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Artificial intelligence (AI) uses in stereotactic radiosurgery (SRS): diagnosis with brain metastasis (BM) - A systematic review.

BACKGROUND: Brain metastases (BM) are the most common intracranial tumors in adults, and stereotactic radiosurgery (SRS) has become a mainstay of management. However, several diagnostic challenges persist in the SRS pathway, particularly the differentiation of radiation necrosis (RN) from true tumor progression, which conventional MRI and even advanced imaging techniques often cannot reliably resolve. Recent advances in artificial intelligence (AI) offer the potential to address these diagnostic limitations. This systematic review synthesizes current literature on AI applications for MRI-based diagnostic decision support in BM patients undergoing SRS, with a focus on radiomics and deep learning tools for distinguishing RN from progression, classifying molecular and histologic subtypes, and predicting treatment response. METHODS: A systematic review was performed in accordance with PRISMA guidelines. PubMed, Web of Science, and Scopus were searched using a targeted query combining terms related to AI, brain metastasis, diagnosis or imaging, and SRS. After screening 483 records and applying strict inclusion and exclusion criteria, 18 studies published between 2015 and 2025 were included. Data were extracted on study design, cohort characteristics, imaging modality, AI methodology, validation strategy, and reported diagnostic performance. RESULTS: Among the 18 included studies, AI models demonstrated strong performance across diagnostic tasks in the BM-SRS pathway. The differentiation of RN from true tumor progression was the most extensively studied application, addressed by 14 of 18 studies, with reported AUCs ranging from 0.71 to 0.94. Support vector machines, random-forest ensembles, convolutional neural networks, and transformer-based multimodal architectures were widely used. The literature evolved from single-sequence radiomic classifiers in 2018 to multimodal deep learning frameworks fusing imaging with clinical and genomic data in 2025. Contrast-enhanced T1-weighted MRI was the dominant imaging input, and texture-based radiomic features (GLCM, GLSZM, GLDM, and wavelet-derived features) were the most consistently predictive. The highest-performing models reached AUCs of 0.85-0.91 through multimodal integration of imaging with clinical and genomic features, and consistently outperformed expert neuroradiologist read on matched cases. Remaining studies addressed longitudinal segmentation-based detection of local failure and adverse radiation effects, BRAF mutation status in melanoma BM, early Gamma Knife treatment response, and primary tumor histology classification, with more variable performance. CONCLUSION: AI models, particularly those integrating MRI-derived radiomic features with clinical and genomic data, show high accuracy in supporting diagnostic decisions for BM patients treated with SRS. The post-SRS differentiation of radiation necrosis from true tumor progression has reached the greatest level of maturity and is closest to clinical translation, with potential to reduce unnecessary biopsies, personalize surveillance intervals, and rationalize treatment-pathway decisions. Other diagnostic applications, including molecular subtyping and primary tumor histology classification, remain exploratory and require further multicenter validation. Integration of AI tools into multidisciplinary tumor-board workflows, combined with prospective validation and standardized reporting, will be essential to realize the full clinical benefits of AI in SRS for brain metastases.

Humans

Activity shapes large herbivores' ecological influences.

The ecological effects of large herbivores are shaped by their spatial and temporal patterns of activity (i.e. where, when and how intensely they use specific locations). When large herbivores' ecological influences are perceived to be undesirable, the traditional approach has been to reduce their population size. This numbers-first logic assumes that ecological effects scale primarily with abundance. We argue that this framing provides an incomplete understanding of large herbivores' ecological impacts. Using African elephants (Loxodonta africana) as a well-documented case study, we show that ecological effects on plants, animals and ecosystem processes correlate more with spatio-temporal patterns of activity than with population size. In large, open systems characterized by strong gradients of water availability, forage quality, shade and risk, elephants concentrate into predictable hotspots while relaxing activity elsewhere, generating localized impacts and opportunities for recovery. By contrast, in small, fenced or fragmented landscapes, where movements are constrained, and gradients are weak, spatial self-regulation breaks down, producing homogenized use and widespread ecological effects. We contend that understanding where, when and under what constraints herbivores use space provides a more general and mechanistic basis for interpreting ecological influence than abundance alone, with implications that extend beyond elephants to large herbivores globally.

