Hypertensive disorders of pregnancy (HDP) are a major public health problem that increase morbidity and mortality in many mothers and newborn infants and are considered a significant clinical and economic burden worldwide. The precise pathogenesis of HDP is not yet fully understood, but as the disease progresses, noncoding RNAs (ncRNAs) such as long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and circular RNAs (circRNAs) play abnormal regulatory roles. These ncRNAs function in complex regulatory networks and regulate key biological processes such as cell proliferation, invasion, migration, and apoptosis. Special attention is given to their molecular targets, associated signaling pathways, and the underlying mechanisms of regulatory imbalances. By integrating recent findings and identifying gaps in the main knowledge, this article aims to provide valuable insights into ncRNAs in HDP and to guide therapeutic strategies for this maternal-fetal condition. This will help to establish a profile in this important area of knowledge concerning the clinical management of pregnant women and encourage further research.

Chromosomal inversion is one of the common types of chromosomal structural rearrangements. For couples with chromosomal inversions, the appropriate recommendations for preimplantation genetic testing (PGT) remain a subject of ongoing debate. This study retrospectively included couples who underwent PGT between January 2019 and December 2024. All included couples were classified into subgroups based on karyotyping analysis: PGT-INV (chromosomal inversion), PGT-PV (chromosomal polymorphic variation), PGT-A (normal karyotype), and PGT-SR (other balanced chromosomal rearrangements). The euploid rate of biopsied blastocysts did not differ significantly among the PGT-INV, PGT-PV, and PGT-A groups (P > 0.05); however, a statistically significant difference was observed between the PGT-SR group and each of the other three groups (P < 0.001). The aneuploidy rate in couples with female inversion was significantly higher than that in couples with male inversion (P = 0.046). Meanwhile, the proportion of aneuploid blastocysts associated with rearrangement was significantly higher in pericentric (38.94%) compared to paracentric inversions (23.60%) (P = 0.022). With the inverted fragment size increased, the proportion of aneuploid blastocysts associated with rearranged chromosomes increased accordingly and exhibited a linear trend (P < 0.05). In conclusion, the overall euploid rate of blastocysts in couples with chromosomal inversion showed no statistically significant difference compared to those with normal karyotype and chromosomal polymorphic variation; however, the carrier gender and the size of the inverted fragment are influencing factors for the abnormality rate associated with homologous rearranged chromosomes. Genetic counseling is strongly recommended for couples carrying chromosomal inversions.

Periodontitis, a leading cause of alveolar bone destruction and tooth loss, is associated with oral microbiota dysbiosis and shows higher susceptibility in males than in females. This study investigated sex-specific variations in the subgingival microbiome of elderly patients with moderate periodontitis. Subgingival plaque samples were collected from 25 patients with moderate periodontitis (8 males, 17 females; aged 50-73 years). The microbial composition was analyzed using 16S rRNA gene sequencing (V3-V4 region). Functional prediction was conducted utilizing the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Males exhibited higher Chao1 diversity, and beta diversity analysis revealed sex-based clustering. Wilcoxon rank-sum tests and LEfSe analysis identified Lactobacillus was enriched in females. KEGG analysis predicted a trend of enrichment of Immune system and Metabolic pathways in females. This exploratory study observed sex-specific subgingival microbiome variations of elderly patients with moderate periodontitis. Females exhibited specific enrichment of Lactobacillus, which may be associated with predicted Immune system and Metabolic pathways. These findings suggest that sex-specific microbiome differences may be a relevant biological variable in future periodontitis research, and their potential link to alveolar bone loss deserves further exploration.

To construct a prognostic risk model for thyroid cancer based on immune genes and analyze the correlation between immune genes and immune infiltration. A retrospective study was conducted on 180 patients with thyroid cancer treated in our hospital during May 2022 to April 2025. Based on the prognosis, the subjects were graded as good prognosis group of 126 cases and poor prognosis group of 54 cases. The influencing factors were analyzed by a binary logistic regression model, receiver operating characteristic curve and goodness of fit test. Single sample gene set enrichment analysis was used to perform immune infiltration analysis on the expression matrix of peripheral blood mononuclear cells. The GSEA algorithm was used to calculate the abundance of tumor associated immune cell infiltration. Pearson correlation analysis was used to investigate the correlation. The TCGA-THCA database was used to analyze the differential expression of genes, as well as the correlation with clinical pathological features. The expression levels of CDK1, B3GNT7, S100A9, and MMP9 genes were higher in the poor prognosis group than the good prognosis group (P < 0.05). A prognostic prediction model was constructed according to formula [1/1 + exp (4.125 + 1.250 × CDK1 + 1.880 × B3GNT7 + 0.920 × S100A9 + 1.050 × MMP9)]. The average C-index of the model was 0.919 (95% CI: 0.882-0.961). The AUC of the prognosis prediction model was 0.880. The poor prognosis group had much lower infiltration abundance of B lymphocytes, CD4+T lymphocytes, and CD8+T lymphocytes, and higher infiltration abundance of neutrophils and macrophages than the good prognosis group (P < 0.05). CDK1, B3GNT7, S100A9, and MMP9 were negatively correlated with the infiltration abundance of B lymphocytes, CD4+T lymphocytes, and CD8+T lymphocytes, and positively correlated with the infiltration abundance of neutrophils and macrophages (P < 0.05). Further analysis from the TCGA-THCA database showed that the high expression of S100A9 and MMP9 was correlated with advanced lymph node metastasis (pN stage), distant metastasis (pM stage) and overall TNM stage (P < 0.05). CDK1, B3GNT7, S100A9, and MMP9 were independent risk factors for poor prognosis in thyroid cancer. The prognostic prediction model may provide objective evidence for early screening of high-risk cases in clinical practice.

