Search Results (3,257)

Background: The COVID-19 pandemic and related containment measures profoundly affected child and adolescent mental health, with increasing evidence of a rise in psychiatric symptomatology and healthcare burden. This study aimed to evaluate temporal changes in neuropsychiatric presentations before, during, and after the COVID-19 pandemic in a pediatric clinical population. Methods: In this retrospective single-center study, 505 children and adolescents referred to a pediatric neuropsychiatry service were included and stratified into three periods: pre-pandemic (n = 112), pandemic (n = 231), and post-pandemic (n = 162). Clinical and healthcare-related variables were retrospectively collected, including reasons for referral, psychiatric diagnoses, premorbid conditions, and pharmacological treatments. Comparative analyses were performed to identify temporal variations in psychopathological profiles and clinical management. Results: A significant increase in psychiatric symptomatology emerged in the post-pandemic period compared with the pre-pandemic period. In particular, eating disorders, mood disturbances, self-harm, and somatic symptom presentations showed a marked increase over time, presenting as recurrent and associated phenotypes that peaked or consolidated after the acute emergency. The pandemic period was primarily characterized by a greater need for psychopharmacological intervention, specifically driven by the clinical need to manage acute behavioral crises. Overall, findings indicated a persistent increase in the complexity and severity of neuropsychiatric presentations beyond the acute phase of the pandemic. Conclusions: The COVID-19 pandemic was associated with substantial changes in pediatric neuropsychiatric presentations and treatment needs. The persistence of the increased psychopathological burden in the post-pandemic period highlights long-term mental health trajectories associated with the pandemic era. These emerging patterns of phenotypic complexity demonstrate that child and adolescent psychiatric services must transition from single-diagnosis models toward integrated care networks. Practically, strengthening community-based early intervention and creating rapid-access crisis support are essential to manage severe emotional dysregulation in the community and reduce acute psychiatric hospitalizations. Full article

The neurexin1 gene (NRXN1) encodes a presynaptic adhesion molecule that plays a critical role in synapse formation, maintenance, and function. Copy-number variants (CNVs) affecting the NRXN1 locus, including submicroscopic deletions, represent rare variant acting as a predisposition for neurodevelopmental disorders, such as Pitt–Hopkins-like syndrome type 2 (MIM #614325) and susceptibility to schizophrenia (MIM #621407). Variations in NRXN1 gene are associated with marked clinical heterogeneity. We present a familial case involving two male siblings (aged 6 and 5 years) and their 28-year-old mother, all exhibiting variable neurodevelopmental phenotypes. Both children demonstrated disharmonic developmental profiles characterized by impaired communication, speech largely intelligible only to their parents, and behaviors consistent with autism spectrum disorder, including reduced eye contact. Mother represents a carrier with only subtle, nonspecific behavioral traits, further supporting the concept of incomplete penetrance and variable expressivity associated with this genetic alteration. Genetic analysis identified a 317 kb NRXN1 deletion shared by all affected family members, accompanied by significant intrafamilial phenotypic variability, suggesting the contribution of additional genetic and/or modifying factors. These findings support the concept that NRXN1 deletions alone do not determine clinical outcome but rather act within a broader genetic and biological context. The marked intrafamilial phenotypic variability and incomplete penetrance observed in this family is compatible with a multiple-hit model, whereby NRXN1 deletions act as susceptibility factors whose phenotypic consequences are shaped by additional genetic and modifying influences. However, the genetic mechanisms underlying the observed phenotypic variability warrant further investigation. Full article

