Exploring dysfunction in medial temporal lobe networks, particularly the anterior-temporal (AT) and posterior-medial (PM) systems, may provide key insights, as these networks exhibit functional connectivity alterations along the entire Alzheimer's continuum, potentially influencing disease propagation. However, the specific changes in each network and their clinical relevance across stages are not yet fully understood. This requires considering commonly used biomarkers, clinical progression, individual variability, and age confounds. Here, we leveraged monocentric longitudinal data from 261 participants spanning the adult lifespan and the Alzheimer's continuum. The sample included cognitively unimpaired adults aged 19 to 85 years (n = 209; eight out of 64 older adults over 60 were Aβ-positive) and Aβ-positive patients fulfilling diagnostic criteria for mild cognitive impairment (MCI, n = 26; 18 progressed to Alzheimer-dementia within seven years) or Alzheimer's type dementia (n = 26). Participants underwent structural and resting-state functional (f) MRI, florbetapir and FDG-PET, and global cognitive assessments, with up to three visits over a maximum period of 47 months. Network connectivity was assessed using seed-based analyses with the perirhinal and parahippocampal cortices as seeds, within data-driven masks reflecting the AT and PM networks. Generalized additive and linear mixed models were run to assess age-specific effects and Alzheimer's-related alterations. In this context, we explored various markers of pathological and clinical severity, including cerebral amyloid uptake, glucose metabolism, hippocampal volume, global cognition, diagnostic staging, and time to dementia onset. Our findings revealed distinct patterns of connectivity linked to normal aging or Alzheimer's disease. Advancing age throughout adulthood was associated with lower PM connectivity and more subtle changes in AT connectivity, while Alzheimer's disease was characterised by AT hyperconnectivity without global changes in PM connectivity. Specifically, AT connectivity was higher in MCI and Alzheimer-dementia patients compared to older controls and was positively associated with amyloid burden, glucose hypometabolism, hippocampal atrophy, and global cognitive deficits in older adults, ranging from unimpaired to demented. Additionally, higher AT connectivity correlated with faster progression to Alzheimer-dementia in MCI patients. This comprehensive approach allowed to reveal that excessive connectivity within the AT network is intrinsically linked to the pathological and clinical progression of Alzheimer's disease. These insights may guide future research to better understand cascading events leading to the disease and hold promise for developing prognostic tools and therapeutic interventions targeting these specific network alterations.

Tracking changes in autonomic function by coupled analysis of wavelet-based dispersion of heart rate variability and gastrointestinal symptom severity in individuals with hypermobile Ehlers–Danlos syndrome

IntroductionPeople with hypermobile Ehlers–Danlos syndrome (hEDS) experience multisystemic dysfunction with varying severity and unpredictability of flare occurrence. Cohort studies suggest that individuals with hEDS have a higher risk for autonomic dysfunction. The gold standard for assessing autonomic function, clinically, is the heart rate variability (HRV) assessment from 24-h Holter monitor electrocardiogram data, but this is expensive and can only be performed in short durations. Since their advent, biometric devices have been a non-invasive method for tracking HRV to assess autonomic function. This study aimed to understand the intra- and inter-individual variability in autonomic function and to associate this variability with gastrointestinal symptoms in individuals with hEDS using wearable devices.MethodsWe studied 122 days of biometric device data from 26 individuals, including 35 days highlighted as high gastrointestinal (GI) dysfunction and 48 days as low GI dysfunction. Utilizing wavelet analysis to assess the frequency domains of heart rate signals, we compared participants’ HRV data for high, low, very low (VLF), and ultralow (ULF) frequency domains associated with physiological differences.ResultsWe found a significant difference between the VLF and ULF signals on high-GI symptom days compared with low-symptoms days for 92 and 76% of the signals sampled, respectively.DiscussionOur pilot data show a change in HRV for individuals with hEDS experiencing a flare day for a single-body system. Future research will focus on evaluating the relationship between longitudinal multisystemic symptom severity fluctuations and HRV.

Advancing veterinary vaccines design through trained immunity insights

Trained immunity, characterized by long-term functional reprogramming of innate immune cells, offers promising new directions for veterinary vaccine development. This perspective examines how trained immunity can be integrated into veterinary vaccine design through metabolic reprogramming and epigenetic modifications. We analyze key molecular mechanisms, including the shift to aerobic glycolysis and sustained epigenetic changes, that enable enhanced immune responses. Strategic approaches for vaccine optimization are proposed, focusing on selecting effective trained immunity inducers, developing innovative adjuvant systems, and achieving synergistic enhancement of immune responses. While implementation challenges exist, including individual response variations and safety considerations, trained immunity-based vaccines show potential for providing broader protection against emerging pathogens. This approach could revolutionize veterinary vaccinology by offering enhanced efficacy and cross-protection against heterologous infections, particularly valuable for zoonotic disease control.

