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Abstract The spirochete bacterial pathogen Borrelia (Borreliella) burgdorferi (Bbu) affects more than 10% of the world population and causes Lyme disease in about half a million people in the US annually. Therapy for Lyme disease includes antibiotics that target the Bbu ribosome. Here we present the structure of the Bbu 70S ribosome obtained by single particle cryo-electron microscopy at 2.9 Å resolution, revealing a bound hibernation promotion factor protein and two genetically non-annotated ribosomal proteins bS22 and bL38. The ribosomal protein uL30 in Bbu has an N-terminal α-helical extension, partly resembling the mycobacterial bL37 protein, suggesting evolution of bL37 and a shorter uL30 from a longer uL30 protein. Its analogy to proteins uL30m and mL63 in mammalian mitochondrial ribosomes also suggests a plausible evolutionary pathway for expansion of protein content in mammalian mitochondrial ribosomes. Computational binding free energy predictions for antibiotics reflect subtle distinctions in antibiotic-binding sites in the Bbu ribosome. Discovery of these features in the Bbu ribosome may enable better ribosome-targeted antibiotic design for Lyme disease treatment.

Antimony-doped tin oxide nanoparticles (ATO NPs) have emerged as a promising tool in biomedical applications, namely robust photothermal effects upon near-infrared (NIR) light exposure, enabling controlled thermal dynamics to induce spatial cell death. This study investigated the interplay between ATO NPs and macrophages, understanding cellular uptake and cytokine release. ATO NPs demonstrated biocompatibility with no impact on macrophage viability and cytokine secretion. These findings highlight the potential of ATO NPs for inducing targeted cell death in cancer treatments, leveraging their feasibility, unique NIR properties, and safe interactions with immune cells. ATO NPs offer a transformative platform with significant potential for future biomedical applications by combining photothermal capabilities and biocompatibility.

The North American Prodrome Longitudinal Study (NAPLS) is a consortium of nine programs focusing on youth at clinical high risk (CHR) for psychosis. Funded by the National Institute of Mental Health (NIMH), the sites are located at Emory University, Harvard University, University of Calgary, University of California at Los Angeles, at San Diego, and at San Francisco, University of North Carolina Chapel Hill, Yale University, and Zucker Hillside Hospital. There have been two previous endeavors completed by this consortium, known as NAPLS-1 and NAPLS-2. This paper first offers an overview of the methodology of the third phase of the NAPLS consortium, the second five-year prospective study NAPLS-3, which aims to determine mechanisms of the development of psychosis. In addition, we report on the ascertainment and demographics of the 710 CHR participants in NAPLS-3.

Background The proposed research aims to test the effects and mechanisms of a six-month yoga-based intervention as an add-on to standard treatment in opioid use disorder (OUD) by conducting a randomized controlled study with the following primary outcome variables: 1) clinical: abstinence (opioid negative urine test), and reductions in pain and craving, and 2) mechanisms: reward circuit activation in response to opioid visual cue craving paradigm, activation in response to a cognitive control task, and resting state functional connectivity through fMRI, and plasma beta-endorphin levels. Secondary outcome variables are perceived stress, anxiety, sleep quality, cognitive performance, pain threshold, buprenorphine dosage and side effects, withdrawal symptoms, socio-occupational functioning, vedic personality traits, heart rate variability, serum cortisol, and brain GABA levels through magnetic resonance spectroscopy (MRS). Methods In this single-blinded, randomized, controlled, parallel-group superiority trial with 1:1 allocation ratio, 164 patients with OUD availing the outpatient/ inpatient clinical services at a tertiary mental healthcare hospital in India will be enrolled after giving informed consent. Consecutive consenting patients will be randomly allotted to one of the two groups – yoga arm (standard treatment + yoga-based intervention), or waitlist group (standard treatment alone). Allocation concealment will be followed, the clinicians, outcome assessors and data analysts will remain blind to subject-group allocation. A validated and standardized yoga program for OUD will be used as an intervention. Participants in the yoga arm will receive 10 supervised in-person sessions of yoga in the initial two weeks followed by tele-yoga sessions thrice a week for the next 22 weeks. The wait-list control group will continue the standard treatment alone for 24 weeks. Assessments will be done at baseline, two weeks, 12 weeks, and 24 weeks. Data from all randomized subjects will be analysed using intent-to-treat analysis and mixed model multivariate analysis. Dissemination Findings will be disseminated through peer-reviewed publication, conference presentations, and social media. Trial registration number The trial has been registered under Clinical Trials Registry-India with registration number CTRI/2023/03/050737.

