Search Results (4,895)

Germplasm resources embody the genetic diversity of plants and form the foundation for breeding and the ongoing improvement of elite cultivars. The establishment of germplasm banks, along with their systematic evaluation, constitutes a critical step toward the conservation, sustainable use, and innovative utilization of these resources. Liriodendron, a rare and endangered tree genus with species distributed in both East Asia and North America, holds considerable ecological, ornamental, and economic significance. However, a standardized evaluation system for Liriodendron germplasm remains unavailable. In this study, 297 Liriodendron germplasm accessions were comprehensively evaluated using 34 phenotypic traits and whole-genome resequencing data. Substantial variation was observed in most phenotypic traits, with significant correlations identified among several characteristics. Cluster analysis based on phenotypic data grouped the accessions into three distinct clusters, each exhibiting unique distribution patterns. This classification was further supported by principal component analysis (PCA), which effectively captured the underlying variation among accessions. These phenotypic groupings demonstrated high consistency with subsequent population structure analysis based on SNP markers (K = 3). Notably, several key traits exhibited significant divergence (p < 0.05) among distinct genetic clusters, thereby validating the coordinated association between phenotypic variation and molecular markers. Genetic diversity and population structure were assessed using 4204 high-quality single-nucleotide polymorphism (SNP) markers obtained through stringent filtering. The results indicated that the Liriodendron sino-americanum displayed the highest genetic diversity, with an expected heterozygosity (He) of 0.18 and a polymorphic information content (PIC) of 0.14. In addition, both hierarchical clustering and PCA revealed clear population differentiation among the accessions. Association analysis between three phenotypic traits (DBH, annual height increment, and branch number) and SNPs identified 25 highly significant SNP loci (p < 0.01). Of particular interest, the branch number-associated locus SNP_17_69375264 (p = 1.03 × 10⁻⁵) demonstrated the strongest association, highlighting distinct genetic regulation patterns among different growth traits. A minimal set of 13 core SNP markers was subsequently used to construct unique DNA fingerprints for all 297 accessions. In conclusion, this study systematically characterized phenotypic traits in Liriodendron, identified high-quality and core SNPs, and established correlations between key phenotypic and molecular markers. These achievements enabled differential analysis and genetic diversity assessment of Liriodendron germplasm, along with the construction of DNA fingerprint profiles. The results provide crucial theoretical basis and technical support for germplasm conservation, accurate identification, and utilization of Liriodendron resources, while offering significant practical value for variety selection, reproduction and commercial applications of this species. Full article

Capsicum is one of the most economically significant vegetable crops worldwide, owing to its high content of bioactive compounds with nutritional, pharmacological, and industrial relevance. However, research has focused on C. annuum, often disregarding local diversity and secondary gene pools, which may contain hidden variation for quality traits. Therefore, this study evaluated the genetic and phenotypic diversity of 283 accessions from the Colombian germplasm collection in the agrobiodiversity hotspot of northwest South America, representing all five domesticated species of the genus. A total of 18 morphological, physicochemical, and biochemical fruit traits were assessed, including texture, color, capsaicinoid, and carotenoid content. The phenotypic data were integrated with genomic information obtained through genotyping-by-sequencing (GBS) using the C. annuum reference genome and a multispecies pangenome. Fixed-and-Random-Model-Circulating-Probability-Unification (FarmCPU) and Bayesian-information-and-Linkage-disequilibrium-Iteratively-Nested-Keyway (BLINK) genome-wide association studies (GWAS) were performed on both alignments, respectively, leading to the identification of complex polygenic architectures with 144 and 150 single nucleotide polymorphisms (SNPs) significantly associated with key fruit quality traits. Candidate genes involved in capsaicinoid biosynthesis were identified within associated genomic regions, terpenoid and sterol pathways, and cell wall modifiers. These findings highlight the potential of integrating pangenomic resources with multi-omics approaches to accelerate Capsicum improvement programs and facilitate the development of cultivars with enhanced quality traits and increased agro-industrial value. Full article

