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PubMed2026

Digital and computational morphology in hematology: current platforms, clinical evidence, and future requirements.

INTRODUCTION: Morphologic examination of peripheral blood and bone marrow remains central to the diagnosis and classification of hematologic disorders. Conventional optical microscopy, however, is labor-intensive, dependent on operator expertise, and affected by interobserver variability. Digital morphology has developed from automated image acquisition and cell pre-classification into a broader field that includes whole-slide imaging, remote review, quantitative morphometry, and artificial intelligence-based analysis. CONTENT: This review examines current applications of digital morphology in peripheral blood, bone marrow aspirates, malaria detection, and body-fluid analysis. Commercial platforms are evaluated with particular attention to the distinction between raw automated pre-classification, expert digital post-classification, and comparison with independent optical microscopy. Digital systems generally perform well for common mature leukocyte populations but remain less reliable for rare or diagnostically critical cells, including blasts, abnormal lymphoid cells, plasma cells, and intermediate maturation stages. Research systems increasingly extend analysis from individual-cell classification to whole-slide, specimen-level, and patient-level assessment. SUMMARY: Digital morphology can improve standardization, image traceability, remote consultation, education, proficiency testing, quality assurance, and selected aspects of laboratory workflow. Its clinical value depends on appropriate validation, transparent reporting of reference methods, recognition of algorithm-specific failure modes, and clearly defined criteria for expert review and conventional microscopy. Human expertise remains essential not only for validating results but also for adapting cell taxonomies and interpretive rules to evolving classifications of hematologic diseases. OUTLOOK: Future progress will require representative multicenter datasets, harmonized morphologic terminology, external validation, interoperability with laboratory information systems, and continuous monitoring after software or hardware updates. Integration of morphology with quantitative hematology, flow cytometry, cytogenetics, genomics, and clinical data may support more comprehensive computational diagnosis. Digital platforms may also broaden access to specialist expertise, training, and quality programs in resource-limited institutions and regions, provided that infrastructure, governance, and professional competency are adequately supported.

artificial intelligence↗

PubMed2026

Higher Rates of PASS and SCB After Arthroscopic Subspine Decompression Are Associated With a Positive Diagnostic AIIS Injection: A Propensity Score-Matched Cohort Study.

BACKGROUND: Hip arthroscopy effectively treats femoroacetabular impingement syndrome (FAIS), but persistent pain may be related to concomitant extra-articular pathology such as subspine impingement syndrome (SSI). Standard diagnosis of SSI often relies on 3-dimensional computed tomography (3D-CT) morphology (Hetsroni type II/III), although this morphology is common in individuals who are asymptomatic and correlates poorly with symptoms. PURPOSE: To compare minimum 2-year clinical outcomes after arthroscopic subspine decompression in patients with concurrent FAIS and type II/III anterior inferior iliac spine (AIIS) morphology, stratified by diagnostic method: 3D-CT morphology alone versus 3D-CT morphology plus a positive ultrasound-guided diagnostic injection. STUDY DESIGN: Cohort study; Level of evidence, 3. METHODS: This study included patients aged 18 to 55 years with type II/III AIIS morphology who underwent primary hip arthroscopy for FAIS and SSI between January 2021 and November 2023 and had minimum 2-year follow-up. Patients diagnosed by CT morphology alone (CT classification group) were propensity score matched 1:1 to patients with a positive ultrasound-guided AIIS injection (injection group), with 57 patients per group. Matching variables were age, sex, body mass index, lateral center-edge angle, alpha angle, Tönnis grade, and Beighton score. All patients underwent arthroscopic subspine decompression. Patient-reported outcomes and rates of achieving the minimal clinically important difference, Patient Acceptable Symptom State (PASS), and substantial clinical benefit (SCB) were compared. RESULTS: Preoperative patient-reported outcome scores were similar between groups (all P > .05). At minimum 2-year follow-up, the injection group had significantly better scores on the modified Harris Hip Score (90.8 vs 84.2), Hip Outcome Score-Activities of Daily Living (88.4 vs 82.4), Hip Outcome Score-Sports Subscale (71.9 vs 64.1), 12-item International Hip Outcome Tool (83.9 vs 76.1), and visual analog scale for pain (1.2 vs 2.0) (all P < .001). Minimal clinically important difference rates were high in both groups, with higher rates in the injection group for modified Harris Hip Score (93% vs 77%; P = .033) and Hip Outcome Score-Activities of Daily Living (91% vs 75%; P = .042). PASS and SCB rates were significantly higher in the injection group across all patient-reported outcome measures (all P < .05). Revision and complication rates were low and did not differ significantly between groups. CONCLUSION: Both groups improved significantly after arthroscopic subspine decompression. However, patients with a positive ultrasound-guided diagnostic AIIS injection achieved higher PASS and SCB rates than those selected by CT morphology alone, suggesting that injection-confirmed SSI may improve patient selection for subspine decompression.