Background: Febrile seizures (FSs) are the most common neurological emergency in early childhood; however, the biological basis of disease heterogeneity remains poorly understood. Although growing evidence suggests that gut–brain axis dysregulation contributes to seizure susceptibility, it remains unclear whether gut microbiota-associated metabolic disturbances are linked to clinical phenotypes, particularly simple FS (SFS) and complex FS (CFS). Methods: An integrated multiomics study was conducted in clinically characterized pediatric cohorts, comprising 50 children with FS and 50 healthy controls, and their gut microbiota was profiled via 16S rRNA sequencing. As some pediatric serum specimens did not meet the minimum volume requirement of the analytical platform, serum amino acid profiling was performed in a subset of samples using an equal-volume pooling strategy. In brief, two individual serum samples from the same study group were combined into one composite sample, yielding 25 pooled samples in the FS group and 25 in the control group. Subsequently, untargeted fecal metabolomics was performed in an expanded cohort of 53 healthy controls, 50 children with SFS, and 42 children with CFS. Additionally, the central metabolic profiles of the CFS and SFS groups were compared using untargeted cerebrospinal fluid metabolomics. Given the variation in sample sizes across omics platforms, each dataset was analyzed within its corresponding eligible subset, and cross-omics integration was interpreted primarily at the pathway and phenotype levels. Results: Children with FS exhibited reduced gut microbial diversity and altered microbial composition, characterized by the enrichment of Streptococcus, Enterococcus, and Escherichia–Shigella, along with the depletion of beneficial taxa, including Faecalibacterium, Lachnoclostridium, and Parasutterella. Functional prediction indicated significant changes in amino acid-related pathways, especially arginine and proline metabolism, amino acid metabolism, and glutathione metabolism. Serum profiling showed elevated levels of phenylalanine, kynurenine, and γ-aminobutyric acid, along with reduced levels of tryptophan, threonine, lysine, glutamine, taurine, citrulline, 3-methylhistidine, α-aminobutyric acid, hydroxyproline, and phosphoethanolamine. Correlation analysis identified Lachnoclostridium and Parasutterella as key taxa associated with neuroactive metabolites. Additionally, fecal metabolomics revealed that both SFS and CFS samples exhibited significant metabolic divergence from the controls, with arginine biosynthesis emerging as a shared altered pathway and L-arginine reduced in both phenotypes. Notably, cerebrospinal fluid metabolomics demonstrated clear metabolic separation between CFS and SFS, signifying phenotype-specific central metabolic signatures. Conclusions: FS is related to gut microbiota dysbiosis, systemic amino acid remodeling, and phenotype-associated metabolic stratification. Arginine metabolism may represent a shared mechanistic hub across FS phenotypes, while central metabolic divergence may contribute to the biological distinction between SFS and CFS. These findings establish a multiomics framework for understanding FS pathogenesis and identifying potential biomarkers and therapeutic targets. Full article

Background: Despite advances in genetic testing, many 46,XY Disorders of sex development (DSD) cases remain unsolved after whole-exome sequencing (WES). This study intended to explore rare variants in patients with micropenis, cryptorchidism, or hypospadias using bioinformatics analysis to identify potential pathogenic contributors and pathways underlying 46,XY DSD. Methods: A total of 35 patients with specific phenotypes (micropenis/cryptorchidism/hypospadias) and negative whole-exome sequencing results were enrolled. Bioinformatics analysis methods (SKAT-O test and GO enrichment) were applied to identify the putative loss-of-function (pLoF) variation, including nonsense, frameshift, and canonical splice-site variants, and predicted deleterious missense variants (CADD Phred > 20). Literature was reviewed to explore the correlation of detected candidate genes/pathways and 46,XY disorder of sex development. Results: After variant quality filtering, we identified 307,638 pLoF variants and 127,857 predicted deleterious missense variants across all samples. In subgroup A (micropenis, n = 21), we identified 146,268 pLoF variants and 104,746 predicted deleterious missense variants. In subgroup B (cryptorchidism, n = 10), we identified 111,172 pLoF variants and 77,244 predicted deleterious missense variants. In subgroup C (hypospadias, n = 4), we identified 50,198 pLoF variants and 23,111 predicted deleterious missense variants. Using SKAT-O with an initial screening threshold of p < 0.005 (FDR q < 0.05), we obtained 67 candidate genes from the pLoF variant set and 59 candidate genes from the predicted deleterious missense variant set in subgroup A; 81 and 11 candidate genes, respectively, in subgroup B; and 17 and 0 candidate genes, respectively, in subgroup C. Conclusions: Assessment of rare variants helps further explore the genetic contributors to 46,XY disorder of sex development and provide potential candidate genes and associated pathways. Full article

