The artificial intelligence-assisted ASPECTS (AI-ASPECTS) system has become an increasingly common tool in clinical practice for assessing acute ischemic stroke (AIS). However, current AI-ASPECTS implementations still rely on the conventional expert-evaluation framework, which uses a simplified two-slice atlas and arbitrarily selected lesion-load thresholds. Our study aimed to develop a refined AI-assisted ASPECTS (Ref-AI-ASPECTS) framework featuring a seamless & whole middle cerebral artery (MCA) territory atlas and region-specific, optimally determined lesion-load thresholds, and comprehensively evaluate the performance of this framework across various clinical scenarios for AIS. We enrolled a cohort of 7,655 AIS patients from eleven centers. Modified atlas was created by expanding conventional atlas based on full MCA territory. Ref-AI-ASPECTS with modified atlas and specific lesion-load thresholds was established using a genetic algorithm. The clinical utility of Ref-AI-ASPECTS was assessed by comparing it to the conventional framework (Con-AI-ASPECTS) in terms of correlation with NIHSS scores on admission, dichotomized prediction of mRS at 3 months, and consistency with expert scoring across the training DWI data, external DWI data, expanded CT data, and real-world prospective DWI data. The Ref-AI-ASPECTS frameworks with modified atlas and specific lesion-load thresholds (2% to 29%) achieved correlation coefficients (r) of -0.414/-0.438/-0.375 and AUC values of 0.665/0.723/0.707 in the training/internal validation/external validation sets, surpassing both Con-AI- (r: -0.336/-0.402/-0.331; AUC: 0.615/0.654/0.654) and expert-ASPECTS (r: -0.196/-0.206/-0.173; AUC: 0.600/0.641/0.644) (all P < 0.01). The intraclass correlation coefficients for expert- and Ref-AI-ASPECTS were 0.82 and 0.81 in the training and external validation DWI sets, respectively, exceeding those of expert- and Con-AI-ASPECTS (0.69/0.67; both P < 0.01). These improvements were consistently validated across expanded CT datasets (AUC: 0.696 and 0.679) and in a real-world prospective cohort (AUC: 0.710). The Ref-AI-ASPECTS framework outperformed conventional approaches in evaluating baseline neurological deficits and predicting functional outcomes in AIS. Our findings support the potential for its wider implementation in AI-ASPECTS systems. Prospective external real‑world validation remains necessary. ClinicalTrials.gov Identifier: NCT04775147; chictr.org.cn Identifier: ChiCTR2400092230.
Plant development arises from the coordinated execution of gene regulatory programs across diverse cell types. While classical genetic and genomic approaches have revealed many of the genes required for plant growth and patterning, these methods often average signals across heterogeneous tissues, thereby obscuring how regulatory programs operate within individual cells. Resolving gene expression at cellular resolution is therefore essential for understanding how developmental decisions are made, integrated, and propagated during organ growth. The Arabidopsis root, with its simple anatomy and invariant cell lineages, provides an ideal system for addressing these questions. Recent advances in single-cell and single-nucleus transcriptomics have enabled the construction of comprehensive cellular atlases that capture gene expression dynamics across cell identities and developmental trajectories. In this Expert Views article, we highlight recent conceptual and technical developments that illustrate how single-cell atlases have transformed studies of root development. We emphasize how these atlases both serve as community resources to inform the interpretation of new datasets, including those generated from mutants and in response to perturbation, as well as provide a platform for meta-analysis to initiate new studies. Using auxin signaling as a meta-analysis case study, we demonstrate how legacy transcriptomic data can be reinterpreted within a cell lineage-resolved framework. Finally, we highlight how spatial transcriptomics and rigorous data-sharing practices will extend cellular atlases across tissues and species, thereby enabling increasingly precise strategies for understanding and engineering plant growth and resilience.
Eduard Pernkopf (1888-1955), a prominent representative of the Viennese Anatomical School, produced one of the most detailed and visually refined anatomical atlases in the history of medicine: Topographische Anatomie des Menschen. Despite its exceptional scientific and artistic value, the Atlas remains deeply controversial because of its association with National Socialist ideology and the probable use of bodies of executed prisoners during its production. This study provides a historical, morphological, and ethical analysis of Pernkopf's life, scientific work, and enduring influence on anatomical education. Special attention is devoted to the morphological and methodological innovations of Pernkopf's topographical dissection technique, including his systematic layer-by-layer anatomical stratification and the unprecedented three-dimensional realism of his anatomical illustrations. Through analysis of the historiographical and bioethical literature, the study examines the epistemological significance of Pernkopf's anatomical method, the historical context of Nazi-era anatomical science, and the ongoing debate regarding the Atlas's contemporary use. Pernkopf's Atlas emerges as both a landmark in morphological representation and a lasting ethical warning for the anatomical sciences. Its legacy underscores both the enduring methodological influence of Pernkopf's topographical anatomical approach and the necessity of integrating scientific excellence with ethical accountability in modern anatomical science.
