Search Results (101,833)

Multiple myeloma (MM) is an oncohematological neoplasm characterized by the abnormal proliferation of neoplastic plasma cells in the bone marrow and the excessive secretion of monoclonal antibodies into the bloodstream. Approximately 3 to 5% of patients present with a variant form of the disease where there is no secretion of monoclonal proteins, characterizing the non-secretory MM picture. It exhibits a highly complex and heterogeneous genetic signature, allowing the disease to be classified into premalignant entities and symptomatic forms. In this context, an integrative narrative review was conducted, encompassing genomic, epigenomic, proteomic, metabolomic, and radiomic biomarkers described in the literature between 2018 and 2025. Emphasis was placed on their translational potential, current limitations in clinical practice, and gaps within recent recommendations. Several categories of biomarkers, particularly ctDNA methylome, single-cell multiomics, proteomics of surface antigens, functional ex vivo assays, and PET/CT radiomics, demonstrate strong potential for enhancing risk stratification, detecting early progression, guiding therapy selection, and identifying novel therapeutic targets. These applications extend beyond existing guideline frameworks. Thus, integrating advanced biomarker platforms can overcome limitations of current diagnostic and therapeutic models and enhance precision strategies across plasma cell disorders. Full article

Background: Trisomy 18 (T18; Edwards syndrome) and Trisomy 13 (T13; Patau syndrome) are rare autosomal aneuploidies characterized by severe congenital anomalies, high neonatal mortality, and complex clinical trajectories. Objective: This study aimed to describe the clinical features, management approaches, and outcomes of genetically confirmed patients aged 0–18 years diagnosed with T18 or T13 in a tertiary care center. Methods: This retrospective study reviewed hospital records of genetically confirmed T18 and T13 cases identified through ICD-10 codes (Q91–Q92) between January 2015 and December 2024. Patients aged 0–18 years at diagnosis were included. Demographic, clinical, and interventional data were collected from electronic medical records. Survival analyses were conducted using the Kaplan–Meier method, with comparisons assessed using the log-rank test. Results: Among 29 patients, 23 had T18 and 6 had T13. Cardiovascular involvement was the most frequent anomaly, and overall mortality was high despite intensive care. Median survival was 90 days for T18 and 120 days for T13, with more than 80% surviving the first month but showing a steep decline thereafter. Most deaths were attributed to cardiopulmonary complications or sepsis secondary to prolonged intensive care. Kaplan–Meier analysis revealed marked early mortality in both groups, with no significant survival difference (log-rank p ≈ 0.3). A small subset demonstrated longer-term survival with heterogeneous clinical courses. Conclusions: T18 and T13 are associated with high early mortality driven by complex congenital heart disease, respiratory instability, and infection-related complications. Although the overall prognosis remains poor, a minority of patients achieve extended survival, highlighting variable trajectories. Early multidisciplinary care, individualized decision-making, and strict infection prevention remain essential to optimize outcomes and support families. Full article

Background: Mesenchymal stem cells (MSCs) exhibit a high capacity for differentiation, possess anti-inflammatory and proangiogenic properties, and stimulate the growth and proliferation of neighboring cells. MSCs are a promising tool in regenerative medicine. However, the molecular mechanisms underlying the properties of these cells are not yet fully understood. Gene expression in MSCs influences their characteristics and differentiation potential. Therefore, it is essential to investigate factors affecting gene expression as well as those activating signaling pathways, which will enable more effective and individualized applications of MSCs. In this study, we aimed to identify signaling pathways involved in gene expression in umbilical cord-derived MSCs (UC-MSCs) that may be altered by maternal diabetes and hypothyroidism during pregnancy. Methods: The research material consisted of UC-MSCs. Samples obtained from nine participants were analyzed. UC-MSCs were isolated and cultured, and RNA was extracted. The isolated RNA was used for microarray-based gene expression analysis. Subsequently, pathway enrichment analysis was performed to identify the signaling pathways involved. Results: In the diabetes group, 340 genes (0.71%) were upregulated, while 268 genes (0.56%) were downregulated compared with UC-MSCs from the control group. In the diabetes group, the most compact module was composed of proteins associated with WNT/planar cell polarity (WNT/PCP) signaling. The second module included genes related to smooth muscle activity. In the hypothyroidism group, an association was identified between the extracellular matrix organization pathways (GO:0030198) and the extracellular structure organization (GO:0043062) pathways. Moreover, in this group, increased expression of MMP1, MMP10, and GREM1 was observed. Conclusions: In summary, our study demonstrated the impact of diabetes and hypothyroidism on gene expression in UC-MSCs. We also observed the activation of distinct signaling pathways depending on the presence of these conditions. However, this work represents a preliminary screening, and the results should be validated by PCR in a larger cohort. Full article

