Search Results (1,104)

Background: Pediatric acute myeloid leukemia (pAML) is the second most common type of childhood leukemia, behind acute lymphoblastic leukemia. High-throughput technologies have enabled the identification of increasing molecular alterations linked to AML prognosis, revealing genomic heterogeneity among individual patients and providing clinically valuable diagnostic and prognostic information. This study systematically analyzed the correlation between high-frequency mutated genes and prognosis in pAML by performing whole-transcriptome sequencing (WTS) of bone marrow samples from newly diagnosed AML children in Southwest China and mapping their genetic profiles. Methods: pAML patients treated at the Department of Hematology and Oncology, Children’s Hospital of Chongqing Medical University, from January 2015 to October 2024, were enrolled, and WTS was performed. The study described the frequency, pathogenicity classification, and risk stratification of mutation genes and fusion genes, and constructed a genetic landscape. For high-frequency pAML mutations, the impact on early induction remission rate (CR) and long-term event-free survival (EFS) was evaluated. Results: A total of 134 pediatric AML patients from Southwest China were included, with a male-to-female ratio of 74:60 and a median diagnosis age of 5.96 years. Based on pathogenicity classification using WTS, fusion genes were categorized into level 1, level 2, and level 3 genes, as well as mutation genes. The study identified five fusion genes of level 1, the most frequent being RUNX1::RUNX1T1 (32/134, 23.88%), KMT2A rearrangements (29/134, 21.64%), and CBFB::MYH11 (13/134, 9.7%). Sixteen mutation genes of level 1 were detected, seven of which recurred in over 5% of patients, including NRAS (31/134, 23.13%), FLT3 (25/134, 18.66%), KIT (24/134, 17.91%), CEBPA (14/134, 10.45%), WT1 (13/134, 9.7%), KRAS (11/134, 8.2%), and PTPN11 (7/134, 5.22%). Sex-based analysis revealed that PTPN11 mutations were significantly more frequent in males (9.45% vs. 0%, p = 0.023), as were KIT mutations (24.32% vs. 10.00%, p = 0.044). Risk-stratified analysis showed that WT1 mutations (14.13% vs. 0%, p = 0.031) and FLT3-ITD mutations (13.19% vs. 0%, p = 0.042) were enriched in intermediate- and high-risk groups, whereas CEBPA (25.64% vs. 5.43%, p = 0.012), KIT (35.90% vs. 10.87%, p = 0.003), and KIT-E8 (20.51% vs. 1.10%, p < 0.001) mutations were more prevalent in low-risk groups. Prognostic analysis indicated that PTPN11 and KIT mutations did not affect CR or EFS across sexes, nor did WT1, CEBPA, or KIT mutations influence outcomes by risk stratification. However, FLT3-ITD-positive patients had significantly lower CRs (χ² value = 11.965, p = 0.007), although EFS differences were nonsignificant. In contrast, WT1 mutations were associated with inferior EFS compared to wild-type (p = 0.036). Furthermore, the univariate and multivariate Cox regression revealed consistent results with the above findings, indicating that WT1 mutation was an independent adverse prognostic factor for EFS (HR = 2.400, 95% CI: 1.101–5.233, p = 0.028). The results of univariate and multivariate logistic regression analyses also confirmed that FLT3-ITD mutation was an independent predictor of initial treatment response in our cohort (OR = 10.699, 95% CI: 2.108–54.302, p = 0.004). Conclusions: This study delineated the genetic landscape of pAML in Southwest China and explored the prognostic value of gene fusions and mutations in early and long-term outcomes. These findings provide a foundation for understanding the genetic heterogeneity of pAML and offer evidence for the development of precision medicine approaches. Full article

