Citations

ACCESS is a prospective, multicenter phase II trial evaluating peripheral blood stem cell (PBSC) transplantation using 4-7/8 HLA-mismatched unrelated donors (MMUD) with post-transplant cyclophosphamide (PTCy), tacrolimus, and mycophenolate. Adults undergoing first HCT with myeloablative (MAC) or reduced-intensity/nonmyeloablative (RIC/NMA) conditioning were enrolled, with donors aged 18-35 years and matched at 4/8-7/8 HLA loci by high-resolution typing. This expanded analysis includes all enrolled adult PBSC recipients, including the protocol-specified RIC/NMA cohort expansion, to improve precision of outcome estimates and provide descriptive analyses by HLA match level. Among 268 adults, 183 received 7/8 and 85 received <7/8 MMUD grafts; 82.4% of the <7/8 cohort received 6/8 grafts. Median follow-up among survivors was 11.9 months. At 1-year, overall survival was 78.6% (95% CI, 71.9-83.9) in the 7/8 cohort and 85.6% (95% CI, 76.0-91.5) in the <7/8 cohort. One-year relapse, non-relapse mortality, and GVHD-free relapse-free survival were 17.1%, 13.7%, and 51.1% versus 22.8%, 8.4%, and 54.6%, respectively. The cumulative incidence of grade II-IV and grade III-IV acute GVHD by day 100 was 36.6% and 7.7% in the 7/8 cohort versus 28.3% and 5.9% in the <7/8 cohort. Moderate-to-severe chronic GVHD at 1 year was 11.3% versus 7.7%, respectively. Among adult ACCESS recipients treated on a uniform young-donor PBSC/PTCy platform, short-term outcomes with predominantly 6/8 MMUD transplantation were encouraging. Because donor match level was not prospectively assigned and between-group comparisons were exploratory, these findings are descriptive and should not be interpreted as establishing equivalence with 7/8 MMUD transplantation. (Registered as NCT04904588 at CT.gov)

OBJECTIVE Genetic variation in the glucagon-like peptide 1 receptor (GLP1R) has been implicated in type 2 diabetes (T2D) risk and treatment response. We investigated whether GLP1R R131Q, which was previously reported as a T2D-protective variant in genome-wide association studies, alters receptor signaling, β-cell function, and response to glucagon-like peptide 1 receptor agonists (GLP-1RAs). RESEARCH DESIGN AND METHODS Trajectory of β-cell function was evaluated in a 20-year community-based prospective cohort in Korea (n = 6,373), where participants underwent biennial 2-h 75-g oral glucose tolerance tests, and disposition index was used as surrogate marker. Pharmacogenetic response to GLP-1RAs was assessed in a hospital-based T2D cohort in Korea (n = 177). Hyperglycemic clamp studies (n = 17), human islet experiments (n = 21), and in vitro assays were conducted to characterize GLP1R R131Q effects on receptor signaling and islet function. RESULTS GLP1R R131Q was associated with slower decline in disposition index in individuals without T2D, with reductions from baseline of 30% in homozygous carriers, 35% in heterozygotes, and 37% in wild-type individuals. In people with T2D, each allele conferred an additional 0.53% or 5.8 mmol/mol reduction in HbA1c after 6 months of GLP-1RA treatment (P = 5.8 × 10−4). Hyperglycemic clamp and human islet experiments demonstrated allele-dependent enhancement of GLP-1RA–stimulated insulin secretion (P = 0.050 and P = 0.037, respectively). In vitro, GLP1R R131Q increased GLP-1RA–stimulated cAMP production with directional observations consistent with pathway bias. CONCLUSIONS GLP1R R131Q is a gain-of-function variant associated with preservation of β-cell function and enhanced glycemic response to GLP-1RA treatment, supporting further investigation as a candidate pharmacogenetic marker for precision diabetes care.