Executive dysfunction is frequently observed in multiple system atrophy (MSA), yet its neuroanatomical substrates remain incompletely characterized. Emerging evidence suggests that the cerebellum contributes to higher cognitive functions beyond motor control. To investigate structural cerebellar alterations associated with executive dysfunction in patients with MSA using complementary voxel-based and atlas-based morphometric analyses. In this case-control study, 27 patients with clinically established MSA and 19 age-matched healthy controls underwent 3D T1-weighted MRI. Voxel-based morphometry and subsequent atlas-based cerebellar volumetry were performed to identify regional brain volume differences between groups, adjusting for age, sex, total intracranial volume, and MSA clinical subtype (MSA-P vs. MSA-C). Executive function was assessed with the Frontal Assessment Battery (FAB). Partial correlations between regional cerebellar volumes and FAB scores were examined within the MSA group. Compared with healthy controls, patients with MSA showed significant gray matter volume reductions in the bilateral putamen and cerebellar cortex, as well as white matter reductions extending from the brainstem to the middle cerebellar peduncles. Atlas-based analyses demonstrated reduced normalized volumes in bilateral cerebellar white matter and left vermian VIIIA, whereas larger volumes were observed in bilateral vermian Crus II and left lobule IV. Within the MSA group, FAB scores showed nominal positive associations with left VIIIB, bilateral VIIIA, and right vermis IX volumes, without surviving multiple-comparison correction. Posterior cerebellar degeneration may be related to executive dysfunction in MSA. These exploratory findings warrant validation in larger longitudinal studies with detailed cognitive and motor assessments.
Teachers are a particularly stressed occupational group with above-average burnout rates compared to other professions. Teacher stress significantly challenges teachers' health, classroom interactions, and positive student development. Preventing this stress is of utmost importance. Proven frameworks help us understand and buffer teacher stress. However, each approach has its specific strengths and limitations in understanding the complex problem of teacher stress. We propose the comprehensive ATLAS Model of Psychobiological Teacher Stress in Classroom Interactions that builds on and extends existing frameworks. ATLAS considers objective measures, biological and interactional processes, the temporal dimensions of acute and chronic stress, and the effects of cumulative stress. The ATLAS Model permits us to understand (1) how teacher stress impairs teachers' ability to provide an effective learning environment and (2) how this affects students' learning and social development. (3) Finally, the model describes how teacher and student behavior shape dysfunctional classroom environments. A better understanding of the interplay between psychobiological stress in teachers, the classroom environment, and student development may help teacher education, schools, and healthcare providers mitigate adverse health outcomes and ultimately improve education quality.
Metaphoric 3D glyphs offer a rich design space for visualizing multivariate data in web-based information landscapes, but their effective use requires careful decisions regarding perceptual design, metaphor selection, and scalable rendering. This article presents a structured workflow for designing metaphoric 3D glyph atlases from reusable 3D assets. The workflow covers model collection, preprocessing into reusable glyph components, parameterization of visual variables, and efficient browser-based rendering using instanced Web3D techniques. To support these steps, we relate the workflow to established concepts from glyph design, cartographic map- like visualization, and metaphor theory, including the CARSE framework. We further discuss interaction techniques for exploratory use and outline how semantic generalization can complement level-of-detail methods when dense glyph populations cause clutter. Using software analytics examples, we illustrate how information landscapes with metaphoric 3D glyphs can support the exploration of patterns, neighborhoods, and outliers in complex multivariate datasets.
