Hyperpolarized (HP) [1-13C]pyruvate MRI can noninvasively detect dynamic metabolic activity in the brain. This study utilizes HP-[1-13C]pyruvate MRI to monitor treatment-related metabolism and evaluate early therapeutic response in twenty patients with recurrent grade 4 glioma undergoing cytotoxic, antiangiogenic, and targeted chemotherapies. Metabolic changes within the T2-lesion and normal-appearing white matter were compared among patients with similar treatments and/or outcomes. The lactate/pyruvate ratio increased by 14.3% at 1 month in the group whose therapy included bevacizumab, while it decreased by 13.1% at 2 months in the normal-appearing white matter of patients on everolimus. In the T2-lesion, patients on bevacizumab showed a 24.3% increase, whereas patients on everolimus showed a 7.6% decrease in normalized lactate/pyruvate ratios. Patients with shorter 6-month progression-free survival showed an average 9.6% increase in the lactate/pyruvate ratio as early as 1 month after treatment. This study demonstrates the potential of real-time metabolic imaging for response monitoring in patients with glioma.

Stereoselective nucleophilic substitution to access α-tertiary amines relies on copper-catalyzed radical approaches in which the substitution is mediated by metal-anilide coordination.1 These systems, however, are constrained by competing arene radical alkylation pathways.2 Here we report a distinct photoenzymatic mechanism for enantioconvergent nucleophilic substitution that operates without metal coordination to the nucleophile. Six rounds of protein engineering yielded a variant of a flavin-dependent oxidoreductase that promotes C(sp3)-N coupling between tertiary alkyl halides and simple anilines in good yields, with high chemoselectivity for N- over C-alkylation and high enantioselectivity across a broad substrate range. Multivariate statistical analysis, density functional theory, and mechanistic experiments show that the active site templates π-stacking, hydrogen-bonding, and water-bridged interactions between a tertiary radical and the aniline lone pair to generate an intermolecular n→SOMO hyperconjugative complex that is energetically disfavored in bulk solution, thereby simultaneously lowering the radical oxidation potential and suppressing arene addition.3 This work uncovers a previously inaccessible, copper-free manifold for nucleophilic substitution at sterically congested carbon centers and expands how enzymes can catalyze C(sp3)-N bond formation with control over both stereo- and chemoselectivity.

Genetic predisposition and alcohol consumption are risk factors for increased blood pressure (BP), but their interactions influencing BP remain understudied. We conducted population-specific and cross-population meta-analyses of genome-wide gene-alcohol (GxAlc) interactions affecting BP in >1.1M individuals from multiple populations. We identified 46 GxAlc interaction loci for BP, including 21 from one-degree-of-freedom interaction tests (PGxAlc<5×10-8; or <0.05/Meff, Meff independent BP associations at P<10-5), and 25 from two-degree-of-freedom tests of main and interaction effects (PGxAlc<0.05/M2df, M2df independent 2df-associations at P2df<5×10-8), including 7 novel and 39 known BP loci. The 12q24 locus highlights the genetic effect of BRAP-rs11066001 on BP, being ~6 times larger in current drinkers than in non-drinkers. Gene prioritization with 46 GxAlc loci identified 15 genes with ≥3 lines of evidence (location, literature, druggability, functional/regulatory annotation, or pathway analyses). Several loci showed sex- and population-specific effects and revealed biological pathways of alcohol's influence on BP, suggesting mechanisms underlying alcohol-induced hypertension.

Episodic future thinking (EFT) is a promising intervention for alcohol use disorder (AUD) as it has been shown to decrease delay discounting (DD) and alcohol valuation. In the current randomized controlled trial, we evaluated the effects of EFT on DD, behavioral economic demand, and daily measures of real-world alcohol consumption among individuals with AUD. Sixty-four non-treatment-seeking adults with AUD who wished to reduce or quit drinking but had no immediate treatment plans were randomized to EFT (n = 34) or control episodic thinking (CET; n = 30). Participants completed four in-laboratory sessions over the course of five weeks, and a follow-up in-laboratory session one month after the completion of the intervention. Additionally, alcohol consumption was monitored remotely for five weeks via a digital app. EFT exposure acutely decreased DD relative to baseline and CET. Additionally, daily exposure to the EFT, but not to CET, decreased the number of drinks/day and the number of drinks/drinking day. Significant changes in behavioral economic demand were not observed. Overall, the present findings suggest that EFT is a promising intervention to decrease alcohol use with effects on real-world alcohol consumption among individuals with alcohol use disorder, but alcohol demand is not a mechanism of this effect.