Abstract Introduction Distinct temperature patterns have long been recognized to correlate with fevers of differing etiologies. While the use of wearable sensors for high-frequency temperature monitoring (HFTM) on a near minute-by-minute basis has been shown to detect fevers earlier than standard-of-care nursing vital sign assessments in hospitalized patients, leveraging these high-resolution datasets to computationally identify unique digital signatures for real-time diagnosis of underlying fever etiology has not been widely explored. Diagnostic uncertainty is common in patients undergoing hematopoietic stem cell transplantation (HCT), with only 20–30% of febrile neutropenic episodes being microbiologically documented. We hypothesized that unique temperature patterns extracted from HFTM data collected during episodes of febrile neutropenia could be used to develop a supervised machine learning classifier capable of accurately predicting underlying fever etiology in HCT patients. Methods We analyzed 68 clinically independent fever episodes recorded in HCT patients (n=90) outfitted with an FDA-cleared wireless temperature sensor (TempTraq®, BlueSpark Technologies) that measured axillary temperature every 2 minutes throughout hospitalization. Time-series features were extracted from temperature traces spanning 1 hour before to 3 hours after fever onset and used to train a suite of machine-learning models to distinguish engraftment fevers from other fever etiologies. Model training and evaluation were performed using repeated stratified 5-fold patient-level cross-validation, yielding 100 train-test evaluations. Results Among all classification models, the logistic regression classifier provided the best overall performance and interpretability, achieving 94% specificity (95% CI, 0.84–1.0) for identifying engraftment fevers with a mean AUROC of 0.88 ± 0.10. Feature importance analysis demonstrated that both clinical variables and HFTM-derived temperature dynamics contributed to model performance, with a strong reliance on time-series features captured within the first 4 hours of fever onset. Conclusion Our study provides a demonstration that continuous temperature data collected from patients outfitted with wearable sensors can be leveraged not only for early fever detection but also for machine learning–based diagnosis of fever etiology. These findings suggest that dynamic temperature patterns contain clinically meaningful physiologic information that with further studies could support real-time diagnostic decision-making and guide safe de-escalation of empiric antibiotics during febrile neutropenia in patients undergoing intensive cancer therapy.

Abstract Background Upper-airway and respiratory conditions impose a large and growing global burden, yet there is no standardized way to assess whether a nasal microbiome is “healthy”. Currently, monitoring remains reactive, beginning only after symptoms manifest. The nasal cavity is well suited to proactive monitoring: it shapes respiratory health and pathogen colonization resistance, and can be sampled non-invasively and repeatedly. To address this gap, we introduce the Nasal Microbiome Wellness Index (NMWI), a disease-agnostic, continuous score of nasal microbiome health derived from LASSO-penalized logistic regression. Rather than counting taxa, it learns which taxa (and in what balance) characterize a healthy nose and returns the predicted log-odds that a profile resembles a healthy state. The index was trained on 1654 nasal 16S rRNA gene amplicon sequencing samples (589 healthy, 1065 non-healthy) pooled from 27 publicly available studies, uniformly reprocessed through a single computational pipeline. Results The NMWI comprises an interpretable signature of 24 taxa whose combined relative abundances determine the health-associated log-odds. Health-associated genera such as Corynebacterium and Cutibacterium raised the score, while dysbiosis-associated genera such as Pseudomonas and Escherichia – Shigella lowered it. The NMWI substantially outperformed the Shannon, Simpson, and Chao1 diversity indices, which showed negligible, directionally inconsistent separation between healthy and non-healthy samples (|Cliff’s δ | = 0.01–0.20), whereas the NMWI produced large, consistent separation ( δ = 0.65). It achieved a balanced accuracy of 74.37% on the training data (resubstitution estimate), and 73.43% under repeated 10-times 10-fold cross-validation. Performance remained stable at mean balanced accuracy of 73.82% under a leave-one-study-out framework, reflecting cross-study generalizability. In independent external cohorts, the balanced accuracy was 71.49%, and leave-one-disease-out analysis (in which each disease condition was withheld from training) showed a mean balanced accuracy of 63.92% across unseen conditions, consistent with a disease-agnostic design. The index also generalized across heterogeneous datasets spanning multiple 16S rRNA gene hypervariable regions—to our knowledge the first demonstration of such cross-study, cross-region transferability for the nasal cavity. Conclusions The NMWI distills a complex nasal microbial profile into a single interpretable score computed directly from the 16S rRNA gene data that dominate existing nasal research, making it immediately applicable to published and future datasets without re-sequencing. By replacing descriptive, diversity-based comparison with a quantitative standard, it offers a reproducible, open-source foundation for cross-study benchmarking, individual-level phenotyping, and longitudinal respiratory wellness monitoring.

