Citations

Abstract Newer approaches to control alloreactivity may produce similar transplant outcomes using HLA-mismatched donors vs HLA-matched unrelated donors (MUD). However, prospective comparisons are lacking. BMT CTN 1702 used a donor search prognosis score to assign patients to an 8/8 HLA MUD or the center’s preference of haploidentical related donors (HAPLO), mismatched unrelated donors (MMUD), or umbilical cord blood (UCB). Outcomes of MUD were compared to HAPLO, MMUD, and UCB transplantation after adjusting for covariates. Patients (n = 1179 [93% adults]) underwent transplantation with MUD (n = 772), HAPLO (n = 254), MMUD (n = 112), and UCB (n = 41) at a median of 3.7, 3.4, 3.9, and 3.8 months from enrollment. Posttransplant cyclophosphamide (PTCy) was used in 23.9%, 83.9%, 65.2%, and 0% of MUD, HAPLO, MMUD, and UCB. In multivariate analyses, compared to MUD, survival was lower for UCB (hazard ratio [HR], 2.65; P< .001) but not statistically different for HAPLO and MMUD (HRs, 1.08 and 1.18, respectively). Relapse risk was not significantly different by donor, but treatment-related mortality (HR, 3.31; P< .001) and disease-free survival (HR, 1.99; P = .002) were inferior for UCB but not different for HAPLO and MMUD than MUD. In patients who received PTCy, HAPLO and MMUD were associated with increased grade 3 or 4 acute graft-versus-host disease (GVHD; HR, 2.39 [P = .017] and 2.53 [P = .038], respectively) and chronic GVHD (HR, 1.71 for both; P = .028 and .080) than MUD, but other outcomes were not different. HAPLO or MMUD may be used to expedite transplantation when finding MUD is unlikely. This study was registered at www.clinicaltrials.gov as NCT03904134.

Neuroplastic changes in phrenic motor neurons that underlie recovery from spinal cord injury may be mediated by perineuronal nets. We show that changes in perineuronal nets around phrenic motor neurons occur within 7 days after cervical spinal cord injury, and that the increase in perineuronal nets around larger phrenic motor neurons was more pronounced. These changes are consistent with substantial reorganization of the neural network onto intact phrenic motor neurons following cervical spinal cord injury.

Abstract Exposure to asbestos is the primary cause of mesothelioma, however the processes underpinning its initiation and evolutionary trajectory remain elusive. To address this knowledge gap, we conducted whole exome sequencing and phylogenetic analysis of 277 mesotheliomas. Using multidimensional Dirichlet process clustering we inferred phylogenies, uncovering mutation order dominated by early 13q,1p, 8p, 6q and 22q somatic copy number alterations. Mesotheliomas exhibit a spectrum of genomic intra-tumor heterogeneity spanning linear (L) to highly branched (B) tree topologies, quantifiable by the Weighted Shannon Entropy (WSE). Somatic copy number alterations emerge earlier than single nucleotide variants (SNVs), and at a much faster relative rate in L-mesotheliomas. BAP1 is the only positively selected driver in L-mesotheliomas, whereas, B-mesotheliomas harbor multiple positively selected drivers and an aggressive phenotype, including a bias of loss of RPL5, and MTAP deletion linked to breakpoint enriched with long interspersed nuclear elements. L-trees had lower WSE, but greater T-cell inflammation and tertiary lymphoid structures, despite having a lower neoantigen burden. WSE is higher in larger volume, immunologically cold mesotheliomas, and is associated with shorter survival. In summary, progressive genomic heterogeneity is a defining feature of more aggressive mesothelioma yet illuminates opportunities for precision therapeutic intervention.

The 2026 ASAHP (Association of Schools Advancing Health Professions) Clinical Education Committee recommendations present a framework for advancing clinical education across health professions. This report emphasizes the importance of expanding clinical education settings, integrating artificial intelligence and telehealth into curricula, ensuring alignment of interprofessional competencies with accreditation standards, and continuing to facilitate collaborative practice across disciplines. These efforts are essential to training a workforce that is not only clinically competent but also adaptable, mindful of equity, and capable of thriving in diverse, team-based care settings. Equally critical is the call to elevate research and scholarly activity within clinical education. The report emphasizes the need for academic-clinical partnerships that support and complete an inquiry into the value, effectiveness, and innovation of clinical training. These recommendations aim to advance a responsive, inclusive, and outcomes-driven clinical education system that benefits students, educators, healthcare systems, and the communities they serve. These efforts reflect ASAHP's name and mission to advance health professions.

ABSTRACT One quarter of patients with diffuse large B‐cell lymphoma (DLBCL) who achieve a complete response following front‐line therapy will eventually experience disease relapse. Existing prognostic models use baseline factors to predict outcomes from the start of initial therapy and are not intended for use following completion of treatment. We developed a conditional event‐free survival (cEFS) tool that predicts a patient's risk of lymphoma recurrence after completing front‐line therapy taking into consideration baseline risk characteristics plus the time the patient has been in remission. Model development used pooled and harmonized data from two observational cohorts and four randomized trials of patients with newly diagnosed DLBCL treated with immunochemotherapy and either achieving a complete response or not experiencing an event within 12 weeks of end of therapy. Cox proportional‐hazards regression modeling with backwards stepwise selection was utilized for model development. External validation was performed using a large independent data registry. In total, data from 2757 patients were used for model development. The risk of experiencing an event at a time point after having survived a period of time could be computed parsimoniously using four basic predictors: age, ECOG performance status grade, Ann Arbor stage, and lactate dehydrogenase level. C‐index in the model development cohort was 0.65 (95% CI, 0.63–0.68), compared to 0.64 (95% CI, 0.62–0.66) in the external validation cohort. We believe that this dynamic risk prediction tool will not only aid clinicians in providing data‐driven recommendations for surveillance, but also assist patients themselves with key decisions, such as family planning.