Sugar beet (Beta vulgaris L.) is an economically important crop that accounts for approximately 20% of global sugar production. The success of future breeding programs depends on the effective utilization of existing genetic resources. The aim of this study was to assess the genetic diversity and population structure of 192 sugar beet (Beta vulgaris L.) genotypes, including commercial cultivars and accessions obtained from the USDA gene bank, using SCoT and ISSR molecular markers, and to identify potential genetic resources for sugar beet breeding programs. In this study, a total of 192 sugar beet genotypes, including 187 accessions from the USDA (U.S. Department of Agriculture) gene bank and 5 commercial cultivars, were evaluated for genetic diversity using Start Codon Targeted (SCoT) and Inter Simple Sequence Repeat (ISSR) markers. A total of 68 scorable bands were obtained from five SCoT and three ISSR primers, and all bands were found to be polymorphic (100% polymorphism). Parameters such as polymorphic information content (PIC), Nei’s genetic diversity, and Shannon’s index indicated a high level of variation within the gene pool, with SCoT markers being more informative than ISSR markers. Dendrogram analyses based on Nei’s genetic distance revealed that the populations were separated into two main groups, while the sub-clusterings contained broad genetic variation. STRUCTURE analysis identified four (K = 4) populations for the SCoT data and three (K = 3) populations for the ISSR data; the inclusion of a high number of individuals in the admixture population indicated extensive gene flow. Principal component analysis (PCA) revealed both homogeneous groups and differentiated genotypes contributing to within-population diversity. The results demonstrate that the combined use of SCoT and ISSR markers provides powerful and complementary tools for assessing genetic diversity in sugar beet. The findings provide a solid scientific basis for the development of new, high-yielding and high-quality sugar beet cultivars as well as for the conservation of existing genetic resources. Molecular data constitute an important reference for guiding sugar beet breeding programs and for the effective utilization of genetic resources. Full article

Mutants with a bright green appearance due to wax synthesis or deposition defects have been reported in various plants such as Arabidopsis thaliana, corn, and rice, but they are relatively rare in broccoli (a brassicaceae crop). Here, we describe SY03, a natural mutant of broccoli with a glossy green phenotype owing to epidermal wax deficiency. Genetic analysis indicated that the leaf luster trait of SY03 was controlled by a single recessive gene. By using the F₂ generation and combining bulked segregant analysis and molecular marker techniques, the candidate gene BoFAR3a, homologous to the Arabidopsis FAR gene, was identified within a 96.678 kb interval of chromosome C01. The A→G point mutation in exon 1 of the BoFAR3a coding sequence substitutes the canonical ATG start codon with GTG, which is predicted to abrogate or severely reduce translation initiation. RT-qPCR indicated that the expression levels of BoFAR3a were significantly decreased in the leaves of the glossy green phenotype mutant. Heterologous expression of BoFAR3a in A. thaliana restored the phenotype of A. thaliana mutant FAR3. The discovery of BoFAR3a is of great significance for breeding lustrous and commercially appealing broccoli varieties. This study systematically analyzed the molecular basis of the lustrous green phenotype in broccoli, providing new insights into the epidermal waxy regulatory network of cruciferous crops. In the future, the wax synthesis pathway can be precisely improved through gene editing technology, achieving a coordinated enhancement of the appearance quality and stress resistance of broccoli. Full article