Background: Thrushes (family Turdidae) are ecologically important passerine birds widely distributed across the Northern Hemisphere. However, the phylogenetic placement of several East Asian congeners, including Turdus pallidus, remains insufficiently resolved due to the limited resolution of partial mitochondrial or nuclear markers used in previous studies. Methods: In this work, we sequenced and annotated the complete mitochondrial genome of T. pallidus (16,739 bp) using high-throughput Illumina sequencing. The mitogenome exhibited the typical circular architecture and contained 37 genes (13 protein-coding genes, 22 tRNAs, and 2 rRNAs), with an overall GC content of 47.32%. Results: Most protein-coding genes initiated with the standard ATG codon, although lineage-specific deviations such as GTG in COX1 and ND2 were identified, and incomplete stop codons (T– or TA–) were observed, consistent with post-transcriptional polyadenylation. The 22 tRNA genes displayed typical cloverleaf secondary structures, except for trnS(AGN), which lacked a DHU arm, while rRNA genes were 977 bp (12S, 48.52% GC) and 1590 bp (16S, 44.65% GC), showing conserved stem regions but variable loop regions. Codon usage analysis revealed a strong bias toward A/T-ending codons, with a total of 3798 codons and an effective number of codons (ENC) of ~40, indicating moderate codon bias shaped by both mutational pressure and translational selection. Comparative analysis of evolutionary rates demonstrated that conserved genes such as COX1 and CYTB are suitable for resolving deeper relationships, whereas rapidly evolving genes like ATP8 provide resolution among closely related taxa. Conclusions: Phylogenetic reconstructions based on 13 mitochondrial protein-coding genes robustly supported the monophyly of Turdidae and recovered T. pallidus as most closely related to T. obscurus. Overall, this study provides a novel mitogenomic resource for T. pallidus, enhances phylogenetic resolution within Turdus, and underscores the value of complete mitochondrial genomes for molecular identification, conservation management, and avian evolutionary studies. Full article

Modern maize breeding worldwide relies on a broad range of molecular genetics research techniques. These technologies allow us to identify genomic regions associated with various phenotypic traits, including resistance to fungi of the genus Fusarium. Therefore, the aim of this publication was to identify new molecular markers linked to candidate genes that confer maize resistance to Fusarium fungi, using next-generation sequencing, association mapping, and physical mapping. In the study, a total of 5714 significant molecular markers related to maize plant resistance to Fusarium fungi were identified. Of these, 10 markers were selected that were significantly associated (with the highest LOD values) with the disease. These markers were identified on chromosomes 5, 6, 7, 8, and 9. The authors were particularly interested in two markers: SNP 4583014 and SilicoDArT 4579116. The SNP marker is located on chromosome 5, in exon 8 of the gene encoding alpha-mannosidase I MNS5. The SilicoDArT marker is located 240 bp from the gene for peroxisomal carrier protein on chromosome 8. Our own research and the presented literature review indicate that both these genes may be involved in biochemical reactions triggered by the stress caused by plant infection with Fusarium fungal spores. Molecular analyses indicated their role in resistance processes, as resistant varieties responded with an increase in the expression level of these genes at various time points after plant inoculation with Fusarium fungal spores. In the negative control, which was susceptible to Fusarium, no significant fluctuations in the expression levels of either gene were observed. Analyses concerning the identification of Fusarium fungi showed that the most abundant fungi on the infected maize kernels were Fusarium poae and Fusarium culmorum. Individual samples were very sparsely colonized by Fusarium or not at all. By using various molecular technologies, we identified genomic regions associated with maize resistance to Fusarium fungi, which is of fundamental importance for understanding these regions and potentially manipulating them. Full article

Background/Objectives: Soft tissue sarcomas (STSs) are rare tumors arising from mesenchymal tissues, comprising over 100 distinct histological subtypes with varying biological behaviors, metastatic patterns, and treatment responses Despite advances in multimodal therapy, the overall survival of patients with metastatic STS is poor, mainly due to the weak response to conventional chemotherapy based on doxorubicin and ifosfamide. Methods: This review examines the evolution from traditional one-size-fits-all treatments to personalized medicine strategies, primarily focusing on assays based on patient-derived tumor samples, and it highlights their emerging role in guiding personalized treatment decisions and improving clinical outcomes in STS. These approaches, also known as functional precision oncology, are a step closer to the clinical situation as compared to other personalized therapies that rely on the identification of targetable genomic alterations using high-throughput technologies such as whole-genome sequencing, which have thus far failed to show convincing responses in STS treatment. Results: The main functional precision oncology platforms tested in patients with STS are in vitro cell viability tests, organoid cultures, and patient-derived xenografts. Each has advantages and limitations. In this context, in vitro drug sensitivity using cell suspension or organoids has shown a strong correlation with clinical responses. Furthermore, organoids matched the original tumor histology and microenvironment to a satisfactory degree. Establishment of xenografts proved feasible in the majority of patients; the technique could also preserve the tumor architecture and displayed high physiological relevance to the clinical situation. Conclusions: Although a major clinical study directly comparing conventional chemotherapy to personalized treatment guided by functional assays is yet to be published, this approach has gained popularity given the low efficacy of personalized medicine based on genetic alterations. The results thus far show promise for a better outcome for patients with metastatic STS. Full article

