Search Results (2,376)

The cytochrome p450 gene family is widely involved in various biological processes in arthropods. Tick p450s are often associated with chemical acaricides, but knowledge of their involvement in the metabolism of plant-derived essential oil components is limited. In this study, we identified the non-redundant number of p450 transcripts (NRNPTs) from Haemaphysalis longicornis and Hyalomma asiaticum under the Cymbopogon citratus essential oil (CCEO) and terpinolene stress using de novo transcriptome data, respectively. In this study, we identified and characterized the NRNPTs of Ha. longicornis and Hy. asiaticum. Their gene expression patterns and biological functions under CCEO and terpinolene stress were further analyzed. Finally, Hy. asiaticum NRNPTs (87) were more numerous than Ha. longicornis (58). Phylogenetic analyses showed that NRNPTs of both Hy. asiaticum and Ha. longicornis could be categorized in clan 2, clan 3, clan 4, and clan mito, this data comes from the NRNPTs. Phylogenetic analyses showed that NRNPTs of both Hy. asiaticum and Ha. longicornis could be categorized in clan 2, clan 3, clan 4, and clan mito. p450 members of both were most distributed in clan 3. In addition, one Hy. asiaticum NRNPT was identified as belonging to the new classification clan 20 (HyasCYP20A1). The biological functions and pathways of p450 family members enriched in Hy. asiaticum and Ha. longicornis under different exogenous substance stresses were different, and the expression patterns of these genes were inconsistent. Molecular docking results showed that Ha. longicornis p450 members (HaloCYP3A4 and HaloCYP4B1), which were significantly up-regulated under CCEO stress, as well as Hy. asiaticum HyasCYP24A1 and HyasCYP4V2 (the HaloCYP3A4 and HaloCYP4B1 homologous genes), encode proteins that differ in their ability to metabolize CCEO components, but they all bind well to Germacrene D and naphthalene. Our study enriches the knowledge of the involvement of p450 family members of different tick species in the metabolism of essential oil components of plants, and provides a theoretical basis for further in-depth studies on the function of tick p450 enzymes. Full article

Pepper is a major horticultural crop cultivated extensively worldwide. Among its various agronomic characteristics, fruit length is a key trait influencing both yield and visual quality. Despite its importance, the genetic mechanisms regulating fruit length in Capsicum remain insufficiently characterized, hindering the development of high-yielding and aesthetically desirable cultivars. In this study, fruits at three developmental stages (0, 15, and 30 days after flowering) were sampled from the long-fruit mutant fe1 and its wild-type progenitor LY0. Phenotypic characterization and transcriptomic sequencing were conducted to identify candidate genes associated with fruit length regulation. Morphological analysis revealed that the most pronounced difference in fruit length occurred at 30 days after flowering. RNA-seq analysis identified 41,194 genes, including 13,512 differentially expressed genes (DEGs). Enrichment analysis highlighted key pathways, such as plant–pathogen interaction, plant hormone signal transduction, and the MAPK signaling pathway. DEG classification suggested that several downregulated genes related to early auxin responses may contribute to the regulation of fruit elongation. Notably, the gibberellin signaling gene SCL13 (Caz12g26660), transcription factors MYB48 (Caz11g07190) and ERF3-like (Caz10g00810), and the cell-wall-modifying gene XTH15-like (Caz07g19100) showed significantly elevated expression in 30-day-old fruits of fe1. Weighted gene co-expression network analysis (WGCNA) further revealed a strong positive correlation among these genes. Quantitative RT-PCR analysis of eight selected DEGs confirmed the RNA-seq results. This study provides a foundational framework for dissecting the molecular regulatory network of fruit length in Capsicum, offering valuable insights for breeding programs. Full article

This paper investigates the effectiveness of Word2Vec-based molecular representation learning on SMILES (Simplified Molecular Input Line Entry System) strings for a downstream prediction task related to the market approvability of chemical compounds. Here, market approvability is treated as a proxy classification label derived from approval status, where only the molecular structure is analyzed. We train character-level embeddings using Continuous Bag of Words (CBOW) and Skip-Gram with Negative Sampling architectures and apply the resulting embeddings in a downstream classification task using a multi-layer perceptron (MLP). To evaluate the utility of these lightweight embedding techniques, we conduct experiments on a curated SMILES dataset labeled by approval status under both imbalanced and SMOTE-balanced training conditions. In addition to our Word2Vec-based models, we include a ChemBERTa-based baseline using the pretrained ChemBERTa-77M model. Our findings show that while ChemBERTa achieves a higher performance, the Word2Vec-based models offer a favorable trade-off between accuracy and computational efficiency. This efficiency is especially relevant in large-scale compound screening, where rapid exploration of the chemical space can support early-stage cheminformatics workflows. These results suggest that traditional embedding models can serve as viable alternatives for scalable and interpretable cheminformatics pipelines, particularly in resource-constrained environments. Full article

