Mol Ecol Resour. 2025 Apr 1:e14110. doi: 10.1111/1755-0998.14110. Online ahead of print.

ABSTRACT

The percomorph fish clade Gobioidei is a suborder that comprises over 2200 species distributed in nearly all aquatic habitats. To understand the genetics underlying their species diversification, we sequenced and annotated the genome of the loach goby, Rhyacichthys aspro, an early-diverging group, and compared it with nine additional Gobioidei species. Within Gobioidei, the loach goby possesses the smallest genome at 594 Mb, and a rise in species diversity from early-diverging to more recently diverged lineages is mirrored by enlarged genomes and a higher presence of transposable elements (TEs), particularly DNA transposons. These DNA transposons are enriched in genic and regulatory regions and their copy number increase is strongly correlated with substitution rate, suggesting that DNA repair after transposon excision/insertion leads to nearby mutations. Consequently, the proliferation of DNA transposons might be the crucial driver of Gobioidei diversification and adaptability. The loach goby genome also points to mechanisms of ecological adaptation. It contains relatively few genes for lateral line development but an overrepresentation of synaptic function genes, with genes putatively under selection linked to synapse organisation and calcium signalling, implicating a sensory system distinct from other Gobioidei species. We also see an overabundance of genes involved in neurocranium development and renal function, adaptations likely connected to its flat morphology suited for strong currents and an amphidromous life cycle. Comparative analyses with hill-stream loaches and the European eel reveal convergent adaptations in body shape and saltwater balance. These findings shed new light on the loach goby's survival mechanisms and the broader evolutionary trends within Gobioidei.

PMID:40168108 | DOI:10.1111/1755-0998.14110

Methods Mol Biol. 2025;2914:275-302. doi: 10.1007/978-1-0716-4462-1_20.

ABSTRACT

Cerebrospinal fluid (CSF) is a source of valuable information concerning brain disorders. The technical advances of high throughput omics platforms to analyze body fluids can generate a huge amount of data, whose translation of the biological meaning can be a challenge. Several bioinformatics tools have emerged to help handle this data from a systems biology perspective. Herein, we describe a step-by-step tutorial for CSF proteome data analysis in the set of neurodegenerative diseases using: (i) ShinyGO webtool to perform functional enrichment analysis envisioning the characterization of the biological pathways and processes deregulated in neurodegenerative diseases including Alzheimer's and Parkinson's diseases; (ii) Cytoscape to map disease-specific proteins based on evidence from proteomics; (iii) DisGeNET to identify the proteins more strongly and more specifically associated with neurodegenerative diseases to date; (iv) STRING to identify putative therapeutic targets through a combined protein-protein interaction and network topological analyses. This step-by-step guide might help researchers to better characterize disease pathogenesis and to identify putative disease biomarkers and therapeutic targets.

PMID:40167925 | DOI:10.1007/978-1-0716-4462-1_20

Metabolomics. 2025 Apr 1;21(2):48. doi: 10.1007/s11306-025-02247-x.

NO ABSTRACT

PMID:40167843 | DOI:10.1007/s11306-025-02247-x

Semin Immunopathol. 2025 Apr 1;47(1):23. doi: 10.1007/s00281-025-01049-6.

ABSTRACT

Barrier organs such as the gastrointestinal tract, lungs, and skin are colonized by diverse microbial strains, including bacteria, viruses, and fungi. These microorganisms, collectively known as the commensal microbiota, play critical roles in maintaining health by defending against pathogens, metabolizing nutrients, and providing essential metabolites. In the gut, commensal-derived antigens are frequently sensed by the intestinal immune system. Maintaining tolerance toward these beneficial microbial species is crucial, as failure to do so can lead to chronic inflammatory conditions like inflammatory bowel disease (IBD) and can even affect systemic immune or metabolic health. The immune system carefully regulates responses to commensals through various mechanisms, including the induction of anti-inflammatory CD4⁺ T cell responses. Foxp3⁺ regulatory T cells (Foxp3+ Tregs) and Type 1 regulatory T cells (Tr1) play a major role in promoting tolerance, as both cell types can produce the anti-inflammatory cytokine IL-10. In addition to these regulatory T cells, effector T cell subsets, such as Th17 cells, also adopt anti-inflammatory functions within the intestine in response to the microbiota. This process of anti-inflammatory CD4+ T cell induction is heavily influenced by the microbiota and their metabolites. Microbial metabolites affect intestinal epithelial cells, promoting the secretion of anti-inflammatory mediators that create a tolerogenic environment. They also modulate intestinal dendritic cells (DCs) and macrophages, inducing a tolerogenic state, and can interact directly with T cells to drive anti-inflammatory CD4⁺ T cell functionality. The disrupted balance of these signals may result in chronic inflammation, with broader implications for systemic health. In this review, we highlight the intricate interplays between commensal microorganisms and the immune system in the gut. We discuss how the microbiota influences the differentiation of commensal-specific anti-inflammatory CD4⁺ T cells, such as Foxp3⁺ Tregs, Tr1 cells, and Th17 cells, and explore the mechanisms through which microbial metabolites modulate these processes. We further discuss the innate signals that prime and commit these cells to an anti-inflammatory fate.