Avocado (Persea americana Mill.) is one of the most widely consumed fruits worldwide. The tree species is traditionally classified into three botanical races: Mexican, Guatemalan, and West Indian (with a potentially distinct Colombian genepool). However, previous studies using molecular markers, such as AFLPs, microsatellites (SSRs), and GBS-derived SNP markers, have only partially resolved this racial divergence, especially in the hyper agrobiodiverse region of northwest South America. Therefore, in order to confirm genetic identity and origin of “criollo” avocado cultivars in the region, as well as to improve their traceability as rootstocks for the Hass variety, we performed low-coverage whole genome resequencing (lcWGS) on 205 ex situ conserved tree samples, comprising 42 commercial varieties and 163 “criollo” trees from various provinces in Colombia. This characterization yielded a total of 64,310,961 SNPs at an average coverage of 4.69×. Population structure analysis using principal component analysis (PCA) and ADMIXTURE retrieved at least five genetic clusters (K = 5), partly confirmed by Bayesian phylogenetic inference. Three clusters matched the recognized Mesoamerican botanical races (Mexican, Guatemalan, and West Indian), and two clusters reinforced the distinctness of two novel Andean and Caribbean Colombian genetic groups. Finally, in order to retrieve high-quality SNP markers for racial screening, a second genomic dataset was filtered, consisting of 68 avocado tree samples exhibiting more than 80% ancestry to a given racial cluster, and 9826 SNPs with a minimum allele frequency (maf) of 5%, a minimum sequencing depth (SD) of 10× per position, and missing data per variant not exceeding 20% (i.e., variants with genotypes present in at least 80% of the samples). This racially segregating high-quality subset was analyzed against the racial substructure using linear mixed models (LMMs), enabling the identification of 254 SNP markers associated with the five avocado genetic races. The previous candidate SNPs may be leveraged by nurseries and producers through a high-throughput SNP screening system for the racial traceability of seedling donor trees, saplings, and rootstocks. These genomic resources will support the selection of regionally adapted elite rootstocks and represent a landmark in Colombian horticulture as the first large-scale lcWGS-based characterization of a local avocado germplasm collection. Full article

Monkeypox (Mpox) has re-emerged as a global public health threat, with recent outbreaks linked to novel mutations that enhance viral transmissibility and immune evasion. The Mpox virus (MPXV), a double-stranded deoxyribonucleic acid (DNA) orthopoxvirus, shares high structural and enzymatic similarity with the variola virus, underscoring the need for urgent therapeutic interventions. While conventional antiviral development is time-intensive and costly, drug repurposing offers a rapid and cost-effective strategy by leveraging the established safety and pharmacological profiles of existing medications. This is a narrative integrative review synthesizing published evidence on drug repurposing strategies against MPXV. To address these issues, this review explores MPXV molecular targets critical for genome replication, transcription, and viral assembly, highlighting how the Food and Drug Administration (FDA)-approved antivirals (cidofovir, tecovirimat), antibiotics (minocycline, nitroxoline), antimalarials (atovaquone, mefloquine), immunomodulators (infliximab, adalimumab), and chemotherapeutics (doxorubicin) have demonstrated inhibitory activity against the virus using computational or experimental approaches. This review further evaluates advances in computational methodologies that have accelerated the identification of host-directed and viral-directed therapeutic candidates. Nonetheless, translational challenges persist, including pharmacokinetic limitations, toxicity concerns, and the limited efficacy of current antivirals such as tecovirimat in severe Mpox cases. Future research should integrate computational predictions with high-throughput screening, organ-on-chip technologies, and clinical pipelines, while using real-time genomic surveillance to track viral evolution. These strategies establish a scalable and sustainable framework for the MPXV drug discovery. Full article