Animals

Wedge tarsectomy using patient specific instrumentation for complex multiplanar foot deformity Reconstruction: A prospective case series.

BACKGROUND: Bony correction in complex cavovarus deformities is often multiplanar. We examine our results following wedge tarsectomy (WT) using patient-specific instrumentation (PSI). METHODS: This single-centre, prospective case series evaluated noncorrectable cavovarus feet undergoing PSI-guided WT. Accuracy of PSI guides/plans, operative duration, and adjunctive procedures were recorded. Weightbearing CT (WBCT) measurements and PROM scores were recorded preoperatively and postoperatively, with 1 year follow-up. Data was then statistically analysed. RESULTS: Eleven patients were included. Planned correction was achieved (two required minor intraoperative adjustments to the initial osteotomy and nine required adjunctive procedures). Mean operative time was 135 min. Postoperative improvements were significant radiologically and in MOxFW walking distance. All fused by 3 months, with no significant complications. CONCLUSION: PSI-guided wedge tarsectomy safely achieves predictable multiplanar corrections. Our unit's experience has been excellent, with improvement in patients' walking, particularly with larger deformity corrections. LEVEL OF EVIDENCE: Level IV, prospective case series.

Humans

Association between anaemia and osteoporosis: a systematic review and meta-analysis.

BACKGROUND: Osteoporosis significantly impacts global morbidity. Recent evidence suggests anaemia may contribute to osteoporosis risk. This systematic review and meta-analysis investigates this association. METHODS: PubMed, Scopus, EBSCO, and ScienceDirect were searched for papers. Studies with definition of anaemia and assessing osteoporosis outcomes were included. Meta-analysis utilized random-effects models (DerSimonian-Laird method), and study quality was assessed via Newcastle-Ottawa Scale (NOS). Analyses were performed using R Studio. RESULT: Eighteen studies (861,540 participants) were analyzed. Anaemia significantly increased osteoporosis risk in univariate analysis (OR 1.62; 95% CI 1.33-1.98; p&#x2009;<&#x2009;0.001), despite high heterogeneity (I2 = 92.7%). The results remain significant in studies that reported multivariate analysis (OR 2.01; 95% CI 1.26-3.21; p&#x2009;=&#x2009;0.004). Sensitivity analyses confirmed the robustness of our result. CONCLUSION: Anaemia significantly associated with osteoporosis, emphasizing the need for targeted screening in anaemic individuals. Further studies should consider incorporating anaemia into osteoporosis and fracture prediction tools.

Humans

Performance of AI-Based Screening Tools for Obstructive Sleep Apnea Across Apnea-Hypopnea Index Thresholds: Systematic Review and Meta-Analysis.