IntroductionArea-level residential instability (ARI), an index of social fragmentation, has been shown to explain the association between urbanicity and psychosis. Urban upbringing has been shown to be associated with reduced gray matter volumes (GMV)s of brain regions corresponding to the right caudal middle frontal gyrus (CMFG) and rostral anterior cingulate cortex (rACC). We hypothesize that greater ARI will be associated with reduced right CMFG and rACC GMVs.MethodsData were collected at baseline as part of the North American Prodrome Longitudinal Study Phase 2. Counties where participants resided during childhood were geographically coded using the US Census to area-level factors. ARI was defined as the percentage of residents living in a different house 5 years ago. Generalized linear mixed models tested associations between ARI and GMVs.ResultsThis study included 29 healthy controls (HC)s and 64 clinical high risk for psychosis (CHR-P) individuals who were aged 12 to 24 years, had remained in their baseline residential area, and had magnetic resonance imaging scans. ARI was associated with reduced right CMFG (adjusted β = -0.258; 95% CI = -0.502 to -0.015) and right rACC volumes (adjusted β = -0.318; 95% CI = -0.612 to -0.023). The interaction term (ARI-by-diagnostic group) in the prediction of both brain regions was not significant, indicating that the relationships between ARI and regional brain volumes held for both CHR-P and HCs.ConclusionsARI may adversely impact similar brain regions as urban upbringing. Further investigation into the potential mechanisms of the relationship between ARI and neurobiology, including social stress, is needed.

The clinical high-risk period before a first episode of psychosis (CHR-P) has been widely studied with the goal of understanding the development of psychosis; however, less attention has been paid to the 75%-80% of CHR-P individuals who do not transition to psychosis. It is an open question whether multivariable models could be developed to predict remission outcomes at the same level of performance and generalizability as those that predict conversion to psychosis. Participants were drawn from the North American Prodrome Longitudinal Study (NAPLS3). An empirically derived set of clinical and demographic predictor variables were selected with elastic net regularization and were included in a gradient boosting machine algorithm to predict prodromal symptom remission. The predictive model was tested in a comparably sized independent sample (NAPLS2). The classification algorithm developed in NAPLS3 achieved an area under the curve of 0.66 (0.60-0.72) with a sensitivity of 0.68 and specificity of 0.53 when tested in an independent external sample (NAPLS2). Overall, future remitters had lower baseline prodromal symptoms than nonremitters. This study is the first to use a data-driven machine-learning approach to assess clinical and demographic predictors of symptomatic remission in individuals who do not convert to psychosis. The predictive power of the models in this study suggest that remission represents a unique clinical phenomenon. Further study is warranted to best understand factors contributing to resilience and recovery from the CHR-P state.

ObjectiveA major challenge in multiple sclerosis (MS) research is the understanding of silent progression and Progressive MS. Using a novel method to accurately capture upper cervical cord area from legacy brain MRI scans we aimed to study the role of spinal cord and brain atrophy for silent progression and conversion to secondary progressive disease (SPMS).MethodsFrom a single-center observational study, all RRMS (n = 360) and SPMS (n = 47) patients and 80 matched controls were evaluated. RRMS patient subsets who converted to SPMS (n = 54) or silently progressed (n = 159), respectively, during the 12-year observation period were compared to clinically matched RRMS patients remaining RRMS (n = 54) or stable (n = 147), respectively. From brain MRI, we assessed the value of brain and spinal cord measures to predict silent progression and SPMS conversion.ResultsPatients who developed SPMS showed faster cord atrophy rates (-2.19%/yr) at least 4 years before conversion compared to their RRMS matches (-0.88%/yr, p

