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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.
RESUMEN
Background: There is an urgent need for pharmacological treatment for cocaine (COC) use disorder (CUD). Glutamatergic transmission in the prefrontal cortex is affected by addictive behaviors. Clavulanic acid (CLAV), a glutamate transporter GLT-1 (excitatory amino acid transporter) activator, is a clinical-stage medication that has potential for treating CUD. Methods: In a pilot study, nine participants with CUD received 500 mg CLAV with dose escalations to 750 mg and 1000 mg over 10 days. In 5 separate magnetic resonance imaging (MRI) sessions, brain anterior cingulate cortex (ACC) glutamate level and resting state network (RSN) functional connectivity (FC) were assessed using MR spectroscopy and functional MRI. Craving was assessed at the same time points, between baseline (before CLAV), 6 days, and 10 days of CLAV. Independent component analysis with dual regression was used to identify RSN FC changes from baseline to Days 6 and 10. Relationships among glutamate, craving, and resting state FC values were analyzed. Results: Participants who achieved high ACC glutamate levels after CLAV treatment had robust decreases in COC craving (râ¯=â¯-0.90, Pâ¯=â¯0.0009, nâ¯=â¯9). The salience network (SN) and executive control network (ECN) demonstrated an association between increased FC after CLAV treatment and low baseline ACC Glu levels (SN CLAV 750 mg, râ¯=â¯-0.82, Pâ¯=â¯0.007) (ECN CLAV 1000 mg, râ¯=â¯-0.667, Pâ¯=â¯0.050; nâ¯=â¯9). Conclusions: Glutamate associated changes in craving and FC of the salience and executive control brain networks support CLAV as a potentially efficacious pharmacological treatment for CUD.
RESUMEN
BACKGROUND: Identifying stable and consistent resting-state functional connectivity patterns across illness trajectories has the potential to be considered fundamental to the pathophysiology of schizophrenia. We aimed to identify consistent resting-state functional connectivity patterns across heterogeneous schizophrenia groups defined based on treatment response. METHODS: In phase 1, we used a cross-sectional case-control design to characterize and compare stable independent component networks from resting-state functional magnetic resonance imaging scans of antipsychotic-naïve participants with first-episode schizophrenia (n = 54) and healthy participants (n = 43); we also examined associations with symptoms, cognition, and disability. In phase 2, we examined the stability (and replicability) of our phase 1 results in 4 groups (N = 105) representing a cross-sequential gradation of schizophrenia based on treatment response: risperidone responders, clozapine responders, clozapine nonresponders, and clozapine nonresponders following electroconvulsive therapy. Hypothesis-free whole-brain within- and between-network connectivity were examined. RESULTS: Phase 1 identified posterior and anterior cerebellar hypoconnectivity and limbic hyperconnectivity in schizophrenia at a familywise error rate-corrected cluster significance threshold of p < .01. These network aberrations had unique associations with positive symptoms, cognition, and disability. During phase 2, we replicated the phase 1 results while comparing each of the 4 schizophrenia groups to the healthy participants. The participants in 2 longitudinal subdatasets did not demonstrate a significant change in these network aberrations following risperidone or electroconvulsive therapy. Posterior cerebellar hypoconnectivity (with thalamus and cingulate) emerged as the most consistent finding; it was replicated across different stages of treatment response (Cohen's d range -0.95 to -1.44), reproduced using different preprocessing techniques, and not confounded by educational attainment. CONCLUSIONS: Posterior cerebellar-thalamo-cingulate hypoconnectivity is a consistent and stable state-independent neural marker of schizophrenia.