Search Results (8,270)

Purple pakchoi (Brassica rapa subsp. chinensis (L.) Hanelt) is rich in anthocyanins, which contribute to its significant edible, ornamental, and potential health-promoting value. The previous research on the purple-leaf trait of pakchoi was rather insufficient, key gene controlling the purple-leaf trait remains to be further elucidated. Fine mapping of the genes responsible for the purple-leaf trait is essential for establishing molecular marker-assisted breeding and facilitating genetic improvement. In this study, we used the inbred purple-leaf line ‘PQC’ and green-leaf line ‘HYYTC’ as parents to construct a six-generation genetic segregation population. We analyzed the inheritance pattern of the purple-leaf trait and combined Bulked Segregant Analysis Sequencing (BSA-seq) with penta-primer amplification refractory mutation system (PARMS) to map the causal gene. The main findings are as follows: the purple-leaf trait is controlled by a single dominant gene. Using BSA-seq and PARMS, the genes were mapped to a 470 kb region (31.18–31.65 Mb) on chromosome A03. Within this interval, 29 candidate genes were identified. Bra017888 which encoding trehalose phosphate synthase 10 (TPS10), was highlighted as a potential regulator of anthocyanin biosynthesis. A developed molecular marker, SNP31304070, based on the final candidate region, successfully distinguished between purple homozygous and purple heterozygous plants in the F₂ and F₃ populations, showing complete co-segregation with the trait. The marker could be applied to molecular-assisted breeding in purple pakchoi. Full article

Parkinson’s disease (PD) is a progressive neurological disorder marked by the gradual loss of dopamine-producing neurons in the brain. This neuronal degradation causes motor symptoms such as tremors, stiffness, and slowness of movement. Despite decades of research, current treatments remain limited to symptom management, highlighting the urgent need for deeper insights into PD mechanisms and new therapeutic approaches. Among model organisms, zebrafish (Danio rerio) have emerged as a valuable tool for PD research due to the possibility of genetic manipulation. Zebrafish can be engineered to carry human PD-associated mutations, such as those in α-synuclein, LRRK2, and Parkin, enabling researchers to study the molecular and cellular basis of the disease. Additionally, exposure to neurotoxins like MPTP and paraquat allows scientists to replicate PD-like symptoms in zebrafish, supporting drug screening and behavioural analysis. This review summarises the key advantages and limitations of zebrafish as a model for PD, compares it with rodent models, and discusses recent advances and future directions that may improve translational outcomes in PD therapy and personalised medicine. Full article

The antigenic relationship between Eurasian avian-like H1N1 swine influenza viruses (EA H1N1) and human pandemic 2009 H1N1 viruses (2009/H1N1) remains a critical question for influenza surveillance and vaccine efficacy. This study systematically investigated the antigenic differences between strains A/swine/Tianjin/312/2016 (TJ312, EA H1N1) and A/Guangdong-Maonan/SWL1536/2019 (GD1536, 2009/H1N1). Cross-hemagglutination inhibition (HI) assays revealed a significant antigenic disparity, with a 16-fold reduction in heterologous versus homologous HI titers. Comparative sequence analysis identified 22 amino acid differences across the five major antigenic sites (Sa, Sb, Ca1, Ca2, and Cb) of the HA1 subunit. Using reverse genetics, a panel of mutant viruses was generated. This study revealed that a single histidine (H)-to-asparagine (N) substitution at residue 128 (H3 numbering) in the Sa antigenic site acts as a primary determinant of antigenic variation, sufficient to cause a four-fold change in HI titers and a measurable drift in antigenic distance. Structural modeling via AlphaFold3 and PyMOL software suggests that the H128N mutation may alter the local conformation of the antigenic site. It is plausible that H at position 128 could exert electrostatic repulsion with adjacent amino acids, whereas N might facilitate hydrogen bond formation with neighboring residues. These interactions would potentially lead to structural changes in the antigenic site. Our findings confirm that residue 128 is a critical molecular marker for the antigenic differentiation of EA H1N1 and 2009/H1N1 viruses. The study underscores the necessity of monitoring specific HA mutations that could reduce cross-reactivity and provides valuable insights for refining vaccine strain selection and pandemic preparedness strategies. Full article