PMID:40167791 | DOI:10.1007/s00281-025-01049-6

Funct Integr Genomics. 2025 Apr 1;25(1):78. doi: 10.1007/s10142-025-01588-z.

ABSTRACT

Metabolic engineering of lipids in crops presents a promising strategy to enhance resilience against environmental stressors while improving nutritional quality. By manipulating key enzymes in lipid metabolism, introducing novel genes, and utilizing genome editing technologies, researchers have improved crop tolerance to abiotic stresses such as drought, salinity, and extreme temperatures. Additionally, modified lipid pathways contribute to resistance against biotic stresses, including pathogen attacks and pest infestations. Engineering multiple stress-resistance traits through lipid metabolism offers a holistic approach to strengthening crop resilience amid changing environmental conditions. Beyond stress tolerance, lipid engineering enhances the nutritional profile of crops by increasing beneficial lipids such as omega-3 fatty acids, vitamins, and antioxidants. This dual approach not only improves crop yield and quality but also supports global food security by ensuring sustainable agricultural production. Integrating advanced biotechnological tools with a deeper understanding of lipid biology paves the way for developing resilient, nutrient-rich crops capable of withstanding climate change and feeding a growing population.

PMID:40167787 | DOI:10.1007/s10142-025-01588-z

Adv Sci (Weinh). 2025 Apr 1:e2412921. doi: 10.1002/advs.202412921. Online ahead of print.

ABSTRACT

HDAC6 is integral to the regulation of primary cilia, which are specialized structures that serve as crucial signaling hubs for cellular communication and environmental response. These ciliary functions are essential for maintaining cellular homeostasis and orchestrating developmental processes. Dysregulation of HDAC6 activity is implicated in ciliopathies, a group of disorders characterized by defective ciliary structure or function, resulting in widespread organ involvement and significant morbidity. This review provides a comprehensive examination of the molecular dynamics of HDAC6 in the context of ciliogenesis and ciliopathies, emphasizing its dual role in the deacetylation of microtubules and regulation of the ciliary axoneme. Furthermore, HDAC6 interacts with key signaling molecules, modulating processes ranging from cell cycle regulation to inflammatory responses, which highlights its central role in cellular physiology and pathology. The therapeutic potential of HDAC6 inhibitors has been explored, with promising results in various disease models, including retinal and renal ciliopathies, highlighting their ability to restore normal ciliary function. This analysis not only underscores the critical importance of HDAC6 in maintaining ciliary integrity but also illustrates how targeting the HDAC6-cilia axis could provide a groundbreaking approach to treating these complex disorders. In doing so, this review sets the stage for future investigations into HDAC6-targeted therapies, potentially transforming the clinical management of ciliopathies and significantly improving patient outcomes.

PMID:40167251 | DOI:10.1002/advs.202412921

J Gerontol A Biol Sci Med Sci. 2025 Mar 28:glaf053. doi: 10.1093/gerona/glaf053. Online ahead of print.