Turbidite lobe reservoirs represent critical deep-sea hydrocarbon targets, yet preferred seepage channels within them remain poorly characterized. This paper establishes a method for identifying internal preferred seepage channels in turbidite lobe reservoirs using data including seismic, core, thin section, logging, and production performance, combined with neural network technology. A neural network model for predicting reservoir productivity types can be obtained by taking the average logging data of reservoir intervals as input and the reservoir productivity types categorized by meter oil production index calculated by actual production data as the target. By applying the trained neural network model and inputting actual logging attribute model, the reservoir productivity types of single wells are obtained. Using the attribute model of natural gamma ray, acoustic, neutron, density, deep lateral, and shallow lateral logs, which are built by using the actual logging data and Sequential Gaussian Simulation, and supervising with the single well reservoir productivity type, the reservoir productivity type at any position in the reservoir can be predicted. It predicts their spatial distribution characteristics, reveals the genetic mechanism of preferred seepage channels, and discusses the significance of identifying preferred seepage channels for oilfield development. The results show that the reservoir productivity types in the study area can be divided into five categories with progressive improvement in productivity (A, B, C, D, and E) according to the increase in oil production index per meter, among which Type E reservoirs represent typical preferred seepage channels. The attribute model of reservoir productivity types indicates that, horizontally, types E and B are locally developed in the study area, while types D, C, and A are widely distributed. The preferred seepage channels can be divided into two types according to the shape: zonal (length to width > 2:1) and sheet-like (length to width ≤ 2:1). Vertically, types C, D, and E are relatively well-developed in layers III and IV, whereas types A and B are more common in layers I and II. The vertical combination patterns of preferred seepage channels reveal four types, including homogeneous, bottom-dominated, top-dominated, and interbedded patterns. The formation of preferred seepage channels is influenced by both sedimentary and diagenetic processes, and sedimentary is the most important controlling factors. The identification of preferred seepage channels in turbidite lobe reservoirs is of great significance for formulating development policies and tapping remaining oil. Full article

Chicken meat represents the most widely consumed source of animal protein globally. The identification of non-coding RNAs (ncRNAs) that affect muscle development provides new selection targets for poultry breeding. In this study, muscle samples from high- and low-breast-weight chickens were collected and sequenced for long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), and mRNAs. Using weighted gene co-expression network analysis, we found 95 lncRNAs and 46 circRNAs that were significantly associated with breast muscle traits. Subsequently, 51 candidate lncRNAs and 22 candidate circRNAs were screened through differential expression analysis. Finally, by constructing an ncRNA–mRNA regulatory network and performing pathway enrichment analysis, we identified four lncRNAs (e.g., MSTRG.9172.1) and seven circRNAs (e.g., novel_circ_009419) as key regulatory molecules. Functional analysis revealed that these molecules modulate genes such as CD28, CCND2, TIAM1, and RRM2 through pathways including the actin cytoskeleton, p53 signaling pathway, and other pathways. In conclusion, this study provides clearer insight into the epigenetic regulatory network involved in chicken breast muscle development and offers important molecular markers for chicken genetic selection. Full article

Background/Objectives: Peripheral nerve tumours are commonly encountered in clinical practice. Although most are benign, a subset can exhibit aggressive and invasive behaviour, evolving into malignant peripheral nerve sheath tumours (MPNSTs). Due to their rarity and overlapping features with benign lesions, MPNSTs are frequently misdiagnosed during the initial evaluation. Preoperative biopsy may aid in distinguishing malignant from benign lesions. This single-center study aimed to develop and validate a diagnostic algorithm—based on a systematic literature review and institutional case series—to assess the role of preoperative biopsy in the diagnostic workflow. Methods: A systematic review of the literature was conducted in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, covering the period from 1998 to 2024. Additionally, a retrospective case series of patients with peripheral nerve lesions treated at the authors’ institution between January 2018 and June 2024 was analysed. Results: Forty-eight articles met the inclusion criteria and were categorized into five key domains: radiological features of MPNSTs, associated risk factors and genetic conditions, the role of preoperative biopsy, use of radiotherapy, and general clinical management strategies. The proposed diagnostic algorithm was applied to a series of 36 patients, four of whom met the criteria for preoperative biopsy. In three of these cases, early diagnosis of MPNSTs was achieved. Conclusions: Preoperative biopsy appears to be a safe and cost-effective tool for the early identification of MPNSTs. Early diagnosis may facilitate the use of neoadjuvant therapies—such as radiotherapy or chemotherapy—potentially enabling more radical surgical resection and improving overall patient outcomes. Full article