Background/Objectives: Plant architecture and kernel-related traits are important determinants of yield potential and breeding value in peanut (Arachis hypogaea L.). This study aimed to construct a high-density genetic linkage map, identify quantitative trait loci (QTL) associated with these traits, and prioritize candidate genes underlying key genomic regions in cultivated peanut. Methods: A recombinant inbred line population derived from Luojiangjiwo, a sprawling large-pod line, and Fuhuasheng, an erect small-pod line, was used to construct a high-density genetic linkage map and identify QTL associated with plant architecture and kernel traits. Results: Specific-locus amplified fragment sequencing generated 1,295,490,603 clean reads, with an average Q30 of 93.67%. After SNP discovery, filtering, and linkage analysis, 2646 SNP markers were mapped to 20 linkage groups, spanning 1338.86 cM with an average marker interval of 0.51 cM. Phenotypic evaluation of 16 traits revealed broad variation among 200 recombinant inbred lines, with strong positive correlations among pod-size traits and among kernel-size traits. Composite interval mapping detected eight QTL distributed on chr04, chr05, chr13, and chr15, including five QTL for plant architecture traits and three QTL for kernel-related traits. qLBL13 for lateral branch length explained the highest phenotypic variation, whereas qMKL05 for mean kernel length was delimited to a 0.151 Mb interval containing only nine genes. Candidate-gene analysis prioritized AH05G29360, encoding a knotted-1-like homeobox protein; AH05G29380, encoding mitogen-activated protein kinase kinase 9; AH05G29350, encoding COP1-interacting protein 7; and AH05G29410, encoding a pentatricopeptide repeat-containing protein. Additional candidates included AH15G16520, AH15G16460, AH15G16630, and AH15G16770 in the shared qHKW15/qMKW15 interval. Conclusions: This study identified genomic regions and biologically relevant candidate genes associated with plant architecture and kernel-related traits in peanut. These findings provide valuable genomic resources for future functional validation and facilitate marker-assisted breeding for improved plant architecture and kernel characteristics. Full article

Rice yield is a complex polygenic trait influenced by intricate interactions among component characters. In this study, integrative quantitative genetics and multivariate models were used to dissect yield architecture and trait networks, and identify the promising genotypes among 21 rice genotypes that were tested in a randomized block design with three replicates. Analysis of variance revealed highly significant genotypic differences (p < 0.001) for most agronomic, yield, and grain-quality traits. Genetic variability analysis revealed high genotypic and phenotypic coefficients of variation, together with high heritability and genetic advance, for grain density per panicle, number of grains per panicle, biomass, flag leaf area, tillering ability, harvest index, and grain yield, indicating considerable genetic potential for genetic improvement. Pearson’s correlation and path coefficient analyses revealed that biomass and number of grains per panicle were the major determinants of grain yield per hill, with biomass exhibiting the strongest positive association (r = 0.678) and the largest direct effect. Principal component analysis indicated that the first two principal components explained 51.4% of the total phenotypic variation, with yield components, biomass, tillering traits, and grain-quality attributes contributing most strongly to genotype differentiation. Hierarchical cluster analysis grouped the genotypes into four distinct clusters, revealing substantial phenotypic divergence and valuable parental combinations for hybridization. The multi-trait selection index identified VAR16 as the most promising genotype, followed by VAR1, VAR17, VAR18, and VAR12, owing to their desirable combination of high grain yield and superior grain quality. Overall, this study offers a robust foundation for ideotype breeding and parental selection to enhance rice productivity and grain quality under subtropical conditions. Full article