BACKGROUND: Obstructive sleep apnea (OSA) is highly prevalent but remains substantially underdiagnosed. Polysomnography (PSG) is the reference standard, but its cost and limited availability constrain large-scale case identification. AI-based screening tools may support risk stratification and referral prioritization, but their diagnostic accuracy across apnea-hypopnea index (AHI) thresholds remains uncertain. OBJECTIVE: This review aimed to systematically evaluate the diagnostic accuracy of AI-based OSA screening tools at AHI thresholds of &#x2265;5, &#x2265;15, and &#x2265;30 events/hour, with emphasis on models using non-PSG-derived inputs. METHODS: PubMed, Embase, Scopus, and Web of Science were searched for studies published from January 1, 2016, to May 3, 2026. Eligible studies included adults evaluated for suspected OSA or recruited from population-based cohorts, assessed AI-based models intended or interpretable for OSA screening, risk prediction, or screening-oriented severity classification, used PSG as the reference standard, and reported sufficient data to construct or reconstruct 2&#xd7;2 contingency tables. Diagnostic accuracy was synthesized separately by AHI threshold and input source using bivariate random-effects models, with 95% CIs and prediction intervals (PIs). Risk of bias and certainty of evidence were assessed using QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies 2) and GRADE (Grading of Recommendations Assessment, Development, and Evaluation), respectively. RESULTS: A total of 60 studies were included, of which 47 contributed data to the meta-analysis. At AHI thresholds of &#x2265;5, &#x2265;15, and &#x2265;30 events/hour, pooled sensitivities were 0.94 (95% CI 0.92-0.96; 95% PI 0.71-0.99), 0.87 (95% CI 0.84-0.89; 95% PI 0.66-0.96), and 0.83 (95% CI 0.79-0.87; 95% PI 0.61-0.94), respectively; the corresponding specificities were 0.77 (95% CI 0.69-0.84; 95% PI 0.30-0.96), 0.81 (95% CI 0.75-0.85; 95% PI 0.39-0.96), and 0.91 (95% CI 0.87-0.94; 95% PI 0.55-0.99), respectively. The corresponding areas under the summary receiver operating characteristic curves were 0.943, 0.907, and 0.920. For non-PSG-derived tools, sensitivities were 0.92, 0.85, and 0.81, and specificities were 0.70, 0.74, and 0.85 at the 3 thresholds, respectively. For PSG-derived models, sensitivities were 0.96, 0.90, and 0.85, and specificities were 0.82, 0.88, and 0.96, respectively. Exploratory subgroup analyses suggested performance variation across selected study and model characteristics, including region, algorithmic framework, data source, and validation method. CONCLUSIONS: AI-based tools showed generally favorable screening performance for OSA across clinically relevant AHI thresholds, although wide PIs suggest variable performance across future comparable populations and settings. By synthesizing diagnostic accuracy across 3 AHI thresholds and distinguishing non-PSG-derived from PSG-derived models, this review extends previous broad or modality-specific reviews and offers a clinically interpretable, pathway-specific basis for linking model performance to intended use. The findings may clarify potential roles for non-PSG-derived tools in front-end screening and referral prioritization and for PSG-derived models in reduced-channel assessment and sleep-laboratory workflow support. Given substantial heterogeneity, limited external validation, and low or very low certainty of evidence, prospective validation is needed before routine implementation.

Humans

Insights from expert panels on the EU clinical evaluation consultation procedure.

BACKGROUND: The Clinical Evaluation Consultation Procedure (CECP) under the EU Medical Device Regulation aims to strengthen and harmonize the assessment of high-risk medical devices. This review summarizes early insights from expert panels to support improved clinical evaluation practices. RESEARCH DESIGN AND METHODS: This review analyses 34 expert panel opinions derived from 281 CECP submissions between April 2021 and December 2025. Statements from opinions were systematically extracted, de-duplicated, and grouped into thematic categories, with independent review and validation. The analysis focuses on common challenges found during the consultation procedure of the expert panels on the content of the clinical assessment in relation to clinical evidence, benefit-risk assessment, intended purpose alignment, and post-market clinical follow-up planning. RESULTS: Expert panel findings highlight recurrent issues in the sufficiency, consistency, and transparency of clinical evidence, underscoring the need for improved standardization and clearer guidance. CONCLUSIONS: Strengthening documentation quality and alignment across stakeholders will enhance the robustness, efficiency, and predictability of conformity assessments for high-risk medical devices.

Humans

Symptoms and treatment response to florensocatib and inhaled tobramycin in bronchiectasis: Post hoc analysis of two randomized trials.

Inhaled antibiotics and DPP-1 inhibitors improve clinical outcomes in bronchiectasis, but whether baseline symptom burden predicts differential treatment responses remains unclear. In this post hoc analysis of two multicenter randomized trials (SAVE-BE, n = 224; TORNASOL, n = 357), we evaluate the association between baseline Quality of Life-Bronchiectasis Respiratory Symptom Scale (QoL-B-RSS) and treatment effects of florensocatib and inhaled tobramycin. In SAVE-BE, florensocatib reduces exacerbation rates versus placebo (relative risk [RR], 0.47; 95% confidence interval [CI], 0.33-0.67; p < 0.0001), with RRs of 0.53 and 0.40 observed in patients with high and low symptom burdens, respectively, but no significant symptomatic improvement. In TORNASOL, tobramycin produces clinically meaningful QoL-B-RSS improvements (exceeding the 8-point cutoff in high-symptom patients) and ameliorates bronchitic symptoms, with greater benefits in those with higher baseline symptom burden. These hypothesis-generating findings suggest that baseline symptom burden may identify differential responses to anti-inflammatory versus anti-infective therapies in bronchiectasis and support its potential as a simple, practical stratification tool to guide personalized treatment.

