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PubMed2026

A User-Friendly Protocol for Microinjection into Teleost Embryos to Study Gene Function.

Zebrafish (Danio rerio) and medaka (Oryzias latipes) are popular teleost models used in developmental biology and functional genomics. To achieve high-quality and reproducible microinjections, it is essential to have robust protocols for breeding, egg collection, and the precise delivery of genetic material. In this protocol, we present a comprehensive and optimized methodology for setting up breeding tanks under controlled photoperiod conditions to maximize egg yield while minimizing contamination. We provide detailed procedures for sex identification, pair selection, the use of grated breeding inserts, and methods to increase egg collection efficiency. We outline procedures for making injection gel beds, pulling needles, and calibration using one-microliter microcapillaries to achieve consistent nanoliter-scale injections. Our protocol outlines settings for the pico-liter injector that are optimized to deliver a precise amount per pulse with minimal variability. Finally, we demonstrate the application of these methods for gene knockdown using morpholino antisense oligonucleotides, gene knockout using CRISPR-Cas9, and gain-of-function mRNA overexpression experiments. Phenotypic assessments conducted at various developmental stages to evaluate gene-specific effects reveal consistent phenotypic outcomes between the morpholino and CRISPR-Cas9 approaches. This easy and comprehensive protocol enables efficient, precise, and scalable genetic manipulation of zebrafish and medaka embryos, thereby supporting advanced functional studies in developmental biology and disease modeling. To our knowledge, this is the first unified protocol for both zebrafish and medaka microinjection systems achieving 97.7% phenotype penetrance in CRISPR-Cas9 knockouts with precision together with a triple validation approach that confirms gene function across multiple techniques.

Animals↗
PubMed2026

Genome-wide profiling of histone modifications and transcription factor binding at single-cell resolution by DeChIC-seq.

Mapping of protein-DNA interactions at single-cell resolution remains a central challenge in epigenomics, particularly for transcription factors (TFs), whose sparse binding limits reliable detection. Here, we establish DeChIC-seq (DNA Deaminase-based Chromatin Immuno-Conversion sequencing), a conversion-based strategy that uses a protein A-DddAtox fusion to directly record protein-DNA interactions by inducing localized C-to-U conversions near antibody-bound chromatin. Retaining genome-wide background sequence information without immunoprecipitation, DeChIC-seq enables profiling of histone modifications and sensitive detection of TF binding. Integration with single-cell whole-genome amplification extends DeChIC-seq to single-cell applications (scDeChIC-seq), enabling chromatin profiling of individual cells. Applied to mouse embryogenesis, scDeChIC-seq resolves lineage-specific chromatin states through profiling of H3K4me3, CTCF, and RAD21 and sensitively detects TF binding, including that of NR5A2, TFAP2C, and KLF5, from extremely limited blastomere inputs. This underscores its strong potential for detecting TF-binding sites in scarce biological samples. DeChIC-seq establishes a conversion-based framework for chromatin profiling that enables mechanistic dissection of TF-driven gene regulation across rare cells, developmental systems, and disease contexts.

Animals↗
PubMed2025

Bayesian reconstruction and differential testing of excised introns.

MOTIVATION: Characterizing the differential excision of introns is critical for understanding the functional complexity of a cell or tissue, from normal developmental processes to disease pathogenesis. Most transcript reconstruction methods infer full-length transcripts from high-throughput sequencing data. However, this is a challenging task due to incomplete annotations and the heterogeneous expression of transcripts across cell-types, tissues, and experimental conditions. Several recent methods circumvent these difficulties by considering local splicing events, but these methods lose transcript-level splicing information and may conflate similar, but distinct transcripts. RESULTS: In this work, we formalize a new transcript reconstruction problem that interpolates between the full-length and local splicing perspectives by considering sequences of exon-exon junctions (SEEJs) that co-occur in transcripts. We then present a hierarchical Bayesian admixture model and posterior inference algorithms for computing SEEJs (BSEEJ), and a generalized linear model for characterizing differential SEEJ usage based on model parameter estimates. We show that BSEEJ achieves high F1 score for reconstruction tasks and improved accuracy and sensitivity in differential splicing when compared with six transcript and local splicing methods on simulated data. Lastly, we evaluate BSEEJ on experimental data based on transcript reconstruction, novelty of transcripts produced, model sensitivity to hyperparameters, and a functional analysis of differentially expressed SEEJs. AVAILABILITY AND IMPLEMENTATION: BSEEJ is freely available at https://github.com/bayesomicslab/BSEEJ.