Tomato gray leaf spot (TGLS), caused by Stemphylium spp., is a common disease leading to significant economic losses in tomato production. Pydiflumetofen is a novel succinate dehydrogenase inhibitor (SDHI) fungicide that has been registered for TGLS management. To evaluate the susceptibility of S. lycopersici to pydiflumetofen in tomato-producing regions of Hebei Province, we determined the sensitivity of 212 S. lycopersici isolates using mycelial growth inhibition. The sensitivity distribution exhibited a multimodal pattern. Resistance to pydiflumetofen was observed in some field isolates, with highly resistant isolates being identified in Chengde, Hengshui, and Tangshan. After removing outliers, the baseline sensitivity of S. lycopersici to pydiflumetofen was established, with a mean EC₅₀ value of 1.0400 ± 0.0515 μg/mL. Sequence analysis revealed point mutations only in SdhC (SdhC^S73P, SdhC^G79R, SdhC^H134R, SdhC^S135R) among the resistant isolates. No significant differences were observed between certain resistant isolates (FQSL1-10 and FQSL1-14) and the sensitive isolates in temperature adaptability, mycelial growth rate, or pathogenicity. These results suggest that pydiflumetofen has high activity against TGLS, but integrated fungicide application is necessary for delaying resistance evolution in TGLS management. Full article

Taro (Colocasia esculenta) is the fifth most cultivated root crop in the world. During the asexual reproduction of taro, the frequent mutation of somatic cells leads to high genetic diversity. With the continuous increase in the amount of taro germplasm resources collected, efficiently and accurately genotyping taro has become a major problem. The identification of taro resources using penta-primer amplification refractory mutation system single-nucleotide polymorphisms (SNP-PARMS) is a relatively efficient method. After resequencing 29 taro resources in this study, approximately 86.95 million SNPs were obtained. Then, 252 specific SNP loci were screened. Based on these 252 specific SNP loci, 36 pairs of PARMS-SNP markers were formed. Among them, 9 pairs of PARMS-SNP markers with a sample loss rate > 15% were eliminated, and finally 27 pairs of PARMS-SNP markers were determined. The average values of minimal allele frequency (MAF), polymorphic information content (PIC), gene diversity (GD), and heterozygosity of these markers are 0.63, 0.34, 0.49, and 0.45, respectively. We analyzed the population structure and the evolutionary group, and the results showed that the 72 taro resources could be divided into 6 groups. The clustering result of the 72 taro resources based on phenotypic traits showed a potential congruence with the result of grouping in the evolutionary tree, with only a few differences detected between the two classifications. Using these markers, DNA fingerprint maps of 72 taro resources were constructed, and all taro resources were differentiated. Some resources show potential similarities in DNA fingerprint maps, as well is in their phenotypic traits, confirming the validity of the fingerprint. The study’s findings serve as a reference for the analysis of the genetic diversity of taro resources. Full article

Acute myeloid leukemia (AML) accounts for 15–20% of childhood leukemia cases; however, it is characterized by very high aggressiveness and has the highest mortality rate among leukemias, with relapse rates ranging from 34% to 38%. It is a disease characterized by high molecular diversity, and the frequency of specific genetic alterations in children is different from that in adults. Furthermore, mutations and rearrangements vary with age within the pediatric population. To date, a wide spectrum of genetic alterations has already been studied, but the molecular landscape of each patient is unique. An analysis of rearrangements and mutations specific to children of different ages appears to be crucial in order to individualize diagnosis and therapy appropriately. The aim of the following review is to analyze the molecular landscape of pediatric AML by age in detail in order to prioritize therapeutic strategies dedicated to specific age groups. Full article

Objective: This study conducted a comprehensive analysis of molecular transmission networks and pretreatment drug resistance (PDR) in newly diagnosed HIV-1 infections in Taizhou, China. Methods: From 2021 to 2023, we collected 1126 plasma samples from newly diagnosed HIV patients in Taizhou. The HIV pol gene was amplified, and the obtained sequence was used to construct a maximum likelihood (ML) phylogenetic tree and molecular transmission network. PDR-related mutations were analyzed based on the Stanford University HIV Resistance Database. We conducted genotyping analysis and analysis of factors related to the larger clusters (≥10). Results: We successfully amplified and sequenced the pol region from 937 (83.2%, 937/1126) treatment-naïve HIV-1 patients, each with comprehensive epidemiological documentation. Phylogenetic characterization revealed significant subtype heterogeneity, with CRF07_BC (42.1%, 395/937), CRF01_AE (27.6%, 259/937) and CRF08_BC (22.1%, 209/937) being the most prevalent. Notably, 11.4% of the sequenced population (107/937) presented detectable PDR mutations. Univariate analysis revealed that larger clusters (≥10) are more inclined to be aged ≥60, divorced or widowed, have high or technical secondary school education, and have sexual contact with homosexuality. Multivariate analysis revealed that age ≥60 years and not having a PDR mutation (p < 0.05) were factors associated with larger clusters (≥10). Conclusions: Molecular transmission networks suggest that CRF08_BC is spreading rapidly among the older male population. Consequently, targeted interventions aimed at this population are crucial for halting the ongoing rapid dissemination of this subtype. Full article

