Young adulthood is a period of significant and unique physiological, psychological, sexual and social upheaval. Related challenges can have an impact on effective diabetes self-management, with high rates of unplanned healthcare use recorded for many, and consequent increases in the risks of premature morbidity and mortality.

To maximise insight from today's high throughput microscopy experiments, it is essential for a microscopist to familiarise themselves with the latest analysis software and undertake appropriate training. This can be challenging, however, due to the rapid development of software in the field, which often has complex installation steps and requires computational resources or storage beyond the capacity of personal computers. Cloud platforms running software containers remove these barriers, particularly when the platform is customised to specific end-user needs. We have developed a platform for the Volume Electron Microscopy community, Ada-vEM, that aims to lower barriers to evaluating and adopting new software for tasks such as registration and segmentation, while also providing a mechanism to streamline the provision of training. We describe the architecture of the platform and the underlying methods that enable rapid, scalable deployment of software and courses, together with its use for the delivery of remote training. We provide guidance on good practice, and hope that our experience can serve as an exemplar for other projects.

At barrier tissues such as the skin and gut, sensory neurons interface with environmental stimuli and coordinate with neighboring epithelial and immune cells to detect tissue perturbations. In teeth, however, the sensory dentin-pulp complex is insulated from the oral environment by highly mineralized enamel. Although dentin-pulp responses to severe injury have been studied in models with direct pulp exposure, it remains unclear whether enamel barrier dysfunction alone alters pulpal and neuronal homeostasis. Using a kallikrein-related peptidase 4 knockout (KLK4 KO) mouse model of enamel hypomineralization, we demonstrated that defective enamel induced structural, molecular, and transcriptional responses in the dental pulp and in the trigeminal system innervating teeth, despite the absence of direct pulp exposure to the oral cavity. Hypomineralized molars exhibited increased reactionary dentin formation accompanied by retraction of sensory afferents from the dentin-pulp junction. Consistent with these structural findings, trigeminal ganglia of KLK4 KO mice displayed upregulation of genes associated with cytoskeletal remodeling and stimulus response pathways. Despite increased bacterial burden and biofilm accumulation on the enamel surface, enamel hypomineralization did not induce substantial innate immune responses in the pulp. In addition, following severe dental pulp injury, teeth with hypomineralized enamel exhibited reduced sensory afferent loss and tissue damage. Together, these findings reveal that enamel integrity functions as a critical regulator of dentin-pulp homeostasis and that barrier dysfunction alone can precondition tissue responses to subsequent injury.

Urinary extracellular vesicles (uEVs) are promising non-invasive biomarkers of renal physiology and pathology; however, their temporal excretion patterns and optimal normalization strategies remain incompletely defined, particularly because urine concentration varies diurnally. This basic physiology study used a uniquely designed protocol of urine collection to characterize 24-hour variation in uEV excretion and cargo in thirteen healthy adults collected every void over 24 hours. Each void and a representative 24-hour collection sample were analyzed. uEVs were enriched by low-speed centrifugation with three buffer washes to deplete uromodulin. uEV size, concentration, morphology and cargo were characterized with nanoparticle tracking analysis, cryo-electron microscopy, immunoblotting and single EV flow cytometry. uEV concentrations varied up to 100-fold between individuals, ranging from 6.2 * 10[6] to 4.5 * 10[9] particles/mL. The relationship between urine flow and uEV excretion varied significantly across the day. uEV concentration was positively associated with urine creatinine, specific gravity, and TSG101 EV cargo signal, allowing normalization of uEVs to urine creatinine and TSG101. Normalized uEV cargo markers exhibited substantial within individual variation without consistent interindividual trends. When voids were grouped into predefined time periods, sodium chloride cotransporter (NCC) normalized to TSG101 showed a transient dip at noon followed by a significant increase in the next period, indicating a temporal excretion pattern. TSG101 signal didn't vary significantly over the day and was notably positively correlated with uEV excretion rate. These findings offer insight into uEV excretion patterns and highlight the importance of normalization, methodological design, and temporal patterns in advancing uEV biomarker research.