ABSTRACT

Ageing-associated cognitive decline affects more than half of those in long-term residential aged care. Emerging evidence suggests that gut microbiome-host interactions influence the effects of modifiable risk factors. We investigated the relationship between gut microbiome characteristics and severity of cognitive impairment CI in 159 residents of long-term aged care. Severe CI was associated with a significantly increased abundance of proinflammatory bacterial species, including Methanobrevibacter smithii and Alistipes finegoldii, and decreased relative abundance of beneficial bacterial clades. Severe CI was associated with increased microbial capacity for methanogenesis, and reduced capacity for synthesis of short-chain fatty acids, neurotransmitters glutamate and gamma-aminobutyric acid, and amino acids required for neuro-protective lysosomal activity. These relationships were independent of age, sex, antibiotic exposure, and diet. Our findings implicate multiple gut microbiome-brain pathways in ageing-associated cognitive decline, including inflammation, neurotransmission, and autophagy, and highlight the potential to predict and prevent cognitive decline through microbiome-targeted strategies.

PMID:40166866 | DOI:10.1093/gerona/glaf053

Fundam Res. 2023 Feb 19;5(1):215-227. doi: 10.1016/j.fmre.2023.01.009. eCollection 2025 Jan.

ABSTRACT

There are critical transition phenomena during the progression of many diseases. Such critical transitions are usually accompanied by catastrophic disease deterioration, and their prediction is of significant importance for disease prevention and treatment. However, predicting disease deterioration solely based on a single sample is a difficult problem. In this study, we presented the network information gain (NIG) method, for predicting the critical transitions or disease state based on network flow entropy from omics data of each individual. NIG can not only efficiently predict disease deteriorations but also detect their dynamic network biomarkers on an individual basis and further identify potential therapeutic targets. The numerical simulation demonstrates the effectiveness of NIG. Moreover, our method was validated by successfully predicting disease deteriorations and identifying their potential therapeutic targets from four real omics datasets, i.e., an influenza dataset and three cancer datasets.

PMID:40166114 | PMC:PMC11955047 | DOI:10.1016/j.fmre.2023.01.009

Plant Cell Environ. 2025 Mar 31. doi: 10.1111/pce.15494. Online ahead of print.

ABSTRACT

As the most prevalent RNA modification in eukaryotes, N6-methyladenosine (m6A) plays a crucial role in regulating various biological processes in plants, including embryonic development and flowering. However, the function of m6A RNA methyltransferase in moso bamboo remains poorly understood. In this study, we identified two m6A methyltransferases in moso bamboo, PheMTA1 and PheMTA2. Overexpression of PheMTA1 and PheMTA2 significantly promoted root development and enhanced salt tolerance in rice. Using the HyperTRIBE method, we fused PheMTA1 and PheMTA2 with ADARcdE488Q and introduced them into rice. RNA sequencing (RNA-seq) of the overexpressing rice identified the target RNAs bound by PheMTA1 and PheMTA2. PheMTA1 and PheMTA2 bind to OsATM3 and OsSF3B1, which were involved in the development of root and salt resistance. Finally, we revealed the effects of transcription or alternative splicing on resistance-related genes like OsRS33, OsPRR73, OsAPX2 and OsHAP2E, which are associated with the observed phenotype. In conclusion, our study demonstrates that the m6A methyltransferases PheMTA1 and PheMTA2 from moso bamboo are involved in root development and enhance plant resistance to salt stress.

PMID:40165397 | DOI:10.1111/pce.15494

Plant Genome. 2025 Jun;18(2):e70023. doi: 10.1002/tpg2.70023.

ABSTRACT

Ascochyta blight (AB) is one of the most devastating fungal diseases of chickpea (Cicer arietinum L.). Conventional breeding has focused on exploiting and introgressing major genes (qualitative effect) to improve AB resistance in released varieties. However, such approaches are time-consuming and prone to the breakdown of disease resistance due to the fast evolution of AB pathogen. Genomic selection (GS) offers a promising alternative by predicting breeding values using genome-wide single nucleotide polymorphisms (SNPs), regardless of major or minor effects. To our knowledge, this is the first study to develop and implement GS to improve AB resistance in chickpea. Over 4 years, 2790 chickpea lines, representing a broad range of germplasm collections primarily sourced from the Australian Grains Genebank, were evaluated for AB disease response in the field and in an outdoor pot-based facility. Plants were genotyped with the Illumina multispecies pulse 30K SNP array, resulting in 23,239 high-quality SNPs distributed across the genome. Intermediate-to-high genomic prediction accuracies (0.40-0.90) were achieved across validation scenarios. Bayesian modeling identified six major QTL explaining 33% of the genetic variance for AB resistance, with the remaining variance explained by minor effect genes. Using genomic estimated breeding values (GEBVs), 462 lines of the 2790 lines were predicted to have higher resistance compared to the released check varieties, revealing the potential of further improvement of AB resistance for the industry. The desirable genomic prediction accuracy obtained in the study supports the applicability of GS to breed for AB resistance in chickpea.