Triple-negative breast cancer (TNBC) is defined by the absence of estrogen, progesterone, and HER2 receptor expression. A critical challenge in managing TNBC is its high concentration of cancer stem cells (CSCs), which drives chemotherapy resistance and correlates with poor patient survival. In normal physiology, stem cell pluripotency and differentiation are governed by core transcription factors (such as Oct4, Sox2, Nanog, Klf4, and c-Myc) alongside key signaling networks, including the Notch, Wnt/β-catenin, and Sonic Hedgehog (Shh) pathways. During carcinogenesis, aberrant activation of these regulators in TNBC not only promotes the self-renewal of tumor cells but also actively facilitates immune evasion. Specifically, overexpressed pluripotency transcription factors enable cancer cells to downregulate antigen presentation molecules (e.g., MHC class I) and secrete immunomodulatory cytokines. Concurrently, dysregulated signaling, such as the Wnt/β-catenin pathway, inhibits dendritic cell maturation and recruits Myeloid-Derived Suppressor Cells (MDSCs) and regulatory T cells (Tregs) into the tumor microenvironment, thereby blunting the anti-tumor T cell response. This review examines the role of key pluripotency regulators in TNBC-mediated immune evasion, highlighting emerging immunotherapeutic strategies targeting these networks and summarizing current clinical research.

Thalassemia and sickle cell disease are inherited hemoglobinopathies caused by pathogenic variants in the globin genes and represent a major global health burden. Despite major advances in screening and diagnostics, challenges persist due to extensive genetic heterogeneity and complex genotype-phenotype relationships. Conventional workflows typically combine hematologic and biochemical analyses with targeted DNA-based testing. However, traditional molecular approaches are often sequential and labor-intensive, with limited capacity to detect the full spectrum of pathogenic variation. Advances in next-generation sequencing (NGS) now enables integrated and comprehensive strategies to support hemoglobinopathy diagnostics and screening follow-up. Currently available NGS-based platforms allow simultaneous detection of diverse variant classes, including sequence variants and copy number alterations, across multiple disease-relevant genes, including genetic modifiers that may influence disease severity. This review summarizes the genetic basis of thalassemia and sickle cell disease and compiles traditional and emerging molecular testing methodologies. It further discusses the strengths, limitations and utility of NGS-based platforms, and considers their role in shaping future screening and diagnostic workflows for hemoglobinopathies.

N 6-methyladenosine (m6A) is a pivotal RNA modification involved in diverse biological and pathological processes. Compared to the m6A detection methods based on second-generation sequencing, Nanopore direct RNA sequencing (DRS) offers the unique advantage of capturing native modifications. Here, we present Nanopore-m6A-Finder (NP-mFinder), a reference-free m6A prediction computational framework that employs the XGBoost model in the mRNA exonic region and a hard-voting ensemble of XGBoost and random forest models in the poly(A) region. NP-mFinder can determine m6A sites as well as estimate their methylation levels from Guppy basecalled DRS data. After training with DRS data of in vitro-transcribed RNA, NP-mFinder achieved high performance on held-out test datasets (area under the curve (AUC) ≈0.90; accuracy, precision, recall, and F1-score >0.80). Comparing with canonical m6A detection methods, it recovered 20% of meRIP-seq-defined m6A sites in yeast, and 27% of our HEK293 site prediction overlapped with miCLIP calls. Although single-base overlap with existing DRS-based tools of EpiNano and mAFiA was limited, 73% of our identified m6A-containing genes were validated by at least one of them. Benchmarking our method with GLORI v2.0 revealed concordance of 28% at a site level and 85% at a gene level, as well as a mild correlation on m6A level estimations. Notably, NP-mFinder achieved 93% precision in detecting m6A within the "AAAAA" sequence context in the mRNA exonic region of HEK293T DRS data when compared to high-confidence m6A site annotation in GLORI v2.0, demonstrating the good performance of our method in the region possessing a stretch of continuous A-sequences. Moreover, our method predicted that m6A might exist in the human HEK293 poly(A) region, suggesting a possibly conserved phenomenon of a modified poly(A) tail beyond the previously reported T. brucei variant surface glycoprotein (VSG) transcripts. Together, these results established NP-mFinder as a robust and versatile tool for transcriptome-wide m6A profiling with DRS data at single-read resolution.