Viruses have evolved sophisticated solutions to evade host immunity. One of the most pervasive strategies is molecular mimicry, whereby viruses imitate the molecular and biophysical features of their hosts. This mimicry poses significant challenges for immune recognition, therapeutic targeting, and vaccine development. In this study, we leverage pretrained protein language models (PLMs) to distinguish between viral and human proteins. Our model enables the identification and interpretation of viral proteins that most frequently elude classification. We characterize these by integrating PLMs with explainable models. Our approach achieves state-of-the-art performance with ROC-AUC of 99.7%. The 3.9% of misclassified sequences are signified by viral proteins with low immunogenicity. These errors disproportionately involve human-specific viral families associated with chronic infections and immune evasion, suggesting that both the immune system and machine learning models are confounded by overlapping biophysical signals. By coupling PLMs with explainable AI techniques, our work advances computational virology and offers mechanistic insights into viral immune escape. These findings carry implications for the rational design of vaccines, and improved strategies to counteract viral persistence and pathogenicity. Full article

Background: Soft tissue sarcomas (STSs) histopathological classification system and the clinical and molecular-based tools that are currently employed to estimate its prognosis have several limitations, impacting prognostication and treatment. Clinically driven molecular profiling studies may cover these gaps and offer alternative tools with superior prognostication capability and enhanced precision and personalized treatment approaches identification ability. Materials and Methods: We performed DNA sequencing (DNA-seq) and RNA sequencing (RNA-seq) to portray the molecular profile of 102 samples of high-grade STS, comprising the three most common STS histotypes. Results: The analysis of RNA-seq data using unsupervised machine learning models revealed previously unknown molecular patterns, identifying four transcriptomic subtypes/clusters (TCs). This TC-based classification has a clear prognostic value (in terms of overall survival (OS) and disease-free survival (DFS)), a finding that was externally validated using independent patient cohorts. The prognostic value of this TC-based classification outperforms the prognostic accuracy of clinical-based (SARCULATOR nomograms) and molecular-based (CINSARC) prognostication tools, being one of the first molecular-based classifications capable of predicting OS in STS. The analysis of DNA-seq data from the same cohort revealed numerous and, in some cases, never documented molecular targets for precision treatment across different transcriptomic subtypes. The functional and predictive value of each genomic variant was analyzed using the Molecular Tumor Board Portal. Conclusions: This newly identified TC-based classification offers a superior prognostic value when compared with current gold-standard clinical and molecular-based prognostication tools, and identifies novel molecular targets for precision treatment, representing a cutting-edge tool for predicting prognosis and guiding treatment across different stages of STS. Full article

Extracellular vesicles (EVs) are mediators of intercellular communication and serve as promising tools for drug discovery and targeted therapies. These lipid bilayer-bound nanovesicles facilitate the transfer of functional proteins, RNAs, lipids, and other biomolecules between cells, thereby influencing various physiological and pathological processes. This review outlines the molecular mechanisms governing EV biogenesis and cargo sorting, emphasizing the role of key regulatory proteins in modulating selective protein packaging. We explore the critical involvement of EVs in various disease microenvironments, including cancer progression, neurodegeneration, and immunological modulation. Their ability to cross biological barriers and deliver bioactive cargo makes them desirable candidates for precise drug delivery systems, especially in neurological and oncological disorders. Moreover, this review highlights advances in engineering EVs for the delivery of RNA therapeutics, CRISPR-Cas systems, and targeted small molecules. The utility of EVs as diagnostic tools in liquid biopsies and their integration into personalized medicine and companion diagnostics are also discussed. Patient-derived EVs offer dynamic insights into disease states and enable real-time treatment stratification. Despite their potential, challenges such as scalable isolation, cargo heterogeneity, and regulatory ambiguity remain significant hurdles. Recent studies have reported novel pharmacological approaches targeting EV biogenesis, secretion, and uptake pathways, with emerging regulators showing promise as drug targets for modulating EV cargo. Future directions include the standardization of EV analytics, scalable biomanufacturing, and the classification of EV-based therapeutics under evolving regulatory frameworks. This review emphasizes the multifaceted roles of EVs and their transformative potential as therapeutic platforms and biomarker reservoirs in next-generation precision medicine. Full article

