Citations

Aims: To synthesise and critically appraise evidence on artificial intelligence (AI) and multimodal data approaches for diagnosis, prognosis, and treatment decision support in diffuse large B-cell lymphoma (DLBCL) and acute myeloid leukaemia (AML), and to compare how disease biology shapes model design and clinical readiness. Study Design: Systematic review with narrative synthesis. Place and Duration of Study: PubMed/MEDLINE, Embase, Scopus, Web of Science Core Collection, IEEE Xplore, and the Cochrane Library were searched from database inception to 29 July 2026. Methodology: English-language original studies involving human participants, clinical images, human-derived samples, or patient-derived datasets were eligible. Two reviewers independently screened records, assessed full texts, and extracted study characteristics, data modalities, analytical methods, validation approaches, and performance measures. PROBAST+AI domains were used to guide appraisal of eligible patient-level prediction models; exploratory multi-omics, molecular-subtyping, biomarker-discovery, and segmentation studies underwent structured descriptive appraisal. TRIPOD+AI informed assessment of reporting completeness. Owing to substantial clinical and methodological heterogeneity, findings were synthesised narratively. Results: Twenty-eight studies were included: 22 on DLBCL and six on AML. DLBCL research was dominated by PET/CT radiomics, deep imaging, digital pathology, and imaging-clinical-molecular fusion. Internally evaluated diagnostic models reported area under the curve values as high as 0.999, whereas externally validated prognostic models achieved values of 0.66-0.71 and showed inconsistent incremental improvement over the International Prognostic Index. AML studies mainly integrated genomic, transcriptomic, epigenomic, single-cell, proteomic, metabolic, and functional drug-response data. Prognostic models reported concordance indices of 0.72-0.81 and time-dependent area under the curve values of 0.795-0.899. The most frequent methodological concerns were retrospective sampling, high-dimensional modelling in modest cohorts, incomplete calibration reporting, and limited independent validation. Treatment-response models in both diseases remained retrospective or exploratory, and none demonstrated improved outcomes through AI-guided treatment allocation. Conclusion: AI and multimodal data approaches show greatest maturity for prognostic stratification, but diagnostic replacement and treatment selection remain unproven. Prospective, multicentre clinical-impact validation is the principal requirement for translation into routine care.

Abstract The management of diverticular disease has undergone a major evolution over the past two decades, shifting away from episode-count triggers for surgery toward individualized strategies informed by patient-reported outcomes, recurrence risk, and high-quality randomized clinical trials. Pivotal decision analyses and randomized trials have reshaped the surgical treatment landscape, while parallel trials of antibiotic therapy have transformed the nonoperative management of uncomplicated disease. In this study, we provide a comprehensive synthesis of historical perspectives and modern evidence regarding the surgical and nonoperative management of diverticulitis, summarize key randomized trials across the disease spectrum, describe the evolution of operative techniques, and translate these findings into actionable guidance, including a patient-centered decision aid. A structured narrative review of pivotal trials, major guidelines, and multicenter randomized studies were performed, encompassing trials of antibiotic therapy for uncomplicated diverticulitis, laparoscopic lavage for perforated disease, operative strategy for complicated disease, elective resection versus conservative therapy for recurrent or persistent symptoms, and the evolution of minimally invasive and robotic surgical techniques. Trial design, eligibility, interventions, outcomes, and limitations were extracted and synthesized. The traditional “two-episode rule” has been supplanted by individualized, symptom- and quality of life (QoL)-driven decision-making. Routine antibiotic therapy for uncomplicated diverticulitis is not supported by randomized evidence and is now reserved for select patients. Laparoscopic lavage, initially promising for perforated diverticulitis, demonstrates variable outcomes and is now reserved for selected patients with Hinchey III disease; when resection is required, primary anastomosis with diverting ileostomy is increasingly favored over Hartmann's procedure because of markedly higher stoma reversal rates. Randomized trials of elective sigmoid resection show reduced recurrence and improved QoL for patients with persistent symptoms, though not universally across all patient groups, and minimally invasive-particularly robotic-surgical techniques continue to reduce perioperative morbidity. Contemporary management of diverticulitis requires individualized evaluation anchored in patient-reported outcomes, disease phenotype, comorbidity, and shared decision-making. This study synthesizes the current evidence and provides clinic-ready decision aid for patient discussions.