A unique feature of Plasmodium vivax is the presence of dormant hypnozoites that cause relapses weeks after the initial infection. While relapses may account for the majority of vivax malaria cases, the determinants of relapse periodicity, the genetic relationships between parasites, and the transmission potential of relapsing parasites in endemic populations remain poorly understood. We characterized P. vivax relapses in a cohort of 59 Cambodian patients treated with artesunate and relocated to a malaria-free area to prevent reinfection. Participants were followed every two days for 90 days using qPCR and microscopy. Genomes of blood stage parasites were sequenced to determine clonality and genetic relatedness between initial and relapsing infections. Membrane-feeding assays using Anopheles dirus mosquitoes were performed to evaluate the transmission potential of relapse infections. Relapses occurred frequently, with 81% of the patients experiencing at least one relapse within 90 days, with up to four consecutive relapses per individual and a median time to first relapse of 20 days. Genome sequencing revealed that relapsing parasites in monoclonal infections could be genetically identical, siblings of, or unrelated to the parasites present at enrollment. Patients with polyclonal infections at enrollment experienced significantly more relapses than those with monoclonal infections, suggesting that infection complexity may reflect the heterogeneity of the hypnozoite reservoir. Parasite growth rates during relapses varied widely among individuals but were associated with the degree of relatedness to those present in the initial infection. Despite low parasitemia and the absence of symptoms in most cases, relapse infections were frequently infectious to mosquitoes in membrane-feeding assays. Our findings show that P. vivax relapses occur commonly and frequently, and often involve genetically distinct parasites, reflecting complex hypnozoite reservoirs. Importantly, even low-density relapse infections can transmit efficiently to mosquitoes, highlighting the critical role of hypnozoites in sustaining malaria transmission and the importance of radical cure strategies for vivax malaria elimination.

While sleep is fundamental to human health, sleep disturbances reduce quality of life and constitute risk factors for neurodegenerative diseases including Parkinson's and Alzheimer's. Automated sleep staging networks achieve human-level performance on multimodal physiological signals, but they operate as black boxes, limiting clinical trust and preventing the discovery and validation of sleep biomarkers linked to human health status. We propose ProtoSleepNet (PSN), the fist prototype-based sequence-to-sequence sleep staging architecture that achieves human-level sleep staging accuracy while providing interpretability through an intrinsic codebook of learned prototypes. Each prototype captures distinctive sleep microstructure patterns, visualized as physiologically meaningful features across EEG, EOG, and EMG channels. We validate PSN against state-of-the-art approaches on over 10,000 subject recordings across 10 benchmark datasets, demonstrating in-line or superior sleep staging performance, robustness to channel occlusion attacks, and interpretability through a novel explainability framework that translates abstract prototypes into clinically aligned natural-language matching rules. Finally, we show that prototype sequences (prototype-grams) from individual patients encode clinically relevant information: without any disease-specific training, prototype-grams effectively discriminate Parkinson's and Alzheimer's disease patients from healthy controls, revealing disease-specific sleep microstructure alterations aligned with known pathophysiology.

Animals must flexibly adjust their behavior to respond appropriately in changing behavioral situations, in order to survive and thrive. The posterior parietal cortex (PPC) has been implicated in flexible decision-making, as it encodes sensory stimuli depending on their behavioral relevance [1] and is required to adapt to changes in stimulus-response contingencies in behavioral tasks [2]. Here, we show that while mice performed an auditory decision-making task, the temporal organization of neural activity differed across excitatory and inhibitory interneuron subtypes, with pyramidal neurons sparsely encoding task-related information. Sensory responses of all cell types were modulated according to behavioral relevance in the task, and signatures of this modulation were evident even before the presentation of sensory stimuli. Population activity patterns preceding stimulus presentation predicted the strength of sensory responses and even the mouse's behavioral accuracy in the task. A network model revealed that randomly organized inhibitory connectivity could replicate the selective filtering of sensory responses, but that context-dependent inputs to the network must be targeted to neurons responding to behaviorally relevant cues, and avoid those responding to irrelevant cues. Our results reveal a selective filtering mechanism in cortical circuits underlying flexible decision-making.