Glioblastoma (GBM) is the most common and aggressive malignant brain tumor in adults. This review explains the connections between the genesis and progression of GBM and particular cellular tumorigenic mechanisms, such as angiogenesis, invasion, migration, growth factor overexpression, genetic instability, and apoptotic disorders, as well as possible therapeutic targets that help predict the course of the disease. Glioblastoma multiforme (GBM) diagnosis relies heavily on histopathological features, molecular markers, extracellular vesicles, neuroimaging, and biofluid-based glial tumor identification. In order to improve miRNA stability and stop the proliferation of cancer cells, nanoparticles, magnetic nanoparticles, contrast agents, gold nanoparticles, and nanoprobes are being created for use in cancer treatments, neuroimaging, and biopsy. Targeted nanoparticles can boost the strength of an MRI signal by about 28–50% when compared to healthy tissue or controls in a preclinical model like mouse lymph node metastasis. Combining the investigation of CNAs and noncoding RNAs with deep learning-driven global profiling of genes, proteins, RNAs, miRNAs, and metabolites presents exciting opportunities for creating new diagnostic markers for malignancies of the central nervous system. Artificial intelligence (AI) advances precision medicine and cancer treatment by enabling the real-time analysis of complex biological and clinical data through wearable sensors and nanosensors; optimizing drug dosages, nanomaterial design, and treatment plans; and accelerating the development of nanomedicine through high-throughput testing and predictive modeling. Full article

Accurate differentiation between Coilia brachygnathus and Coilia nasus is imperative for the effective management of fisheries, the conservation of aquatic ecosystems, and the mitigation of commercial fraud. Current morphological identification remains challenging due to their high morphological similarity—particularly for processed samples—while conventional molecular methods often lack the speed or specificity required for field applications or high-throughput screening. In this study, a novel integrated approach was developed and validated, combining TaqMan quantitative real-time PCR (qPCR). for precise genotyping of C. brachygnathus and C. nasus with Recombinase Polymerase Amplification coupled with Lateral Flow Dipstick (RPA-LFD) for rapid on-site screening. First, species-specific RPA-LFD assays were designed to target the mitochondrial COI gene sequence. This enabled visual detection within 10 min at 37 °C, with a sensitivity of 10² copies/μL, and required no complex equipment. A dual TaqMan MGB qPCR assay was further developed by validating stable differentiating SNPs (chr21:3798155, C/T) between C. brachygnathus and C. nasus, using FAM/VIC dual-labeled MGB probes. Results showed that this assay could distinguish the two species in a single tube: for C. brachygnathus, Ct values in the FAM channel were significantly earlier than those in the VIC channel (ΔCt ≥ 1), with a FAM detection limit of 125 copies/reaction; for C. nasus, only VIC channel amplification was observed, with a detection limit as low as 12.5 copies/reaction. Validation with 171 known tissue samples demonstrated 100% concordance with expected species identities. This integrated approach effectively combines the high accuracy and quantitative capacity of TaqMan qPCR for confirmatory laboratory genotyping with the speed, simplicity, and portability of RPA-LFD for initial field or point-of-need screening. This reliable, efficient, and user-friendly technique provides a powerful tool for resource management, biodiversity monitoring, and ensuring the authenticity of high-quality C. brachygnathus and C. nasus. Full article

The soybean Glycine max (L.) Merrill is a key crop in Brazil’s agricultural sector and is essential for both domestic food security and international trade. However, water stress severely impacts its productivity. In this study, we examined the physiological and biochemical responses of soybean plants to various water regimes via hyperspectral reflectance (350–2500 nm) and machine learning (ML) models. The plants were subjected to eleven distinct water regimes, ranging from 100% to 0% field capacity, over 14 days. Seventeen key physiological parameters, including chlorophyll, carotenoids, flavonoids, proline, stress markers and water content, and hyperspectral data were measured to capture changes induced by water deficit. Principal component analysis (PCA) revealed significant spectral differences between the water treatments, with the first two principal components explaining 88% of the variance. Hyperspectral indices and reflectance patterns in the visible (VIS), near-infrared (NIR), and shortwave-infrared (SWIR) regions are linked to specific stress markers, such as pigment degradation and osmotic adjustment. Machine learning classifiers, including random forest and gradient boosting, achieved over 95% accuracy in predicting drought-induced stress. Notably, a minimal set of 12 spectral bands (including red-edge and SWIR features) was used to predict both stress levels and biochemical changes with comparable accuracy to traditional laboratory assays. These findings demonstrate that spectroscopy by hyperspectral sensors, when combined with ML techniques, provides a nondestructive, field-deployable solution for early drought detection and precision irrigation in soybean cultivation. Full article