PMID:40164996 | DOI:10.1002/tpg2.70023

bioRxiv [Preprint]. 2025 Mar 15:2025.03.14.643192. doi: 10.1101/2025.03.14.643192.

ABSTRACT

Semilunar Granule Cells (SGCs) are sparse dentate gyrus projection neurons whose role in the dentate circuit, including pathway specific inputs, remains unknown. We report that SGCs receive more frequent spontaneous excitatory synaptic inputs than granule cells (GCs). Dual GC-SGC recordings identified that SGCs receive stronger medial entorhinal cortex and associational synaptic drive but lack short-term facilitation of lateral entorhinal cortex inputs observed in GCs. SGCs dendritic spine density in proximal and middle dendrites was greater than in GCs. However, the strength of commissural inputs and dendritic input integration, examined in passive morphometric simulations, were not different between cell types. Activity dependent labeling identified an overrepresentation of SGCs among neuronal ensembles in both mice trained in a spatial memory task and task naïve controls. The divergence of modality specific inputs to SGCs and GCs can enable parallel processing of information streams and expand the computational capacity of the dentate gyrus.

PMID:40161709 | PMC:PMC11952520 | DOI:10.1101/2025.03.14.643192

bioRxiv [Preprint]. 2025 Mar 16:2025.03.14.643160. doi: 10.1101/2025.03.14.643160.

ABSTRACT

The accurate assignment of transcripts to their cells of origin remains the Achilles heel of imaging-based spatial transcriptomics, despite being critical for nearly all downstream analyses. Current cell segmentation methods are prone to over- and under-segmentation, misassign transcripts to cells, require manual intervention, and suffer from low sensitivity and scalability. We introduce segger, a versatile graph neural network based on a heterogeneous graph representation of individual transcripts and cells, that frames cell segmentation as a transcript-to-cell link prediction task and can leverage single-cell RNA-seq information to improve transcript assignments. On multiple Xenium dataset benchmarks, segger exhibits superior sensitivity and specificity, while requiring orders of magnitude less compute time than existing methods. The user-friendly open-source software implementation has extensive documentation (https://elihei2.github.io/segger_dev/), requires little manual intervention, integrates seamlessly into existing workflows, and enables atlas-scale applications.

PMID:40161614 | PMC:PMC11952575 | DOI:10.1101/2025.03.14.643160

Plant Genome. 2025 Jun;18(2):e70019. doi: 10.1002/tpg2.70019.

ABSTRACT

Groundnut (Arachis hypogaea L.), also known as peanut, is an allotetraploid legume crop composed of two different progenitor sub-genomes. This crop is an important source for food, feed, and confectioneries. Leveraging translational genomics research has expedited the precision and speed in making selections of progenies in several crops through either marker-assisted selection or genomic selection, including groundnut. The availability of foundational genomic resources such as reference genomes for diploid progenitors and cultivated tetraploids, offered substantial opportunities for genomic interventions, including the development of genotyping assays. Here, a cost-effective and high-throughput genotyping assay has been developed with 5,081 single nucleotide polymorphisms (SNPs) referred to as "mid-density assay." This multi-purpose assay includes 5,000 highly informative SNPs selected based on higher polymorphism information content (PIC) from our previously developed high-density "Axiom_Arachis" array containing 58,233 SNPs. Additionally 82 SNPs associated with five resilience and quality traits were included for marker-assisted selection. To test the utility of the mid-density genotyping (MDG) assay, 2,573 genotypes from distinct sets of breeding populations were genotyped with the 5,081 SNPs. PIC of the SNPs in the MDG ranged from 0.34 to 0.37 among diverse sets. The first three principal components collectively explained 82.08% of the variance among these genotypes. The mid-density assay demonstrated a proficient ability to distinguish between the genotypes, offering a high level of genome-wide nucleotide diversity. This assay holds promise for possible deployment in the identification of varietal seed mixtures, genetic purity within gene bank germplasms and seed systems, foreground and background selection in backcross breeding programs, genomic selection, and sparse trait mapping studies in groundnut.