Osteosarcoma is characterized by extensive inter- and intra-tumoral heterogeneity, contributing to treatment resistance and poor outcomes. Here, we present a comprehensive spatial transcriptomics analysis of osteosarcoma, encompassing primary tumors and local or metastatic relapses across diverse phenotypic subtypes. Despite this heterogeneity, we identify a nine-gene cell surface signature with theranostic potential, validated in independent datasets and shown by immunohistochemistry to be distributed across distinct tumor compartments, supporting multi-targeted therapeutic strategies. Analysis of the tumor immune microenvironment reveals systematic lymphoid exclusion, differential myeloid infiltration patterns, and a type I interferon response signature that may explain the failure of IFN-α supplementation in prior trials. Notably, we provide evidence of monocyte-derived osteoclastic differentiation within human osteosarcoma lung metastases, identifying precursor populations with complex secretory phenotypes representing potential immunomodulatory targets. This study offers biological insights and translational opportunities while providing a resource for the osteosarcoma research community.
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Single-cell RNA sequencing (scRNA-seq) has transformed transcriptomic studies by enabling gene expression profiling at the resolution of individual cells within and across a broad range of tissue types, revealing cellular heterogeneity that is obscured in bulk tissue transcriptomes. Over the past decade, improvements in microfluidics and library preparation have drastically increased throughput, allowing tens of thousands of cells to be assayed in a single experiment. Although initially developed in animal systems, scRNA-seq has rapidly emerged as a powerful and widely adopted approach in plant biology. Beyond transcriptomics, the integration of single-cell data with chromatin accessibility, proteomics, metabolomics, and spatial omics is enabling a system-level understanding of plant gene regulation and cellular organization. Network-based analytical frameworks further support the reconstruction of gene regulatory networks and the interpretation of complex single-cell data. In this review, we summarize the current technological landscape of plant single-cell studies, discuss key experimental and analytical challenges, and review emerging strategies for validating single-cell discoveries. We also discuss future directions in applying single-cell technologies to woody perennials plants and bioenergy-relevant crops, emphasizing their potential to accelerate the discovery of cell type-specific regulatory mechanisms underlying growth, stress resilience, and biomass production.
Breast cancer remains a leading cause of cancer-related mortality in women, and current prognostic models are suboptimal. The transcriptomic role of programmed cell death (PCD) in breast cancer progression is not fully understood. Here, we integrated single-cell RNA sequencing data from breast tumors with nine bulk transcriptomic cohorts to systematically analyze 19 PCD modalities. Using a machine learning framework incorporating 14 algorithms, we constructed a prognostic signature, with a ridge regression-based PCD riskscore showing optimal performance and being further integrated into a clinical nomogram. Functional roles of key genes were validated through in vitro and in vivo experiments. We identified a prognostic signature comprising 26 core PCD genes, which effectively stratified patients into distinct risk groups and robustly predicted overall survival. Single-cell analyses revealed that a high PCD risk core was associated with an immunosuppressive tumor microenvironment and reduced immune checkpoint expression, whereas low-risk patients showed greater sensitivity to targeted therapies. Among the signature genes, PDIA4 was consistently overexpressed in 50 paired breast cancer tissues, and its knockdown markedly inhibited tumor growth and malignant phenotypes. This study establishes a novel PCD-based prognostic signature for breast cancer and identifies PDIA4 as a functionally important oncogene.
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Reproducibility and cross-species translation using the domestic pig (Sus scrofa) are limited by the lack of a standardised molecular framework for biological maturation: the pig's developmental tempo differs substantially from the human's, yet no tissue-resolved transcriptomic staging system exists. Synchronising porcine and human maturation is essential to move preclinical research from descriptive to predictive. We built a transcriptomic atlas of porcine development across five tissues (muscle, brain, liver, blood, lung) from 1,924 PigGTEx RNA-seq profiles. A single partial-least-squares (PLS) regressor staged each tissue at its native ordinal resolution and also drove cross-species transfer and biomarker extraction. Our central result: transfer of a pig-trained developmental score to other species is dominated by tissue identity, with phylogenetic distance a weaker secondary effect. Projected onto the seven-species Cardoso-Moreira atlas, transfer was strongest for brain and heart ([Formula: see text]-0.92) and weakest for the labile liver and ovary ([Formula: see text] and 0.42). Brain and heart stayed high even from pig to chicken ([Formula: see text] across ∼320 Myr), whereas liver and ovary collapsed. A variance partition confirmed the ranking (organ Type-II [Formula: see text], [Formula: see text]; phylogeny significant only at the species level, Spearman [Formula: see text], [Formula: see text], [Formula: see text]). The score independently confirmed lung, muscle, and adipose on the human dGTEx resource ([Formula: see text]-0.67) against an ortholog-scramble null and three controls. Because it is fit on pig and projected onto foreign-batch atlases, the transfer cannot arise from a pig-side artefact. A web application is available at https://pigdevstage.streamlit.app. The porcine developmental programme transfers to humans and more distant amniotes in a tissue-dependent manner, so the pig's value as a developmental model is set by how conserved each organ's developmental logic is, not by phylogenetic proximity. Validated on foreign-species atlases, the transfer sidesteps the stage-study confound that bounds within-pig staging to muscle and liver. The atlas is therefore best used organ by organ: strong for conserved organs (brain, heart) and weak for labile ones (liver).