Lateral Spreading Tumors (LSTs) are a type of non-polypoid lesion known for their flat morphology, which often leads to them going undetected. However, especially nongranular (NG) LSTs have the potential for malignant transformation. Recent advances in endoscopic technologies have improved the detection of these lesions. Despite growing research interest in their role in colorectal cancer (CRC) development, a comprehensive molecular characterization of LSTs is still lacking. The aim of this review is to highlight the current knowledge of the molecular characteristics of LSTs, that may help in determining whether LSTs can be prognostic indicators and identifying cases where they may rapidly progress to CRC through characteristic molecular pathways. From a mutational point of view, LSTs seem to be more closely associated with inflammatory bowel diseases (IBDs) than with polypoid lesions. Nonetheless, they have peculiar epigenetic and genetic traits, which set them apart from other adenomas or bowel diseases. Elucidating their role in CRC development would provide benefits for their classification and management, by enhancing clinical surveillance strategies for patients diagnosed with these lesions in order to improve the efficient prevention of colorectal cancer. Full article

A comprehensive analysis of the molecular epidemiology of SARS-CoV-2 in the Kandy District of Sri Lanka from November 2020 to March 2022 was conducted to address the limited genomic surveillance data available across the country. The study investigated the circulating SARS-CoV-2 lineages, their temporal dynamics, and the associated mutational profiles in the study area. A total of 280 SARS-CoV-2-positive samples were selected, and 252 complete genomes were successfully sequenced using Oxford Nanopore Technology. Lineage classification was performed using the EPI2ME tool, while phylogenetic relationships were inferred through maximum likelihood and time-scaled phylogenetic trees using IQ-TREE2 and BEAST, respectively. Amino acid substitutions were analyzed to understand lineage-specific mutation patterns. Fifteen SARS-CoV-2 lineages were identified, and of those B.1.411 (36%) was the most prevalent, followed by Q.8 (21%), AY.28 (9.5%), and the Delta and Omicron variants. The lineage distribution showed a temporal shift from B.1.411 to Alpha, Delta, and finally the Omicron, mirroring the global trends. Time to the most recent common ancestor analyses provided estimates for the introduction of major variants, while mutation analysis revealed the widespread occurrence of D614G in the spike protein and lineage-specific mutations across structural, non-structural, and accessory proteins.Detection of the Epsilon variant (absent in other national-level studies) in November 2020, highlighted the regional heterogeneity viral spread. This study emphasizes the importance of localized genomic surveillance to capture the true diversity and evolution of SARS-CoV-2, to facilitate containment strategies in resource-limited settings. Full article

Background: Traditional morphology-based classification of the Oriental Plover (Anarhynchus veredus) is inconsistent with molecular evidence, underscoring the necessity of incorporating molecular data to elucidate its evolutionary relationships within Charadriidae. Methods: Here, we present the first complete mitochondrial genome of A. veredus by Illumina NovaSeq Sequencing and explore its evolutionary implications within Charadriidae. Results: The mitogenome spans 16,886 bp and exhibits conserved structural features typical of Charadriidae, including gene order, overlapping coding regions, and intergenic spacers. Nucleotide composition analysis revealed a GC content of 44.3%, aligning with other Charadriidae species (44.5–45.8%), and hierarchical GC distribution across rRNA, tRNA, and protein-coding genes (PCGs) reflects structural and functional optimization. Evolutionary rate heterogeneity was observed among PCGs, with ATP8 and ND6 showing accelerated substitution rates (Ka/Ks = 0.1748 and 0.1352) and COX2 under strong purifying selection (Ka/Ks = 0.0678). Notably, a conserved translational frameshift in ND3 (position 174) was identified. Phylogenetic analyses (ML/NJ) of 88 Charadriiformes species recovered robust topologies, confirming that the division of Charadriidae into four monophyletic clades (Pluvialis, Vanellus, Charadrius, and Anarhynchus) and supporting the reclassification of A. veredus under Anarhynchus. Conclusions: This study resolves the systematic position of A. veredus and highlights the interplay between conserved mitochondrial architecture and lineage-specific adaptations in shaping shorebird evolution. Full article