Coccidioides immitis and Coccidioides posadasii, the causative agents of coccidioidomycosis, represent a major public health concern in endemic regions of North and South America. The disease spectrum ranges from mild respiratory illness to severe disseminated infections, with thousands of cases reported annually in the United States and an increasing recognition of its global impact. Despite existing antifungal therapies, treatment remains challenging due to toxicity, drug resistance, and limited therapeutic options. High-throughput screening platforms have revolutionized drug discovery for infectious diseases; however, progress in antifungal screening for Coccidioides spp. has been hampered by the requirement for Biosafety Level 3 (BSL-3) containment. To overcome these barriers, we leveraged an attenuated C. posadasii strain that can be safely handled under BSL-2 conditions. Here, we describe the development and optimization of 96-well and 384-well plate screening methodologies, providing a safer and more efficient platform for antifungal discovery. This approach enhances the feasibility of large-scale screening efforts and may facilitate the identification of novel therapeutics for coccidioidomycosis. Full article

Acute respiratory infections (ARIs) continue to pose a major global health threat, particularly among vulnerable populations. These infections often present with similar clinical symptoms, complicating accurate diagnosis and facilitating unmonitored transmissions. Genomic surveillance has emerged as an invaluable tool for pathogen identification and monitoring of such infectious pathogens; however, its implementation is frequently limited by high costs. The widespread use of high-throughput sequencing during the COVID-19 pandemic has created an opportunity to repurpose existing genomic platforms for broader respiratory virus surveillance. In this study, we evaluated the feasibility of adapting the Illumina COVIDSeq assay—initially designed for SARS-CoV-2 whole-genome sequencing—for use with Influenza A/B, Respiratory Syncytial Virus (RSV), and Rhinovirus. Positive control samples were processed using two approaches for library preparation: four virus-specific multiple workflows and a combined rapid workflow. Both workflows incorporated pathogen-specific primers for amplification and followed the Illumina COVIDSeq protocol for library preparation and sequencing. Sequencing quality metrics were analysed, including Phred scores, read length distribution, and coverage depth. The study did not identify significant differences in genome coverage and genetic diversity metrics between workflows. Genome Detective consistently identified the correct species across both methods. The findings of this study demonstrate that the COVIDSeq assay can be effectively adapted for multi-pathogen genomic surveillance and that the combined rapid workflow can offer a cost- and labour-efficient alternative with minimal compromise to data quality. Full article

CRISPR (clustered regularly interspaced short palindromic repeats)-Cas (CRISPR-associated protein) nucleases enable precise genome editing, but off-target cleavage remains a critical challenge. Here, we report the development of MAD7_HF, a high-fidelity variant of the MAD7 nuclease engineered through a bacterial screening system leveraging the DNA gyrase-targeting toxic gene ccdB. This system couples survival to efficient on-target cleavage and minimal off-target activity, mimicking the transient action required for high-precision editing. Through iterative selection and sequencing validation, we identified MAD7_HF, harboring three substitutions (R187C, S350T, K1019N) that enhanced discrimination between on- and off-target sites. In Escherichia coli assays, MAD7_HF exhibited a >20-fold reduction in off-target cleavage across multiple mismatch contexts while maintaining on-target efficiency comparable to wild-type MAD7. Structural modeling revealed that these mutations stabilize the guide RNA-DNA hybrid at on-target sites and weaken interactions with mismatched sequences. This work establishes a high-throughput bacterial screening strategy that allows the identification of Cas12a variants with improved specificity at a given target site, providing a useful framework for future efforts to develop precision genome-editing tools. Full article