Background: Dominantly acting variants in TUBB2B have primarily been associated with cortical dysplasia complex with other brain malformations 7 (CDCBM7), a disorder in which cortical brain abnormalities are typically linked to developmental delay/intellectual disability (DD/ID) and seizures. While the majority of TUBB2B pathogenic variants have been linked to isolated CDCBM7, only one family with CDCBM7 and congenital fibrosis of the extraocular muscles (CFEOM) has been reported so far. We describe a second individual with a severe phenotype of CFEOM combined with CDCBM7 carrying a pathogenic TUBB2B missense variant previously reported in two individuals with isolated CDCBM7. Methods: A trio-based WGS analysis was performed. The structural impact of the identified substitution was assessed by using the UCSF Chimera (v.1.17.3) software and PyMOL docking plugin DockingPie tool. Results: WGS analysis identified a de novo missense TUBB2B variant (p.Ile202Thr, NM_178012.5), previously associated with isolated CDCBM7. Structural analysis and docking simulations revealed that Ile202 contributes to establishing a proper hydrophobic environment required to stabilize GTP/GDP in the β-tubulin pocket. p.Ile202Thr was predicted to disrupt these interactions. Conclusions: Our findings broaden the mutational spectrum of TUBB2B-related CFEOM, targeting a different functional domain of the protein, and further document the occurrence of phenotypic heterogeneity. We also highlight the limitations of exome sequencing in accurately mapping TUBB2B coding exons due to its high sequence homology with TUBB2A and suggest targeted or genome analyses when clinical suspicion is strong. Full article

Background/Objectives: CLIFAHDD syndrome (OMIM # 616266) is a rare neurodevelopmental disorder caused by mutations in the NALCN gene. It is characterized by hypotonia, developmental delay, and congenital contractures of the limbs and face. We report a 33-year-old Italian woman with a mild form of CLIFAHDD who exhibited early-onset language difficulties and mild intellectual disability and later developed gait and balance impairments in adulthood. Methods and Results: Whole Exome Sequencing (WES) identified a novel missense variant c.1514A>T; p.(Lys505Met) in the NALCN gene. The allele frequency of this variant is not detected (MAF = 0.0), the variant is classified as likely pathogenic according to ACMG criteria, and predicted to be probably damaging by PolyPhen-2. It affects a critical residue within the second pore-forming domain of the NALCN channel, potentially altering lipid interactions and channel regulation. Sanger sequencing and segregation analysis confirmed the variant to be heterozygous and de novo. Conclusions: The patient’s milder symptoms and later onset, compared to severe pediatric cases, suggest that the clinical spectrum of CLIFAHDD syndrome may be broader than previously recognized. These findings underscore the potential influence of mutation location on disease presentation and severity. Full article