Osteoporosis is a common disease characterized by a reduction in bone mineral density (BMD), leading to an increased risk of pathological fractures and even mortality. Although menopause is a major risk factor, osteoporosis can also occur in premenopausal women. The aim of this study was to identify genetic variants associated with the development of osteoporosis in Korean premenopausal women. Subjects were recruited from the Anseong and Ansan cohorts of the Korean Genome and Epidemiology Study (KoGES). Clinical and epidemiological characteristics were assessed, and participants were classified based on BMD values measured at the distal radius and mid-shaft tibia. Individuals with confounding risk factors such as low body weight, smoking, high alcohol consumption, steroid/hormone therapy, or relevant medical history were excluded. A total of 247 healthy controls and 57 osteoporosis patients were included. Genotyping was performed using the Illumina Infinium HumanExome BeadChip and the Affymetrix Axiom Exome Array. Data were analyzed using the SNP and Variation Suite and PLINK, with quality control thresholds set at MAF ≥ 0.05 and HWE p ≥ 0.01. Functional annotation and protein structure predictions were performed using PolyPhen-2, SIFT, and PROVEAN. Genome-wide association analyses identified 113 single-nucleotide polymorphisms (SNPs) in 69 genes significantly associated with osteoporosis (p < 0.05) in both platforms, with 18 SNPs showing high cross-platform consistency (p < 0.01). Several of these genes were implicated in bone metabolism (e.g., ESRRG, PECAM1, COL6A5), vitamin D metabolism (e.g., NADSYN1, EFTUD1), skeletal muscle function (e.g., PACSIN2, ESRRG), and reproductive processes (e.g., CPEB1, EFCAB6, ASXL3). Notably, the CPEB1 rs783540 SNP exhibited the strongest association (p < 0.001) in both analyses. Our findings suggest that genetic polymorphisms in pathways related to bone metabolism, vitamin D signaling, muscle–bone interaction, and reproductive hormone regulation may contribute to the development of osteoporosis in Korean premenopausal women. These results provide a genetic basis for early identification of at-risk individuals and warrant further functional studies to elucidate the underlying mechanisms. Full article

Artificial neural networks have been used in a multitude of applications in various research areas in recent decades, providing excellent results in both data classification and data fitting. Their success is based on the effective identification (training) of their parameters using optimization techniques, and hence a series of programming methods have been developed for training these models. However, many times these techniques either can identity only some local minima of the error function with poor overall results or present overfitting problems in which the performance of the artificial neural network is significantly reduced when it is applied to different data from the training set. This manuscript introduces a method for the efficient training of artificial neural networks, where a series of genetic algorithms is applied to the network parameters in several stages. In the first stage, an initial identification of the network value interval is performed; in the second stage, the initial estimate of the value interval is improved; and in the third stage, the final adjustment of the network parameters within the previously identified value interval takes place. The new method was tested on some classification and regression problems found in the relevant literature, and the experimental results were compared against the results obtained by the application of other well-known methods used for neural network training. Full article