The development of effective tools to combat viral diseases remains a major challenge for the aquaculture industry. Infectious pancreatic necrosis virus (IPNv) is one of the most devastating pathogens affecting salmonids, leading to high mortality rates and substantial economic losses worldwide. Here, we present a novel nanobody discovery pipeline based on a Type IIS restriction enzyme-driven library assembly method that enables the rapid generation of highly diverse nanobody repertoires. This streamlined approach not only shortens the time required for nanobody identification but also offers remarkable adaptability, allowing its application to virtually any protein target, including antigens from aquaculture pathogens and beyond. By integrating this strategy with density gradient–based enrichment and high-throughput screening, we successfully identified and validated a nanobody against the VP2 protein of IPNv, a key structural component essential for viral infectivity. These findings highlight the potential of this platform both as a versatile methodological advance in antibody engineering and as a practical foundation for developing innovative diagnostic and therapeutic tools. Ultimately, nanobodies generated through this pipeline could play a pivotal role in improving disease management and enhancing sustainability in aquaculture. Full article

The undefined microbial ecology of Aconitum carmichaelii root rot in western Yunnan constrains the advancement of eco-friendly control strategies. The identification of potential pathogenic determinants affecting A. carmichaelii growth is imperative for sustainable cultivation and ecosystem integrity. High-throughput sequencing was employed to profile microbial communities across four critical niches, namely rhizosphere soil, tuberous root epidermis, root endosphere, and fibrous roots of healthy and diseased A. carmichaelii. The physicochemical properties of corresponding rhizosphere soils were concurrently analyzed. Putative pathogens were isolated from diseased rhizospheres and tubers through culturing with Koch’s postulates validation, while beneficial microorganisms exhibiting antagonism against pathogens and plant growth-promoting (PGP) traits were isolated from healthy rhizospheres. Highly virulent strains (2F14, FZ1, L23) and their consortia were targeted for suppression. Strain DX3, demonstrating optimal PGP and antagonistic capacity in vitro, was selected for pot trials evaluating growth enhancement and disease control efficacy. Significant disparities in rhizosphere soil properties and bacterial/fungal community structures were evident between healthy and diseased cohorts. Fifteen putative pathogens spanning eight species across four genera were isolated: Fusarium solani, F. avenaceum, Clonostachys rosea, Mucor racemosus, M. irregularis, M. hiemalis, Serratia liquefaciens, and S. marcescens. Concurrently, eight PGP biocontrol strains were identified: Bacillus amyloliquefaciens, B. velezensis, B. subtilis, B. pumilus, and Paenibacillus polymyxa. Pot trials revealed that Bacillus spp. enhanced soil physiochemical properties through nitrogen fixation, phosphate solubilization, potassium mobilization, siderophore production, and cellulose degradation, significantly promoting plant growth. Critically, DX3 inoculation elevated defense-related enzyme activities in A. carmichaelii, enhanced host resistance to root rot, and achieved >50% disease suppression efficacy. This work delineates key pathogenic determinants of Yunnan A. carmichaelii root rot and identifies promising multifunctional microbial resources with dual PGP and biocontrol attributes. Our findings provide novel insights into rhizosphere microbiome-mediated plant health and establish a paradigm for sustainable disease management. Full article

The pressing global challenges of parasitic diseases, particularly prevalent in tropical and subtropical regions, underscore the critical urgent need for innovative therapeutic strategies in identifying and developing new treatments. The immense chemical diversity inherent in nature has rendered natural product (NP) chemistry a promising avenue for the discovery of novel antiparasitic chemotypes. Despite challenges such as sourcing, synthetic complexity, and drug resistance, NPs continue to offer invaluable contributions to antiparasitic therapy. This review focuses on recent advancements in NP chemistry and their application in the development of antiparasitic therapeutics. Key highlights include the identification of new molecular targets such as enzymes, membrane proteins, and metabolic pathways in parasites, as well as the role of metabolomics, genomics, and high-throughput screening in accelerating drug development. Additionally, the exploration of microorganisms (including soil bacteria and fungi) and marine organisms as a latent reserve of bioactive compounds with potent antiparasitic activity is discussed. The review further examines emerging strategies such as chemoinformatics and combination and polypharmacology therapies, aimed at addressing the challenges of antiparasitic chemotherapeutic treatment and advancing the development of new and effective treatments. Ultimately, NP chemistry represents a frontier for the design of novel antiparasitic drugs, offering the potential for more effective and sustainable therapies for combating parasitic diseases. Full article