Citations

Abstract Patients at risk for progression from myeloid precursor states (idiopathic cytopenia of undetermined significance [ICUS] and clonal cytopenia of undetermined significance [CCUS]) to myelodysplastic syndrome (MDS) are not well defined. Epidemiologic risk factors, clonal changes for MDS development, and evolution from one MDS state to another were available in the MDS Natural History Study (NHS), a prospective cohort enrolled at diverse US sites. Extensive clinical data and biospecimens were collected at baseline and follow-up. A total of 1177 (56%) individuals with MDS or MDS-related precursor conditions (ICUS/idiopathic dysplasia of undetermined significance [IDUS], CCUS, and MDS/myeloproliferative neoplasm overlap) were enrolled and diagnosed in the MDS NHS. The median age was 74 years, with 89% aged ≥60 years, and most were male patients. Median follow-up time was 1.6 years and was similar among ICUS/IDUS, CCUS, and MDS. During follow-up period, 68% of participants terminated the study, 35% died, and 38% had disease progression. Using a refined clinical definition of progression, the greatest proportion of progression was observed among higher-risk-MDS (116 [73%]), followed by lower-risk-MDS (170 [52%]); fewer progression events were observed among participants with CCUS (65 [22%]) and ICUS/IDUS (46 [17%]). Predictors of progression are delineated, including female sex, higher quantity of mutations, the presence of TP53 mutation, and poor/very poor cytogenetic score. Based on these prospective data, guidelines for clinical management including monitoring and surveillance are outlined. The MDS NHS provides real-world data to illustrate how clinical and genotypic differences inform the classification, disease course, and approach to therapy, with informed monitoring guidelines for patients. This trial was registered at www.ClinicalTrials.gov as NCT02775383.

INTRODUCTION: High-quality colonoscopy requires accurate risk stratification for surveillance per the 2020 US Multi-Society Task Force guidelines and adherence to 2024 American College of Gastroenterology/American Society for Gastrointestinal Endoscopy quality benchmarks. Both are operationally challenging in clinical practice. We developed and validated Colon-Pilot, a large language model—powered clinical decision support system using GPT-4o to automate and standardize both functions. METHODS: The system was evaluated in 2 operational modes: (i) a human-in-the-loop clinical decision support validation of surveillance recommendations for 596 colonoscopies, comparing concordance with 2020 US Multi-Society Task Force guidelines against expert consensus, and (ii) an automated administrative audit applying Colon-Pilot to 42,632 colonoscopies across the Mayo Clinic Health System to calculate 2024 American College of Gastroenterology/American Society for Gastrointestinal Endoscopy priority quality indicators. Recommendations were autogenerated unless predefined safety criteria triggered manual review. RESULTS: Colon-Pilot issued recommendations for 522 of 596 cases (87.6%) and flagged 12.4% for manual review. For automated cases, guideline-concordant accuracy was 97.5% (Cohen κ = 0.970) versus 69.7% (κ = 0.781) for original endoscopist recommendations. Discordant artificial intelligence (AI) cases (n = 13) most often recommended longer-than-appropriate intervals (62%). Applied to the enterprise data set, Colon-Pilot calculated performance exceeding 2024 targets: adenoma detection rate 49.8% (≥35%), sessile serrated lesion detection rate 17.7% (≥6%), bowel preparation adequacy 91.8% (≥90%), and cecal intubation rate 97.4% (≥95%). DISCUSSION: Colon-Pilot demonstrated high fidelity in applying surveillance guidelines and automated quality benchmarking, outperforming unassisted endoscopists in guideline adherence. By combining safety protocols with large-scale automated reporting, it offers a scalable solution for improving both efficiency and quality in colorectal cancer prevention.

