Search

Objectives: Insomnia symptoms are negatively related to opioid use disorder (OUD) treatment outcomes, possibly reflecting the influence of sleep on neurofunctional domains implicated in addiction. Moreover, the intersection between OUD recovery and sleep represents an area well-suited for the development of novel, personalized treatment strategies. This study assessed the prevalence of clinically significant insomnia symptoms and characterized its neurofunctional correlates among a clinical sample of adults with OUD receiving buprenorphine. Methods: Adults (N = 129) receiving buprenorphine for OUD from an outpatient clinic participated in a cross-sectional survey. Participants completed an abbreviated version of NIDA's Phenotyping Assessment Battery, which assessed 6 neurofunctional domains: sleep, negative emotionality, metacognition, interoception, cognition, and reward. Bivariate descriptive statistics compared those with evidence of clinically significant insomnia symptoms (Insomnia Severity Index [ISI] score of ≥11) to those with minimal evidence of clinically significant insomnia symptoms (ISI score of ≤10) across each of the neurofunctional domains. Results: Roughly 60% of participants reported clinically significant insomnia symptoms (ISI score of ≥11). Experiencing clinically significant insomnia symptoms was associated with reporting greater levels of depression, anxiety, post-traumatic stress, stress intolerance, unhelpful metacognition, and interoceptive awareness (ps<0.05). Participants with evidence of clinically significant insomnia were more likely to report that poor sleep was interfering with their OUD treatment and that improved sleep would assist with their treatment (ps<0.05). Conclusions: Insomnia was prevalent among adults receiving buprenorphine for OUD. Insomnia was associated with neurofunctional performance, which may impact OUD treatment trajectories. Our findings indicate potential targets in the development of personalized treatment plans for patients with co-morbid insomnia and OUD. To inform the development of novel treatment strategies, more research is needed to understand the potential mechanistic links between sleep disturbances and substance use. [ABSTRACT FROM AUTHOR]

Background: Malformations of cortical development (MCDs) in children with focal epilepsy pose significant diagnostic challenges, and a precise radiological diagnosis is crucial for surgical planning. New MRI sequences and the use of artificial intelligence (AI) algorithms are considered very promising in this regard, yet studies evaluating the relative contribution of each diagnostic technique are lacking., Methods: The study was conducted using a dedicated "EPI-MCD MR protocol" with a 3 Tesla MRI scanner in patients with focal epilepsy and previously negative MRI. MRI sequences evaluated included 3D FLAIR, 3D T1 MPRAGE, T2 Turbo Spin Echo (TSE), 3D T1 MP2RAGE, and Arterial Spin Labelling (ASL). Two paediatric neuroradiologists scored each sequence for localisation and extension of the lesion. The MELD-FCD AI classifier's performance in identifying pathological findings was also assessed. We only included patients where a diagnosis of MCD was subsequently confirmed on histology and/or sEEG., Results: The 3D FLAIR sequence showed the highest yield in detecting epileptogenic lesions, with 3D T1 MPRAGE, T2 TSE, and 3D T1 MP2RAGE sequences showing moderate to low yield. ASL was the least useful. The MELD-FCD classifier achieved a 69.2% true positive rate. In one case, MELD identified a subtle area of cortical dysplasia overlooked by the neuroradiologists, changing the management of the patient., Conclusions: The 3D FLAIR sequence is the most effective in the MRI-based diagnosis of subtle epileptogenic lesions, outperforming other sequences in localisation and extension. This pilot study emphasizes the importance of careful assessment of the value of additional sequences., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

As a neurobiological process, addiction involves pathological patterns of engagement with substances and a range of behaviors with a chronic and relapsing course. Neuroimaging technologies assess brain activity, structure, physiology, and metabolism at scales ranging from neurotransmitter receptors to large-scale brain networks, providing unique windows into the core neural processes implicated in substance use disorders. Identified aberrations in the neural substrates of reward and salience processing, response inhibition, interoception, and executive functions with neuroimaging can inform the development of pharmacological, neuromodulatory, and psychotherapeutic interventions to modulate the disordered neurobiology. Based on our systematic search, 409 protocols registered on ClinicalTrials.gov include the use of one or more neuroimaging paradigms as an outcome measure in addiction, with the majority (N=268) employing functional magnetic resonance imaging (fMRI), followed by positron emission tomography (PET) (N=71), electroencephalography (EEG) (N=50), structural magnetic resonance imaging (MRI) (N=35) and magnetic resonance spectroscopy (MRS) (N=35). Furthermore, in a PubMed systematic review, we identified 61 meta-analyses including 30 fMRI, 22 structural MRI, 8 EEG, 7 PET, and 3 MRS meta-analyses suggesting potential biomarkers in addictions. These studies can facilitate the development of a range of biomarkers that may prove useful in the arsenal of addiction treatments in the coming years. There is evidence that these markers of large-scale brain structure and activity may indicate vulnerability or separate disease subtypes, predict response to treatment, or provide objective measures of treatment response or recovery. Neuroimaging biomarkers can also suggest novel targets for interventions. Closed or open loop interventions can integrate these biomarkers with neuromodulation in real-time or offline to personalize stimulation parameters and deliver the precise intervention. This review provides an overview of neuroimaging modalities in addiction, potential neuroimaging biomarkers, and their physiologic and clinical relevance. Future directions and challenges in bringing these putative biomarkers from the bench to the bedside are also discussed., Competing Interests: O.C. has received grant funding from Eli Lilly, Inc, and Nestle, Inc. He has provided paid consulting to Novo Nordisk. Dr. Paulus is an advisor to Spring Care, Inc., a behavioral health startup, he has received royalties for an article about methamphetamine in UpToDate. M.P.P. has a consulting agreement with and receives compensation from F. Hoffmann-La Roche Ltd. P.O. is an employee and shareholder of Sage Therapeutics. Other authors report no conflicts of interest. Disclaimer: The views and opinions expressed in this manuscript are those of the authors only and do not necessarily represent the views, official policy or position of the U.S. Department of Health and Human Services or any of its affiliated institutions or agencies.