Humans

Advanced mitigation strategies for acrylamide formation in foods: Mechanistic insights, emerging innovations, and future perspectives.

Acrylamide is a heat-induced contaminant formed predominantly in carbohydrate-rich foods during high-temperature processing, posing significant concerns due to its potential carcinogenic, neurotoxic, and genotoxic effects. This review critically examines the mechanisms of acrylamide formation, emphasizing the role of the Maillard reaction and key precursors such as asparagine and reducing sugars, along with the influence of processing conditions including temperature, time, pH, and moisture. Various mitigation strategies are comprehensively discussed, ranging from raw material selection and genetic approaches to enzymatic treatments such as asparaginase and the application of natural and chemical inhibitors. Advances in processing technologies, including optimization of conventional thermal methods and emerging non-thermal techniques such as cold plasma and ultrasound, are evaluated for their effectiveness. The review also highlights the role of food additives, functional ingredients, and fermentation in reducing acrylamide formation. Furthermore, recent developments in analytical techniques, including chromatographic methods, biosensors, and artificial intelligence-based predictive models, are explored for improved detection and control. Risk assessment, toxicological implications, and global regulatory frameworks are also examined. Finally, future perspectives focusing on genetic engineering, personalized nutrition, and digital technologies such as AI and blockchain are discussed to support sustainable and industry-applicable mitigation strategies.

Acrylamide

LitCTL1: A novel C-type lectin involved in the mucosal and cellular immunity of the common periwinkle Littorinalittorea.

C-type lectins (CTLs) are vital pattern-recognition receptors (PRRs) that mediate innate immune responses in mollusks, yet their characterization in Caenogastropoda, the largest gastropod group, remains limited. This study characterizes LitCTL1, a novel secreted single-domain C-type lectin from the common periwinkle, Littorina littorea. The 199-amino acid polypeptide contains a conserved carbohydrate recognition domain with canonical QPD and WND motifs and is predicted to form a homodimer. Uniquely, LitCTL1 was localized in both circulating hemocytes and mucus-secreting epithelial cells of the foot, mantle, and hypobranchial gland - the first report of such dual localization for a molluscan lectin, linking systemic and mucosal defense. Expression analysis revealed that LitCTL1 is constitutively expressed in hemocytes. Functional assays with recombinant LitCTL1 demonstrated its role as a potent opsonin with hemagglutinating activity, significantly enhancing hemocyte spreading and the phagocytosis of zymosan. Genomic analysis reveals that LitCTL1 belongs to a rapidly diversifying, genus-specific expansion distinct from conserved perlucin-like lineages. These results identify LitCTL1 as a key effector molecule in both systemic and mucosal innate immunity, likely reflecting an evolutionary adaptation to the microbial challenges of the intertidal environment.

Animals

Genome-wide identification and characterization of ABC transporters and their expression in response to saline-alkaline stress and WSSV infection in Fenneropenaeus chinensis.

ATP-binding cassette (ABC) transporters play crucial roles in stress responses across organisms, yet their functions in Fenneropenaeus chinensis remain largely unknown. In this study, we identified 42 FcABC genes (FcABCs) in the F. chinensis genome and analyzed their phylogenetic relationships, gene structures, and chromosomal distributions. Phylogenetic analysis grouped the FcABCs into eight subfamilies (ABCA-ABCH), with conserved motif and domain compositions within each subfamily. Expression analysis showed that several FcABC genes, including FcABCG5, FcABCA1, and FcABCC3, were significantly induced under saline-alkaline stress in gill and hepatopancreas tissues. In contrast, most FcABCs were downregulated after WSSV challenge, though a subset (e.g., FcABCB1, FcABCC1) exhibited early upregulation. Functional validation via RNA interference demonstrated that knockdown of FcABCG5 increased shrimp mortality under saline-alkaline stress. Cis-regulatory element analysis revealed an enrichment of stress- and immune-related elements in FcABC promoters. Protein-protein interaction network predictions indicated potential roles for FcABCs in cholesterol metabolism and organic anion transport. Our findings provide insights into the roles of FcABC genes in stress adaptation and immune defense, offering candidate genes for the breeding of stress-resistant shrimp varieties.