IntroductionDisturbed sleep is a common feature of psychotic disorders that is also present in the clinical high risk (CHR) state. Evidence suggests a potential role of sleep disturbance in symptom progression, yet the interrelationship between sleep and CHR symptoms remains to be determined. To address this knowledge gap, we examined the association between disturbed sleep and CHR symptoms over time.MethodsData were obtained from the North American Prodrome Longitudinal Study (NAPLS)-3 consortium, including 688 CHR individuals and 94 controls (mean age 18.25, 46% female) for whom sleep was tracked prospectively for 8 months. We used Cox regression analyses to investigate whether sleep disturbances predicted conversion to psychosis up to >2 years later. With regressions and cross-lagged panel models, we analyzed longitudinal and bidirectional associations between sleep (the Pittsburgh Sleep Quality Index in conjunction with additional sleep items) and CHR symptoms. We also investigated the independent contribution of individual sleep characteristics on CHR symptom domains separately and explored whether cognitive impairments, stress, depression, and psychotropic medication affected the associations.ResultsDisturbed sleep at baseline did not predict conversion to psychosis. However, sleep disturbance was strongly correlated with heightened CHR symptoms over time. Depression accounted for half of the association between sleep and symptoms. Importantly, sleep was a significant predictor of CHR symptoms but not vice versa, although bidirectional effect sizes were similar.DiscussionThe critical role of sleep disturbance in CHR symptom changes suggests that sleep may be a promising intervention target to moderate outcome in the CHR state.

Abstract Traditional diagnostic formulations of psychotic disorders have low correspondence with underlying disease neurobiology. This has led to a growing interest in using brain-based biomarkers to capture biologically-informed psychosis constructs. Building upon our prior work on the B-SNIP Psychosis Biotypes, we aimed to examine whether structural MRI (an independent biomarker not used in the Biotype development) can effectively classify the Biotypes. Whole brain voxel-wise grey matter density (GMD) maps from T1-weighted images were used to train and test (using repeated randomized train/test splits) binary L2-penalized logistic regression models to discriminate psychosis cases (n = 557) from healthy controls (CON, n = 251). A total of six models were evaluated across two psychosis categorization schemes: (i) three Biotypes (B1, B2, B3) and (ii) three DSM diagnoses (schizophrenia (SZ), schizoaffective (SAD) and bipolar (BD) disorders). Above-chance classification accuracies were observed in all Biotype (B1 = 0.70, B2 = 0.65, and B3 = 0.56) and diagnosis (SZ = 0.64, SAD = 0.64, and BD = 0.59) models. However, the only model that showed evidence of specificity was B1, i.e., the model was able to discriminate B1 vs. CON and did not misclassify other psychosis cases (B2 or B3) as B1 at rates above nominal chance. The GMD-based classifier evidence for B1 showed a negative association with an estimate of premorbid general intellectual ability, regardless of group membership, i.e. psychosis or CON. Our findings indicate that, complimentary to clinical diagnoses, the B-SNIP Psychosis Biotypes may offer a promising approach to capture specific aspects of psychosis neurobiology.

OBJECTIVE: Accumulating evidence supports an association between residential instability and increased risk for psychosis, but the association between residential instability and conversion to psychosis among adolescents at clinical high risk (CHR) is unclear. In this study, we determined whether individual-level and area-level residential instability and their interaction are associated with conversion to psychosis within two years. METHODS: Data were collected as part of the North American Prodrome Longitudinal Study Phase 2. Individual-level residential instability, defined as having ever moved during lifetime, was derived from the Life Events Scale. Area-level residential instability, defined as the percentage of people who were not living in the same house five years ago, was derived from the U.S. Decennial Censuses. RESULTS: This study included 285 adolescents at CHR (including 36 subjects who later converted to full psychosis). We found that individual-level residential instability was associated with conversion (adjusted OR = 2.769; 95% CI = 1.037-7.393). The interaction between individual-level and area-level residential instability was significant (p = 0.030). In a subgroup of CHR participants who have never moved (n = 91), area-level residential instability during childhood was associated with conversion (adjusted OR = 1.231; 95% CI = 1.029-1.473). Conversely, in a subgroup of CHR participants who resided in residentially stable areas during childhood (n = 142), the association between individual-level residential instability and conversion remained significant (adjusted OR = 15.171; 95% CI = 1.753-131.305). CONCLUSIONS: These findings suggest that individual-level and area-level residential instability may be associated with conversion to psychosis.