Purpose: Familial history of aortic disease has been associated with increased risk of aneurysm-related complications after standard endovascular aortic repair. The aim of this study was to evaluate outcomes of fenestrated-branched endovascular aortic repair (FB-EVAR) for complex aortic aneurysms in patients with or without familial aortic aneurysms (FAAs). Materials and Methods: We reviewed the clinical data of consecutive patients enrolled in a prospective non-randomized study to investigate outcomes after FB-EVAR for treatment of complex aortic aneurysms between 2013 and 2022. Familial aortic aneurysm was defined as occurrence of an aortic aneurysm or dissections in a first- or second-degree relative and compared with patients with sporadic aortic aneurysms (SAAs). Endpoints included procedural metrics, 30-day mortality and major adverse events (MAEs), mid-term patient survival, freedom from reintervention and endoleak, and aneurysm sac shrinkage. Results: There were 499 patients treated with FB-EVAR (70% males, mean age was 74±7.7 years) including 66 (13%) patients with FAAs and 434 (87%) with SAAs. Both groups had similar demographics, clinical characteristics, aneurysm extent, and prior history of aortic dissection or aortic repair. Patients with FAAs had longer fluoroscopy time (82 vs 71 minutes) and radiation exposure (1856 vs 1213 mGy; each p<0.05), with no difference in technical success (FAA, 94% vs SAA, 97%; p=0.51). There was no difference in 30-day mortality (1.5% vs 0.9%; p=1.00) and MAEs (23% vs 18%; p=0.44) among patients with FAA and SAA, respectively. Median follow-up was 28 months. At 3 years, patient survival, freedom from secondary interventions, and cumulative incidence of sac shrinkage were 76±2.5%, 74±2.5%, and 32±2.6% for all patients, respectively, with no difference between FAA and SAA groups. Conclusion: Fenestrated-branched endovascular aortic repair was performed with high technical success, low mortality, and low incidence of MAEs regardless of the presence of FAA. There was no difference in mid-term patient survival, secondary interventions, and sac changes among patients with or without family history of aortic disease. Clinical Impact This study demonstrates that fenestrated-branched endovascular aortic repair (FB-EVAR) can be performed with high technical success and comparable early and mid-term outcomes in patients with or without a familial history of aortic aneurysm, after exclusion of genetically triggered aortic diseases. These findings challenge the assumption that family history alone should preclude complex endovascular repair. Clinically, this supports broader use of FB-EVAR in carefully selected patients with familial aortic disease, emphasizing anatomical suitability rather than pedigree alone. The innovation lies in validating FB-EVAR as a safe alternative to open repair for this understudied population, informing patient selection, counseling, and surveillance strategies.

Chronic wounds remain a major unmet clinical challenge, often failing to progress to normal healing due to persistent inflammation, impaired angiogenesis, and cellular senescence. Exosomes have recently been investigated as promising acellular therapeutics capable of restoring intercellular communication and promoting tissue regeneration. Among these, the Purified Exosome Product (PEP) represents a next-generation, platelet-derived exosome formulation manufactured under Good Manufacturing Practice (GMP) conditions with high purity, stability, and reproducibility. This review summarizes the current advances in exosome-based chronic wound therapeutics and PEP delivery systems and their translational potentials. Incorporation of PEP into bioengineered carriers such as fibrin sealant, collagen scaffolds, and hyaluronic acid (HA) hydrogels enables localized and sustained exosome release, significantly prolonging therapeutic effects and improving regenerative outcomes. Fibrin-based PEP delivery achieved complete wound closure and functional skin regeneration in animal models, while collagen and HA-based systems showed promising results for injectable and dermatologic applications. Beyond its intrinsic healing effects, PEP may also serve as a nanocarrier for other drugs, offering a future direction in chronic wound management.

In this short report, we detail new data on the upper limits of human energy expenditure (9.6 times basal metabolic rate) and water turnover (10.5 L·12 h −1 ) during continuous single-day exercise in the cold. Our results indicated elevated energy use, and impressively, water turnover comparable to exercise in warmer conditions. These findings have implications for training and endurance performance of strenuous exercise in cold weather environments.