Humans↗

PubMed2026

A Boveri perspective on cancer biomarker testing using artificial intelligence.

Artificial intelligence (AI) can predict genomic alterations from histology, yet its adoption is slowed by a lack of trust. We argue that deliberate morphology (i.e., a cognitive understanding of histological features supported by standardized annotations) creates a bidirectional feedback loop between clinical practice and model outputs.We translate these observations into an actionable hypothesis for clinical and computational teams: that by enhancing explainability, deliberate morphology could facilitate the responsible deployment of AI biomarkers in oncology.

Journal Article↗

PubMed2024

Advancing responsible genomic analyses of ancient mollusc shells.

The analysis of the DNA entrapped in ancient shells of molluscs has the potential to shed light on the evolution and ecology of this very diverse phylum. Ancient genomics could help reconstruct the responses of molluscs to past climate change, pollution, and human subsistence practices at unprecedented temporal resolutions. Applications are however still in their infancy, partly due to our limited knowledge of DNA preservation in calcium carbonate shells and the need for optimized methods for responsible genomic data generation. To improve ancient shell genomic analyses, we applied high-throughput DNA sequencing to 27 Mytilus mussel shells dated to ~111-6500 years Before Present, and investigated the impact, on DNA recovery, of shell imaging, DNA extraction protocols and shell sub-sampling strategies. First, we detected no quantitative or qualitative deleterious effect of micro-computed tomography for recording shell 3D morphological information prior to sub-sampling. Then, we showed that double-digestion and bleach treatment of shell powder prior to silica-based DNA extraction improves shell DNA recovery, also suggesting that DNA is protected in preservation niches within ancient shells. Finally, all layers that compose Mytilus shells, i.e., the nacreous (aragonite) and prismatic (calcite) carbonate layers, with or without the outer organic layer (periostracum) proved to be valuable DNA reservoirs, with aragonite appearing as the best substrate for genomic analyses. Our work contributes to the understanding of long-term molecular preservation in biominerals and we anticipate that resulting recommendations will be helpful for future efficient and responsible genomic analyses of ancient mollusc shells.

Animals↗

PubMed2026

CT-Derived pelvic morphometry for preoperative risk assessment of recurrent unilateral inguinal hernia.

BACKGROUND: Recurrent inguinal hernia remains a significant challenge in abdominal wall surgery despite advances in mesh-based repair techniques and minimally invasive approaches. Although pelvic skeletal morphology has been implicated in inguinal hernia development, its association with recurrent disease remains incompletely understood. This study aimed to evaluate computed tomography (CT)-derived pelvic morphometric parameters and investigate their potential value in preoperative recurrence risk assessment. METHODS: This retrospective study included 251 male patients with preoperative abdominal CT examinations and complete clinical records who underwent elective inguinal hernia repair at a tertiary referral center. After applying the predefined eligibility criteria, 188 patients with unilateral inguinal hernias constituted the primary study cohort, including 162 primary and 26 recurrent unilateral hernias. The Radoievitch angle and Ami's line were measured independently by two blinded radiology residents using a standardized CT-based pelvic morphometric measurement protocol, and the mean values were used for analysis. Multivariable logistic regression and receiver operating characteristic (ROC) curve analyses were performed to evaluate the association between pelvic morphometric parameters and recurrent inguinal hernia. RESULTS: Patients with recurrent unilateral inguinal hernias demonstrated significantly greater affected-side Ami's line measurements (8.27 ± 0.63 vs. 7.90 ± 0.71 cm, p = 0.014) and larger Radoievitch angles (40.68 ± 4.02° vs. 38.80 ± 3.68°, p = 0.018) than patients with primary unilateral hernias. Both the Radoievitch angle (OR 1.14, 95% CI 1.01-1.28, p = 0.033) and Ami's line (OR 2.26, 95% CI 1.14-4.49, p = 0.020) remained independently associated with recurrent inguinal hernia after adjustment for age and body mass index. ROC analysis demonstrated modest discriminatory performance (AUC 0.634 for the Radoievitch angle and 0.633 for Ami's line), while the multivariable model incorporating age, body mass index, and Ami's line showed slightly improved discrimination (AUC 0.655). CONCLUSION: CT-derived pelvic morphometric parameters were independently associated with recurrent unilateral inguinal hernia. Although their individual discriminatory performance was modest, standardized CT-based pelvimetry may serve as an objective adjunctive tool for individualized preoperative recurrence risk assessment in patients who already undergo CT imaging for unrelated clinical indications. Prospective multicenter studies are warranted to validate these findings and determine their clinical applicability.