Bayes Theorem↗
PubMed2026

Geometric mechanogenomics: engineering boundary conditions for deterministic cell fate control.

In tissue development and regeneration, cellular behavior has traditionally been interpreted through biochemical signaling frameworks. However, cells exist within physically defined environments, where geometric boundary conditions - including confinement, curvature, anisotropy, and multicellular architecture - define the mechanical state space in which mechanical forces are generated, transmitted, and interpreted. Here, we introduce geometric mechanogenomics, a conceptual framework that positions geometry as an upstream spatial regulator linking tissue-scale boundary conditions to nuclear mechanics, chromatin organization, and genome regulation. We propose a boundary-to-nucleus axis through which geometric information is decoded by adhesion-mediated mechanotransduction, cytoskeletal force transmission, and nuclear mechanoregulation to regulate chromatin accessibility, epigenetic remodeling, and transcriptional programs. Rather than introducing new mechanotransduction pathways, this framework emphasizes that geometry spatially organizes conserved mechanotransductive machinery to generate context-dependent mechanogenomic outcomes. We further discuss how engineered geometries reduce morphogenetic stochasticity, coordinate multicellular organization, and establish mechanical memory that influences long-term cell fate. Finally, we highlight current challenges in establishing predictive geometry-to-genome relationships and discuss emerging opportunities enabled by spatial omics, artificial intelligence-assisted inverse design, and dynamic biomaterials for programmable mechanobiology, regenerative medicine, developmental biology, and disease modeling.

genome organization↗
PubMed2026

A synonymous NPR2 variant causes acromesomelic dysplasia through aberrant pre-mRNA splicing.

Precise regulation of pre-mRNA splicing is essential for normal development, and its disruption represents an important but frequently underrecognized mechanism of human disease. The C-type natriuretic peptide (CNP) receptor NPR2 is a critical regulator of growth plate chondrocyte proliferation and differentiation, and loss-of-function variants in NPR2 cause acromesomelic dysplasia, Maroteaux type (AMDM). Here, we identify a homozygous synonymous NPR2 variant (NM_003995.4:c.2484C > T) in an individual with AMDM and demonstrate its pathogenic mechanism at the RNA level. Although predicted to be silent at the protein level, in silico analysis suggested splice donor gain. Functional analysis using patient-derived leukocyte RNA revealed aberrant splicing leading to partial exon truncation, frameshift, and premature termination of NPR2 which is predicted to trigger nonsense-mediated mRNA decay given its position upstream of multiple downstream exon-exon junctions. Heterozygous family members expressed both normal and aberrant transcripts, whereas the affected individual showed exclusive expression of the aberrant isoform, consistent with a dosage-dependent loss-of-function mechanism. These findings establish aberrant splicing induced by a synonymous variant as a disease-causing mechanism affecting a core developmental signaling pathway. Our study highlights the importance of transcript-level functional analysis in the interpretation of rare variants and underscores the central role of precise RNA processing in skeletal development and human disease.

Humans↗
PubMed2026

Clinical and Functional Characterization of Gain-of-Function ABL1 Variants Expands the Phenotypic Spectrum of CHDSKM.