Cardiac surgery is a major therapeutic advancement but remains associated with neurological complications, including ischemic stroke and postoperative cognitive decline. Compared with stroke of other etiologies, ischemic brain injury following cardiac surgery may involve distinct vascular territories and functional networks, potentially influencing its characteristic cognitive profile. We performed a systematic review of case reports describing ischemic brain lesions occurring after cardiac surgery in adults with available neuroimaging data. Lesions were manually traced onto a standard brain atlas and compared with ischemic stroke lesions from the ATLAS database, matched for hemispheric involvement. Lesion topography was analyzed at the arterial territory and voxel levels. Lesion network mapping was conducted using normative resting-state functional connectivity data to identify patterns of functional disconnection. Permutation-based statistical analyses were applied, with correction for multiple comparisons and lesion volume included as a covariate. Nineteen articles met the inclusion criteria, yielding 20 cases of post-cardiac surgery ischemic lesions. Compared with stroke controls, these lesions more frequently involved posterior arterial territories, particularly the occipital branches of the posterior cerebral arteries and posterior thalamic regions. Lesion network mapping revealed a distinct pattern of functional disconnection in the occipital lobes, posterior thalamus (including the pulvinar), and medial frontal cortex. Our results suggest that ischemia associated with cardiac surgery may preferentially involve posterior arterial territories and be associated with distinct patterns of functional disconnection involving the occipital lobe, the pulvinar, and the medial frontal cortex.
Gliomas are highly malignant brain tumors characterized by an immunosuppressive microenvironment, which limits therapeutic efficacy and contributes to poor clinical outcomes. The WNT/β-catenin signaling pathway is critically involved in tumor progression, and FZD5, a key receptor within this pathway, may participate in immune regulation. However, its specific role and underlying mechanisms in glioma remain unclear. RNA-seq and microarray datasets from the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA), together with single-cell RNA sequencing (scRNA-seq) datasets from GEO, were comprehensively analyzed. The Seurat package was used to identify macrophage-related clusters and mitophagy-associated pathways. Cox and LASSO regression analyses, along with a prognostic nomogram, were applied to evaluate the prognostic significance of FZD5. Immune infiltration, functional enrichment, and immunotherapy response analyses were conducted, followed by validation using spatial transcriptomics, immunohistochemistry, and in vitro assays. In bulk glioma transcriptomes, FZD5 emerged as an independent predictor of poor prognosis. Crucially, single-cell and spatial analyses revealed that the biologically significant FZD5 signal originated predominantly within tumor-associated macrophages (TAMs), where it colocalized with the M2 marker CD163. Consistently, elevated FZD5 levels correlated with increased myeloid infiltration and an immunosuppressive tumor microenvironment. Functionally, macrophage-expressed FZD5 was associated with mitophagy-related programs and promoted an M2-skewed phenotype, thereby enhancing glioma cell proliferation, migration, and invasion via macrophage-glioma crosstalk. FZD5 is a TAM-enriched marker in glioma tissues and a potential regulator of macrophage-associated immunosuppressive programs, supporting its utility as a prognostic biomarker and a candidate target for microenvironment-oriented interventions in glioma.