Humans↗

PubMed2026

Integrating histology and spatial transcriptomics via multimodal transformers and contrastive representation learning for accurate gene expression prediction.

Predicting spatial gene expression from Histological images is a fundamental task in understanding tissue organization and molecular phenotypes. However, existing methods often rely on single-model representations or lack effective alignment between image and transcriptomic features. To address these limitations, we propose a unified multimodal learning framework that integrates histological imaging and spatial transcriptomics through a shared latent representation space. Specifically, histological H&E images are encoded by a ResNet50-based convolutional stem and a MobileViT Transformer backbone to extract hierarchical visual representations. Both modalities are projected into a shared latent space via linear-GELU-dropout transformation blocks, enabling cross-modal alignment through a contrastive learning objective that maximizes agreement between the corresponding image and the spot embeddings. Experimental results on the 10x Genomics Visium dataset of human liver tissue demonstrate that MViTGene achieves significantly higher prediction accuracy than existing methods across multiple gene subsets, with improvements of 20%, 33%, and 12% in predicting marker genes, highly expressed genes, and highly variable genes, respectively. The significant improvement in relevance indicates that the model can more accurately capture the true correspondence between tissue morphology and gene expression, therefore enabling more reliable biological interpretation. It provides a computational tool for high-throughput spatial gene expression prediction that balances performance and interpretability.

Humans↗

PubMed2026

AI In Leukemia Diagnostics: Complementing the Pathologist's Role.

Artificial intelligence (AI) is reshaping every stage of leukemia diagnostics, from digital morphology and multiparameter flow cytometry to next-generation sequencing, multi-omics analysis, and emerging computational frontiers such as quantum-inspired feature selection. This review outlines how contemporary AI tools can automate labor-intensive quantitation, flag diagnostically salient patterns, and standardize interpretation, while the pathologist or hematologist retains authority over validation, context-specific integration, and clinical decision-making. We present an illustrative "human-in-the-loop" workflow that embeds AI modules within current laboratory information systems, emphasizing points where expert oversight mitigates algorithmic bias and resolves discordant findings. We further map the validator-integrator role across morphology, flow cytometry, and genomic/multi-omic interpretation and provide practical training competencies and use cases for AI-assisted hematopathology. Beyond technical deployment, the article addresses the educational transformation required for sustainable adoption. Drawing on international competency frameworks, including the Digital Health Competencies in Medical Education Framework and recently proposed AI-specific Entrustable Professional Activities, we map core skills that future hematopathologists must master: data-science literacy, critical appraisal of AI outputs, and ethical governance. We highlight evaluated training models such as the Pathology Informatics Essentials for Residents curriculum, Stanford Artificial Intelligence in Machine and Imaging workshops, and College of American Pathologists bootcamps and propose integration strategies adaptable across resource settings. By pairing rigorous validation with targeted education, AI can elevate rather than eclipse the diagnostic role of the leukemia specialist, enabling more timely, reproducible, and personalized patient care.

Humans↗

PubMed2025

Biophysical metabolic modeling of complex bacterial colony morphology.

Microbial colony growth is shaped by the physics of biomass propagation and nutrient diffusion and by the metabolic reactions that organisms activate as a function of the surrounding environment. While microbial colonies have been explored using minimal models of growth and motility, full integration of biomass propagation and metabolism is still lacking. Here, building upon our framework for computation of microbial ecosystems in time and space (COMETS), we combine dynamic flux balance modeling of metabolism with collective biomass propagation and demographic fluctuations to provide nuanced simulations of E. coli colonies. Simulations produced realistic colony morphology, consistent with our experiments. They characterize the transition between smooth and furcated colonies and the decay of genetic diversity. Furthermore, we demonstrate that under certain conditions, biomass can accumulate along "metabolic rings" that are reminiscent of coffee-stain rings but have a completely different origin. Our approach is a key step toward predictive microbial ecosystems modeling. A record of this paper's transparent peer review process is included in the supplemental information.