Animals

Longitudinal associations between family factors and the neurodevelopmental and psychosocial outcomes of children with congenital heart disease: A systematic review.

Family factors have been gaining increased attention in understanding adverse neurodevelopmental and psychosocial outcomes for children with congenital heart disease (CHD). To clarify relevance, we undertook a systematic review of only longitudinal studies which assessed such associations. Comparisons with the contribution of disease/surgical factors were also made where included studies considered such. We included longitudinal studies which assessed dynamic family factors (e.g. parent mental health, attachment, family functioning) and later child outcomes. Searches were conducted across CINAHL, Medline-Pubmed, PsychInfo and SCOPUS Web of Science. The NIH Quality Assessment Tool was used to evaluate study quality and risk of bias. Eighteen studies, utilizing data from 11 study samples and 2109 participants, met inclusion criteria. These studies included samples from infancy, with follow-up periods stretching into young adulthood, and with various degrees of CHD severity. The quality of studies was "good" to "fair", with key limitations of attrition and limited sociocultural diversity in samples. Findings suggested that family factors predicted later child psychosocial outcomes and more consistently than severity of disease indicators. This contrasted with a much smaller number of studies examining family factors and child neurodevelopmental outcomes, where no reliable conclusions could be reached. Findings highlight the importance of screening and family focused interventions for this population.

Child

A Multi-omics Regulated Cell Death Framework Defines Immune Phenotypes and Guides Precision Therapy in Colorectal Cancer.

Colorectal cancer (CRC) is molecularly and immunologically heterogeneous, contributing to variable treatment response. Because regulated cell death (RCD) intersects with tumor metabolism, immune regulation, and therapeutic susceptibility, we built an RCD-centered framework for CRC stratification. Multi-cohort transcriptomic data were used to infer RCD subtypes with non-negative matrix factorization (NMF) and non-negative least squares (NNLS). Genomic, bulk RNA-seq, single-cell RNA-seq, and spatial transcriptomic datasets were integrated to characterize subtype-associated biology. Machine-learning models were developed for immunotherapy response and survival-risk estimation. Candidate compounds were screened by GDSC2-based drug-sensitivity modeling and molecular docking, and FSTL3 was functionally assessed in vitro. The framework separated CRC samples into two RCD-related phenotypes resembling immune-hot and immune-cold states. RCD1 showed immune activation and higher mutational burden, whereas RCD2 showed immune-suppressed features, intratumoral heterogeneity, and aggressive biology. RCD-associated signatures showed potential for predicting immunotherapy response and survival risk. Dasatinib was prioritized for immune-cold, high-risk tumors, with preliminary evidence supporting its activity in CRC cells, while functional assays suggested a role for FSTL3 in growth, invasion, epithelial-mesenchymal transition, and apoptosis regulation. These findings suggest that RCD-based multi-omics analysis may refine CRC stratification and help generate therapeutic hypotheses.

Colorectal cancer

Recent advances in Strongyloides screening, diagnostics, therapeutics, and management.