Background: A critical component of conducting systematic reviews or meta-analyses is assessing the methodological quality and bias of included studies. Several methodological quality assessment tools have been developed; however, these tools may not be relevant to observational sports medicine research, which carries numerous unique nuances and biases. Purpose: To develop the Sport Publication Observational Research Tool (SPORT), which evaluates and scores the methodological quality of observational sports medicine research. Study Design: Consensus statement. Methods: SPORT was developed through a modified Delphi approach involving members from the Herodicus Society and The FORUM. All active members were invited to participate in the process aimed at building consensus on SPORT content and scoring. After finalizing SPORT, a power analysis led to the independent selection of 55 observational clinical sports medicine studies, which were scored twice by 4 reviewers of varying training levels. Interrater and intrarater reliability for SPORT was assessed using intraclass correlation coefficients (ICCs). The distribution and percentiles for total SPORT score across the 55 studies were calculated. SPORT was also compared with the methodological index for non-randomized studies (MINORS), a commonly utilized quality assessment tool. Results: A total of 51 members participated and achieved 100%, 100%, 98.0%, and 98.0% completion rates for rounds 1 through 4, respectively. The final SPORT included 19 subscores related to methodological quality and bias and achieved 94% consensus approval. Mean SPORT completion time was 6 minutes and 19 seconds per study, which varied significantly by reviewer training level. The subscore "peer review" demonstrated unacceptable reliability and was removed. The remaining 18 subscores exhibited ICC ranges of 0.599 to 0.955 for interrater reliability and 0.530 to 0.936 for intrarater reliability. Total SPORT score demonstrated excellent agreement, for interrater (ICC, 0.967) and intrarater reliability (ICC, 0.966). Median SPORT score across the 55 studies was 20.0 and skewed toward lower scores. There was a moderate significant correlation between SPORT and MINORS ( r [53] = 0.575; P < .001). Conclusion: An objective tool to assess the methodologic quality of observational sports medicine research (SPORT) was successfully developed through a modified Delphi approach with numerous content experts in the field. This tool may be useful in assessing the methodological quality of primary observational sports medicine studies included in systematic reviews and meta-analyses.

GGGGCC (G 4 C 2 ) repeat expansion in C9ORF72 is the most common genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Toxicity is thought to result from the accumulation of either repeat RNAs and/or dipeptide repeat proteins (DPRs) translated from repeat-containing transcripts through repeat-associated non-AUG (RAN) translation. To disentangle RNA from DPR toxicity, we mutated a CUG codon predominantly used to initiate DPR translation from all three reading frames. This mutation disrupted DPR synthesis while preserving the expression of repeat-containing RNAs. Despite the accumulation of RNA foci, behavioral deficits and pathological abnormalities, including p-TDP-43 inclusions, STING activation, motor neuron loss, neuroinflammation, and increased plasma neurofilament concentration, were alleviated in C9ORF72 mice. Base editing of the CUG codon also improved molecular phenotypes and survival in patient induced pluripotent stem cell–derived neurons, which highlights the potential of therapeutically targeting DPR production rather than repeat RNAs.