Pancreatic ductal adenocarcinoma (PDAC) exhibits profound therapy resistance driven by lysosome-dependent nutrient recycling, metabolic adaptation, and stress tolerance. Current lysosome targeting agents such as chloroquine (CQ)/hydroxychloroquine (HCQ) show limited efficacy due to transient activity and dose-limiting-toxicities. To overcome these limitations, we developed lysostilbenes, a new class of hybrid small molecules combining the CQ pharmacophore with lysosome-disrupting stilbene analogs. Stilbene pharmacophore is the core structural component of resveratrol. Among the synthesized hybrids, lysostilbene-4 emerged as the lead candidate, demonstrating ~30-40-fold greater cytotoxicity against PDAC cells than parent compounds, while sparing nonmalignant cells. At nanomolar concentrations, lysostilbene-4 induced rapid, irreversible lysosomal membrane permeabilization (LMP), initiating a lysosome mitochondria apoptotic cascade via CTSB (cathepsin B) release, BID cleavage, BAX activation, and caspase-mediated apoptosis. In parallel, it abrogated lysosomal recovery by significantly reducing repair, lysophagy, autophagosome maturation, and uncoupling TFEB-driven transcriptional programs from effective lysosome biogenesis. Reduced TFEB mRNA expression correlated with poor overall-survival and disease-free-survival across multiple cancer patients, with a particularly strong association in pancreatic cancer patients. Using TFEB+/+ and TFEB-/- knockout pancreatic cancer cells we establish that lysostilbene-4 exerts severe cytotoxicity by inducing persistent lysosomal-damage and disrupting autophagosome-lysosome assembly, with vulnerability further amplified in TFEB-deficient cells. This finding underscores TFEB as a key determinant of lysosomal-resilience and a potential predictive biomarker. Importantly, lysostilbene-4 was well tolerated in preclinical mouse-models at supra-therapeutic doses without systemic-toxicity. These findings position lysostilbene-4 as a first-in-class lysosome-targeting therapeutic that enforces sustained lysosomal collapse while compromising adaptive recovery-mechanisms, providing a mechanistically precise and safe strategy against PDAC.Abbreviations: ALG: autophagy-lysosome genes; AMPK: AMP-activated protein kinase; CASM: conjugation of ATG8s to single membranes; CTSB: cathepsin B; LGALS3: galectin 3; LMP: lysosomal membrane permeabilization; LS: lysostilbene; MTOR: mechanistic target of rapamycin kinase; PDAC: pancreatic ductal adenocarcinoma; TCGA: The Cancer Genome Atlas; TFEB: transcription factor EB; ULK1: unc-51 like autophagy activating kinase 1.
Modern contraceptives have contributed to reduction of unintended pregnancy among the women of reproductive age (15 to 49) globally. Use of long-term reversible contraceptives is low (13%) in Uganda yet they are cost-effective. This study aimed to identify factors influencing preference of short-term reversible contraceptives over long-term methods among women of reproductive age attending the family planning clinic at Lira Regional Referral Hospital (LRRH). We performed a mixed-methods cross-sectional study, in which structured interviews were administered to 220 family planning users from December 2022-February 2023, data were analyzed using IBM SPSS Statistics version 29 and cleaned prior to analysis. Descriptive statistical analyses were performed to summarize participant characteristics and contraceptive preferences, and results were presented using tables and figures. Frequencies, percentages, and cross-tabulations were computed. Bivariate analysis using binary logistic regression was conducted to assess associations between independent variables and preference for short-term versus long-term reversible contraceptive methods. Crude odds ratios (CORs) with 95% confidence intervals (CI) were reported. Variables with a p-value ≤ 0.05 at bivariate analysis were included in a multivariate binary logistic regression model to identify independent predictors of contraceptive method preference. Adjusted odds ratios (AORs) with 95% CI were calculated, and statistical significance was set at p-value ≤ 0.05. Qualitative data were audio-recorded, transcribed verbatim, and analyzed using applied thematic analysis. Atlas.ti version 23 was used to support data organization and coding. Analysis followed an iterative process involving open coding, development of summary memos, and construction of a structured codebook. Related codes were grouped into overarching domains, with sub-themes used to organize emerging patterns. Coded transcripts were reviewed and synthesized, and representative participant quotes were selected to provide contextual understanding of factors influencing women's contraceptive method preferences. Discrepancies in coding and interpretation were resolved through consensus discussions among the research team. Ethical approval was obtained from Gulu Research and Ethics Committee (GUREC), and administrative clearance from Lira Regional Referral Hospital and Informed consent /assent from study participants. Of 220 women 63.6% preferred short term, 36.4% preferred long-term reversible contraceptive methods. Age between 25-34 years were 47.7%, 91.8% were married, and 70.5% attained primary education. Reasons for preference of short-term contraceptives were; less side effects 50%, protection for a short period of time 21.4%, confidentiality 28.6%. Partners approval (AOR: 0.253, 95% CI: 0.194-0.680, P=0.006), was significantly associated with short term preference. Providers cited confidentiality, quick return to fertility, and of methods availability as influence for short-term preference. This study found that women of reproductive age predominantly preferred short-term reversible contraceptive methods. Despite the effectiveness and cost-efficiency of long-acting contraceptives, their uptake remains low due to socio-cultural factors, misconceptions, and health system barriers. Strengthened client-centered counseling, consistent method availability, community education, and male engagement are essential to improve informed choice and increase uptake of long-acting reversible contraceptives.