PURPOSE OF REVIEW: Strongyloidiasis affects an estimated 30-100 million people globally and can have life-threatening consequences in immunocompromised hosts, yet it remains underdiagnosed due to limited access and performance of available diagnostics. Novel assays and anthelmintics may reshape screening, diagnosis, treatment, and prevention for at-risk populations. RECENT FINDINGS: Advances in molecular diagnostics coupled with robust stool extraction methods have supplanted traditional parasitologic methods in settings where nucleic acid amplification is feasible. Transition from standard immunoglobulin G (IgG)-based immunoassays to the new IgG- and IgG4-based rapid diagnostic tests using recombinant Strongyloides stercoralis nematode immunodominant E antigen (NIE) and/or S. stercoralis immunoreactive antigen (SsIR) has facilitated serologic screening at the point of care. The World Health Organization now conditionally recommends community-wide ivermectin mass drug administration in highly endemic settings. Regarding new treatment options, moxidectin is noninferior to ivermectin with 93-94% cure rates and a longer half-life, while emodepside shows 80-90% predicted cure rates in early trials and offers a mechanistically distinct option. Understanding of immunosuppressed populations at risk for hyperinfection has expanded, prompting updated screening recommendations. SUMMARY: Serologic and molecular tools are improving screening and diagnosis, and moxidectin and emodepside may broaden treatment options, but data in severe disease and special populations remain limited. Priorities include harmonized screening algorithms and prospective studies in high-risk groups.

Humans

Free polyphenols and multi-omics traits underlying antioxidant variation across Paeonia lactiflora leaf cultivars.

Leaves of Paeonia lactiflora are underutilized by-products with potential as natural antioxidant sources. In this study, 18 cultivars were evaluated for phytochemical composition and in vitro antioxidant capacity. Total phenolic content correlated strongly with DPPH and ABTS activities, and the comprehensive antioxidant index identified 'Coral Charm' and 'Hangshao' as representative high- and low-antioxidant cultivars, respectively. Untargeted metabolomics detected 2677 metabolites and identified 908 differential metabolites between the two cultivars. Targeted phenolic profiling quantified 27 compounds, among which 11 differed significantly between the two cultivars. Catechin and epicatechin were enriched in 'Coral Charm', with contents of 6.62 and 0.397&#xa0;ng/mg, respectively, compared with 0.012 and 0.002&#xa0;ng/mg in 'Hangshao'. (+)-Dihydroquercetin was also more abundant in 'Coral Charm', while caffeic acid showed an upward trend. Proteomic analysis identified 423 differentially expressed proteins, mainly associated with secondary metabolite biosynthesis, redox homeostasis, and central carbon metabolism. Integrated analysis identified pyruvate metabolism as the only pathway significantly enriched in both metabolomic and proteomic datasets. Molecular docking predicted favorable binding between representative phenolics and selected proteins. These findings link cultivar-dependent antioxidant variation in peony leaves with free-phenolic accumulation and pathway-level metabolic differences, supporting the selection and utilization of antioxidant-rich peony leaf resources.

Antioxidants

Efferocytosis regulatory factors in atherosclerosis: A preclinical systematic review.

BACKGROUND: Impaired efferocytosis is a key driver of plaque instability during atherosclerosis progression. Efficient clearance of apoptotic cells through efferocytosis relies on the coordinated action of multiple regulatory factors. METHODS: PubMed, Web of Science, ScienceDirect, OVID MEDLINE, and Scopus were searched for studies published up to February 7, 2026. Eligible preclinical studies were systematically reviewed to identify endogenous factors that regulate efferocytosis in atherosclerosis. Clinical evidence was also incorporated to enable a preliminary translational assessment of these regulatory factors. RESULTS: Thirty-five endogenous regulatory factors were identified from 36 included studies, and their functional roles across distinct stages of efferocytosis were characterized. Notably, metabolic regulators such as PKM2, PFKFB3, GLS1, and Drp1 were involved in distinct efferocytosis stages. This suggests that metabolic reprogramming may provide the metabolic support require for efficient efferocytosis and inflammation resolution. Ten factors were supported by preliminary clinical evidence consistent with preclinical data. PKM2 was the only candidate biomarker with prospective observational data. However, its independent predictive value still requires validation in multicenter prospective studies. CONCLUSIONS: This review provides a systematic synthesis of 35 endogenous efferocytosis regulators and elucidates their regulatory network in atherosclerosis based on a functional stage framework. Metabolic reprogramming is identified as a central hub linking efferocytosis efficiency to inflammation resolution. This review offers a new theoretical basis for efferocytosis-targeted intervention strategies.

Animals

Multiscale Modeling Primer: Focus on Chromatin and Epigenetics.