Key Points Atrial fibrillation after kidney transplantation is common and is associated with poor prognosis. Artificial intelligence applied to 12-lead electrocardiograms pretransplant accurately predicts the risk of new-onset atrial fibrillation in our cohort. High-risk artificial intelligence electrocardiography score was independently associated with increased risk of mortality and allograft failure. Background Incident atrial fibrillation (AF) is common after kidney transplantation (KTx) and is associated with worse clinical outcomes. Artificial intelligence electrocardiography (AI-ECG) algorithms have demonstrated efficacy in predicting risk of new-onset AF in the general population; however, their prognostic value in KTx recipients is relatively unknown. Methods Retrospective analysis was conducted on KTx recipients without AF, with at least one pretransplant ECG between 2011 and 2021 across three tertiary centers in the United States (Mayo Clinic sites in MN, AZ, and FL). A previously validated AI-ECG algorithm estimated the probability of incident AF for each patient. Based on AI-ECG probabilities, patients were categorized into high-risk and low-risk groups, with the optimal AI-ECG score cutoff determined. The incidence of new-onset AF, allograft failure, and mortality was compared between groups. Results Overall, 6246 patients (age 53.5±13.8 years; 58.9% male) were included. Pretransplant AI-ECG probability of AF ≥5% was the optimal cutoff for high risk of incident AF (sensitivity 72%, specificity 62%). High-risk scores were associated with true new-onset AF at 30 days (adjusted hazard ratio [aHR], 2.89; 95% confidence intervals [CI], 2.05 to 4.09; P < 0.001), 3 years (aHR, 2.54; 95% CI, 1.99 to 3.26, P < 0.001), and 5 years post-transplant (aHR, 2.48; 95% CI, 1.99 to 3.09, P < 0.001). High-risk AI-ECG scores were also associated with increased mortality (aHR, 1.56; 95% CI, 1.30 to 1.88, P < 0.001) and overall allograft failure (aHR, 1.50; 95% CI, 1.30 to 1.75, P < 0.001) through the 5-year follow-up. Conclusions This pretransplant AI-ECG parameter identified patients at increased risk of new-onset AF post-KTx and provided prognostic utility. Overall, this easy to obtain tool allows for risk stratification of patients who may benefit from closer monitoring, targeted risk factor modification, and early intervention.

ABSTRACT Tumorigenesis and metastasis are frequently attributed to the intricate interplay between cancer cells and the tumor microenvironment (TME). Comprehending the mechanisms and key regulators of cancer‐immune crosstalk in the TME is imperative for developing efficacious immunotherapy. Through a series of in vivo CRISPR screens, we identified tumor‐intrinsic ITGB1 as a critical regulator of triple‐negative breast cancer (TNBC) development and deciphered its underlying mechanisms. Tumoral ITGB1 facilitated the establishment of pro‐tumorigenic TME by orchestrating tumor‐associated myeloid populations. Suppressing ITGB1 favored the enrichment of anti‐tumorigenic myeloid cells and enhanced infiltration of CD4 and CD8 T cells, culminating in superior antitumor effects. CRISPR scanning pinpointed a previously unrecognized functional domain essential for ITGB1's pro‐tumorigenic activity. This domain is distinct from all known ligand‐binding sites in ITGB1. An antibody capable of sterically blocking this domain significantly impaired TNBC progression. These findings position tumoral ITGB1 as a promising therapeutic target for reprogramming the TME from a pro‐ to an anti‐tumorigenic state, thereby effectively inhibiting TNBC development. Our study uncovers a novel mechanism of TNBC development and provides a unique therapeutic strategy for targeting ITGB1 in TNBC treatment.

Abstract High-grade gliomas (HGGs) are aggressive tumors with poor outcomes and limited treatment options. Here, we combined genomic and transcriptomic tumor profiling with drug testing in a patient-derived 3-dimensional culture model to identify individualized treatments and predictive biomarkers. Activity of single agents targeting frequently dysregulated glioma pathways was relatively poor ex vivo and generally reflected historical patient data. However, compounds targeting PI3K, epigenetic, and survival/senescence signaling were effective in some cases. Drug sensitivity correlated with transcriptional rather than genomic features and suggested heterogeneity as a resistance mechanism. Bromodomain and extraterminal domain inhibition was particularly effective in tumors enriched in the mesenchymal transcriptional subtype, promoted proneural transition, and was overcome by upregulated PI3K signaling. Notably, combinations were largely effective, with 6 strategies exhibiting stronger efficacy than corresponding single agents in most cases (58-77%). This study identifies HGG vulnerabilities and associated biomarkers, resistance mechanisms, and effective combination strategies that warrant further clinical validation. Graphical Abstract