Sustainable synergy: exploring the nexus of green initiatives and digitalization in gulf countries – a comprehensive study on environmental, social, and governance (ESG) indicators

Purpose This research investigates the trajectory of Gulf region, focusing on the interplay between environmental, social and governance (ESG) factors and key elements – digital economy, green economy (GE), green finance, green energy and green innovation. This study aims to provide a nuanced understanding of how Gulf economies align their developmental pursuits with sustainability principles amidst the rapid evolution of digital technologies. Design/methodology/approach A data set of 95 listed companies from six Gulf Cooperation Council countries – Bahrain, Kuwait, Oman, Qatar, Saudi Arabia and the United Arab Emirates – from year 2016 to 2022 was compiled from reputable sources. Using fixed effect regression techniques, this study explores relationships, accounting for individual and time-specific variations. Findings This study indicates that key factors – digital economy, GE, green energy and green innovation – significantly influence ESG performance across Gulf nations underscoring the potential for strategic integration of these elements to enhance sustainable practices. However, the nonsignificant impact of green finance highlights a need for further exploration and refinement of financial mechanisms to effectively contribute to ESG goals in the Gulf region. Research limitations/implications The findings underscore the importance for Gulf policymakers to prioritize ongoing support and policy formulation fostering digitalization and green initiatives. Businesses in the region can enhance ESG performance by integrating sustainable practices, promoting long-term resilience and reputation. Investors and financial institutions can use these insights to guide investment decisions, prioritizing projects contributing to environmental sustainability and social responsibility. Originality/value Amidst the current sustainability imperative, this research holds unique value in its timely exploration of the Gulf region’s sustainable landscape, providing crucial insights into the interplay between ESG factors and digital and green initiatives.

Weights of tensor, abductor and adductor muscles of the human larynx

The intrinsic muscles of the larynx interconnect the laryngeal cartilages and help in their mobility. Three muscles cricothyroid tensor of vocal cord, supplied by external laryngeal nerve. Posterior cricoarytenoid abductor of vocal cord, Lateral cricoarytenoid adductor of vocal cord both these muscles are supplied by recurrent laryngeal nerve. This study is important in various clinical laryngeal palsies.A good understanding of the anatomy and the knowledge of laryngeal muscles is important.Aim of the present study was to measure the weight of cricothyroid (Tensor), posterior cricoarytenoid (Abductor) and lateral cricoarytenoid (Adductor) muscles. Proposal of practical use of data on the basis of this study.Fifty laryngeal preparations from adult cadavers of Western India were assessed. Sections were prepared via dissection and the removed muscles weighed&amp; statistical analysis was done.The mean weight of the cricothyroid on right side was 309.68±102.94 on left side was 332.81±116.7. The mean weight of the posterior cricotarytenoid on right side was 230.01±60.93 on left side was 231.06±61.35.The mean weight of the lateral cricotarytenoid on right side was 60.56±24.10 on left side was 63.48±19.67.Wide individual variation in weight of the muscles was observed. The Average weight of thecricothyroid muscle (tensor) was more than the Posterior cricoarytenoid (abductor) &amp; Lateral cricoarytenoid muscle (adductor). The Average weight of the Posterior cricoarytenoid (abductor) was more as compared to Lateral cricoarytenoid muscle (adductor).

Integrated omics profiling of individual variations in intestinal damage to the soybean allergen in piglets

IntroductionA small number of soybean allergens [including Glycinin (11S) and β-Conglycinin (7S)] in the commercially available corn-soybean meal diet can still cause allergy in some weaned piglets, which may be the result of the interaction of genetic, and nutrition, but the specific mechanism is still unclear.MethodsIn this study, 20 allergic piglets and 20 non-allergic piglets were selected from 92 weaned piglets by skin sensitization tests, which were used to examine the whole sequence genome. The indicators related to humoral and cellular immunity, transcriptomics, and metabolomics analysis were determined by randomly selecting 5 boars in the allergic group and non-allergic group and then performing a validation in vitro.ResultsThe sensitization rate of soybean antigen in the corn-soybean meal diet was 21.74% and there was a gender difference with the sensitization rate of female pigs (31.34%) being higher than that of male pigs (13.23%). Moreover, the levels of inflammatory factors (IL-1β, IL-4, TNF-α) and antibodies (IgG, IgE, and specific IgG) in allergic piglets were significantly higher than those in non-allergic piglets (P &amp;lt; 0.05). Whole genome re-sequencing analysis revealed specific mutations in the exons and URT5 of TRAPPC2, PIR, CFP, and SOWAHD genes and showed significantly higher expression levels of related genes in the spleen of allergic piglets (P &amp;lt; 0.05). Transcriptome analysis identified IL17REL, CCL19, CD1E, CD1.1, etc. immune differential genes, metabolomics results showed that soybean antigen affected the utilization and metabolism of intestinal nutrients in piglets, mainly the digestion and absorption of protein and the synthesis and metabolism of amino acids. Transfection of CFP/TRAPPC2/CCL19 siRNA could partially alleviate the injury of RAW264.7 cells or IPEC-J2 cells induced by β-Conglycinin.ConclusionTherefore, the individual differences in intestinal damage induced by soybean antigen protein in the corn-soybean meal diet are closely related to PIR, CFP, TRAPPC2, SOWAHD, and CCL19 genes. Soybean antigens affect the intestinal nutrient utilization and metabolism of piglets, which provides a scientific reference for the study of soybean antigen sensitization mechanisms, precision nutrition, disease prevention, and control of piglets, and also lays a foundation for human foodborne diseases.