Flowering time is an important trait affecting regional adaptation and yield stability in rapeseed (Brassica napus). To dissect the genetic basis of flowering time and vernalization-type differentiation in B. napus, this study integrated genome-wide SNPs, flowering-time phenotypes, vernalization types, and geographic origin information to establish a candidate QTL discovery framework combining genome-wide association study (GWAS) and machine learning. Based on 8,387,529 high-quality SNPs, GWAS was performed using the FarmCPU model under two covariate settings: a PC-corrected model and a PC + vernalization type-corrected model. These two models identified 32 and 27 suggestive SNPs, respectively. In parallel, ExtraTreesRegressor was used to estimate the feature contribution of SNPs to flowering-time prediction, leading to the identification of 18,854 ML_delta10SD high-contribution SNPs, which were further merged into 997 ML-derived candidate QTL intervals, hereafter referred to as ML-QTLs. By integrating GWAS-derived QTLs and ML-QTLs at the interval level, 34 GWAS- and ML-supported candidate regions were prioritized. Candidate gene annotation revealed that these regions contained genes related to flowering regulation, including FLC, FRIGIDA-like, VIN3-like, SOC1, ELF3, CONSTANS-like, APETALA1-like, and genes involved in the gibberellin pathway. Top-SNP genotypic effect analysis and multi-SNP genotype combination analysis further showed that genetic variation within representative candidate regions was significantly associated with flowering-time differences and vernalization-type differentiation. Predictive modeling indicated that candidate markers selected by GWAS and machine learning showed predictive potential within the present population. Overall, this study prioritized a set of GWAS- and ML-supported candidate regions and putative candidate genes associated with flowering time in B. napus from the complementary perspectives of statistical association and machine learning-based predictive contribution, providing candidate resources for future marker development, functional validation, and adaptive improvement in rapeseed. Full article

Mitochondrial genetic disorders compromise oxidative phosphorylation (OXPHOS) and cellular energy supply, and the eye is among the first organs to feel the deficit. Photoreceptors and retinal ganglion cells (RGCs) sustain among the highest metabolic rates in the body, so ophthalmic features often dominate the clinical picture and arrive before systemic disease is recognized. More than half of all patients with confirmed mitochondrial disease develop sight-threatening complications. This review integrates mtDNA and nuclear genetics; ophthalmic and extraocular phenotypes; the bioenergetic and apoptotic mechanisms that drive vision loss; the clinical examination and investigations that delineate the problem; the differential diagnoses that must be excluded; the contribution of common mtDNA haplogroup variation to age-related retinal disease; and the diagnostic, therapeutic, and counseling approaches that turn a molecular result into useful care. Recurring themes are heteroplasmy, the threshold effect, and the selective vulnerability of RGCs and extraocular muscle across genetically distinct disorders. Treatment remains largely supportive, but idebenone, gene therapy, mitophagy modulation, and targeted antioxidants now offer mechanism-based intervention for several ophthalmic manifestations. Full article

Background: Tight junctions are major components of apical junction complexes and are crucial for the maintenance of cell polarity, healthy tissue architecture, adhesion, and permeability. These junctions include the claudin family of transmembrane proteins, which act as paracellular barriers to regulate selective permeability. Abnormal claudin expression disturbs cell adhesions and is associated with cancer through promoting cell invasion, migration, and metastasis. Claudin 6 (CLDN6) overexpression, in particular, is linked to several types of cancer with malignant phenotypes. The present study aimed to investigate the association between CLDN6 protein expression and its copy number variations (CNVs) with clinicopathological features and survival outcomes of ovarian cancer (OC) patients. Methods: A total of 114 formalin-fixed paraffin-embedded blocks from primary OC patients were used to construct tissue microarray slides. Automated immunostaining was used to assess CLDN6 protein expression levels, and next-generation knowledge discovery platforms were used to further evaluate CLDN6 CNV levels using The Cancer Genome Atlas open-source data. The relationships between CLDN6 CNVs and tumor stage, overall survival, disease-specific survival (DSS), and disease-free survival (DFS) were investigated. Results: This study demonstrated that CLDN6 had a mixed membranous-cytoplasmic expression pattern. The cytoplasmic expression of CLDN6 was significantly associated with tumor stage (p = 0.05), tumor size (p = 0.04), and recurrence (p = 0.05). In Univariate analysis, Kaplan–Meier analysis demonstrated that CLDN6 expression was significantly correlated with DFS (p = 0.01). OC patients with lower cytoplasmic CLDN6 expression levels lived longer and had lower recurrence rates. These findings were further confirmed through CLDN6 CNVs analysis, where OC with lower CLDN6 cytoplasmic expression positively correlated with longer DFS and DSS. No independent prognosticator was found when using Cox-regression multivariate analysis (p > 0.05). Conclusions: These results suggest CLDN6 as an interesting prognosticator to identify OC patients at a higher risk of recurrence in order to provide personalized management, alleviate the burden of this disease on women’s health, and improve their survival outcomes. Full article