PMID:40164965 | DOI:10.1002/tpg2.70019

Nat Methods. 2025 Mar 31. doi: 10.1038/s41592-025-02643-0. Online ahead of print.

ABSTRACT

Data from the first phase of the Human Tumor Atlas Network (HTAN) are now available, comprising 8,425 biospecimens from 2,042 research participants profiled with more than 20 molecular assays. The data were generated to study the evolution from precancerous to advanced disease. The HTAN Data Coordinating Center (DCC) has enabled their dissemination and effective reuse. We describe the diverse datasets, how to access them, data standards, underlying infrastructure and governance approaches, and our methods to sustain community engagement. HTAN data can be accessed through the HTAN Portal, explored in visualization tools-including CellxGene, Minerva and cBioPortal-and analyzed in the cloud through the NCI Cancer Research Data Commons. Infrastructure was developed to enable data ingestion and dissemination through the Synapse platform. The HTAN DCC's flexible and modular approach to sharing complex cancer research data offers valuable insights to other data-coordination efforts and researchers looking to leverage HTAN data.

PMID:40164800 | DOI:10.1038/s41592-025-02643-0

Commun Biol. 2025 Mar 31;8(1):527. doi: 10.1038/s42003-025-07954-8.

ABSTRACT

Epigenomic mechanisms are critically involved in mediation of genetic and environmental factors that underlie cancer development. Histone modifications represent highly informative epigenomic marks that reveal activation and repression of gene activities and dysregulation of transcriptional control due to tumorigenesis. Here, we present a comprehensive epigenomic and transcriptomic mapping of 18 stage I and II tumor and 20 non-neoplastic tissues from non-small cell lung adenocarcinoma patients. Our profiling covers 5 histone marks including activating (H3K4me3, H3K4me1, and H3K27ac) and repressive (H3K27me3 and H3K9me3) marks and the transcriptome using only 20 mg of tissue per sample, enabled by low-input omic technologies. Using advanced integrative bioinformatic analysis, we uncover cancer-driving signaling cascade networks, changes in 3D genome modularity, differential expression and functionalities of transcription factors and noncoding RNAs. Many of these identified genes and regulatory molecules show no significant change in their expression or a single epigenomic modality, emphasizing the power of integrative multimodal and multiomic analysis using patient samples.

PMID:40164799 | DOI:10.1038/s42003-025-07954-8

Nat Genet. 2025 Mar 31. doi: 10.1038/s41588-025-02134-0. Online ahead of print.

ABSTRACT

Tobacco smoke, alone or combined with alcohol, is the predominant cause of head and neck cancer (HNC). We explore how tobacco exposure contributes to cancer development by mutational signature analysis of 265 whole-genome sequenced HNC samples from eight countries. Six tobacco-associated mutational signatures were detected, including some not previously reported. Differences in HNC incidence between countries corresponded with differences in mutation burdens of tobacco-associated signatures, consistent with the dominant role of tobacco in HNC causation. Differences were found in the burden of tobacco-associated signatures between anatomical subsites, suggesting that tissue-specific factors modulate mutagenesis. We identified an association between tobacco smoking and alcohol-related signatures, indicating a combined effect of these exposures. Tobacco smoking was associated with differences in the mutational spectra, repertoire of driver mutations in cancer genes and patterns of copy number change. Our results demonstrate the multiple pathways by which tobacco smoke can influence the evolution of cancer cell clones.

PMID:40164736 | DOI:10.1038/s41588-025-02134-0

Mol Psychiatry. 2025 Mar 31. doi: 10.1038/s41380-025-02973-7. Online ahead of print.

ABSTRACT

Alzheimer's disease (AD) is a progressive neurodegenerative disorder with a decade-long preclinical pathological period that can be divided into several stages. Emerging evidence has revealed that the microbiota-gut-brain axis plays an important role in AD pathology. However, the role of gut microbiota in different AD stages has not been well characterized. In this study, we performed fecal shotgun metagenomic analysis on a Chinese cohort with 476 participants across five stages of AD pathology to characterize stage-specific alterations in gut microbiota and evaluate their diagnostic potential. We discovered extensive gut dysbiosis that is associated with neuroinflammation and neurotransmitter dysregulation, with over 10% of microbial species and gene families showing significant alterations during AD progression. Furthermore, we demonstrated that microbial gene families exhibited strong diagnostic capabilities, evidenced by an average AUC of 0.80 in cross-validation and 0.75 in independent external validation. In the optimal model, the most discriminant gene families are primarily involved in the metabolism of carbohydrates, amino acids, energy, glycan and vitamins. We found that stage-specific microbial gene families in AD pathology could be validated by an in vitro gut simulator and were associated with specific genera. We also observed that the gut microbiota could affect the progression of cognitive decline in 5xFAD mice through fecal microbiota transplantation, which could be used for early intervention of AD. Our multi-stage large cohort metagenomic analysis demonstrates that alterations in gut microbiota occur from the very early stages of AD pathology, offering important etiological and diagnostic insights.

