Citations

Importance Amyloid positron emission tomography (PET) is increasingly used in research and clinical settings to determine the etiology of cognitive decline and eligibility for amyloid-targeting therapies. To assist with amyloid PET evaluation and to guide clinical decision-making, images can be quantified in a standardized unit called Centiloid, the interpretation of which can vary according to the method and threshold used. Objective To collect Centiloid values from available studies and determine robust positivity cutoffs using data-driven methods and correspondence with visual reads. Data Sources PubMed search (October 2024) identified studies with Centiloid values. Corresponding authors were invited to share individual participant data. Additional data were obtained through access-controlled repositories and conference outreach (July 2024-July 2025). Study Selection Studies were included if they provided Centiloids, radiotracer, age, and sex. Data Extraction and Synthesis Each study was analyzed using a unified statistical pipeline; study estimates were pooled using random-effects meta-analysis. Main Outcomes and Measures Gaussian mixture models (GMMs) were fitted to Centiloid values for each study. In studies with a bimodal distribution (per integrated completed likelihood), single cutoffs for positivity were set as mean plus 2 SDs of the lower gaussian component. Using GMMs, a double-cutoff approach defined a lower certainty range using a 90% posterior probability cutoff for assignment to the low (amyloid-negative) vs high (amyloid-positive) component. An alternative Centiloid cutoff was derived from maximizing the correspondence (Cohen κ) with the binary visual reads when available. Results This meta-analysis included cross-sectional amyloid PET scans acquired with 5 radiotracers from 49 227 participants across 53 studies from 15 countries (mean age, 71 years; 54% female, 62% cognitively impaired). The data-driven GMM approach identified a bimodal distribution in 51 studies (n = 48 786), resulting in a single cutoff for positivity of 18 Centiloids (95% CI,16-19; I 2 = 97%). The double-cutoff approach revealed high confidence for interpreting scans as negative when Centiloid values were lower than 11 (95% CI, 9-13; I 2 = 95%) and interpreting scans as positive if Centiloid values were higher than 26 (95% CI, 24-28; I 2 = 95%). In analyses of correspondence with binary (positive or negative) visual reads of amyloid PET scans (n = 35 045; 36 studies), Centiloids were highly predictive of visual positivity (Cohen κ, 0.86; 95% CI, 0.83-0.89; I 2 = 96%) with a cutoff of 27 Centiloids (95% CI, 24-30; I 2 = 80%). Conclusions and Relevance In this individual participant data meta-analysis, positivity cutoffs converged around 18 Centiloids (data-driven) and 27 Centiloids (visual reads). Findings from a double-cutoff analysis suggest that scans in the 11 to 26 Centiloid range should be interpreted with caution depending on the context of use.

Abstract How glial cells sense and regulate neuronal hypoactivity remains poorly understood. Using in vivo imaging in anesthetized, sleeping, and behaving mice, we identified a glial purinergic signaling mechanism that converts neuronal hypoactivity into local circuit regulation. Cortical hypoactivity increased spatially confined ATP release through astrocytic pannexin-1 hemichannels, which were structurally enriched near perisomatic parvalbumin-positive boutons. Local ATP release directed microglial process movement and stabilized bulbous endings through microglial P2Y12 signaling, accompanied by localized Ca²⁺ activity in microglial processes. Disruption of astrocytic pannexin-1 or microglial P2Y12 impaired bulbous-ending stabilization and abolished rebound increases in neuronal activity during emergence from anesthesia. Similar ATP release and bulbous-ending formation were observed during chemogenetic neuronal silencing or natural sleep in freely behaving mice. These findings identify astrocyte-to-microglia purinergic signaling as a mechanism that converts neuronal hypoactivity into synapse-selective microglial regulation of circuit activity.

Abstract The human pancreas contains diverse endocrine and exocrine cell populations whose spatial organization is essential for tissue physiology. While single-cell and spatial transcriptomics revealed molecular heterogeneity across pancreatic cell types, linking these states to physiological activity in situ has remained challenging. Here, we combined single-nucleus RNA sequencing, spatial transcriptomics, and functional calcium imaging across pancreatic samples in health and metabolic disease. We identified heterogeneous endocrine and exocrine cell states associated with obesity and diabetes, including inflammatory remodeling of acinar and ductal populations. To directly couple tissue physiology with molecular state, we developed Slice-seq, which integrates calcium imaging with spatial transcriptomics in acute pancreatic slices. Slice-seq linked local endocrine composition and transcriptional programs with β cell activity and identified extra-islet β cells with reduced glucose responsiveness and mitochondrial oxidative metabolism. Together, our study provides a framework for linking pancreatic cell states to tissue organization and physiological activity in health and disease.