Fruit taste in apple (Malus × domestica) is one of the most important quality attributes and it is primarily determined by the balance between soluble sugars (mainly glucose, fructose, and sucrose) and organic acid. The combination of these metabolites influences the consumer preference by impacting sweetness and acidity, and therefore represent the central target of several apple breeding programs. To investigate the genetic control of taste-related traits, a pedigree-based QTL (Quantitative Trait Loci) analysis (PBA) across six full-sub apple families was performed to identify major QTL-associated traits in elite accessions. Bayesian statistics and Markov Chain Monte Carlo (MCMC) methods revealed the presence of a common QTL for glucose and fructose on linkage group (LG) 16 as well as sugar-specific intervals mapped on LG1 for fructose and LG12 for glucose. Furthermore, phenotypic sugars variation enabled also the identification of a QTL on LG4 for sucrose, while a QTL for malic acid content was detected on LG8. The LG16 was consistent between QTL-estimated genotypes, supporting its potential for marker-assisted selection. Our findings identified the genetic basis of apple taste traits, which can contribute to the development of improved apple cultivars with optimized sweetness and acidity balance and ultimately improved apple consumer appeal. Full article

Morphostructural characterization of Creole cattle is essential for assessing the diversity and productive potential in the highland livestock systems. The study was conducted in Chuschi and Chipao districts, at 3800 m above sea level, with the objective of morphostructurally characterizing 154 Creole cows. Seventeen phaneroptic variables and twenty-one morphometric variables were recorded. The multivariate analysis identified three cattle biotypes. Based on proportionality, compactness, and cannon bone load indices, Biotype 1 (16.9%) comprised more compact, robust, and heavier animals with a greater tendency toward meat production aptitude, followed by Biotype 2 (48.1%) and Biotype 3 (35.1%), which were more slender but with a stronger bone structure. No association was found between biotypes and phaneroptic characteristics, except for teat type (p < 0.05). The proportions of red, black, dull black, qosca, and roan coat colors were common across all biotypes; however, Biotype 1 predominated in callejón (15.38%), Biotype 2 in qosne (8.11%) and in other less frequent coat colors (10.81%), while Biotype 3 predominated in dark roan (16.67%) and jet black (11.11%). In the high-Andean region of Ayacucho, three subpopulations of Creole cattle were identified with potential for beef production, dual-purpose use, and adaptation to rugged terrain, highlighting the need to investigate their genetic diversity. Full article

Durio zibethinus Murr., commonly known as durian or the “King of Fruits,” is prized for its strong aroma, spiny rind, and unique flavor. With global demand rising, it has become a key export, especially for Thailand, which led the market in 2024 with US$4.4 billion in revenue. However, breeding efforts are hindered by limited genetic diversity research, long generation times, and environmental sensitivity. These challenges are compounded by weak enforcement of intellectual property protections under Thailand’s Plant Variety Protection Act (PVP), which limits incentives for breeders. To address this, Thailand has turned to Geographical Indications (GIs) to protect and promote region-specific varieties. By 2024, 17 GI designations were granted across 16 provinces, including the notable Monthong durian from Pakchong in Nakhon Ratchasima. Although classified under the Monthong group, genetic similarity was observed, while notable phenotypic variation exists among varieties. These differences may be attributed to specific agronomic or genetic traits, warranting investigation into the cultivation characteristics that influence consumer-related qualities and preferences. Strengthening supply chain standards through good agricultural practices, GIs, genetic profiling, and international certification, combined with the adoption of modern molecular breeding tools including marker-assisted selection, genomic selection, and CRISPR/Cas9, would support sustainable innovation, improved farmer revenues, and long-term global competitiveness in the durian industry across Southeast Asia. Full article