PMID:40164697 | DOI:10.1038/s41380-025-02973-7

PLoS Comput Biol. 2025 Mar 31;21(3):e1012927. doi: 10.1371/journal.pcbi.1012927. Online ahead of print.

ABSTRACT

Systems vaccinology studies have been used to build computational models that predict individual vaccine responses and identify the factors contributing to differences in outcome. Comparing such models is challenging due to variability in study designs. To address this, we established a community resource to compare models predicting B. pertussis booster responses and generate experimental data for the explicit purpose of model evaluation. We here describe our second computational prediction challenge using this resource, where we benchmarked 49 algorithms from 53 scientists. We found that the most successful models stood out in their handling of nonlinearities, reducing large feature sets to representative subsets, and advanced data preprocessing. In contrast, we found that models adopted from literature that were developed to predict vaccine antibody responses in other settings performed poorly, reinforcing the need for purpose-built models. Overall, this demonstrates the value of purpose-generated datasets for rigorous and open model evaluations to identify features that improve the reliability and applicability of computational models in vaccine response prediction.

PMID:40163550 | DOI:10.1371/journal.pcbi.1012927

J Vis Exp. 2025 Mar 14;(217). doi: 10.3791/67925.

ABSTRACT

Pure bacterial cultures are essential for the study of microbial culturomics. Traditional methods based on solid plates, well plates, and micro-reactors are hindered by cumbersome procedures and low throughput, impeding the rapid progress of microbial culturomics research. To address these challenges, we had successfully developed the Single-cell Microliter-droplet Culture Omics System (MISS cell), an automated high-throughput platform that utilizes droplet microfluidic technology for microbial monoclonal isolation, cultivation, and screening. This system can generate a large number of single-cell droplets and cultivate, screen, and collect monoclonal colonies in a short time, facilitating an integrated process from microbial isolation to picking. In this protocol, we demonstrated its application using the isolation and cultivation of human gut microbiota as an example and compared the microbial isolation efficiency, monoclonal culture performance, and screening throughput using the solid-plate culture method. The experimental workflow was simple, and reagent consumption was very low. Compared to solid-plate culture methods, the MISS cell could cultivate a greater diversity of gut microbiota species, offering significant potential and value for microbial culturomics research.

PMID:40163395 | DOI:10.3791/67925

Adv Sci (Weinh). 2025 Mar 31:e2414918. doi: 10.1002/advs.202414918. Online ahead of print.

ABSTRACT

The early detection of high-risk human papillomavirus (HR-HPV) is crucial for the assessment and improvement of prognosis in cervical cancer. However, existing PCR-based screening methods suffer from inadequate accessibility, which dampens the enthusiasm for screening among grassroots populations, especially in resource-limited areas, and contributes to the persistently high mortality rate of cervical cancer. Here, a portable system is proposed for multiplexed nucleic acid detection, termed R-CHIP, that integrates Recombinase polymerase amplification (RPA), CRISPR detection, Hand-driven microfluidics, and an artificial Intelligence Platform. The system can go from sample pre-processing to results readout in less than an hour with simple manual operation. Optimized for sensitivity of 10-17 M for HPV-16 and 10-18 M for HPV-18, R-CHIP has an accuracy of over 95% in 300 tests on clinical samples. In addition, a smartphone microimaging system combined with the ResNet-18 deep learning model is used to improve the readout efficiency and convenience of the detection system, with initial prediction accuracies of 96.0% and 98.0% for HPV-16 and HPV-18, respectively. R-CHIP, as a user-friendly and intelligent detection platform, has great potential for community-level HR-HPV screening in resource-constrained settings, and contributes to the prevention and early diagnosis of other diseases.

PMID:40163382 | DOI:10.1002/advs.202414918