Background/Objective: Thyroid nodules are rare in the pediatric population but carry a higher malignancy risk compared to adults. Evaluation and management of cytologically indeterminate nodules vary considerably between institutions and countries. The aim was to systematically review current evidence on the management of indeterminate thyroid nodules in the pediatric population. Methods: A systematic review of the literature was conducted, focusing on cytological classification systems, surgical strategies, and the use of ancillary tools such as molecular testing. Results: Most studies (42.9%) recommend lobectomy for indeterminate thyroid nodules in children; however, considerable heterogeneity in management strategies was observed among institutions. This variability precluded the possibility of conducting a meta-analysis of surgical outcomes. Additionally, a lack of pediatric-specific risk of malignancy (ROM) data for the British Thyroid Association (BTA) and SIAPEC cytological classification systems was noted. Conclusions: We propose the development of a pediatric-specific, multiparametric risk stratification model that incorporates clinical features, biochemical markers, ultrasound characteristics, cytological classification, and molecular profiling. This comprehensive score could help standardize the management of indeterminate thyroid nodules in children and guide clinical decision-making, ranging from observation to total thyroidectomy. Prospective validation in multicenter pediatric cohorts is essential to confirm its clinical utility. Full article

Indocalamus Nakai, a genus within the tribe Arundinarieae, has significant horticultural and economic value. However, its classification has long been challenging, and due to limited sampling, both intra- and intergeneric phylogenetic relationships, as well as its evolutionary history, remain unclear. In this study, extensive field surveys and comprehensive sample collection were conducted to address these challenges. A total of 31 complete plastomes of Indocalamus species were assembled. All plastomes exhibit a typical quadripartite structure, ranging in length from 139,555 bp to 139,791 bp, and contain 137 genes, including 90 protein-coding genes, 39 tRNA genes, and 8 rRNA genes. Phylogenetic analyses indicate that Indocalamus is polyphyletic and divided into three distinct clades (IV, V, and X). Based on integrated phylogenomic and morphological evidence, we propose a revised classification of Indocalamus into three major sections. Fossil-calibrated divergence estimates reveal that the major clades of Indocalamus are not monophyletic, highlighting a complex reticulate evolutionary history exemplifying the widespread rapid radiation observed in temperate woody bamboos. The intensification of the East Asian monsoon is likely to have played a key role in driving the rapid radiation of these lineages. Additionally, several clade-specific DNA barcodes (trnT-trnE, petN-trnC, petA-psbJ, and petD-rpoA) were identified, which will enhance the identification of Indocalamus and its closely related genera. This study, through extensive sampling and integration of morphological and molecular phylogenetic evidence, provides a preliminary delimitation of the genus Indocalamus, elucidates its complex evolutionary history, and lays a solid foundation for future systematic research and horticultural applications. Full article

Acute lymphoblastic leukemia (ALL) is the most common childhood cancer, with pediatric ALL having a ~90 percent cure rate, while the adult cure rate is considerably lower. B-cell acute lymphoblastic leukemia (B-ALL) is the most common subtype of ALL and is generally treated through a variety of chemotherapy drugs that can cause undesired side effects, adverse events, or other complications. Consequently, there is a need for improved understanding of the shared gene expression profiles and underlying molecular mechanisms shared among various B-ALL subtypes. In this study, 259 publicly available RNA-sequencing samples were evaluated and retrieved from the NCBI Gene Expression Omnibus (GEO) database and then pre-processed using a robust computational workflow. Differential gene expression, pathway enrichment, marker prediction, and drug repurposing analyses were then performed to facilitate a better mechanistic understanding of disease. We found both previously identified as well as novel differentially expressed genes. Specifically, we observed upregulation in the HIST2H2AA3, EPHA7, and MPR1 genes; while downregulation was observed for the IGHA1, ANGPTL1, and CHAD genes. We identified multiple pathways, including “Integrins in Angiogenesis”, to be significantly affected in B-ALL. We then used these significant pathways to predict and rank 306 existing therapeutic targets that could potentially be repurposed for B-ALL, including three that have not been evaluated in human clinical trials. Using a tree-based classification algorithm, we also predicted ADAM28 as a possible mechanistic marker. The results of this study have potential implications for patients who have been diagnosed with B-ALL by providing improved mechanistic understanding and information on possible diagnostics and repurposed therapeutics for B-ALL. Full article