Germline gain-of-function (GOF) variants in ABL1 cause congenital heart defects and skeletal malformations syndrome (CHDSKM), a multisystem developmental disorder characterized by congenital heart disease, skeletal abnormalities, dysmorphic features, and variable developmental delay. More recently, biallelic loss-of-function variants and ABL haploinsufficiency have been associated with distinct phenotypes, expanding the allelic spectrum of ABL1-related disorders. We report three individuals with ABL1 variants. A female infant with tetralogy of Fallot, critical pulmonary stenosis, covered omphalocele, and a lethal outcome was found by rapid trio genome sequencing to harbor a de novo likely pathogenic ABL1 variant, NM_007313.2:c.354G>T p.(Trp118Cys). We also provide updated clinical follow-up of a previously reported individual and describe a third individual, both carrying the recurrent p.(Tyr245Cys) variant. Functional studies were performed and support a GOF mechanism. Similar activation was observed for Tyr245Cys despite the differences in clinical severity. Our findings expand the phenotypic spectrum of ABL1-related CHDSKM to include severe conotruncal heart disease and covered omphalocele. The comparison of two biochemically activating ABL1 variants demonstrates substantial clinical variability despite a shared molecular mechanism. Furthermore, the overlap between ventral body wall abnormalities in GOF disease and omphalocele associated with ABL1 haploinsufficiency suggests that precise regulation of ABL1 signaling is critical for normal ventral body wall formation.

ABL1↗
PubMed2026

Maternal DNA repair safeguards genome stability during the oocyte-to-embryo transition.

De novo mutations are a major source of genetic variation and disease risk, yet the developmental timing and mechanisms underlying their origin require further investigation. While germ cells have traditionally been considered the primary source of these mutations, increasing evidence suggests that a substantial fraction arise after fertilization. Here, we investigated the role of maternal DNA repair in shaping mutagenesis during this critical window by using a mouse model with oocyte-specific disruption of the homologous recombination factor RAD51 and a combination of cellular and molecular analyses. Loss of maternal RAD51 led to the accumulation of DNA double-strand breaks in oocytes without impairing their growth, meiotic maturation, or fertilization competence. In contrast, embryos derived from RAD51-deficient oocytes exhibited increased DNA damage and developmental delay during early cleavage stages. Whole-genome sequencing revealed a significant increase in de novo variants in offspring, the majority displaying intermediate allele frequencies consistent with post-zygotic mosaic mutations. These findings confirm that maternal DNA repair safeguards genome stability across the oocyte-to-embryo transition and identify early embryogenesis as a major source of de novo mutations, with implications for reproductive biology and the origins of genetic diseases.

DNA↗
PubMed2024

Acute MeCP2 loss in adult mice reveals transcriptional and chromatin changes that precede neurological dysfunction and inform pathogenesis.

Mutations in the X-linked methyl-CpG-binding protein 2 (MECP2) gene cause Rett syndrome, a severe childhood neurological disorder. MeCP2 is a well-established transcriptional repressor, yet upon its loss, hundreds of genes are dysregulated in both directions. To understand what drives such dysregulation, we deleted Mecp2 in adult mice, circumventing developmental contributions and secondary pathogenesis. We performed time series transcriptional, chromatin, and phenotypic analyses of the hippocampus to determine the immediate consequences of MeCP2 loss and the cascade of pathogenesis. We find that loss of MeCP2 causes immediate and bidirectional progressive dysregulation of the transcriptome. To understand what drives gene downregulation, we profiled genome-wide histone modifications and found that a decrease in histone H3 acetylation (ac) at downregulated genes is among the earliest molecular changes occurring well before any measurable deficiencies in electrophysiology and neurological function. These data reveal a molecular cascade that drives disease independent of any developmental contributions or secondary pathogenesis.

Animals↗
PubMed2026

Phytoplasma-plant interactions: effector-mediated host reprogramming, hormonal crosstalk, metabolic alterations and plant-mediated vector manipulation.