Synthetic pesticides are widely used in agriculture to manage pests and reduce yield loss. Phytochemicals with antioxidant and antibacterial activities have great potential for treating plant diseases and reducing the use of synthetic chemicals. Identifying compounds from various plant species is crucial for their potential agricultural applications. In the present study, Cynoglossum lanceolatum was screened for potential antioxidant, antimicrobial, and bacterial blight protection abilities. Methanol and aqueous extracts of C. Lanceolatum root was tested for their polyphenol content, antioxidant potential, metabolomics and antimicrobial study. Results revealed that methanol extract exhibited higher phytochemical content and antioxidant activity. FTIR examination of extracts identified functional groups such as OH, C-H, C=C, and C-N, indicating the presence of distinct metabolites. The GC-MS investigation indicated the existence of 59 metabolites, several of which had previously been described as antimicrobial agents. Furthermore, in vitro antibacterial studies confirmed the antimicrobial effect of methanol extract against Xanthomonas oryzae pv. oryzae (Xoo). Moreover, prediction of antimicrobial metabolites, particularly 7-hydroxy-4-methylcoumarin-3-acetic acid, was confirmed through molecular docking study with D-alanine-D-alanine ligase A (DdlA) and the peptide deformylase (PDF) protein of Xoo. Finally, the study evaluated the effectiveness of C. lanceolatum root extract against bacterial blight disease, finding a significant reduction in Xoo lesions in pre-treatment and also showing their efficacy in post-treatment. Effect of extract was also observed in the photosynthetic status of rice by measuring chlorophyll A fluorescence. C. lanceolatum is a promising plant for its versatile role as an antioxidant, antimicrobial, and bacterial blight disease protection in rice.

Insects across different orders have convergently evolved adaptations to toxic cardiac glycosides (CGs), which are derived either from their diet or via endogenous synthesis. Previous studies on CG-resistance focused on changes in ATPα that is the direct inhibition target of CGs. Adaptation of whole organisms to toxic CGs could involve orchestrated changes at multiple genes and at multiple biological levels. Here, we explore this possibility by using whole genome sequences to identify several signatures of molecular convergence across multiple CG-adapted species. We identify gene families that changed convergently in CG-adapted species, including one member of stable fatty acyl-CoA reductase, CG5065, carboxylesterases and gustatory receptors that expanded in two of the three species. We find a number of candidate genes under positive selection in all CG-adapted species. We also identify convergent amino acid substitutions that have independently evolved in CG-adapted insects, including a conserved gene involved in the septate junction, Gliotactin (Gli). We used CRISPR-Cas9 to generate viable, homozygous Gli knock-in Drosophila lines with the convergent substitution. Through egg-larva and larva-adult survival experiments, we found that mutant flies consistently exhibit a lower survival rate compared to wild-type lines. Transmission electron microscopy (TEM) analysis of stage 17 embryos showed that in Gli mutants, the dihedral angles of bicellular membranes near the tricellular junction (TCJ) were unequal, and electron-dense materials were absent in the TCJ center. We propose that this convergently evolved Gli variant may contribute to CG adaptation by modulating epithelial permeability, potentially facilitating the sequestration of toxic CGs.

Genetic variation within livestock populations underpins global food security, resilience, and the long-term sustainability of breeding programs. Despite its fundamental role, harmonized approaches for assessing and monitoring genetic variation across data sources remain limited. This review provides an integrated framework for assessing genetic variation in livestock using demographic, pedigree, and genomic data, developed by FAO experts and international collaborators. Demographic indicators offer essential insight into population size, sex ratio, and reproductive structure, while pedigree data allow detailed evaluation of genetic relatedness, inbreeding, and effective population size (N e ) over time. Genomic information now provides unprecedented accuracy in characterizing allelic variation, population structure with admixture, and the dynamics of inbreeding and drift. Each data source differs in availability, resolution, and interpretive limits; therefore, complementary use of demographic, pedigree, and genomic measures is recommended for effective monitoring and decision-making. This framework outlines the main properties, applications, and constraints of these approaches and provides guidance on selecting appropriate indicators for monitoring genetic variation within and among livestock populations. Its implementation supports the objectives of the Global Plan of Action for Animal Genetic Resources and the Kunming-Montreal Global Biodiversity Framework, contributing to evidence-based management of livestock diversity worldwide.