Background Immune checkpoint inhibitor-based combinations represent the standard of care for advanced renal cell carcinoma. The OMNIVORE trial investigated a response-adaptive strategy, including treatment discontinuation in early nivolumab responders (Arm A) and salvage ipilimumab addition in non-responders (Arm B). Here we report outcomes with extended follow-up. Methods OMNIVORE was a phase II response-adaptive trial in which patients received induction nivolumab monotherapy. Patients achieving a confirmed complete or partial response discontinued nivolumab and entered observation (Arm A), while patients with stable disease or progressive disease received two doses of ipilimumab added to ongoing nivolumab (Arm B). This analysis characterizes long-term overall survival across the full study cohort and durability of response among patients who discontinued nivolumab following an early objective response. Results Of 83 patients who initiated treatment, 12 (14%) were allocated to Arm A and 57 (69%) to Arm B, with a median follow-up among living patients of 59.4 months (range 29.1–85.4 months) in Arm A and 31.4 months (range 4.6–62.6 months) in Arm B. The 3-year overall survival rate from nivolumab initiation was 64% (95% CI 51% to 74%) in the overall cohort, 83% (95% CI 48% to 96%) in Arm A, and 63% (95% CI 47% to 76%) in Arm B. Of the 12 Arm A patients, 6 (50%) remained off nivolumab at 1 year following treatment discontinuation, of whom 5 maintained responses beyond 43 months off therapy, with all remaining alive at last known follow-up, with overall survival ranging from 48.8 to 85.4 months from nivolumab initiation. Of the six patients who resumed treatment, only one achieved a durable complete response remaining on treatment at 83.2 months from nivolumab initiation. All 57 Arm B patients discontinued treatment with a median treatment duration of 3.7 months (range 1–24.8 months) and a median progression-free survival from nivolumab plus ipilimumab initiation of 4.6 months (95% CI 2.7 to 6.5 months). Conclusions With extended follow-up, a meaningful subset of patients achieving an early objective response to nivolumab maintained prolonged treatment-free survival following a short course of treatment. Salvage ipilimumab in nivolumab non-responders demonstrated limited benefit, reinforcing that upfront concurrent dual checkpoint blockade remains the preferred approach. Trial registration number NCT03203473 .

Abstract Purpose: The addition of MEK inhibition (MEKi) to programmed cell death ligand 1 (PD-L1) blockade improves progression-free survival (PFS) in patients with advanced biliary tract cancer. Although MEK inhibitors may increase tumor cell immunogenicity, they can impair T-cell priming/effector function, limiting combination efficacy. We hypothesized that the addition of a CD27 agonist could restore T-cell function and enhance antitumor immunity in this combination. Patients and Methods: We conducted a randomized, phase II trial evaluating atezolizumab (840 mg, intravenously, days 1 and 15) in combination with the CD27 costimulatory monoclonal antibody [CDX-1127/varlilumab (3 mg/kg, intravenously, days 1 and 15)], with/without the addition of an MEK inhibitor [cobimetinib (60 mg, orally, daily, days 1–21, off days 22–28)] in unresectable biliary tract cancer following at least one metastatic therapy. Overall response rate (ORR) and PFS were coprimary endpoints. Treatment-related changes in CD8+ tumor-infiltrating lymphocytes (TIL) were the primary correlative outcomes. Results: The trial was closed early following interim preplanned ORR analysis. At closure, 57 patients had been enrolled [n = 29 in the cobimetinib + atezolizumab + varlilumab (CAV) arm; n = 28 in the atezolizumab + varlilumab (AV) arm]. A majority (67%) had intrahepatic cholangiocarcinoma, and 32% were immunotherapy experienced. Both regimens were well tolerated without new safety signals. Objective responses were rare [0% (CAV); 3.8% (AV)]. The median PFS (mPFS) was 2.40 (CAV) and 1.84 (AV) months [hazard ratio (HR), 0.67; 95% confidence interval (CI), 0.38–1.18]. Among immunotherapy-experienced patients, the mPFS was 3.62 (CAV) and 1.84 (AV) months (HR, 0.54; 95% CI, 0.18–1.62). Treatment with CAV increased intratumoral CD8+ T-cell density compared with treatment with AV. Conclusions: The combinations of atezolizumab and varlilumab with/without cobimetinib were safe, but neither meaningfully improved outcomes in biliary tract cancer treated in the later lines. Correlative tissue studies validated preclinical work that MEKi increases CD8+ TILs.