Phytoplasmas are wall-less, phloem-restricted bacterial pathogens that infect over 1,000 plant species, causing substantial losses in agriculture, horticulture, and forestry worldwide. Despite their reduced genomes and limited metabolic autonomy, these obligate parasites colonize diverse hosts through secreted effector proteins that extensively reprogram plant development, metabolism, immune signalling, and vector interactions. Advances in genomics, transcriptomics, proteomics, metabolomics, and functional studies have substantially clarified the molecular basis of phytoplasma pathogenicity and symptom development. This review synthesizes current understanding of phytoplasma-plant interactions, covering phytoplasma biology, genome evolution, and the infection cycle across plant and insect vector hosts. We examine the molecular functions of key effectors, SAP11, SAP54/PHYL1, SAP05, TENGU, SWP1, and recently identified virulence factors, focusing on how they target host transcription factors, phytohormone networks, protein degradation pathways, and immune responses to promote colonization and disease progression. We further discuss how phytoplasma infection disrupts phytohormone signalling, primary and secondary metabolism, and developmental programs to produce characteristic disease symptoms, with particular attention to pathogen-induced changes in host volatiles and nutritional quality that alter vector behaviour and enhance transmission. Finally, we summarize insights from multi-omics studies and emerging management strategies, including CRISPR-based genome editing, RNAi, rapid molecular diagnostics, resistant cultivars, microbiome-based approaches, and sustainable vector control, and highlight key knowledge gaps and priorities for developing effective, environmentally sustainable phytoplasma disease management.

Phytoplasma↗
PubMed2026

Predictive Models for Hypoglycemia Risk in Haemodialysis Patients With Diabetic Kidney Disease: Systematic Review and Meta-Analysis.

AIM: To provide evidence for selecting and developing reliable clinical assessment tools for hypoglycemia in diabetic kidney disease patients during haemodialysis. DESIGN: Review. METHODS: Systematic searches were performed in 9 Chinese and English databases to collect literature regarding the development of hypoglycemia risk prediction models in haemodialysis patients with diabetic kidney disease. Two reviewers independently performed literature screening, data extraction, risk-of-bias assessment, and applicability evaluation. The Prediction Model Risk of Bias Assessment Tool was used to assess the risk of bias and applicability of the included studies. Meta-analysis was conducted using R software. DATA SOURCES: CNKI, Wanfang, VIP, CBM, PubMed, Cochrane Library, EMbase, Web of Science, and CINAHL. The search period covered from the establishment date of each database to December 2025. RESULTS: Six studies, comprising six prediction models, were included. Two studies performed internal validation, and three conducted external validation. All models reported the area under the curve, ranging from 0.813 to 0.866, and calibration measures. Four studies were rated as having a high risk of bias, while all six demonstrated good overall applicability. The meta-analysis showed that the pooled AUC value of the six studies was 0.846 (95% CI: 0.823-0.867). CONCLUSION: Research on hypoglycemia risk prediction models in haemodialysis patients with diabetic kidney disease remains in the developmental stage. Although the included prediction models exhibited satisfactory apparent discriminatory ability and clinical applicability, most of the original studies suffered from a high risk of bias and lacked adequate validation. The true predictive performance and clinical application value of these models remain to be further verified. Accordingly, routine and unconditional clinical application is not recommended at this stage. Future studies should include more high-quality, multicenter external validation and develop models with high generalizability, favourable clinical applicability, and robust predictive performance to facilitate early identification of hypoglycemia risk in this population. IMPACT: This study systematically evaluated the hypoglycemia risk prediction models for diabetic kidney disease patients during haemodialysis, and the research on hypoglycemia risk prediction models for maintenance haemodialysis patients during dialysis is still in the development stage. This study provides a reference for clinical medical staff to select or develop hypoglycemia risk prediction and assessment tools for diabetic kidney disease patients during haemodialysis. REPORTING METHOD: This study was conducted in accordance with the relevant guidelines of the EQUATOR Network and followed the TRIPOD-SRMA Checklist. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution. TRIAL REGISTRATION: PROSPERO: CRD420251243352.