ASCO Guidelines provide recommendations with comprehensive review and analyses of the relevant literature for each recommendation, following the guideline development process as outlined in the https://www.asco.org/practice-patients/guidelines/guideline-methodology . ASCO Guidelines follow the https://www.asco.org/about-asco/legal/conflict-interest-coi . Clinical Practice Guidelines and other guidance (“Guidance”) provided by ASCO is not a comprehensive or definitive guide to treatment options. It is intended for voluntary use by clinicians and should be used in conjunction with independent professional judgment. Guidance may not be applicable to all patients, interventions, diseases or stages of diseases. Guidance is based on review and analysis of relevant literature, and is not intended as a statement of the standard of care. ASCO does not endorse third-party drugs, devices, services, or therapies and assumes no responsibility for any harm arising from or related to the use of this information. See complete disclaimer in Appendix 1 and Appendix 2 (online only) for more . PURPOSE To offer clinicians recommendations concerning breast cancer follow-up and surveillance after primary treatment. METHODS ASCO convened an Expert Panel to develop recommendations based on a systematic review and a formal consensus process. RESULTS One randomized controlled trial (RCT) was identified and formed the evidentiary basis for the surveillance mammography guideline recommendation. No RCTs were identified that evaluated different follow-up approaches by risk of relapse in patients treated for early-stage breast cancer. Given the dearth of evidence identified in the systematic review of the literature, formal modified Delphi consensus-based recommendations were generated. RECOMMENDATIONS The guideline offers recommendations on the role of a risk-based approach to the frequency and intensity of follow-up among patients with breast cancer in the adjuvant setting. Regular history, physical examination, and mammography are recommended for breast cancer follow-up. Either virtual or in-person visits can be offered. Certain patients at a high risk of cancer recurrence warrant closer surveillance, such as those patients with locally advanced disease or residual disease following neoadjuvant chemotherapy. Recommendations on the use of blood-based biomarkers and supplemental imaging are provided. Guideline recommendations will be updated once additional evidence-based tools become available to better individualize surveillance. Additional information is available at www.ascopubs.org/topics/asco-guidelines/breast-cancer .

Most genetic variants associated with complex traits are hypothesized to regulate gene expression. To understand the genetics underlying gene expression variability, we characterized 14,324 RNA-sequencing samples from the Trans-Omics for Precision Medicine program and performed expression and splicing quantitative trait locus (e/sQTL) analyses in six tissues and cell types, including whole blood ( n = 6454) and lung ( n = 1291). We detected tens of thousands of secondary cis-e/sQTLs, showing that secondary cis-e/sQTL discovery remains unsaturated. We fine-mapped UK Biobank–derived genome-wide association study (GWAS) signals from 164 traits and identified e/sQTL colocalizations for 10,611 GWAS signals, including 7096 that colocalize with secondary e/sQTLs. Our results suggest that even larger e/sQTL analyses will uncover additional secondary e/sQTLs, further benefiting GWAS interpretation.

Background Lewy body disease (LBD) is a progressive neurodegenerative a-synucleinopathy, whereas isolated REM sleep behavior disorder (iRBD) is recognized as a prodromal stage of LBD. Although growing evidence implicates the gut–brain axis in neurodegeneration, the taxonomic and functional roles of the gut microbiome across the prodromal-to-symptomatic LBD continuum remain poorly defined. Methods Here, we performed shotgun metagenomic sequencing on stool samples from 25 patients with LBD (10 mild cognitive impairment due to LBD [MCI-LB] and 15 dementia with Lewy bodies [DLB]), 10 individuals with iRBD, and their household matched cohabitant controls to characterize disease-associated microbial alterations while minimizing environmental confounding. Results Despite no significant differences in global microbial diversity, we identified convergent shifts in microbial taxa, metabolic pathways, and gene families across disease stages. Both LBD and iRBD showed increased abundance of microbial taxa potentially associated with gut barrier disruption, as well as higher abundance of functional pathways related to lipopolysaccharide biosynthesis. LBD showed lower abundance of pathways related to complex carbohydrate fermentation, and both groups showed lower abundance of pathways associated with neurotransmitter-related metabolism. In particular, pathways and gene families associated with starch degradation were reduced in LBD, and those associated with histidine-to-glutamate/ GABA metabolism were reduced in both groups. Discussion These exploratory findings represent the first high-resolution, shotgun metagenomic characterization of gut microbiome alterations across the LBD continuum, highlighting functional patterns that may serve as candidate markers of disease progression in future longitudinal and mechanistic studies.