Thousand-seed weight (TSW) is a critical determinant of yield in rapeseed (Brassica napus L.). Developing germplasm with high TSW is therefore a key strategy in high-yield rapeseed breeding. However, the genetic and molecular mechanisms underlying TSW in rapeseed remain poorly understood. In our earlier work, we identified a mutant, designated GRG177, which exhibits a remarkably high TSW exceeding 7 g. To unravel the mechanisms driving this elevated TSW, we conducted a comprehensive analysis of GRG177, integrating morphological, genetic, developmental, anatomical, and physiological approaches. Compared with the control germplasm GRD328 (TSW ≈ 3.5 g), GRG177 displayed a significant increase in seed weight and seed volume, larger silique surface area, and higher yield per plant. However, it also showed a notable reduction in both silique number per plant and seed number per silique. Genetic analysis of a segregating population revealed that the high-TSW trait in GRG177 is governed by two pairs of dominant epistatic major genes plus polygenes. Endogenous hormone analysis revealed significantly higher zeatin riboside (ZR) content in the early stage of seed development in GRG177, whereas indole-3-acetic acid (IAA) and abscisic acid (ABA) levels were significantly up-regulated in the late stage of seed development. Anatomical observation using paraffin sections further confirmed that enhanced cell division activity in the early stage and improved cell expansion capacity in the later stage underpin the formation of high TSW. Furthermore, BSA-seq was utilized to map four TSW-related Quantitative Trait Loci (QTLs) and screen 13 candidate genes involved in IAA, ZR, and ABA signaling pathways. In conclusion, these findings provide novel insights into the regulatory mechanisms governing high-TSW formation in rapeseed and present valuable genetic resources for high-yield breeding. Full article

Thyroid hormones profoundly modulate hepatic fatty acid and cholesterol synthesis and turnover. Although nonalcoholic fatty liver disease (NAFLD) shows epidemiological links to hypothyroidism, the genetic substrates of this relationship remain unresolved. Integrating large-scale genome-wide association studies with single-cell transcriptomics, spatial transcriptomics, and single-cell chromatin accessibility via state-of-the-art computational approaches, we interrogated the association between NAFLD and hypothyroidism across organ systems, cellular expression landscapes, and molecular–genetic strata. We uncovered pronounced spatial specificity in genetic risk within the liver, prioritized hepatocytes as the principal shared cell type affected, and, leveraging spatial transcriptomics, advanced a dynamic spatiotemporal two-hit model. We further nominated MAGI3, RRNAD1, and PRCC as high-confidence candidate genes and pinpointed a key risk locus, rs926103. These findings deliver a dynamic, testable framework for the full pathophysiological continuum linking NAFLD and hypothyroidism and yield new targets and leads for precision intervention. Full article

Mycobacterium bovis is the causative agent of tuberculosis (TB) infecting a wide range of animal hosts, including humans. Domestic pigs (Sus scrofa domestica) are susceptible to different mycobacteria, particularly species within the Mycobacterium avium complex (MAC). However, in countries where bovine TB is endemic, such as Argentina, M. bovis is the most frequently reported species in pigs. This study aimed to evaluate the immune response and disease progression of a local strain (MB894) isolated from pigs and compare its pathogenicity with the highly virulent strain MB303, isolated from wild boar. Additionally, we sought to explore the genomic basis underlying the virulent phenotype of MB894. For this purpose, a murine infection model was used to assess pathogenicity, organ colonization, dissemination and cytokine induction. Whole-genome sequencing was performed to identify genetic features, including non-synonymous SNPs and INDELs, potentially associated with virulence. The severe immunopathogenesis produced by MB894, the higher multiplication rate in the evaluated organs, and the greater dissemination to other organs compared to MB303, combined with the cytokine levels induced by this strain, prompted us to classify MB894 as a hypervirulent strain. Genomic analysis revealed candidate genes that may be virulence factors contributing to this phenotype. In summary, MB894 represents a hypervirulent M. bovis strain with distinct pathogenic and genomic characteristics. These findings provide insights into the molecular determinants of virulence and highlight the need for further evaluation of identified gene candidates. Full article