Humans↗
PubMed2024

The effect of low birth weight as an intrauterine exposure on the early onset of sarcopenia through possible molecular pathways.

Sarcopenia, a musculoskeletal disease characterized by the progressive loss of skeletal muscle mass, strength, and physical performance, presents significant challenges to global public health due to its adverse effects on mobility, morbidity, mortality, and healthcare costs. This comprehensive review explores the intricate connections between sarcopenia and low birth weight (LBW), emphasizing the developmental origins of health and disease (DOHaD) hypothesis, inflammatory processes (inflammaging), mitochondrial dysfunction, circadian rhythm disruptions, epigenetic mechanisms, and genetic variations revealed through genome-wide studies (GWAS). A systematic search strategy was developed using PubMed to identify relevant English-language publications on sarcopenia, LBW, DOHaD, inflammaging, mitochondrial dysfunction, circadian disruption, epigenetic mechanisms, and GWAS. The publications consist of 46.2% reviews, 21.2% cohort studies, 4.8% systematic reviews, 1.9% cross-sectional studies, 13.4% animal studies, 4.8% genome-wide studies, 5.8% epigenome-wide studies, and 1.9% book chapters. The review identified key factors contributing to sarcopenia development, including the DOHaD hypothesis, LBW impact on muscle mass, inflammaging, mitochondrial dysfunction, the influence of clock genes, the role of epigenetic mechanisms, and genetic variations revealed through GWAS. The DOHaD theory suggests that LBW induces epigenetic alterations during foetal development, impacting long-term health outcomes, including the early onset of sarcopenia. LBW correlates with reduced muscle mass, grip strength, and lean body mass in adulthood, increasing the risk of sarcopenia. Chronic inflammation (inflammaging) and mitochondrial dysfunction contribute to sarcopenia, with LBW linked to increased oxidative stress and dysfunction. Disrupted circadian rhythms, regulated by genes such as BMAL1 and CLOCK, are associated with both LBW and sarcopenia, impacting lipid metabolism, muscle mass, and the ageing process. Early-life exposures, including LBW, induce epigenetic modifications like DNA methylation (DNAm) and histone changes, playing a pivotal role in sarcopenia development. Genome-wide studies have identified candidate genes and variants associated with lean body mass, muscle weakness, and sarcopenia, providing insights into genetic factors contributing to the disorder. LBW emerges as a potential early predictor of sarcopenia development, reflecting the impact of intrauterine exposures on long-term health outcomes. Understanding the complex interplay between LBW with inflammaging, mitochondrial dysfunction, circadian disruption, and epigenetic factors is essential for elucidating the pathogenesis of sarcopenia and developing targeted interventions. Future research on GWAS and the underlying mechanisms of LBW-associated sarcopenia is warranted to inform preventive strategies and improve public health outcomes.

Humans↗
PubMed2025

De novo rare EMX2 variants lead to idiopathic hypogonadotropic hypogonadism.

PURPOSE: The genetic etiology of infertility remains unknown. To identify genes for human infertility, we applied a de novo variant analysis in 142 parent-proband trios with idiopathic hypogonadotropic hypogonadism (IHH), an infertility disorder caused by gonadotropin-releasing hormone (GnRH) deficiency. METHODS: Rare de novo copy-number and single-nucleotide variants (CNVs and SNVs) were called from exome sequencing data of the IHH trios. An association study of common EMX2 variants and disease outcomes was performed in the Massachusetts General Brigham Biobank (N = 65,253). GnRH neuronal development and migration was studied in organotypic explants with knocked down of Emx2 and in a mouse model lacking Emx2. RESULTS: We identified that the gene EMX2 harbored both rare de novo CNVs and SNVs. Rare de novo EMX2 variants led to IHH, developmental delay, and hearing loss. Common EMX2 variants were linked to infertility, Parkinson disease, and hearing loss. Knockdown of Emx2 in nasal explants resulted in attenuated GnRH cell migration and GnRH cells were confined to nasal regions of Emx2 knockout (KO) mice, consistent with IHH pathogenesis. CONCLUSION: By utilizing a de novo variant analysis and cellular assays, EMX2 was uncovered as a gene for human infertility.