A central challenge in modern biology is to understand how molecular interactions produce cellular and organismal functions across vast spatiotemporal scales. Nowhere is this challenge more apparent than in the study of chromatin, where meters of DNA compact into a micron-sized nucleus. How this polymer folds is a dynamic process, regulated by epigenetic modifications-chemical changes to DNA and histones that involve only a handful of atoms. These small changes cooperate to produce emergent, higher-order structures that define cellular identity and function. To explain this system, we must integrate static, high-resolution snapshots from techniques like cryo-EM with dynamic, lower-resolution data from microscopy and genomics. Multiscale computational models are essential tools that bridge these experimental gaps and reveal the mechanisms of emergent behavior. However, the communication divide between experimental biologists and quantitative modelers often hampers progress. This primer addresses that gap. It first introduces the fundamental biology of chromatin and epigenetics at an introductory level for non-biologists audiences. We then survey the landscape of computational approaches, from atomistic to systems-level models, and connect them to the experimental data that inform and validate them at an introductory level for non-computationalists. We argue that the next frontier will require us to build integrative models that can predict how molecular perturbations mechanistically alter cellular phenotypes, which will open a new era of chromatin-targeted therapeutics.

Chromatin Dynamics

CNOT1 is a potential YTHDF2 target that orchestrates maternal mRNA decay and zygotic genome activation during goat embryogenesis.

Timely and efficient degradation of maternal mRNA is essential for early embryonic development, which occurs from fertilization through the initiation of zygotic genome activation (ZGA). Yet, the regulatory mechanisms governing this process remain poorly characterized. In the present study, we investigated the function of CCR4-NOT transcription complex subunit 1 (CNOT1) during goat embryogenesis. We found that CNOT1 was upregulated during mammalian ZGA, and that its knockdown led to developmental arrest and a marked reduction in blastocyst formation. Moreover, CNOT1 knockdown impaired nascent RNA activity, resulting in 814 upregulated and 1014 downregulated genes, which were enriched for RNA splicing, regulation of chromosome organization, and RNA localization. RNA splicing analysis revealed differential splicing events in 2959 genes, of which 259 were downregulated following CNOT1 knockdown. Notably, CNOT1 was predicted to crosstalk with the m6A reader YTHDF2. Knockdown of YTHDF2 resulted in CNOT1 downregulation at the 8-cell stage in goats and increased transcription levels around polyadenylation sites during ZGA in mice. Together, these findings indicate that CNOT1 is a potential YTHDF2 target that orchestrates maternal mRNA decay and ZGA during goat embryogenesis. Our work provides new insight into the complex regulatory landscape underlying ZGA and may inform strategies to improve the efficiency of goat embryogenesis.

Animals

Pharmacogenomic and drug interactions risk in cardio-oncology: A precision medicine perspective for India.

Cardio-oncology patients may face complex treatment regimens due to the concurrent existence of cancer and cardiovascular disease, leading to a considerable polypharmacy burden. This significantly increases the prospect of drug-drug interactions (DDIs) and gene-drug interactions. The majority of these interactions arise from comparable pharmacokinetic and pharmacological pathways associated with drug transporters and cytochrome P450 enzymes. The significance of pharmacogenomics in tailored treatment strategies are emphasised by the fact that genetic variability enhances individual differences in drug response, safety, and efficacy. This narrative review focus on the effects of key genetic polymorphisms (e.g., DPYD, CYP2C19, and CYP2C9) on the metabolism and efficacy of commonly prescribed anticancer and cardiovascular medications such as fluoropyrimidines, clopidogrel, and warfarin. In addition it explore the role of pharmacogenomic variants on drug-drug interactions within the field of cardio-oncology. The study ultimately emphasizes the necessity of precision medicine in India to address the genetic diversity and underrepresentation in global genomic databases. The absence of pharmacogenomic testing, infrastructural deficiencies, financial constraints, and insufficient clinical integration hinder the widespread use of this technology in India. The Genome India Project and other national initiatives establish the foundation for pharmacogenomic-guided therapy. Utilizing genetic data, together with artificial intelligence-based predictive tools, for clinical decision-making may enhance medication safety and yield optimal outcomes in Indian cardio-oncology patients.

Humans