Models, Biological↗

PubMed2026

Beyond Morphology: Reframing Lymph-Node Metastasis Prediction Through Clonal Ecology-Decades-Long Genomic Instability and Polyclonal-to-Monoclonal Transitions as the Missing Dimension in Cancer.

Recent whole-genome, lineage-tracing, single-cell, and spatial studies have reshaped our understanding of tumor evolution, revealing that cancers can arise from polyclonal populations, undergo decades-long genomic instability before clinical detection, and progress through dynamic changes in subclonal composition, cellular state, and ecological organization. These findings challenge the assumption underlying morphology-based prediction models that metastatic risk can be inferred from static histological features alone. Here, we revisit lymph-node metastasis prediction in colorectal cancer through clonal ecology, integrating computational pathology with evolutionary oncology. Drawing on the subclonal switchboard model proposed in 2012 and subsequent artificial intelligence (AI)-enabled approaches for tracking dominant and dormant subclones, we synthesize evidence that metastatic potential reflects clonal ancestry, evolutionary timing, spatial niche architecture, cellular plasticity, intercellular interactions, dormancy, and treatment-driven shifts in subclonal fitness. We define five complementary methodological pillars for operationalizing clonal ecology: single-cell transcriptomics for resolving rare subclones, evolutionary trajectories, and adaptive cell states; lineage tracing and phylogenetics for reconstructing clonal ancestry and divergence; spatial transcriptomics and genomics for mapping subclonal geography and tumor-stromal-immune interactions; longitudinal liquid biopsy surveillance for monitoring residual disease, clonal turnover, and emerging resistance; and AI-enabled multimodal integration for connecting histopathology, genomics, spatial biology, and longitudinal data into predictive ecological-state models. Multiple-instance learning and pathology foundation models provide scalable computational foundations for evolution-aware prediction. Translationally, dormant subclones represent actionable reservoirs of recurrence. A longitudinal clinical and experimental study of KMT2A-rearranged acute myeloid leukemia further supports central predictions of the subclonal switchboard framework by demonstrating treatment-associated shifts in subclonal dominance, persistence of cryptic adaptive programs, and ecological rewiring during resistance and relapse. We propose clonal ecology as a measurable dimension for extending morphology-driven prediction toward integrative models that anticipate evolutionary transitions, identify therapeutic windows, and proactively constrain adaptive tumor ecosystems before resistant or metastatic subclones achieve clinical dominance.

Humans↗

PubMed2026

The impact of absolute change in tibiofemoral morphology on patient reported outcome measures post total knee arthroplasty.

BACKGROUND: Reconstructing knee morphology and alignment is important for outcomes post total knee arthroplasty (TKA). Personalised alignment strategies are proposed to improve outcomes by replicating native alignment. However, how change in morphology affects patient outcomes is unclear. This study aimed to investigate the relationship between absolute change in morphological measures post-TKA and patient reported outcome measures (PROMs). METHOD: An observational analysis of a randomised clinical trial was conducted. Participants received preoperative and postoperative CT scans and completed PROMs at six-months post-TKA. Absolute change in hip-knee-ankle angle, medial proximal tibial angle, lateral distal femoral angle, non-weightbearing joint line convergence angle, tibial and femoral rotation, and posterior tibial slope (PTS) were calculated. PROMs included visual analogue scales of pain and satisfaction (0-100), Oxford Knee Score, Forgotten Joint Score, and the Kujala Score. Regression and principal component (PCA) analyses investigated relationships between PROMs and change in morphology. RESULTS: Sixty-one participants were included for analysis (61% women, age 66.9 ± 9.1 [mean ± SD] years, BMI 32.8 ± 6.8 kg/m2). The PCA demonstrated coronal, axial, and sagittal plane measures were interdependent, with over 65% of variability driven by change in tibial rotation (PC1) and the PTS (PC2). The regression analysis showed no relationships between morphological change and PROMs postoperatively. CONCLUSION: Tibiofemoral morphology was interrelated across coronal, axial, and sagittal planes. However, this study suggests absolute morphological change had minimal impact upon PROMs at six-months post-TKA. Future research should clearly distinguish between osteoarthritic versus prearthritic alignment and consider the influence of soft-tissue releases upon PROMs.