Background/Objectives: Late diagnosis and inefficient treatment regimens lead to poor prognosis, with a low 5-year survival rate for both non-small-cell lung cancer (NSCLC) and small-cell lung cancer (SCLC). New targeted therapeutic agents can be developed and introduced only by first discovering new driver oncogenes and with a thorough investigation of the known driver genes. The aim of the current study is to investigate the prevalence of alterations in the eight most frequently altered genes in lung cancer—BRAF, EGFR, KRAS, ALK, ROS1, HER2, PD-L1 and PIK3CA. Methods: Real-time polymerase chain reaction (RT-PCR) was used to detect KRAS and EGFR mutations, multiplex PCR and microarray hybridization for KRAS/BRAF/PIK3CA mutations. Immunohistochemical analysis was performed for the detection of ALK, HER2/NEU, ROS-1 and PD-L1 alterations. Results: Overall, 221/603 patients (36.65%) had at least one genetic alteration, of which 22 patients (3.65%) had two genetic alterations and two patients had more than two genetic alterations. Additionally, 50 patients were identified with one or more KRAS mutations (8.29%), 45 patients with EGFR mutations (7.46%), and 1.82% with PIK3CA mutations and 0.66% with BRAF mutations. Furthermore, 50% of the co-occurring alterations were either on KRAS and PIK3CA genes (3/6), on KRAS and BRAF genes (2/6, 33.33%) or on EGFR and PIK3CA genes (1/6, 16.67%), and 10.45% of the patients exhibited PD-L1 overexpression, 5.31% ALK rearrangements, and 2.36% HER2/NEU expression, with no ROS-1 rearrangements detected. Conclusions: Comprehensive testing for somatic alterations in EGFR, BRAF, KRAS, and PIK3CA is significant in guiding therapeutic decisions in lung cancer management. Such testing should be routinely conducted to establish a thorough genetic profile of lung cancers in a manner that is both time-efficient and cost-effective. Full article

Studies have shown that the iron concentration in the peritoneal fluid of women is associated with the severity of endometriosis. Therefore, investigation of iron metabolism-related genes (IM-RGs) in endometriosis holds significant implications for both prevention and therapeutic strategies in affected patients. Differentially expressed IM-RGs (DEIM-RGs) were identified by intersecting IM-RGs with differentially expressed genes derived from GSE86534. Mendelian randomization analysis was employed to determine DEIM-RGs causally associated with endometriosis, with subsequent verification through sensitivity analyses and the Steiger test. Biomarkers associated with IM-RGs in endometriosis were validated using expression data from GSE86534 and GSE105764. Functional annotation, regulatory network construction, and immunological profiling were conducted for these biomarkers. Single-cell RNA sequencing (scRNA-seq) (GSE213216) was utilized to identify distinctively expressed cellular subsets between endometriosis and controls. Experimental validation of biomarker expression was performed via reverse transcription–quantitative polymerase chain reaction (RT-qPCR). BMP6 and SLC48A1, biomarkers indicative of cellular BMP response, were influenced by a medicus variant mutation that inactivated PINK1 in complex I, concurrently enriched by both biomarkers. The lncRNA NEAT1 regulated BMP6 through hsa-mir-22-3p and hsa-mir-124-3p, while SLC48A1 was modulated by hsa-mir-423-5p, hsa-mir-19a-3p, and hsa-mir-19b-3p. Immune profiling revealed a negative correlation between BMP6 and monocytes, whereas SLC48A1 displayed a positive correlation with activated natural killer cells. scRNA-seq analysis identified macrophages and stromal stem cells as pivotal cellular components in endometriosis, exhibiting altered self-communication networks. RT-qPCR confirmed elevated expression of BMP6 and SLC48A1 in endometriosis samples relative to controls. Both BMP6 and SLC48A1 were consistently overexpressed in endometriosis, reinforcing their potential as biomarkers. Moreover, macrophages and stromal stem cells were delineated as key contributors. These findings provide novel insights into therapeutic and preventive approaches for patients with endometriosis. Full article

This article presents an innovative approach to optimizing the seismic modeling and analysis of high-rise buildings by automating the process with Python 3.13 and the ETABS 22.1.0 API. The process begins with the collection of information on the base building, a structure of seventeen regular levels, which includes data from structural elements, material properties, geometric configuration, and seismic and gravitational loads. These data are organized in an Excel file for further processing. From this information, a code is developed in Python that automates the structural modeling in ETABS through its API. This code defines the sections, materials, edge conditions, and loads and models the elements according to their coordinates. The resulting base model is used as a starting point to generate an optimal solution using a genetic algorithm. The genetic algorithm adjusts column and beam sections using an approach that includes crossover and controlled mutation operations. Each solution is evaluated by the maximum displacement of the structure, calculating the fitness as the inverse of this displacement, favoring solutions with less deformation. The process is repeated across generations, selecting and crossing the best solutions. Finally, the model that generates the smallest displacement is saved as the optimal solution. Once the optimal solution has been obtained, it is implemented a second code in Python is implemented to perform static and dynamic seismic analysis. The key results, such as displacements, drifts, internal and basal shear forces, are processed and verified in accordance with the Peruvian Technical Standard E.030. The automated model with API shows a significant improvement in accuracy and efficiency compared to traditional methods, highlighting an R² = 0.995 in the static analysis, indicating an almost perfect fit, and an RMSE = 1.93261 × 10⁻⁵, reflecting a near-zero error. In the dynamic drift analysis, the automated model reaches an R² = 0.9385 and an RMSE = 5.21742 × 10⁻⁵, demonstrating its high precision. As for the lead time, the model automated completed the process in 13.2 min, which means a 99.5% reduction in comparison with the traditional method, which takes 3 h. On the other hand, the genetic algorithm had a run time of 191 min due to its stochastic nature and iterative process. The performance of the genetic algorithm shows that although the improvement is significant between Generation 1 and Generation 2, is stabilized in the following generations, with a slight decrease in Generation 5, suggesting that the algorithm has reached its level has reached a point of convergence. Full article