Pain drives disability and medication use in autoimmune rheumatic diseases (ARDs), even when inflammation is controlled. The extent of pain-related polypharmacy across ARDs and chronic overlapping pain conditions (COPCs) remains poorly characterized. We aimed to quantify first-year pain medication burden following ARD diagnosis and examine variations by disease, COPC status, and time. Using the Merative MarketScan Commercial Claims database, we identified adults newly diagnosed with rheumatoid arthritis, systemic lupus erythematosus, ankylosing spondylitis, psoriatic arthritis, Sjögren's disease, or systemic sclerosis (2008-2021). We analyzed pain-related medications across ten pharmacologic categories during the first year post-diagnosis. Polypharmacy measures included distinct medication counts, medication categories, ≥ 5 and ≥ 10 medication thresholds, and the Medication Quantification Scale. Among 149,742 adults with newly diagnosed ARDs, 57.6% had at least one COPC. During the first year after diagnosis, patients filled a mean of 9.0 distinct pain medications and 47.9% met criteria for ≥ 5 medications; 30.5% met criteria for ≥ 10 medications. Ankylosing spondylitis demonstrated the highest medication burden (mean 11.6 medications; 57.5% with ≥ 5 medications; 37.9% with ≥ 10 medications). Patients with fibromyalgia had consistently higher medication burden across ARDs and were the only COPC group in whom prescribing increased after 2015. Overall medication burden rose from 2008 to 2014-2015 and declined thereafter; however, absolute levels remained high. Pain-related polypharmacy is common early after ARD diagnosis and varies substantially by disease and pain phenotype. Despite modest declines after 2015, medication burden remains high, underscoring the need for phenotype-informed, nonpharmacologic, and deprescribing strategies in rheumatology. NIAMS (K01AR079039).

Cognitive fluctuations (CF) are a core feature of Lewy body dementia (LBD) that negatively impact quality of life. Despite their prevalence and negative impact, CF are challenging to identify clinically. The goal of this study was to identify easily obtainable EEG features associated with CF across the spectrum of Lewy body disease (LB). We conducted a cross-sectional study of 53 patients prospectively enrolled through the outpatient clinics of the Department of Neurology at Virginia Commonwealth University. Based on the Clinician Assessment of Fluctuations, participants were categorized as LB disease without CF (LB-CF) or LB disease with CF (LB + CF). All participants underwent a resting-state EEG recording with eyes closed for at least 3 minutes. EEG data were preprocessed and the following features were extracted: dominant frequency (DF), dominant frequency variability (DFV), dominant frequency prevalence (DFP), and individual alpha peak frequency (IAF). We applied Kruskal-Wallis tests and logistic regression models to evaluate differences in EEG features between study groups. We analyzed EEG features for 29 LB + CF and 24 LB-CF participants. Compared to the LB-CF group, the LB + CF group had significantly lower DF, DFP-alpha, and IAF in all derivations (all p < 0.05). In logistic regression analysis adjusting for age, sex, and MoCA score, these EEG features remained significant predictors of group (LB + CF vs. LB-CF, all q < 0.05). The elastic-net logistic regression model identified five predictors (anterior DFP-alpha, anterior DFP-theta, anterior DF, temporal DF, temporal IAF, and posterior DFP-pre-alpha) achieving an AUC of 0.86, whereas anterior DFP-alpha alone achieved an AUC of 0.85. Among patients with LB disease, resting-state EEG features were associated with CF and were significant predictors of CF even after adjustment for age, sex, and MoCA. The development of an EEGbased biomarker of CF using this set of features could improve diagnosis of Lewy body dementia.

Caloric restriction (CR) improves markers of biological aging, yet long-term effects on the human metabolome remain unclear. This study examined the effects of CR (2 years) in healthy adults without obesity on circulating metabolites linked to aging and metabolic adaptations. Untargeted metabolomics was performed using fasted plasma samples collected at baseline, 12, and 24 months (BL, 12M, 24M) from CALERIE™ participants randomized to CR or ad libitum (AL) control. A total of 864 known metabolites were identified and grouped into nine biologically coherent super pathways to support pathway-level interpretation (amino acid, peptide, carbohydrate, energy, lipid, nucleotide, cofactors and vitamins, xenobiotics, and partially characterized molecules). Principal component analysis (PCA) summarized metabolite variation, and linear mixed models assessed intervention effects on each PC in group-by-time interactions. Three principal components showed significant group-by-time interactions: PC2 (carbohydrate), PC5 (partially characterized molecules), and PC4 (lipid). Carbohydrate (PC2) and partially characterized metabolites (PC5) decreased from baseline to 12M in both groups; from 12M to 24M, levels stabilized in CR but increased in AL for PC2, while PC5 continued to decline in AL and increased in CR. Lipid metabolites (PC4) decreased in CR and increased in AL at 12M, with the pattern reversing from 12M to 24M. Key contributors included malto-saccharides and related carbohydrate intermediates for PC2, glutamine degradants and lactone sulfates for PC5, and sphingolipids for PC4. Calorie restriction produced distinct, time-dependent shifts in carbohydrate and lipid metabolism, with early reductions during the weight-loss phase followed by stabilization or compensatory responses during weight maintenance. These dynamic metabolic changes may relate to inflammation-linked mechanisms. Further work is needed to distinguish CR-specific adaptations from dietary influences and to clarify the functional significance of these metabolic responses for aging and long-term metabolic health.