Pomegranate (Punica granatum L.) is widely valued for its rich nutritional profile and distinctive sensory characteristics. As one of the oldest cultivated fruits, it has an extensive history of cultivation in China and possesses abundant germplasm resources. Nevertheless, systematic evaluation of these resources remains inadequate, limiting progress in germplasm innovation and utilization. In this study, we analyzed 16 fruit quality traits across 142 pomegranate accessions. Most traits showed wide phenotypic variation, with coefficients of variation (CVs) ranging from 2.10% to 108.83%. Notably, titratable acidity (TA) and anthocyanin content showed high variability (coefficient of variation, CV > 78%), while fruit shape index and total soluble solids (TSS) showed relatively low variability (CV < 10%). Cluster analysis delineated three distinct phenotypic groups. The first group comprised accessions characterized by large fruit size, thick peel, high acidity, and soft seeds. The second group exhibited high seed hardness, low acidity, and elevated sugar-acid and TSS–acid ratios. The third group displayed reduced levels of bioactive compounds such as tannins, phenols, and anthocyanins, combined with high seed hardness. Correlation analysis followed by principal component analysis (PCA) extracted six principal components, and based on comprehensive scoring, SXXA23, AHHB13, SD41, SXXA27, AHHB40, HS1, AHHB8, HY22, HN4, and AH27 were identified as priority accessions for further evaluation within this repository panel. Full article

European plum (Prunus domestica L.) breeding for competitive production increasingly requires donor parents that combine attractive, market-oriented fruit quality with stable trait expression. This study evaluated a set of 36 phenotypically highly different cultivars from the germplasm collection maintained at the Research and Breeding Institute of Pomology Holovousy Ltd. (the Czech Republic). First, genetic analyses based on SSR marker data were performed to assess the diversity and kinship relationships within the selected collection of plum varieties. Several parentage combinations were successfully identified for cultivars with previously undocumented origins. Population-level analyses confirmed broad genetic diversity and separated the collection into four genetically distinct groups. Phenotypes were obtained on fruits ripened on trees from a non-irrigated orchard on myrobalan rootstock over five consecutive years (2019–2023). Pomological and related quality traits were recorded using nine-point UPOV-based rating scales together with instrumental measurements. The dataset included fruit size and shape descriptors, skin and flesh color, wax bloom, soluble solids (°Brix), firmness, bruising resistance, stone separability, and sensory attributes (flavor, aroma, juiciness, texture, and acidity). Interannual variability was quantified using coefficients of variation, and relationships among traits were explored using Pearson correlations. The results revealed broad phenotypic diversity among the individual varieties and also their genetic groups. Finally, phenotypes were associated with genotypes, and the most genetically determined traits were identified. Multi-year stability profiling supported the identification of candidate elite donor cultivars that combine favorable attributes for the fresh market and/or traits relevant to processing. These findings provide a practical pre-breeding shortlist and quantitative trait targets to support crossing design and selection under central European conditions. Full article

Background/Objectives: Healthcare-associated infections (HAIs) are a major and preventable threat to patient safety, yet reported figures in Central and Eastern Europe are widely affected by under-reporting, which can distort both the apparent infection profile and the perceived burden of disease. Patient-level regional surveillance data were analysed to characterise the reported HAI profile, the determinants of in-hospital mortality, and between-hospital surveillance quality in post-pandemic Southeast Romania. Methods: This was a retrospective, cross-sectional analysis of 2878 HAI cases reported across a five-county, multicentre network of 32 hospitals during 2024. Infections were grouped as Clostridioides difficile infection (CDI) versus non-CDI. Logistic regression was applied for in-hospital mortality, Cox and competing-risks models for time to death, negative binomial regression for length of stay, and a Spiegelhalter funnel plot for between-hospital variation. Results:Clostridioides difficile infection accounted for 56.3% of reported cases, a markedly higher proportion than that described in European point-prevalence surveys, although differences in design and denominator preclude direct comparison. CDIs and non-CDIs formed distinct clinical phenotypes. In-hospital mortality was lower in CDI than in non-CDIs (14.9% versus 26.1%) and was independently associated with intensive care admission, age, and immunosuppression, while CDI remained associated with lower mortality. The reported CDI proportion ranged from approximately 1% to 93% between hospitals, with most institutions lying outside the funnel control limits. Conclusions: The predominance of CDI among reported HAIs is best interpreted as a signal of selective ascertainment rather than as direct evidence of a genuinely higher CDI burden. Because the dataset lacked admission or patient-day denominators, the CDI-to-total ratio should be regarded as a simple screening indicator of potential surveillance imbalance, useful for identifying hospitals where non-CDIs may be under-detected. Full article