Animal behavior recognition is an important research area that provides insights into areas such as neural functions, gene mutations, and drug efficacy, among others. The manual coding of behaviors based on video recordings is labor-intensive and prone to inconsistencies and human error. Machine learning approaches have been used to automate the analysis of animal behavior with promising results. Our work builds on existing developments in animal behavior analysis and state-of-the-art approaches in computer vision to identify rodent social behaviors. Specifically, our proposed approach, called Vision Transformer for Rat Social Interactions (ViT-RSI), leverages the existing Global Context Vision Transformer (GC-ViT) architecture to identify rat social interactions. Experimental results using five behaviors of the publicly available Rat Social Interaction (RatSI) dataset show that the ViT-RatSI approach can accurately identify rat social interaction behaviors. When compared with prior results from the literature, the ViT-RatSI approach achieves best results for four out of five behaviors, specifically for the “Approaching”, “Following”, “Moving away”, and “Solitary” behaviors, with F1 scores of 0.81, 0.81, 0.86, and 0.94, respectively. Full article

Acute myeloid leukemia (AML) comprises 15−20% of pediatric leukemia and 35% of adult leukemia cases, requiring insights into prognostic factors of this disease to be an important aspect of diagnosis and treatment. A mutational profile of patients with AML is a crucial predictor of their outcome. Discernment of present mutations, co-mutation combinations, and variations in the mutations in a single gene requires proper research and analysis to determine their impact on a patient’s prognosis. Common and infrequent mutations are continuously investigated and analyzed in different patient cohorts, bringing new insights that lead to changes in classifications, treatments, and diagnoses. For instance, mutations in NPM1, FLT3, and DNMT3A, three frequent driver mutations, have high incident rates with differing prognoses and treatments in pediatric and adult patients. AML patients with MECOM face particularly dire outcomes, as well as those with ASXL1 and TP53, making their mutational analysis crucial for review in developing a prognosis. Full article

Human orthopneumovirus (HOPV) is a major cause of acute respiratory tract infection (ARI) in children around the world. The present study was conceptualized to detect and characterize human orthopneumovirus in 640 NPAs collected from symptomatic ARI pediatric patients younger than 2 years of age. The samples were collected from a hospital in Riyadh, Saudi Arabia, during winter 2022. Orthopneumovirus was detected in 98 (15.31%) of the 640 NPAs. No significant difference in the prevalence of HOPV-A (49%) and HOPV-B (51%) was observed during the study period as they circulated at similar frequencies. The HOPV-A strains (33) and HOPV-B strains (47) clustered into ON1 and BA genotype, respectively. The ON1 genotypes were further categorized into the subgenotype GA-2.3 and three different lineages, GA-2.3.5, GA-2.3.6a, and GA-2.3.6b, whereas the BA genotypes were categorized into the GB-5.0 subgenotype, entirely belonging to the GB-5.0.5a lineage. This is the first report to characterize orthopneumovirus strains from Saudi Arabia using a recently reported method. Several mutations, a few N-/O-glycosylation sites, and some purifying selections were observed in both the ON1 and BA genotypes. The present study demonstrates the equal prevalence of the ON1 and BA genotypes, in contrast to earlier reports on HOPV-A prevalence in the region. Understanding the change in the genotype distribution of HOPV requires the uninterrupted surveillance and genetic characterization of HOPV in circulating respiratory infections. These findings may contribute to a better understanding of HOPV evolution and the dynamics of its distribution at the local and global levels, resulting in improved understanding of epidemics. Full article