Leigh Syndrome Spectrum (LSS) is a rare and heterogeneous disease continuum with most published cohorts in small sizes that limit the statistical power. Large-scale meta-analyses with published case-level clinical data extracted from the literature are essential for robust population analysis but are hindered by the burden of manually standardizing the unstructured, heterogeneous, and sparse case-level data from the literature. We developed a novel workflow which is among the first to combine Generative AI (GenAI) with human-in-the-loop curation to overcome this barrier. This pipeline utilized Google’s Gemini-2.5-pro and rapidly processed over 2300 cases from published case data tables in two weeks and achieved >90% accuracy in mapping raw clinical data to Human Phenotype Ontology (HPO) terms. This process rapidly yielded a harmonized LSS virtual cohort of 1679 data-rich cases, which is the largest LSS virtual cohort reported so far, and thus enables characterization of LSS phenotypic and genetic architectures, revealing that autosomal recessive (932 cases) and mitochondrial (752 cases) inheritance are the most common. The most frequently mutated genes were SURF1 (240 cases), MT-ATP6 (199), and MT-ND3 (183). HPO term consolidation identified common hallmark phenotypes, including lactic acidosis, hypotonia, bilateral basal ganglia lesions, and mitochondrial respiratory chain deficiency. The cohort’s scale enabled large-scale survival analysis, revealing that defects in mitochondrial translation are associated with the poorest prognosis (84% mortality in this group) and early onset (0.23 years). Among the deceased group, patients with Complex V mutations were linked to a significantly shorter mean survival time (1.77 years) than those with Complex I (3.70 years) or IV (3.57 years) mutations. This GenAI-driven methodology establishes a scalable framework for rapidly creating analysis-ready virtual cohorts from heterogeneous literature and accelerating population-level study for rare diseases including Leigh Syndrome and other mitochondrial diseases. Full article

Breast cancer (BC) is a global health problem. BC is a biologically heterogeneous disease in which novel immunotherapeutic strategies are needed, particularly in the metastatic setting. The NKG2D/NKG2D ligand (NKG2DL) axis is a key component of innate antitumor immunity and represents a potential therapeutic target, but its relevance in BC has not been fully characterized. We performed an in silico analysis of NKG2DL expression in BC cell lines, healthy breast tissue, and tumor samples using publicly available transcriptomic databases (DSMZCellDive, ShinyTHOR, GTEx, TCGA, Human Protein Atlas), complemented by survival analyses from TCGA and KMPlot and a narrative review of the literature. NKG2DL transcripts were consistently expressed in BC cell lines and tumor tissues, with higher expression observed in ductal histology, higher tumor stage, and basal molecular subtype. Survival analyses showed heterogeneous and generally weak associations between individual NKG2DLs and clinical outcomes. In silico proteomics data are scarce, but the narrative review showed that NKG2DLs are expressed by immunohistochemistry in tumor tissues but absent in surrounding healthy tissues. The literature review also revealed concomitant dysfunction of NKG2D+ effector cells due to multiple resistance mechanisms (including ligand shedding). We also review potential therapeutic approaches. Full article

Aflatoxin B₁ (AFB₁) produced by Aspergillus flavus poses severe food safety risks. Competitive exclusion using atoxigenic A. flavus strains offers a promising biological control approach to managing agricultural contamination by reducing populations of toxigenic strains and aflatoxin levels. However, reliable identification of atoxigenic strains remains challenging, and the mechanisms underlying competitive interactions between toxigenic and atoxigenic strains require clarification for effective implementation. Therefore, this study systematically analysed A. flavus strains for aflatoxin gene clusters and AFB₁ production to address these critical gaps. Our analysis revealed that atoxigenic strains had intron losses and high-impact mutations in several genes, particularly aflL and aflLa, which affect aflatoxin biosynthesis. Key genes norA/aflE, verA/aflN, and omtA/aflP emerged as mutation hotspots, sometimes causing false-negative PCR results that complicate strain identification. Also, AFB₁ production was inversely related to spore concentration on MEA medium, with fewer spores resulting in higher toxin levels. Interaction tests demonstrated that toxigenic and atoxigenic strains exhibited morphological changes only when co-cultured without physical separation, suggesting that this was mediated by diffusible molecules. Furthermore, differences in the levels of linoleic acid reduction products distinguished toxigenic from atoxigenic strains. These findings thus illuminate the complex genetic and metabolic factors influencing aflatoxin production and fungal interactions. Full article