Humans↗

PubMed2026

Volumetric DNA microscopy for mapping spatial transcriptomes in three dimensions.

The architecture and function of biological systems are inherently three-dimensional, yet most existing spatial transcriptomic technologies remain restricted to thin tissue sections, limiting their capacity to resolve cellular organization and microenvironments within intact tissue volumes. To address this limitation, we developed volumetric DNA microscopy, a scalable, optics-free approach for spatial transcriptome profiling directly within intact biological specimens. The method encodes spatial information into DNA molecules that form a dense intermolecular network in situ, enabling the reconstruction of three-dimensional spatial relationships through short-read sequencing and computational analysis. Here we detail the complete workflow including in situ cDNA synthesis, spatial encoding through DNA nanoball formation, dual-scale proximity bridging between neighboring nanoballs and spatial reconstruction via geodesic spectral embedding. Sequencing libraries can be generated within 7-8 d by a competent graduate-level molecular biologist, followed by standardized downstream computational analysis. Because the workflow requires only routine molecular biology reagents and a benchtop sequencer, volumetric DNA microscopy provides a versatile platform for exploring genetic and morphological features in intact tissues.

Spatial Transcriptomics↗

PubMed2026

Pan-genomics and multi-omics for deciphering genetic variation and accelerating genetic improvement in ruminant livestock.

Livestock reference genomes have transformed the discovery of variants associated with production, reproduction, health, and environmental adaptation. Nevertheless, a single linear reference represents only one mosaic haplotype and incompletely captures sequence diversity within a species, particularly structural variants, copy-number changes, repeat-rich regions, and breed-specific sequences. Pangenomes address this limitation by integrating multiple high-quality assemblies or population-scale variants into a unified sequence or graph representation. Concurrently, multi-omics approaches connect genomic variation with transcriptomic, epigenomic, manuscriptproteomic, metabolomic, and microbiome responses, thereby improving biological interpretation of genotype-phenotype relationships. This review synthesizes recent progress in livestock pangenomics and multi-omics, with emphasis on cattle, goats, sheep, water buffalo, and chickens. It describes advances in long-read and haplotype-resolved sequencing, graph construction, structural-variant discovery and genotyping, functional annotation, and integrative analysis. Recent pangenome studies have uncovered substantial non-reference sequence, reduced reference bias, identified breed- and population-specific structural variants, and resolved candidate variants underlying pigmentation, body size, tail morphology, cashmere production, altitude adaptation, and other economically relevant traits. However, translation into routine breeding remains constrained by uneven population representation, inconsistent structural-variant definitions, limited functional annotation, computational demands, and insufficient validation across environments. Future progress will depend on diverse near-complete assemblies, graph-aware imputation and genomic prediction, long-read transcriptomics, single-cell and spatial omics, rigorous causal validation, and open, interoperable resources. Together, these developments can support more accurate, resilient, and biologically informed livestock improvement. Importantly, current dairy-cattle evidence indicates that pangenome-derived structural variants can substantially improve variant discovery and functional interpretation while yielding only marginal average gains in routine genomic prediction, favoring targeted augmentation rather than wholesale replacement of established SNP-based evaluations.

Animals↗

PubMed2024

Foraging mechanisms in excavate flagellates shed light on the functional ecology of early eukaryotes.

The phagotrophic flagellates described as "typical excavates" have been hypothesized to be morphologically similar to the Last Eukaryotic Common Ancestor and understanding the functional ecology of excavates may therefore help shed light on the ecology of these early eukaryotes. Typical excavates are characterized by a posterior flagellum equipped with a vane that beats in a ventral groove. Here, we combined flow visualization and observations of prey capture in representatives of the three clades of excavates with computational fluid dynamic modeling, to understand the functional significance of this cell architecture. We record substantial differences amongst species in the orientation of the vane and the beat plane of the posterior flagellum. Clearance rate magnitudes estimated from flow visualization and modeling are both like that of other similarly sized flagellates. The interaction between a vaned flagellum beating in a confinement is modeled to produce a very efficient feeding current at low energy costs, irrespective of the beat plane and vane orientation and of all other morphological variations. Given this predicted uniformity of function, we suggest that the foraging systems of typical excavates studied here may be good proxies to understand those potentially used by our distant ancestors more than 1 billion years ago.