ABSTRACT Background The brain–heart axis is central to vascular health, yet no imaging biomarkers capture integrated dysfunction across neural and coronary microvascular networks. Although coronary microvascular dysfunction links to cognitive decline, neural correlates connecting cerebral efficiency with coronary physiology remain unclear. Objectives To determine whether the Unified Structural and Functional Connectivity (USFC)—a multimodal magnetic resonance imaging (MRI) “traffic map” of brain network efficiency—predicts coronary endothelial function and cognition in women with ischemia and no obstructive coronary artery disease (INOCA). Methods Thirty‐three women with suspected INOCA from the Women's Ischemia Syndrome Evaluation (WISE) study (NCT03876223) underwent invasive coronary function testing, cardiac MRI, cognitive evaluation, and multimodal brain MRI. USFC, structural connectivity (SC), and functional connectivity (FC) were computed for predefined 10 backbone pathways. Support vector regression and logistic classification assessed predictive performance. Results USFC explained 16%–20% more variance in coronary endothelial function, myocardial perfusion reserve, and cognition than SC or FC alone ( p < 0.05). Connectivity between the left caudate–superior medial orbital gyrus and right calcarine–inferior occipital gyrus emerged as robust predictors of crystallized cognition ( r = –0.78, p FDR < 0.05) and coronary endothelial function ( r = 0.70, p FDR < 0.05), respectively. USFC also best discriminated low versus high coronary blood flow (area under the ROC curve [AUC]: USFC 0.622 vs. SC 0.349 and FC 0.425; p < 0.05). Conclusions USFC identifies neuro–cardiac pathways linking cerebral efficiency with coronary endothelial function. These results introduce a sensitive biomarker of systemic vulnerability, highlighting occipital and frontostriatal pathways as shared substrates of dysfunction. USFC offers a mechanistic framework for detecting vascular risk across metabolically demanding tissues. Trial Registration ClinicalTrials.gov identifier: NCT03876223

Abstract Myelodysplastic syndromes (MDS) are clinically and biologically diverse disorders, emphasizing the need for personalized treatment approaches. The International Working Group for Prognostication of MDS (IWG_PM) recently introduced a molecular classification, referred to as the MDS taxonomy, that categorizes patients into 16 subgroups based on 21 gene mutations, 6 cytogenetic abnormalities, and loss of heterozygosity (LOH) at TP53 and TET2 loci. This study sought to validate and enhance the clinical relevance of the MDS taxonomy by analyzing a large retrospective cohort ( n = 5136) and transcriptomic data from a prospective cohort ( n = 477). The taxonomy successfully identified subgroups with distinct clinical characteristics and disease progression patterns. However, incorporating gene interactions from taxonomy subgroups did not improve the prognostic performance of the Molecular International Prognostic Scoring System (IPSS‐M). We further assessed whether the taxonomy could guide management in patients receiving disease‐modifying therapies. Except for the “ TP53 ‐complex” subgroup, taxonomy classifications were not predictive of hypomethylating agent response or transplant outcomes. Nonetheless, they correlated with overall survival, suggesting that while both IPSS‐M and the taxonomy capture disease biology, other non‐genetic factors may influence treatment response. RNA sequencing confirmed the biological distinctiveness of the taxonomy groups. Transcriptomic profiling of CD34+ bone marrow cells revealed unique, homogeneous gene expression patterns, particularly within the AML‐like, bi TET2 , SF3B1 , and TP53 ‐complex subgroups. Further integration of multi‐omics data may refine MDS classification, improving clinical decision‐making and guiding the development of targeted therapies.

Background Invasive micropapillary carcinoma (IMPC) of the breast is associated with a high propensity for lymphovascular invasion and lymph node metastasis. However, whether chemotherapy is associated with improved survival outcomes in these patients remains unclear. Methods This retrospective study analyzed IMPC patients from the SEER database (2010–2018) (n=1,150) and an external validation cohort from Nanjing Drum Tower Hospital (n=199). Propensity score matching assessed chemotherapy’s impact on overall survival (OS) and breast cancer-specific survival (BCSS) in the SEER cohort. A risk stratification model was developed and validated using the external cohort. Results In the SEER cohort, chemotherapy was associated with significantly improved OS (HR = 0.517, 95% CI 0.293-0.910, P = 0.020) but not BCSS. A risk model incorporating marital status, tumor size, subtype, and radiotherapy history identified high- and low-risk groups. Chemotherapy was associated with significantly better OS only for high-risk patients (internal training cohort: HR = 0.577, 95% CI 0.349-0.952, P = 0.029; internal validation cohort: HR = 0.213, 95% CI 0.070-0.647, P = 0.003). External validation consistently confirmed poorer prognosis for high-risk patients (HR = 2.969, 95% CI 1.028-8.571, P = 0.035) and verified the model’s ability to identify patients with differential OS associations with chemotherapy: chemotherapy was associated with better OS in high-risk patients (HR = 0.163, 95% CI 0.031-0.868, P = 0.016), but not in low-risk patients (HR = 0.793, 95% CI 0.153-4.103, P = 0.782). Conclusions Chemotherapy was associated with improved prognosis particularly in high-risk patients with IMPC. However, chemotherapy decisions should be made cautiously for low-risk patients, taking into account a comprehensive assessment of clinical and pathological factors.