Background. Rare diseases collectively affect an estimated 300 million people worldwide, yet patients wait an average of 4-8 years for a correct diagnosis after visiting multiple physicians, accumulating unexplained findings, and suffering preventable disease progression before a unifying diagnosis is reached. Electronic health records (EHRs) capture this pre-diagnostic trajectory in rich detail, but conventional methods typically collapse years of longitudinal phenotypic signals into a single static snapshot; our approach instead models this temporal structure directly. Methods. We conducted a retrospective cohort study using longitudinal EHR data from approximately 3 million patients at Mayo Clinic Platform_Accelerate. Cases were patients with confirmed diagnoses of 10 rare diseases; controls (~5,200 per disease) had no record of any rare disease. HPO phenotype terms were extracted from clinical notes and laboratory results using a medspaCy NLP pipeline; ICD codes were grouped at three-character level. We developed and trained two temporal models, GRU-Attn and Conformer, that encode patient histories as quarterly time-binned sequences spanning up to 30 years, and compared these against three static baselines (CatBoost, XGBoost, logistic regression). Models were evaluated systematically at prediction horizons h = 1-10 years before diagnosis. Results. In the full held-out cohort benchmark, temporal models outperformed static baselines across the large majority of diseases and prediction horizons, with the advantage widening substantially as the horizon lengthened. At 1-2 years prior to diagnosis, mean AUROC was 0.928 (GRU-Attn) versus 0.871 (CatBoost); at 6-10 years prior to diagnosis, 0.726 versus 0.693, with static models degrading to near-chance for some diseases. Combining HPO and ICD features yielded the strongest performance, with a mean gain of +0.063 AUROC over the best single source at 1-2 years prior to diagnosis. Separately, in a manually curated cohort of 143 confirmed-undiagnosed cases with extended EHR histories, GRU-Attn identified 138 cases before first disease mention and all 143 cases before formal diagnosis at the prespecified 99th-percentile specificity threshold, with median lead times of 1.1-8.3 years and 1.9-21.7 years, respectively. Conclusions. By learning from the temporal trajectory of phenotypic signals rather than their static aggregate, temporal EHR models improved retrospective early detection performance across several rare diseases, most powerfully for conditions where pre-diagnostic findings accrue gradually and heterogeneously over years. These results show that longitudinal EHR trajectories carry rare-disease signal beyond static phenotypic burden and support prospective evaluation of temporal EHR modeling for rare-disease risk stratification.

Abstract Objectives To compare the efficacy and safety of pharmacologic therapies for spontaneous epistaxis in hereditary hemorrhagic telangiectasia (HHT). Data Sources PubMed, Scopus, Embase, Web of Science, and the Cochrane Library were systematically searched up to August 2025. Review Methods Eligible randomized controlled trials evaluating bevacizumab, doxycycline, tranexamic acid, or β‐blockers versus placebo or standard care were included. Outcomes included epistaxis frequency and duration, hemoglobin (Hb), epistaxis severity score (ESS), transfusion or emergent‐care requirements, quality of life (QOL), and adverse events. Results Tranexamic acid did not significantly reduce epistaxis duration or frequency or improve Hb, and it did not change transfusion or emergent‐care needs, but it increased diarrhea (odds ratio 3.8, 95% confidence interval [CI] [1.7; 8.5]). Bevacizumab produced a modest reduction in epistaxis frequency (standardized mean difference −0.25, 95% CI [−0.47; −0.02]), without significant effects on duration, ESS, Hb, or QOL. Doxycycline showed no significant benefit for duration or frequency. Topical or systemic β‐blockers did not significantly affect ESS, QOL, Hb, or overall adverse events. Across agents, between‐study heterogeneity was generally low to moderate and CIs were wide, reflecting limited sample sizes. Conclusion No pharmacologic agent demonstrated consistent, clinically robust superiority over placebo across primary endpoints. Bevacizumab may modestly reduce bleeding burden, whereas tranexamic acid increases gastrointestinal toxicity without clear efficacy. Pharmacologic control of HHT‐related epistaxis remains suboptimal, underscoring the need for adequately powered trials with standardized outcome measures and optimized dosing and delivery strategies.