TIFY transcription factors play crucial regulatory roles in secondary metabolism and stress response. However, the expression patterns of the Cannabis sativa L. TIFY gene family under alkali stress, their involvement in cannabinoid metabolism, and their underlying genetic evolutionary mechanisms remain largely unexplored. In this study, we used bioinformatics approaches to conduct genome-wide identification and functional characterization of the C. sativa TIFY gene family. Fourteen TIFY genes were identified and mapped onto seven chromosomes. These genes were classified into four subfamilies: TIFY, JAZ, ZML, and PPD, with the JAZ subfamily further subdivided into five distinct branches. Collinearity analysis suggested that gene duplication events contributed to the expansion of the TIFY gene family in C. sativa. Weighted gene coexpression network analysis (WGCNA) revealed that CsJAZ2, CsJAZ3, and CsJAZ6 participated in the cannabinoid regulatory network. Cis-element analysis indicated that the promoter regions of TIFY genes were enriched in hormone- and stress-responsive elements. Furthermore, transcriptome and RT-qPCR analyses were conducted to examine gene expression patterns under alkaline stress (the RNA employed in RT-qPCR was extracted from the apical leaves of samples subjected to short-duration alkaline stress treatment). The results showed that CsJAZ5 and CsJAZ6 were downregulated, whereas CsPPD1, CsTIFY1, and CsZML1 were upregulated in response to alkali stress. In summary, CsJAZ5, CsPPD1, and CsTIFY1 may serve as candidate genes for the development of alkali-tolerant cultivars, while CsJAZ2 and CsJAZ3 may be valuable targets for enhancing cannabinoid production. This study provides important molecular insights and a theoretical basis for future research on the evolutionary dynamics and functional roles of TIFY transcription factors, particularly in stress adaptation and cannabinoid metabolism. Full article

The ABI3 transcription factor is a key regulator in plant growth and development. Through transcriptome analysis of the resistant soybean cultivar ‘Dongnong L10′ and the susceptible cultivar ‘Heinong 37′ exposed to soybean cyst nematode race 3 (SCN 3) stress, the differentially expressed gene GmABI3VP1 was identified. The GmABI3VP1 gene was then cloned and analyzed through bioinformatics, subcellular localization, and qRT-PCR analysis of resistant and susceptible soybean germplasms, as well as overexpression and gene editing of soybean hairy roots followed by SCN 3 identification analysis. It was found that the protein encoded by GmABI3VP1 is an acidic and hydrophilic protein with transmembrane domains. It has a collinear relationship with Arabidopsis and is widely distributed in plants. Through the analysis of promoter elements, it was shown that this gene contains multiple hormone-responsive promoter elements like ABRE/ABRE3a/ABRE/4a/as-1 and stress-responsive elements such as Myb/MYC/MYc. Transient expression in tobacco indicated that the GmABI3VP1 gene is located in the nucleus. The transcription of GmABI3VP1 responds to the stress of SCN, and its transcriptional level is relatively high in the roots of resistant materials. Genetic transformation mediated by Agrobacterium rhizogenes was used to obtain GmABI3VP1 gene overexpressed and CRISPR-Cas9 gene-edited soybean hairy roots. In comparison to the wild type (WT), the density of nematodes per area was notably lower in hairy roots overexpressing (OX) the gene, whereas the density of SCN per unit area (per cm of lateral root length) significantly increased in gene-edited (KO) soybean hairy roots. Through SCN phenotyping, GmABI3VP1 was identified as a contributor to SCN 3 resistance. This study provides initial insights into the role of the GmABI3VP1 gene in SCN resistance, establishing a robust basis for future research on the mechanisms underlying SCN disease resistance and offering valuable genetic reservoirs for SCN 3 resistance. Full article

Background: Intramuscular fat (IMF) enhances marbling, improving meat quality and value. Transcriptome analysis enables the identification of genes and pathways involved in IMF deposition, supporting targeted breeding and nutritional strategies to improve beef quality. Methods: This study used RNA-Seq to compare gene expression in high- (Hereford; Her), moderate- (Holstein Friesian; Hf), and low-marbling (Limousine; Lim) Semitendinosus muscle. Using Illumina’s NovaSeqX Plus, sequencing data underwent quality control with FastQC to remove low-quality reads and adapters, followed by alignment to the bovine genome using HISAT2. Differential expression analysis was performed using DESeq2, and genes were filtered based on a threshold of p-value < 0.05 and |log2FC| > 0.5 to identify significantly regulated genes. Results: A total of 21,881 expressed genes were detected, with 3025 and 7407 significantly differentially expressed in Her and Hf vs. Lim, respectively (|log2FC| > 0.5, p < 0.05). Protein–protein interaction analysis revealed 20 hub genes, including SMAD3, SCD, PLIN2, SHH, SQLE, RXRA, NPPA, NR1H4, PRKCA, and IL10. Gene ontology and KEGG pathway analyses linked these genes to lipid metabolism and IMF-associated pathways, such as PPAR signaling, fatty acid metabolism, and PI3K–Akt signaling. Conclusions: These findings highlight RNA-Seq’s utility in uncovering the genetic basis of marbling and the importance of aligning beef production with consumer demands through genetic improvements. This study aimed to identify breed-independent molecular mechanisms of intramuscular fat deposition and shared metabolic processes in the Semitendinosus muscle to improve beef quality. Full article