Background: Endometrial cancer (EC) is the most common gynecologic malignancy in developed countries. Despite advances in diagnosis and treatment, recurrence and mortality remain significant concerns. The neutrophil-to-lymphocyte ratio (NLR), a marker of systemic inflammation, has shown prognostic value in several malignancies, but its utility in EC remains underexplored. Objective: To evaluate the prognostic significance of the preoperative NLR in patients with endometrial cancer undergoing primary surgical treatment. Methods: We conducted a retrospective cohort study including 398 patients with histologically confirmed endometrial adenocarcinoma surgically treated at a tertiary cancer center. Preoperative complete blood counts were used to calculate NLR, and a cutoff value of 2.27 was determined through Receiver Operating Characteristic (ROC) analysis. Survival outcomes were assessed using Kaplan–Meier analysis and Cox proportional hazards modeling. Results: Patients with NLR ≥ 2.27 had significantly reduced median overall survival (OS) compared to those with NLR < 2.27 (72.3 vs. 92.8 months, p = 0.008). In multivariate analysis, elevated NLR remained an independent predictor of poorer OS (HR = 1.87; 95% CI: 1.156–3.017; p = 0.011), alongside age ≥ 64 years, lymphovascular space invasion (LVSI), lymph node involvement, and distant metastases. ROC analysis yielded an Area Under the Curve (AUC) of 0.646 for NLR. Notably, vaginal brachytherapy was associated with improved survival (HR = 0.53; p = 0.026), while other adjuvant therapies were not independently significant. Conclusions: Preoperative NLR is an accessible, independent prognostic biomarker in endometrial cancer and may serve as a surrogate indicator of tumor-promoting inflammation and immune dysregulation. Its integration into preoperative assessment could enhance risk stratification and guide personalized treatment strategies. However, findings should be interpreted in light of the study’s retrospective design, single-center setting, and lack of molecular classification data. Prospective validation is warranted to confirm its clinical utility. Full article

Background/Objectives: Developmental dyslexia is characterised by neuropsychological processing deficits and marked hemispheric functional asymmetries. To uncover latent neurophysiological features linked to reading impairment, we applied dimensionality reduction and clustering techniques to high-density electroencephalographic (EEG) recordings. We further examined the functional relevance of these features to reading performance under standardised test conditions. Methods: EEG data were collected from 200 children (100 with dyslexia and 100 age- and IQ-matched typically developing controls). Principal Component Analysis (PCA) was applied to high-dimensional EEG spectral power datasets to extract latent neurophysiological components. Twelve principal components, collectively accounting for 84.2% of the variance, were retained. K-means clustering was performed on the PCA-derived components to classify participants. Group differences in spectral power were evaluated, and correlations between principal component scores and reading fluency, measured by the TILLS Reading Fluency Subtest, were computed. Results: K-means clustering trained on PCA-derived features achieved a classification accuracy of 89.5% (silhouette coefficient = 0.67). Dyslexic participants exhibited significantly higher right parietal–occipital alpha (P8) power compared to controls (mean = 3.77 ± 0.61 vs. 2.74 ± 0.56; p < 0.001). Within the dyslexic group, PC1 scores were strongly negatively correlated with reading fluency (r = −0.61, p < 0.001), underscoring the functional relevance of EEG-derived components to behavioural reading performance. Conclusions: PCA-derived EEG patterns can distinguish between dyslexic and typically developing children with high accuracy, revealing spectral power differences consistent with atypical hemispheric specialisation. These results suggest that EEG-derived neurophysiological features hold promise for early dyslexia screening. However, before EEG can be firmly established as a reliable molecular biomarker, further multimodal research integrating EEG with immunological, neurochemical, and genetic measures is warranted. Full article

Background/Objectives: In the past two decades, the primary therapeutic use of sildenafil has shifted significantly, from the treatment of angina to managing erectile dysfunction, and since the early 2000s it has been used in the treatment of pulmonary hypertension, particularly pulmonary arterial hypertension. Sildenafil is used as a citrate salt; after oral administration, it presents an absorption of ~90% and an absolute bioavailability of 38%, due to the first-pass effect, such that it belongs to class II of the Biopharmaceutics Classification System. Currently, studies are seeking to obtain new pharmaceutical formulations with an optimized biopharmaceutical profile. In this study, an inclusion complex of sildenafil citrate and 2-hydroxypropyl-beta-cyclodextrin in a molar ratio of 1:1 was obtained and its pharmaceutical compatibility with six pharmaceutical excipients was assessed. For three of these excipients, the presence of chemical interactions with sildenafil citrate has been presented in the literature, and for the other three, compatibility has not been evaluated. Methods: To certify the stoichiometry of the obtained inclusion complex molecular modeling, Job’s method and the Benesi–Hildebrand method were employed. Furthermore, we have described the inclusion complex and the obtained binary mixtures via ATR-FTIR and thermal (TG/DTG and DSC) analysis. Results: The results indicated a lack of chemical interactions between the inclusion complex and the six pharmaceutical excipients at ambient temperature (confirmed by ATR–FTIR investigations) and the presence of chemical interactions between the inclusion complex and three of the excipients when the mixture was heated under non-isothermal conditions (TG/DTG and DSC investigations). Conclusions: This study describes the inclusion complex between sildenafil citrate and 2-hydroxypropyl-beta-cyclodextrin in a molar ratio of 1:1 and its compatibility with several pharmaceutical excipients, results with further applications in the preformulation stage of novel delivery systems. Full article