Type 1 diabetes (T1D) is an autoimmune condition characterized by the destruction of insulin-producing pancreatic beta cells, leading to lifelong insulin dependence and significant complications. Early detection of T1D is essential to delay disease onset and improve outcomes. Recent advancements in artificial intelligence (AI) and machine learning (ML) have provided powerful tools for predicting and diagnosing T1D. This systematic review evaluates the current landscape of AI/ML-based approaches for early T1D detection. A comprehensive search across PubMed, EMBASE, Science Direct, and Scopus identified 1447 studies, of which 10 met the inclusion criteria for narrative synthesis after screening and full-text review. The studies utilized diverse ML models, including logistic regression, support vector machines, random forests, and artificial neural networks. The datasets encompassed clinical parameters, genetic risk markers, continuous glucose monitoring (CGM) data, and proteomic and metabolomic biomarkers. The included studies involved a total of 49,172 participants and employed case–control, retrospective cohort, and prospective cohort designs. Models integrating multimodal data achieved the highest predictive accuracy, with area under the curve (AUC) values reaching up to 0.993 in sex-specific models. CGM data and plasma biomarkers, such as CXCL10 and IL-1RA, also emerged as valuable tools for identifying at-risk individuals. While the results highlight the potential of AI/ML in revolutionizing T1D risk stratification and diagnosis, challenges remain. Data heterogeneity and limited model generalizability present barriers to widespread implementation. Future research should prioritize the development of universal frameworks and real-world validation to enhance the reliability and clinical integration of these tools. Ultimately, AI/ML technologies hold transformative potential for clinical practice by enabling earlier diagnosis, guiding targeted interventions, and improving long-term patient outcomes. These advancements could support clinicians in making more informed, timely decisions, thus reducing diagnostic delays and paving the way for personalized prevention strategies in both pediatric and adult populations.

Background: As no evidence-based treatment guidelines exist for chronic Achilles tendon rupture (CATR), a systematic review of the literature was performed to compare the different treatment options and recommend a literature-based algorithm. Methods: In June 2022, MEDLINE, Embase, and Cochrane Library databases were systematically reviewed based on the PRISMA guidelines. The level of evidence (LOE) and quality of evidence were evaluated, and statistics on clinical outcomes and complications were calculated. Results: Twenty-seven studies with 614 patients were included. Three studies were LOE III and 25 studies were LOE IV. The mean Achilles tendon rupture score improved from a preoperative weighted mean of 38.8 ± 12.4 to a postoperative score 90.6 ± 4.7. The overall complication rate was 11.4%. Single techniques were used in 23 studies and dual techniques were used in 5 studies. The FHL tendon transfer was the most frequently used technique. We devised an algorithmic approach based on time from injury to surgical intervention and the length of the gap between the tendon stumps: >3 months: FHL transfer; <3 months (a) gap 5 cm, semitendinosus autograft. Conclusion: Surgical management of CATR produced improvements in patient-reported outcome scores at midterm follow up, but a high complication rate (11.4%) was noted. Our proposed treatment algorithm may assist in shared decision making for this complex problem.

Post-traumatic osteoporosis (PTO) presents a significant challenge in clinical practice, characterized by demineralization and decreased skeletal integrity following severe traumatic injuries. This literature review manuscript addresses the knowledge gaps surrounding PTO, encompassing its epidemiology, pathophysiology, risk factors, diagnosis, treatment, prognosis, and future directions. This review emphasizes the complexity of the etiology of PTO, highlighting the dysregulation of biomineralization processes, inflammatory cytokine involvement, hormonal imbalances, glucocorticoid effects, vitamin D deficiency, and disuse osteoporosis. Moreover, it underscores the importance of multidisciplinary approaches for risk mitigation and advocates for improved diagnostic strategies to differentiate PTO from other musculoskeletal pathologies. This manuscript discusses various treatment modalities, including pharmacotherapy, dietary management, and physical rehabilitation, while also acknowledging the limited evidence on their long-term effectiveness and outcomes in PTO patients. Future directions in research are outlined, emphasizing the need for a deeper understanding of the molecular mechanisms underlying PTO and the evaluation of treatment strategies’ efficacy. Overall, this review provides a comprehensive overview of PTO and highlights avenues for future investigation to enhance clinical management and patient outcomes.

High expression of MYC and its target genes identify germinal center B-cell diffuse large B-cell lymphomas (GCB-DLBCL) associated with poor outcomes. We used CRISPR-interference profiling of human lymphoma cell lines to define essential enhancers in the MYC locus and non-immunoglobulin rearrangement partner loci, including a recurrent rearrangement between MYC and the BCL6 locus control region. GCB-DLBCL cell lines without MYC rearrangement were dependent on an evolutionarily conserved enhancer we name “GC B cell MYC enhancer 1,” which was found to be activated by the transcription factor complex of OCT2, OCA-B, and MEF2B, showed an active chromatin state in normal human and mouse GC B cells, and demonstrated selective acetylation and MYC promoter topological interactions in MYC-intact GCB-DLBCL biopsies. Whole-genome sequencing identified tandem copy gains of GC MYC enhancer 1 as a rare but recurrent event in DLBCL. Our findings shed new light on mechanisms that dysregulate MYC, a key driver of B-cell malignancy. Significance: Aberrant MYC activity defines the most aggressive GCB-DLBCLs. We characterized a mechanism of MYC transcriptional activation via a native enhancer that is active in MYC-intact GCB-DLBCL, establishing fitness-sustaining cis- and trans-regulatory circuitry in GCB-DLBCL models that lack MYC enhancer-hijacking rearrangement. See related commentary by Mulet-Lazaro and Delwel, p. 149

We present a case of calcaneal reconstruction after both an improvised explosive device injury and subsequent salvage procedures left the patient with a large calcaneal defect and damaged hindfoot soft tissue. A subtalar arthrodesis was performed with a femoral head allograft, where it was fused to the remaining calcaneus and superiorly through the talus, to successfully reconstruct this defect. Demineralized bone matrix, bone morphogenetic protein, and concentrated bone marrow aspirate were also added as adjuncts to promote bone remodeling. At final follow-up, the patient denied pain, was fully weight-bearing, and had resumed an active lifestyle. Level of Evidence: Level V, Case Report

Supplementary figures S1-S7, showing additional information relevant to the corresponding main figure.