Flagella↗

PubMed2026

Chronic disease in a 15th-century skeleton from the first European settlement of the Canary Islands: Early evidence in the colonial Atlantic expansion (San Marcial de Rubicón, Lanzarote).

OBJECTIVE: This study seeks to evaluate morphological changes in a skeleton recovered from San Marcial de Rubicón, the earliest permanent European settlement in the Canary Islands. MATERIALS: The individual derives from a primary inhumation dated to the early fifteenth century. METHODS: Macroscopic observation was combined with conventional radiography, computed tomography, and mitochondrial DNA analysis. A systematic differential diagnosis considered metabolic, infectious, inflammatory, neoplastic, and degenerative conditions. RESULTS: The individual under investigation is an adult male with evidence of diffuse cortical thickening, periosteal new bone formation, heterogeneous radiodensity, cranial diploic expansion, long-bone bowing, severe degenerative joint disease, sacroiliac ankylosis, and elongated thoracic vertebral defects. Mitochondrial DNA analysis identified haplogroup X2c1, consistent with European maternal ancestry. CONCLUSIONS: The overall pattern is most consistent with polyostotic Paget disease of bone, although coexisting axial ankylosis and vertebral defects complicate the interpretation. These additional lesions are insufficient to support an alternative primary diagnosis. SIGNIFICANCE: This case provides an early extra-European archaeological example of Paget disease in the context of Atlantic colonial expansion. Rather than simply extending the geographic record of the disease, it shows how chronic skeletal conditions with strong European clinical and archaeological associations may be identified in frontier populations formed through mobility, settlement and colonial interaction. LIMITATIONS: The diagnosis is based on a single individual, and nuclear DNA data were insufficient to assess genetic susceptibility. SUGGESTIONS FOR FURTHER RESEARCH: Further radiological, genomic, and isotopic analyses of early colonial skeletal assemblages are needed to evaluate chronic disease, mobility, and biological diversity in Atlantic frontier populations.

Male↗

PubMed2026

Development of the zebrafish foveal analogue: a quantitative atlas of high-acuity zone growth and retinal regionalisation.

The vertebrate retina contains specialised regions for high-acuity vision, exemplified by the human fovea and its zebrafish analogue, the high-acuity zone (HAZ). Despite the widespread use of zebrafish to model retinal disease, a stage-resolved quantitative reference describing normal eye, photoreceptor layer (PRL) and lens growth has been lacking. Here, we apply contrast-enhanced micro-computed tomography (micro-CT) to construct the first three-dimensional micro-CT normative atlas of wild-type zebrafish eye development across five larval stages [3, 5, 7, 10 and 18 days post-fertilisation (dpf)], mapping circumferential PRL thickness, eye and lens morphology, and compartment growth rates. Regional PRL thickening within the temporo-ventral region of the expected HAZ emerged by 5 dpf and was sustained by a localised redistribution of growth, persisting and extending towards the optic nerve through 18 dpf. The PRL, lens and eye grew through four phases, alternating between disproportionate PRL expansion and coordinated growth, while the eye remodelled from a nasal-dominant to a temporo-ventral-dominant form. This regional specialisation was protracted relative to gross ocular growth and could proceed independently of it, paralleling the extended postnatal maturation of the human fovea. This atlas provides a quantitative baseline for distinguishing disease-induced changes from normal variation, supporting zebrafish models of foveal hypoplasia and related disorders.

Animals↗

PubMed2026

Reassessing Semen Analysis: Clinical Insights Beyond Sperm Count and Motility.