Antibiotic prophylaxis decision-making in endodontics represents a core competency in dental education, requiring the integration of systemic risk assessment, guideline interpretation, and antimicrobial stewardship principles. Although artificial intelligence (AI) tools such as ChatGPT are increasingly accessed by students and clinicians for clinical guidance, their educational reliability in teaching evidence-based antibiotic prophylaxis remains unclear. This descriptive study evaluated the accuracy and guideline concordance of ChatGPT-5 responses to predefined clinical scenarios in endodontics. Seventeen clinically relevant questions grounded in current guidelines from the American Heart Association (AHA), American Association of Endodontists (AAE), and American Dental Association (ADA) were submitted to the model. Responses were independently assessed by an experienced endodontist using a five-point Likert scale addressing clinical correctness, guideline concordance, and potential educational risk. Quantitative agreement was summarized descriptively, and a directed qualitative content analysis examined patterns of correct indication, expanded indication, depth of clinical reasoning, and risk of misinterpretation from an educational perspective. ChatGPT demonstrated full agreement with expert, guideline-based recommendations in 10 of 17 scenarios (58.8%), particularly in classical teaching domains such as infective endocarditis prophylaxis, antibiotic selection, dosage, and timing. Partial agreement was observed in four scenarios (23.5%), primarily due to unnecessary expansion of prophylactic indications. Disagreement occurred in three scenarios (17.6%), mainly involving immunocompromised conditions, including HIV infection with low CD4 counts and chemotherapy-related neutropenia. Although no response was deemed clinically unsafe, expanded recommendations in medically complex cases represented a potential educational risk for inappropriate antibiotic prescribing. The study supports cautious, guideline-based interpretation of AI-generated clinical information rather than conclusions about educational effectiveness or curricular implementation.

Epithelial-mesenchymal transition (EMT) of medial edge epithelial cells is a critical mechanism underlying embryonic palatal fusion, driven by transforming growth factor beta 3 (TGF-β3). However, its regulatory interplay with pluripotency factors (SOX2/OCT4) and reliance on downstream cascades remain poorly understood. This study investigates these networks to elucidate the mechanisms of cellular reprogramming during palatogenesis. Embryonic day 15 C57BL6/J mouse palatal epithelial cells were isolated to eliminate mesenchymal interference. Cells were subjected to recombinant TGF-β3 (1, 3, 10 ng/mL) or targeted siRNA knockdowns of Tgfb3, Sox2, Oct4, and Smad2/3, and evaluated via RNA sequencing, qRT-PCR, immunofluorescence, TEER, and flow cytometry. Treatment with 1-3 ng/mL TGF-β3 successfully induced EMT in vitro, characterized by decreased E-cadherin, increased fibronectin, diminished membrane resistance, and a fibroblast-like morphological shift. This transition was predominantly associated with non-canonical pathways; phosphorylated Smad2/3 levels remained unchanged while Smad-independent mediators (p38 MAPK and Mmp13) were upregulated (p<0.05). Furthermore, TGF-β3 downregulated the pluripotency markers Sox2 and Oct4 (p<0.05). Combined Sox2/Oct4 knockdown with TGF-β3 yielded the most pronounced EMT characteristic. While Tgfb3 knockdown heavily attenuated EMT, partial mesenchymal transition persisted, indicating redundant compensatory networks. In conclusion, optimal TGF-β3 concentrations (1-3 ng/mL) shift EMT toward Smad-independent pathways during palatogenesis. This reprogramming requires TGF-β3 to suppress SOX2 and OCT4, underscoring their roles as negative regulators of EMT during palatal fusion.

There is a strong need to quantify skin mechanical properties for flap design in plastic surgery, such as syndactyly reconstruction. Quantitative measurement of skin mechanical properties enables more accurate surgical planning, thereby improving surgical outcomes and reducing complications. Although a large number of methods and devices have been proposed, nearly none of them have been applied in surgical practice. We therefore conducted a comprehensive narrative review of the literature published from 1969 to the present on in vivo skin mechanical property measurement. To identify the factors limiting clinical application, studies using suction, indentation, torsion, stretching, non-contact, and computational approaches were screened and categorized based on their underlying mechanical assumptions and boundary conditions. Three fundamental paradoxes limiting clinical translation were identified: (1) conventional engineering characterization requires destructive testing, which is incompatible with preserving intact skin for surgery; (2) in vivo measurements inevitably capture surrounding tissue boundary constraints rather than intrinsic skin mechanics; and (3) engineering analyses depend on stress-based parameters and skin thickness, whereas thickness is rarely considered in clinical flap planning. Furthermore, inverse numerical models, such as finite element analysis, rely on idealized assumptions that may not fully reflect complex, patient-specific surgical conditions. Rather than attempting to identify a universally accurate conventional measurement device, this review proposes a novel paradigm shift: combining non-invasive microstructural imaging with computer vision and machine learning to predict mechanical transition thresholds (e.g., collagen alignment and tangent modulus) directly from unstretched tissue, with the goal of enabling patient-specific, computational surgical flap planning.