Humans↗
PubMed2026

Accurately Deciphering Tissue Heterogeneity From Spatial Multi-Modal and Multi-Omics With STransformer.

Advances in spatially resolved technologies enable the simultaneous acquisition of diverse data modalities within a tissue slice while preserving critical spatial context, which presents unprecedented opportunities to decipher intricate tissue heterogeneity. However, existing computational approaches lack the intrinsic flexibility to universally process both spatial multi-modal and multi-omics data. Here, we introduce STransformer, a unified deep learning framework designed to seamlessly accommodate a comprehensive landscape of spatial data. By simultaneously capturing short-range cellular interactions and tissue-wide semantic patterns, it extracts robust representations to accurately dissect complex tissue heterogeneity. Systematic evaluations across diverse species, tissue types, and data modalities highlight its profound versatility. For spatial multi-modal data, STransformer delineates intricate anatomical structures in the human cortex, uncovers pathological mechanisms in Alzheimer's disease, and characterizes dynamic spatiotemporal developmental trajectories during chicken cardiogenesis. Scaling to spatial multi-omics data, STransformer synergizes spatial transcriptomic and proteomic profiles to decipher intricate immune microenvironments within the human tonsil, and jointly analyzes spatial epigenomic and transcriptomic data to infer regulatory mechanisms in the mouse embryonic brain. Consequently, STransformer serves as a highly versatile and robust analytical framework for advancing our understanding of tissue heterogeneity and disease pathogenesis.

Multiomics↗
PubMed2025

Obstacles in quantifying A-to-I RNA editing by Sanger sequencing.

Adenosine-to-Inosine (A-to-I) RNA editing is the most prevalent type of RNA editing, in which adenosine within a completely or largely double-stranded RNA (dsRNA) is converted to inosine by deamination. RNA editing was shown to be involved in many neurological diseases and cancer; therefore, detection of A-to-I RNA editing and quantitation of editing levels are necessary for both basic and clinical biomedical research. While high-throughput sequencing (HTS) is widely used for global detection of editing events, Sanger sequencing is the method of choice for precise characterization of editing site clusters (hyper-editing) and for comparing levels of editing at a particular site under different environmental conditions, developmental stages, genetic backgrounds, or disease states. To detect A-to-I editing events and quantify them using Sanger sequencing, RNA samples are reverse transcribed, cDNA is amplified using gene-specific primers, and then sequenced. The chromatogram outputs are then compared to the genomic DNA sequence. As editing occurs in the context of dsRNA, the reverse transcription step is performed at a temperature as high as 65 °C, using thermostable reverse transcriptase to open double-stranded structures. However, this measure alone is insufficient for transcripts possessing long stems comprised of hundreds of nucleotide pairs. Consequently, the editing levels detected by Sanger sequencing are significantly lower than those obtained by HTS, and the amplification yield is low. We suggest that the reverse transcription is biased towards unedited transcripts, and the severity of the bias is dependent on the transcript's secondary structure. Here, we show how this bias can be significantly reduced to allow reliable detection of editing levels and sufficient product yield.

RNA Editing↗
PubMed2026

Asparagine Synthetase Deficiency: Neuropathological Evidence of Disrupted Cortical Development.

Asparagine synthetase deficiency (ASNSD) is a rare metabolic disease causing congenital microcephaly, severe developmental delay, and spastic quadriplegia. Although the central nervous system is severely affected, other organ systems appear unaffected by asparagine deficiency. We present an infant homozygous for the mutation c.904-1G>A in the ASNS gene, whose clinical presentation and radiological findings were typical for ASNSD. Following the patient's death at the age of 6 months, histological and immunohistochemical examination of the telencephalon revealed a vast disturbance of migration of neuronal subpopulations, consequently severe disorganization of cortical layers, and thinning of the cerebral cortex. These findings provide novel insights into disease pathogenesis and may explain the hallmark features of ASNSD, including microcephaly and epilepsy.