BACKGROUND: Semen analysis (SA), recognized by the World Health Organization (WHO) as the cornerstone of male infertility evaluation, remains indispensable in reproductive medicine. However, advances in assisted reproductive technology (ART) and artificial intelligence (AI) have highlighted the limitations of relying solely on conventional semen parameters. OBJECTIVE: To critically review the evolving clinical role of SA by integrating conventional assessment with emerging functional, molecular, and computational approaches that improve diagnostic accuracy and individualized patient care. METHODS: A narrative review of contemporary evidence was conducted, focusing on conventional semen parameters, biofunctional sperm testing, omics technologies, AI-assisted analysis, and broader clinical applications of SA. RESULTS: Conventional parameters, including sperm concentration, motility, and morphology, remain essential but inadequately reflect fertilizing capacity. Adjunctive assessments, including oxidative stress biomarkers and sperm DNA fragmentation, provide valuable insights into sperm function and reproductive potential. Omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, deepen mechanistic understanding, while AI enhances diagnostic precision, reproducibility, and standardization. Beyond infertility evaluation, SA also supports male contraceptive assessment, natural conception, ART, and patient counseling. CONCLUSIONS: Integrating conventional SA with functional, molecular, and AI-driven diagnostics provides a comprehensive framework for evaluating male fertility, advancing precision reproductive medicine and personalized clinical management.

cryopreservation↗

PubMed2024

Adaptive or non-adaptive? Cranial evolution in a radiation of miniaturized day geckos.

Lygodactylus geckos represent a well-documented radiation of miniaturized lizards with diverse life-history traits that are widely distributed in Africa, Madagascar, and South America. The group has diversified into numerous species with high levels of morphological similarity. The evolutionary processes underlying such diversification remain enigmatic, because species live in different ecological biomes, ecoregions and microhabitats, while suggesting strikingly high levels of homoplasy. To underscore this evolutionary pattern, here we explore the shape variation of skull elements (i.e., cranium, jaw and inner ear) using 3D geometric morphometrics and phylogenetic comparative methods on computed tomography scans (CT-scan) of a sample encompassing almost all recognized taxa within Lygodactylus. The results of this work show that skull and inner ear shape variation is low (i.e., there is high overlapping on the morphospace) across geographic regions, macrohabitats and lifestyles, implying extensive homoplasy. Furthermore, we also found a strong influence of allometry shaping cranial variation both at intra and interspecific levels, suggesting a major constraint underlying skull architecture, probably as a consequence of its miniaturization. The remaining variation that is not allometric is independent of phylogeny and ecological adaptation and can probably be interpreted as the result of intrinsic developmental plasticity. This, in turn, supports the interpretation that speciation in this group is largely concordant with a non-adaptive hypothesis, which results mainly from vicariant processes.

Animals↗

PubMed2026

Three-Dimensional Fracture Mapping of the Terrible Triad of the Elbow: Morphological Characteristics and Clinical Implications.

BACKGROUND: The morphology of fractures in the terrible triad of the elbow (TTE) is complex, and precise management relies on a profound understanding of this morphology. This study aims to systematically analyze, for the first time, the distribution and morphological characteristics of TTE fracture lines using three-dimensional (3D) imaging technology. METHODS: Clinical data and thin-slice CT scans of 112 patients with TTE from January 2021 to December 2024 were retrospectively included. 3D fracture models were reconstructed using Mimics software. Virtual reduction and standardized alignment were performed using 3-matic software. Fracture lines were mapped onto standard ulnar and radial templates, and 3D fracture heat maps were generated using the E-3D software to demonstrate the high-frequency distribution zones of the fracture lines visually. Statistical analysis was performed using SPSS software (version 21.0, IBM Corp., Armonk, NY, USA). Continuous variables were compared using one-way analysis of variance (ANOVA), and categorical variables were compared using the chi-square test (χ2 test). A two-tailed p < 0.05 was considered statistically significant. RESULTS: The study revealed distinct patterns in the distribution of TTE fracture lines. In the coronoid process, the fracture "hot zone" presented as an annular high-density band extending from the lateral middle aspect to the tip. In the radial head, an oblique high-density band was observed in the anterolateral quadrant of the articular surface. The radial neck exhibited a circumferential high-density zone, which was most prominent in the anterolateral aspect. Statistical analysis indicated a significant correlation between age and fracture complexity; the proportion of Regan-Morrey type III coronoid fractures and Mason type III radial head fractures was significantly higher in elderly patients (> 60 years) (p < 0.05), suggesting that advanced age is a significant risk factor for complex fractures. CONCLUSION: This study is the first to visually reveal the Collaborative Distribution Patterns of TTE fracture lines using 3D fracture mapping technology. This model provides morphological evidence for understanding the injury mechanism of TTE and offers an anatomical framework that may assist surgeons in individualizing surgical approaches and fixation strategies.

Humans↗