Low temperature is a major abiotic stress that affects maize across its entire growth cycle, with the germination stage being particularly sensitive. To investigate the genetic basis of early-stage cold tolerance, we used quantitative trait locus mapping and identified ZmbHLH30 as a candidate gene regulating maize responses to low temperature. The ZmbHLH30 protein is localized in the cytoplasm of maize protoplasts, and ZmbHLH30 promoter drives β-glucuronidase (GUS) expression in Arabidopsis thaliana leaves. The promoter region of ZmbHLH30 contains multiple environmental stress-responsive elements, including motifs associated with cold and auxin responses. Overexpression of ZmbHLH30 significantly enhanced cold tolerance at the germination, bud, and seedling stages, with the strongest effect observed during germination, where the cold-tolerance D-value increased by 0.366 relative to the control. In contrast, CRISPR/Cas9 knockout lines showed a 0.399 decrease in D-value. Under cold stress, ZmbHLH30 expression was markedly induced in overexpression lines but suppressed in knockout lines. Integrated transcriptomic and metabolomic analyses further identified ZmbHLH30 as a key regulator of cold tolerance in maize. Full article

Blooming time is an important basis for constructing plant landscapes. The short flowering period of Osmanthus fragrans, recognized as one of the ten traditional flowers in China, considerably constrains the further utilization of its resources. To clarify O. fragrans flowering regulation, this study focused on OfCOR27, conducting cloning, expression analysis, and functional verification to explore its effects on O. fragrans flowering time. A COR27 phylogenetic tree was built across six species; OfCOR27 physicochemical properties, conserved structures, and promoter cis-elements were analyzed. OfCOR27 CDS was cloned, fusion vectors were transformed into Nicotiana benthamiana, and organ-specific expression was tested in two O. fragrans cultivars. Overexpression vectors were transformed into Arabidopsis thaliana, with qRT-PCR verifying gene function. Five OfCOR27s were identified, showing evolutionary conservation. OfCOR27, which localizes to the nucleus and is associated with flowering regulation, shows higher expression in ‘Sijigui’ than in ‘XiaoyeSugui’. Overexpression of OfCOR27 promoted flowering in A. thaliana, whereas the AtCOR27 mutant flowered later. This confirms OfCOR27 is a positive regulator of plant flowering, which may promote flowering by enhancing the expression of flowering-promoting genes and altering hormone levels, providing a theoretical basis and candidate gene for the genetic improvement of flowering traits in woody ornamental plants. Full article

Influenza A virus remains a major global health threat, causing annual epidemics and occasional pandemics. Programmed cell death, including apoptosis, pyroptosis, and necroptosis, with emerging evidence for ferroptosis, plays a dual role in influenza pathogenesis, both limiting viral replication and contributing to immunopathology. Most mechanistic insights have been derived from murine genetic models, which have been invaluable for establishing causal roles of these pathways. However, murine models and cancer-derived cell lines differ significantly from human physiology. This review systematically compares influenza-induced programmed cell death across human-relevant platforms, including primary cells, immortalized non-cancerous lines, co-cultures, organoids, and precision-cut lung slices. The increasing complexity of these models reveals distinct aspects of pathway activation, bystander effects, cell-type vulnerability, and spatial dynamics. We highlight critical divergences between model systems, identify gaps in comparative analyses across viral strains and experimental platforms, and outline future directions leveraging advanced model systems, multi-omics, and functional genomics to enhance translational relevance and guide the development of host-directed therapies. Full article

Magnetorheological (MR) dampers exhibit significant hysteretic nonlinearities, particularly under dynamic operating conditions, where accurately modeling the complex coupling between magnetic flux density and excitation current remains challenging. To overcome the limitations of the conventional static Jiles–Atherton (JA) model in capturing dynamic hysteresis responses, a dynamic JA model incorporating multiple loss mechanisms (LS-DJAM) is proposed for MR dampers. Building on loss separation theory, the model integrates eddy current and excess loss mechanisms to more accurately represent the dynamic hysteresis behavior of MR dampers. By coupling the Bingham mechanical model, a magneto-mechanical constitutive relation for MR dampers is established. Furthermore, to enhance the accuracy of LS-DJAM parameter identification, a hybrid particle swarm optimization–genetic algorithm (PSO–GA) is developed. Genetic operators are embedded within the PSO framework to strengthen the global search capability and mitigate premature convergence, thereby enabling efficient LS-DJAM parameter identification. The proposed LS-DJAM, identified via the PSO–GA, significantly enhances the modeling of MR damper output forces. PSO–GA parameter estimation improves accuracy by over 60%, and the LS-DJAM reduces the maximum modeling error by 87.5% compared with the conventional JA model. It accurately captures the dynamic hysteresis characteristics of MR dampers, providing a robust theoretical basis and practical framework for high-performance control and engineering optimization. Full article