Gene- and cell-based therapies (GCTs) represent a disruptive and transformative class of biomedical innovations. They address diseases by adding, removing, repairing, or replacing genes and/or by endowing distinct living cells with additional biological functions. Through this plethora of options, numerous conditions-including genetic disorders, cancers, and degenerative diseases-have become potential targets for a curative therapy. Thus, GCTs are considered the "Future of Medicine" as they (i) offer a potential cure, particularly for rare and severe disorders previously considered untreatable, (ii) expand the treatment options for common diseases, and (iii) possess the possibility to complement currently applied conventional treatment options. Recognizing both the scientific promise and translational challenges of GCTs, Germany has launched a coordinated national initiative-the National Strategy for Gene- and Cell-Based Therapies. The Strategy was commissioned by the German Federal Ministry of Research, Technology and Space (BMFTR, formerly the German Federal Ministry of Education and Research [BMBF]) and developed through a multi-stakeholder process. The latter involved more than 150 experts from academia, industry, health care sector, professional associations, and patient organizations, who were nominated by the community and assembled into eight working groups to identify current roadblocks and propose possible solutions. Summarized in the Strategy Paper, which was submitted to the BMFTR and published on June 12, 2024, a comprehensive roadmap was developed in this bottom-up process to accelerate the development and clinical implementation of GCTs in Germany. Although it initially had a national focus, the resulting framework is increasingly contributing to the international GCT landscape through growing exchange with GCT initiatives launched in other European member states and with the European Society of Gene and Cell Therapy (ESGCT).In brief, the initiative is focusing on translation starting from research through all steps to clinical application and beyond. This includes workforce development, regulatory frameworks, manufacturing capacity, patient access, and communication with the general public. Numerous targeted measures have been developed by the participating experts in the working groups and are currently being implemented in this broad, collaborative, and bottom-up multi-stakeholder approach. They encompass, for example, the establishment of a website as central information platform, including the GCT-Atlas, a web-based networking and information tool for stakeholders and actors in the GCT field, tailored communication and outreach formats, a Regulatory Support Unit providing independent regulatory guidance for publicly funded early-stage, nonclinical product development, different funding and entrepreneurship programs offering researchers and clinicians financial, educational, and mentoring support, as well as the establishment of translational infrastructure and exchange formats with investors to specifically foster the necessary scale-up and commercialization.Overall, the main goal of the German National Strategy for GCT is to ensure patient access to advanced therapies while strengthening Germany's position as an international hub for biomedical innovation. To accomplish this, existing resources need to be coordinated, streamlined, and prioritized to increase efficiency and support the long-term sustainability of the system. These objectives are closely aligned with current emerging European initiatives, including the EU Biotech Act and the Horizon Europe work program 2026, which aim to further optimize the framework conditions for this strategically important field and enhance future European competitiveness.