Obesity is a global health challenge marked by substantial inter-individual differences in responses to dietary and lifestyle interventions. Traditional weight loss strategies often overlook critical biological variations in genetics, metabolic profiles, and gut microbiota composition, contributing to poor adherence and variable outcomes. Our primary aim is to identify key biological and behavioral effectors relevant to precision medicine for weight control, with a particular focus on nutrition, while also discussing their current and potential integration into digital health platforms. Thus, this review aligns more closely with the identification of influential factors within precision medicine (e.g., genetic, metabolic, and microbiome factors) but also explores how these factors are currently integrated into digital health tools. We synthesize recent advances in nutrigenomics, nutritional metabolomics, and microbiome-informed nutrition, highlighting how tailored dietary strategies—such as high-protein, low-glycemic, polyphenol-enriched, and fiber-based diets—can be aligned with specific genetic variants (e.g., FTO and MC4R), metabolic phenotypes (e.g., insulin resistance), and gut microbiota profiles (e.g., Akkermansia muciniphila abundance, SCFA production). In parallel, digital health tools—including mobile health applications, wearable devices, and AI-supported platforms—enhance self-monitoring, adherence, and dynamic feedback in real-world settings. Mechanistic pathways such as gut–brain axis regulation, microbial fermentation, gene–diet interactions, and anti-inflammatory responses are explored to explain inter-individual differences in dietary outcomes. However, challenges such as cost, accessibility, and patient motivation remain and should be addressed to ensure the effective implementation of these integrated strategies in real-world settings. Collectively, these insights underscore the pivotal role of precision nutrition as a cornerstone for personalized, scalable, and sustainable obesity interventions. Full article

Lopezia racemosa Cav., commonly known as “cancer herb” in indigenous communities, has long been used for its medicinal properties. The biotechnological production of its bioactive compounds through genetic transformation represents a valuable approach for obtaining pharmacologically relevant substances. The initial focus of this study was to identify compounds previously reported in the species; however, phytochemical analysis by HPLC and NMR led to the isolation and identification of two pentacyclic triterpene esters not previously described in L. racemosa: 3-O-[(E)-feruloyl]-maslinic acid (1) and 3-O-[(E)-feruloyl]-corosolic acid (2), identified as constituents of fraction 33. The LRTC3.1 callus line was obtained from hairy roots generated by infecting L. racemosa leaf explants with Agrobacterium rhizogenes strain ATCC15834/pTDT. The crude extract, specific fractions, and the mixture of these compounds demonstrated significant anti-inflammatory and cytotoxic activities. Anti-inflammatory activity was evaluated using the carrageenan-induced mouse paw edema model, where the crude extract achieved 51.02% inhibition of inflammation compared to meloxicam (30.86%). Cytotoxicity was assessed against three human cancer cell lines: breast carcinoma (MCF7), cervical carcinoma (SiHa), and colon carcinoma (HCT-15). Fractions FD (28–29) and 33 exhibited potent cytotoxic effects, with IC₅₀ values of 0.508 and 1.345 µg/mL against SiHa cells, and 0.053 and 2.693 µg/mL against MCF-7 cells, respectively. These findings suggest that transformed L. racemosa cultures represent a promising source of bioactive compounds for potential therapeutic development. Full article