Abstract Background Glioblastoma (GBM) represents the most common and aggressive central nervous system malignancy where overall survival is a dismal 14.6 months despite an aggressive standard of care treatment regimen that includes maximally safe surgical resection, radiotherapy, and temozolomide. It has recently been established that GBM tumors have increased transferrin receptor expression and iron content which corresponds with worse patient prognosis. This has led to the hypothesis that iron metabolism is a viable therapeutic target. An emergent therapeutic strategy to target GBM iron metabolism is gallium maltolate (GaM), which is an orally bioavailable form of Ga3+ that functions as a redox inactive iron mimic to disrupt iron metabolism. As mitochondrial iron metabolism serves as a central connection point between iron and DNA metabolism, the goal of this study was to determine if GaM could disrupt this system. Methods The effects of GaM on GBM cells were interrogated using conventional techniques including colony formation assays to assess clonogenicity, alkaline comet assays to evaluate DNA damage induction, and MitoFerro Green analysis to evaluate mitochondrial iron content. The effects of GaM on tumor growth in vivo were evaluated using a subcutaneous flank xenograft model system to determine the induction of DNA damage and an orthtopic model system to evaluate the combinatorial effects of GaM, radiation, and temozolomide on murine survival. Results This study uncovered that maintenance of high mitochondrial iron content corresponds with increased proliferative capacity in GBM cells. This study also shows that GaM can deplete mitochondrial iron to induce DNA damage both in vitro and in a subcutaneous xenograft model. Furthermore, GaM enhances the efficacy of radiation and temozolomide when delivered concomitant and adjuvantly in an orthotopic GBM model system. Conclusion These results suggest that GaM warrants further consideration for use in combination with standard of care GBM therapy.

Cholangiopathies comprise a heterogeneous group of chronic liver diseases characterised by progressive bile duct injury, ductular reaction and fibrotic remodelling. Despite distinct aetiologies, these disorders share common cellular stressors that ultimately converge on cholangiocyte dysfunction and loss. In this context, programmed cell death has emerged as a central mechanism linking epithelial stress, immune activation and the development of biliary fibrosis. A range of regulated cell death pathways, including apoptosis, necroptosis, pyroptosis, ferroptosis and autophagy-dependent cell death, can be triggered in cholangiocytes in a disease-dependent and context-dependent manner. Growing evidence suggests that these pathways rarely act in isolation. Instead, they intersect through shared molecular nodes, forming integrated cell death programmes such as PANoptosis. Importantly, it is becoming clear that not only overt cell death but also sublethal activation of death-related signalling can perpetuate cholangiocyte dysfunction and fuel chronic disease progression. Current therapeutic strategies, such as ursodeoxycholic acid and peroxisome proliferator-activated receptor agonists, mainly aim to modify bile composition and improve biochemical parameters. However, they do not directly target the molecular networks governing cholangiocyte death, which may partly explain their limited impact on fibrosis and long-term outcomes. In this review, we synthesise current knowledge on regulated cell death mechanisms in cholangiopathies, highlight key conceptual and technical challenges that complicate their interpretation and therapeutic targeting, and discuss how sublethal death signalling may connect with senescence to sustain cholangiopathy progression and shape therapeutic perspectives.

Abstract Skin and soft tissues infections (SSTIs) are common conditions, affecting millions worldwide. SSTIs range from uncomplicated cellulitis to necrotizing fasciitis and can be divided into non-purulent and purulent forms. Non-purulent SSTI is most commonly associated with beta-haemolytic streptococci, while purulent SSTI is typically associated with Staphylococcus aureus . Cellulitis most commonly presents with acute warmth, pain, tenderness to palpation, erythema, and oedema. Skin abscess typically presents with a fluctuant tender area with erythema. Laboratory testing is of limited use in most patients. Point-of-care ultrasound is useful for distinguishing cellulitis from abscess if the diagnosis is unclear. Management of SSTI includes antibiotics such as penicillin VK, dicloxacillin, or a cephalosporin, while treatment for skin abscess includes incision and drainage, with antibiotics recommended in select patients. Patients should elevate the affected extremity when possible, and non-steroidal anti-inflammatory drugs may reduce pain and inflammation. The effectiveness of decolonization for patients with recurrent cellulitis or skin abscess is controversial. While most patients with cellulitis or skin abscess are appropriate for discharge with follow-up, patients with sepsis and those with challenges adhering to therapy, immunosuppression, or failed outpatient therapy should be referred to the emergency department. Novel antibiotics such as tedizolid, delafloxacin, omadacycline, and ceftaroline may be considered in select cases.

Eye-tracking provides an objective measure of how observers direct visual attention to presented stimuli and has become an increasingly valuable tool in facial plastic surgery. It offers unique insight into how facial conditions and surgical interventions impact facial attention. A well-designed eye-tracking study can address patient questions about how others look at their face, identify targets for visual improvement, and objectively assess facial plastic surgery outcomes. Significant variability exists in eye-tracking study design and execution within facial plastic surgery, often producing data that are erroneous, difficult to interpret, or not generalizable to clinical practice. There are currently no guidelines for the design of eye-tracking studies in facial plastic surgery. Furthermore, the technical requirements for facial eye-tracking studies differ from those for non-facial studies. This article aims to synthesize the existing literature and authors’ experience to establish basic guidelines for designing eye-tracking studies in facial plastic surgery. We hope this guide will help investigators design high-quality eye-tracking studies to drive meaningful advances in the field of facial plastic surgery.