ASNS gene↗
PubMed2026

High-Content CRISPR Screening: Methods and Applications.

Clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 screening has become a central technology in functional genomics, enabling genome-scale interrogation via pooled perturbations. Early CRISPR screens employed survival or simple phenotypic readouts to identify essential genes and drug resistance mechanisms. However, as biological questions have shifted toward understanding regulatory networks, cellular heterogeneity, and context-dependent gene functions, there has been increasing demand for screening strategies capable of capturing complex cellular phenotypes beyond cell fitness. Recent advances in single-cell sequencing, high-content imaging, and spatial transcriptomics have expanded the resolution of CRISPR screening by enabling multidimensional phenotypic characterization following genetic perturbation. By integrating pooled perturbations with diverse readouts, these approaches systematically map targeted gene edits to transcriptional states, cellular phenotypes, and microenvironmental contexts. Meanwhile, innovations in library design, delivery, and computational pipelines have further improved the robustness and interpretability of high-content screening platforms. This review synthesizes the methodological evolution of CRISPR screening, emphasizing advances in perturbation strategies, delivery systems, and multimodal readouts. Representative applications spanning oncology, immunotherapy, developmental biology, neurobiology, and infectious diseases are delineated to demonstrate refined gene network annotations. Additionally, existing technical bottlenecks, such as scalability, cost constraints, and in vivo limitations, are critically assessed. Finally, future directions are proposed to facilitate the development of precise medicine.

CRISPR screening↗
PubMed2026

Are there any common effects in preclinical models of micro- and nanoplastic (MNP) exposure? A systematic review.

Micro- and nanoplastics (MNPs) are emerging contaminants detected in food sources and the marine food chain, raising concerns about human health. Although no causal relationship has been established between MNP exposure and specific diseases, growing evidence suggests adverse developmental, behavioral, cognitive and biochemical effects. This systematic review synthesized evidence from common preclinical neurotoxicology models, including C. elegans, D. rerio, D. melanogaster, in vitro systems and rodents, to identify convergent developmental, behavioral and biochemical outcomes. The protocol was preregistered in OSF, followed PRISMA-P guidelines, applied PICOS criteria, and assessed methodological quality using the European Commission's ToxRTool. Overall, 185 studies were included. Consistent findings showed impaired survival and disrupted development across all models. Behavioral alterations affecting anxiety, memory, learning, sociability and locomotor activity were also consistently reported. In addition, numerous studies identified disruptions in the serotonergic (5-HT) system, including changes in neurotransmitter levels, transporters and metabolic enzymes. Despite methodological heterogeneity, these findings indicate that MNP exposure produces reproducible neurodevelopmental and neurochemical alterations across experimental models. Future studies should improve methodological harmonization, strengthen cross-model comparability and identify robust biomarkers and key mechanisms underlying MNP-induced neurotoxicity, facilitating translation to human health risk assessment frameworks.

Animals↗
PubMed2025

Predicting emergent phenotypes from single cell populations using CELLECTION.

Biological systems exhibit emergent phenotypes that arise from the collective behavior of individual components, such as whole-organ functions that arise from the coordinated activity of its individual cells, or organism-level phenotypes that result from the functional interplay of collections of genes in the genome. We present CELLECTION, a deep learning framework that learns to associate subgroups of instances with different emergent phenotypes. We show CELLECTION enables interpretable predictions for heterogeneous tasks, including disease classification, identification of disease-associated cell subtypes, alignment of developmental stages between human model systems, and even predicting relative hand-wing indices across the avian lineage. CELLECTION therefore provides a scalable and flexible framework for identifying key cellular or genetic signatures underlying complex traits in development, disease, and evolution.

Journal Article↗