Background: Corynebacterium ulcerans is an emerging zoonotic pathogen capable of cau-sing diphtheria-like infections in humans. Objectives: we report, for the first time in Brazil, the detection and phenotypic/genomic characterization of three atoxigenic ST-339 strains isolated from domestic animals, including one with a ciprofloxacin resistance profile linked to double GyrA mutations (S89L, D93G). Methods: species identification was performed by MALDI-TOF MS, followed by in vitro antimicrobial susceptibility testing, whole-genome sequencing, and bioinformatic analyses to predict virulence determinants, antimicrobial resistance genes, CRISPR–Cas systems, mobile genetic elements, and in silico structural analysis as well as phylogenetic reconstruction. Results: whole-genome sequencing confirmed species identity, revealed high genetic similarity, and identified distinct phylogenetic subclades, suggesting potential international dissemination. Genomic analyses showed conserved virulence determinants, such as incomplete pilus clusters, iron acquisition systems, and the pld gene, with the absence of the tox gene. Molecular modeling and dynamics simulations indicated that GyrA mutations disrupt critical ciprofloxacin–magnesium–water interactions, reducing binding stability. Mobile genetic elements, prophages, and CRISPR–Cas systems underscored the genomic plasticity of these isolates. Conclusions: these findings document a little-studied antimicrobial resistance mechanism in zoonotic C. ulcerans, highlighting the need for strengthened surveillance and further research on virulence and resistance, even in ato-xigenic strains. Full article

Background: IgA vasculitis (IgAV) represents the most frequently seen form of vasculitis among children. Although it often resolves without intervention, renal involvement (IgAV nephritis) poses a risk for long-term complications. Although the lectin and alternative complement pathways are possible causes in its development, dependable serum biomarkers for the early identification of nephritis remain unavailable. Methods: In this prospective case-control study, we examined how the serum levels of a membrane attack complex (sC5b-9), complement factor H (CFH), mannose-binding lectin (MBL), and mannose-binding lectin-associated serine protease-1 (MASP-1) relate to renal involvement in IgAV. These complement proteins were measured in children diagnosed with IgAV and compared to levels in healthy controls (HCs) matched for age and sex. Results: The study cohort comprised 44 IgAV patients with a median age of 8 years and 34 HCs. The CFH levels were reduced significantly in the patient group (median: 357.31 ng/mL; IQR: 228.32) relative to the controls (median: 543.08 ng/mL; IQR: 504.05) (p < 0.001). This decrease was observed irrespective of the presence of nephritis. There were no significant differences in serum sC5b-9, MBL, or MASP-1 levels between the patients and controls. Furthermore, no correlation emerged between these complement components and renal involvement. Conclusion: The data suggest that lower CFH levels may signal systemic dysregulation of the alternative pathway in IgAV. In contrast, the serum levels of sC5b-9, MBL, and MASP-1 appear inadequate as markers for predicting renal involvement. Further research with larger cohorts that includes genetic analyses and examination of kidney tissue is needed to better define the contribution of complement activation in IgAV-related nephritis. Full article

This study conducted a multi-directional evaluation of the chemical potential and biological properties of selected European fungal species of the genus Phellinus. We investigated 30 samples belonging to 22 Phellinus species. Fruiting bodies were collected, among other specimens, in the Białowieża Forest (Poland); Village Kozhle (North Macedonia); Estremadura, Sesimbra, and Lagoa de Albufeira (Portugal); Zlatari close to Prishtina (Kosovo); and Spoleto and the Bosco Siro Negri State Nature Reserve (Italy). Morphological identification of the collected fungi was carried out, and genetic tests were performed to confirm the identity of the collected specimens. Methanol extracts for biological activity tests were prepared. Screening of antimicrobial activity of 30 methanolic extracts was performed on strains of bacteria (Klebsiella pneumoniae, Pseudomonas aeruginosa, Staphylococcus aureus, Staphylococcus epidermidis, and Kocuria rhizophila) and fungi (Candida albicans). Antioxidant activity tests (DPPH and ABTS) were also performed. The three most biologically active fungi species were selected (Phellinus igniarius, Fomitiporia robusta, and Porodaedalea pini) for further research. The chemical composition of the extracts was determined using GC-MS analysis. Thermal decomposition studies and spectroscopic analysis of the dry fruiting bodies were performed. The extracts were tested for their antimicrobial activity against antibiotic-resistant bacteria. Cytotoxic activity was also tested. Full article