Abstract Objective. Modern stereotactic neurosurgery increasingly relies on bilateral and multi-trajectory workflows (e.g. deep brain stimulation (DBS), stereoelectroencephalography (sEEG)), which can exceed the reach and flexibility of conventional frame-based systems. Building on our skull-mounted Navinetics D1 platform, we present a stereotactic frame (Navinetics E1) intended to expand the reachable work envelope, enable independent bilateral targeting, and preserve mechanical accuracy and patient comfort. Approach. We designed the Navinetics E1 stereotactic frame using a center-of-arc architecture with five degrees of freedom per hemisphere ( X, Y, Z , Arc, Collar) and two operating modes: Double Arm (independent left/right arms for simultaneous bilateral targeting) and Single Arm (mechanically coupled arms). The system was designed in CAD and fabricated via carbon fiber-reinforced polylactic acid (PLA-CF) additive manufacturing. Collision-aware MATLAB simulations quantified work volume and admissible approach directions. Mechanical targeting accuracy was evaluated on a ground truth fixture (GTF) platform, with mixed-effects modeling to assess target- and trajectory-dependent effects. Operative feasibility was assessed through an intraoperative entry-point replication test relative to the D1 system. Main results. Compared to the D1, the E1 frame significantly expanded key geometric ranges, including, most notably, 0°–360° Collar rotation and posterior Y -axis reach, thereby increasing the work volume and trajectory range by factors of 3.39 and 8.42, respectively. Mean GTF targeting deviation was 0.78 ± 0.38 mm in Single Arm mode and 1.23 ± 0.36 mm (right) and 1.65 ± 0.47 mm (left) in Double Arm mode. Entry-point replication across 17 clinical cases achieved 76.5% success in overlapping the reference points, providing preliminary evidence of feasibility under real operative conditions. Significance. The E1 frame extends a compact skull-mounted platform to support broader stereotactic reach and trajectory while enabling independent bilateral workflows. These features may reduce intraoperative reconfiguration for complex DBS and sEEG cases. Future work will focus on increasing structural stiffness, improving angular readout/setting, and developing MRI-compatible implementations.

Black race and Hispanic ethnicity are associated with higher mortality in severe combined immunodeficiency (SCID) following hematopoietic cell transplantation (HCT), though mechanisms remain unclear. We evaluated 796 children with SCID who received nonsibling HCT between 1982 and 2020 using data from the Primary Immune Deficiency Treatment Consortium. Overall survival for Black (aHR 2.47, 95%CI 1.64, 3.71) and Asian/Pacific Islander patients (aHR 1.82, 95%CI 1.00, 3.30) was significantly lower compared with non-Hispanic White patients, while Hispanic patients had lower event-free survival (aHR 1.83, 95%CI 1.27, 2.63) compared with non-Hispanic White patients. Even after adjusting for age and infection, Black patients with SCID had more than twofold hazard of death compared with non-Hispanic White patients. NBS was associated with earlier diagnosis, reduced infection at HCT, and elimination of survival disparities between Black and non-Hispanic White patients. These findings suggest that universal, system-level interventions such as NBS can mitigate disparities in outcomes for children with SCID.

Abstract Background An accurate discrete spot scanning (DSS) beam delivery time (BDT) model is essential, particularly as 4D dynamic dose accumulation calculations rely on machine‐specific time models for reliable interplay evaluation. Purpose To derive a BDT model for a synchrotron‐based Hitachi Probeat PBS proton system from oscilloscope measurements of key BDT structures, including multi‐energy extraction (MEE) characteristics. Methods Key BDT structures were characterized using oscilloscope measurements, supplemented by delivery log files where appropriate. Spot‐to‐spot scanning trajectories were visualized using a CROSSmini 2D strip ionization chamber (Liverage Biomedical Inc, Taiwan) via the dose‐driven continuous scanning (DDCS) mode. The MEE design and MEE charge recapture efficiencies were also characterized. In addition, the impact of the number of delivered spots on both the extractable fraction of charge and MEE recapture efficiency was investigated. Results An improved synchrotron‐based BDT model was derived that incorporates dead times between radiofrequency knockout (RFK) and high‐speed steering magnet (HSST) signals. Spot‐to‐spot movement follows a “hockey‐stick”‐like behavior where the effective spot‐to‐spot move time is governed by the slower axis. An energy‐dependent variation in the number of MEE layers deliverable per spill was also observed, with fewer MEE layers per spill (1–3) was observed in low and high energy ranges compared to the mid‐energy range (4–5), deviating from the nominal vendor value of five MEE layers per spill per block. A reduction in the extractable fraction of charge was observed with an increasing number of spots per spill, while increasing the number of delivered spots in the preceding layer significantly reduced the MEE recapture efficiency. Conclusion MEE characteristics should be incorporated into synchrotron‐based time models for accurate beam delivery modeling. The methodology presented here also provides a framework for centers seeking to derive machine‐specific delivery time models for their proton systems.