Radial meniscal tears (RMTs) interrupt circumferential collagen fibers, disrupt hoop stress transmission, and accelerate compartmental cartilage wear. Despite their clinical and biomechanical importance, reporting remains inconsistent because widely used taxonomies are heterogeneous and often assessed with nominal agreement statistics that overlook the ordered nature of tear morphology. To (1) quantify the interobserver and intraobserver reliability of a 5-type morphology-based classification system for RMTs using ordinal agreement metrics and (2) evaluate criterion validity against arthroscopy and construct validity against a prespecified morphology→treatment matrix. Cross-sectional study; Level of evidence, 3. A harmonized case bank of 400 unique RMTs (80 per type I-V; 55.0% medial and 45.0% lateral) was assembled across 5 centers. There were 7 expert knee surgeons (>10 years' experience) who performed test-retest classifications at T1 and T2 (mean washout time, 24.7 ± 3.6 days); a broader panel of 40 knee surgeons (>10 years' experience) conducted classifications at T1 only. Raters were blinded; used a 1-page atlas with explicit criteria (depth/extent, gap thresholds of ≤3/>3 mm, vascular zone); and recorded type (I-V), confidence (Likert), and recommended treatment. The primary endpoint was the Light kappa (κ) (mean of pairwise Cohen κ; quadratic weighting) with bootstrap 95% confidence intervals (CIs) (5000 resamples, stratified by type). The coprimary endpoint was the Gwet AC2 (ordinal). Criterion validity was determined using an arthroscopy-referenced subcohort (n = 260). Construct validity examined concordance between assigned type and the prespecified treatment matrix. Secondary endpoints included exact agreement and ±1-category agreement, the Fleiss κ (nominal), and subgroup analyses (compartment, gap magnitude). Interobserver ordinal agreement was high (Light κ = 0.902 [95% CI, 0.889-0.914]) (AC2 = 0.918 [95% CI, 0.906-0.929]). Agreement was stable by compartment (medial: κ = 0.897; lateral: κ = 0.909) and gap magnitude (no/≤3 mm: κ = 0.907; >3 mm: κ = 0.893). Exact agreement was 83.5%, and ±1-category agreement was 96.8%; nonadjacent misclassifications were 3.2%, with a predictable boundary at type III↔IV. Intraobserver reliability among experts was excellent (mean weighted Cohen κ = 0.913 [range, 0.882-0.942]). Criterion validity versus an arthroscopic reference was strong (weighted κ = 0.887 [95% CI, 0.871-0.902]). Construct validity showed 86.2% exact agreement (κ = 0.842; AC1 = 0.861). Sensitivity analyses (category collapsing, alternative weights, leave-one-rater-out) confirmed robustness. This 5-type classification system demonstrated high reproducibility (ordinal κ≈ 0.90) and clinical validity, providing a practical framework for standardized reporting and treatment selection and a defensible stratification scheme for future trials and meta-analyses.
Meat quality is a critical determinant of the economic value in the broiler industry, with its foundational characteristics established during early post-hatch development. Skeletal muscles comprise a complex mixture of myofiber types, whose initial distribution and molecular signatures set the stage for post-mortem meat quality. However, the early regulatory landscapes governing these myofiber compositions remain to be fully elucidated. In this study, we employed high-resolution single-nucleus RNA sequencing (snRNA-seq) to characterize the transcriptomic divergence between broiler breast muscle (BM) and leg muscle (LM) at the neonatal stage (Day 1). Our panoramic atlas of muscle-resident cells revealed that neonatal LM already possesses a significantly higher proportion of oxidative fibers (Type I and Type IIA) and an enriched population of preadipocytes/adipocytes compared to BM. Functional enrichment analysis identified a prominent upregulation of the adipocytokine signaling pathway in D1 LM, suggesting an early molecular framework for the flavor and juiciness characteristics typically associated with leg meat. Furthermore, GSEA and KEGG analyses revealed a correlation between elevated FOS expression and apoptosis signatures in Type IIA and IIB myonuclei within LM, suggesting its potential involvement in shaping early myofiber type proportions. Additionally, PRKAG2 was identified as a candidate regulator linked to intramuscular lipid and fatty acid biosynthetic pathways. Our analysis indicated a regulatory link between the transcription factor EGR1 and its putative target PRKAG2, which coincides with initial lipid droplet accumulation in intramuscular adipocytes. Collectively, these findings provide a high-resolution genetic blueprint of early-postnatal muscle fiber characteristics and lipid deposition, offering novel developmental insights that may inform molecular breeding strategies aimed at predetermining the nutritional and sensory potential of broiler meat.
Exercise is fundamental to healthy aging, yet how it mitigates age-related molecular changes and how fitness level shapes exercise responses remain unclear. To address these questions, we performed transcriptomics, lipidomics and metabolomics on skeletal muscle of young and older adults with differing physical function, both before and after an acute bout of submaximal exercise. At baseline, older adults exhibited reduced expression of genes associated with cellular respiration and energy metabolism compared to young adults with comparable activity levels. Here we found that 50% of these age-related differences were absent in trained older adults, resulting in profiles resembling those of young adults. Although all participants displayed transcriptional immune and stress responses upon acute exercise, the magnitude of these responses in older adults was positively correlated with their physical fitness. Integrated multiomic analyses further revealed links among mitochondrial respiration, lipid metabolism, stress responses and NAD+ biology. These findings demonstrate that sustained physical training transforms age-related molecular profiles and provide a molecular atlas for study of fitness-dependent aging mechanisms.