Monitoring and evaluation of immunogenicity is important for biological therapeutics due to the potential impact of antibodies on safety and efficacy. A comprehensive immunogenicity assessment was conducted to support clinical development of lonapegsomatropin, a prodrug of somatropin, administered once weekly. Lonapegsomatropin is approved in the United States for pediatric and adult growth hormone deficiency (GHD), and in other countries for pediatric GHD. Lonapegsomatropin consists of somatropin, an inert methoxy polyethylene glycol carrier (mPEG), and a proprietary TransCon® linker that transiently binds somatropin to the carrier. Four dedicated immunoassays were developed, validated, and applied in a risk-based tiered approach to rigorously assess the immunogenicity of lonapegsomatropin in children with GHD. Samples collected from 298 children with GHD treated with lonapegsomatropin for up to six years were analyzed for anti-drug antibodies (ADAs) against lonapegsomatropin (intact prodrug), released somatropin, and mPEG. Treatment-emergent anti-lonapegsomatropin, anti-somatropin, and anti-mPEG binding antibodies were detected in 4.7%, 5.4%, and 0.7% of treated children, respectively. ADA responses were low titer, transiently detected, and primarily observed within the first year of treatment, and no neutralizing antibodies were detected. These findings support the long-term low immunogenicity of lonapegsomatropin in children with GHD, consistent with somatropin. Importantly, the multi-assay tiered strategy applied here was robust and reproducible, enabling sensitive detection of ADAs against the intact prodrug, mPEG, and released somatropin across trials, and demonstrated its clinical applicability for evaluating a complex long-acting growth hormone like lonapegsomatropin.

Signal-to-noise ratio (S/N) has emerged as a practical alternative to endpoint titer for evaluating anti-drug antibody (ADA) response magnitude. When titration is not performed, a scientifically justified threshold is needed to interpret longitudinal increases in S/N, particularly for identifying treatment-boosted ADA responses in subjects with pre-existing ADA. In conventional titer-based assessments, treatment-boosted responses are typically defined by an increase of two dilution steps relative to the pre-dose titer. In the absence of titer testing, an alternative threshold is needed to determine whether a post-dose/pre-dose increase in S/N exceeds expected analytical variability. This study evaluated minimum significant ratio (MSR) as a project-specific, analytical variability-based threshold for treatment-boosted ADA response classification using S/N. Two MSR calculation approaches were assessed across 11 validated clinical ADA assays representing diverse assay formats, therapeutic modalities, and analytical platforms. MSRPOS was derived from inter-assay precision data using positive controls, whereas MSRNEG was derived from ADA-negative individual samples and negative-control data generated during assay validation. Retrospective clinical ADA data from two projects were analyzed to compare longitudinal titer ratios with S/N ratios and evaluate treatment-boosted classifications using conventional titer-ratio and MSR-based S/N approaches. Longitudinal titer ratios and S/N ratios were strongly correlated, and MSR-based classifications were broadly consistent with conventional titer-ratio-based classifications. Compared with MSRPOS, MSRNEG showed higher positive percent agreement while maintaining high negative and overall percent agreement. Overall, these findings support MSR as a practical, project-specific, and statistically justified analytical framework for applying S/N to longitudinal treatment-boosted ADA response characterization.

Type 1 diabetes (T1D) is a progressive autoimmune disease with identifiable presymptomatic stages. Islet autoantibody screening, expanded in Italy by Law 130/2023, identifies children and adults at high risk of progression. Structured longitudinal follow-up is needed to characterise disease trajectories, reduce diabetic ketoacidosis (DKA) at diagnosis and identify candidates for emerging disease-modifying therapies such as teplizumab.

Mutations in the Iduronate 2-sulfatase (IDS) gene cause Hunter syndrome (also known as mucopolysaccharidosis type II, or MPS II), a rare genetic condition that causes glycosaminoglycans (GAGs) to accumulate. Although enzyme replacement therapy (ERT) is the usual course of treatment, it can cause immunological reactions, such as the generation of IgE antibodies specific to the drug, which can result in hypersensitivity reactions. In this study, an ELISA-based test for characterizing anti-idursulfase beta IgE antibodies in human serum was developed and its analytical feasibility was validated. The complex challenges of generating antibodies against the IgE isotype using conventional methods make it difficult to generate an appropriate positive control antibody for IgE-specific tests. In order to overcome this difficulty, Anti-IDS IgG and Human IgE antibodies were chemically linked to generate IgG-IgE conjugate antibodies. Using this conjugated IgG-IgE positive control antibody, we developed the assay and validated it following immunogenicity guidelines, assessing validation parameters such as cut point, sensitivity, specificity, selectivity, precision, drug tolerance, and stability. The results demonstrate the methodological suitability of this assay for IgE isotype characterization.