Neuropsychological impairments are common in children with drug-resistant epilepsy. It has been proposed that epilepsy surgery might alleviate these impairments by providing seizure freedom; however, findings from prior studies have been inconsistent. We mapped long-term neuropsychological trajectories in children before and after undergoing epilepsy surgery, to measure the impact of disease course and surgery on functioning. We performed a retrospective cohort study of 882 children who had undergone epilepsy surgery at Great Ormond Street Hospital (1990-2018). We extracted patient information and neuropsychological functioning [obtained from IQ tests (domains: full-scale IQ, verbal IQ, performance IQ, working memory and processing speed) and tests of academic attainment (reading, spelling and numeracy)] and investigated changes in functioning using regression analyses. We identified 500 children (248 females) who had undergone epilepsy surgery [median age at surgery = 11.9 years, interquartile range = (7.8, 15.0)] and neuropsychological assessment. These children showed declines in all domains of neuropsychological functioning in the time leading up to surgery (all P-values ≤0.001; e.g. βFSIQ = -1.9, SEFSIQ = 0.3, PFSIQ < 0.001). Children lost on average one to four points per year, depending on the domain considered; 27%-43% declined by ≥10 points from their first to their last preoperative assessment. At the time of presurgical evaluation, most children (46%-60%) scored one or more standard deviations below the mean (<85) on the different neuropsychological domains; 37% of these met the threshold for intellectual disability (full-scale IQ < 70). On a group level, there was no change in performance from pre- to postoperative assessment on any of the domains (all P-values ≥0.128). However, children who became seizure free through surgery showed higher postoperative neuropsychological performance (e.g. rrb-FSIQ = 0.37, P < 0.001). These children continued to demonstrate improvements in neuropsychological functioning over the course of their long-term follow-up (e.g. βFSIQ = 0.9, SEFSIQ = 0.3, PFSIQ = 0.004). Children who had discontinued antiseizure medication treatment at 1-year follow-up showed an 8- to 13-point advantage in postoperative working memory, processing speed and numeracy, and greater improvements in verbal IQ, working memory, reading and spelling (all P-values ≤0.034) over the postoperative period compared with children who were seizure free and still receiving antiseizure medication. In conclusion, by providing seizure freedom and the opportunity for antiseizure medication cessation, epilepsy surgery might not only halt but reverse the downward trajectory that children with drug-resistant epilepsy display in neuropsychological functioning. To halt this decline as soon as possible or, potentially, to prevent it from occurring in the first place, children with focal epilepsy should be considered for epilepsy surgery as early as possible after diagnosis., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Objective: The objective was to analyze seizure semiology in pediatric frontal lobe epilepsy patients, considering age, to localize the seizure onset zone for surgical resection in focal epilepsy., Methods: Fifty patients were identified retrospectively, who achieved seizure freedom after frontal lobe resective surgery at Great Ormond Street Hospital. Video-electroencephalography recordings of preoperative ictal seizure semiology were analyzed, stratifying the data based on resection region (mesial or lateral frontal lobe) and age at surgery (≤4 vs >4)., Results: Pediatric frontal lobe epilepsy is characterized by frequent, short, complex seizures, similar to adult cohorts. Children with mesial onset had higher occurrence of head deviation (either direction: 55.6% vs 17.4%; p = 0.02) and contralateral head deviation (22.2% vs 0.0%; p = 0.03), ictal body-turning (55.6% vs 13.0%; p = 0.006; ipsilateral: 55.6% vs 4.3%; p = 0.0003), and complex motor signs (88.9% vs 56.5%; p = 0.037). Both age groups (≤4 and >4 years) showed hyperkinetic features (21.1% vs 32.1%), contrary to previous reports. The very young group showed more myoclonic (36.8% vs 3.6%; p = 0.005) and hypomotor features (31.6% vs 0.0%; p = 0.003), and fewer behavioral features (36.8% vs 71.4%; p = 0.03) and reduced responsiveness (31.6% vs 78.6%; p = 0.002)., Interpretation: This study presents the most extensive semiological analysis of children with confirmed frontal lobe epilepsy. It identifies semiological features that aid in differentiating between mesial and lateral onset. Despite age-dependent differences, typical frontal lobe features, including hyperkinetic seizures, are observed even in very young children. A better understanding of pediatric seizure semiology may enhance the accuracy of onset identification, and enable earlier presurgical evaluation, improving postsurgical outcomes. ANN NEUROL 2024;95:1138-1148., (© 2024 American Neurological Association.)

A new and practical method for the thermal degradation of technically relevant bio-based lignin is presented. By heating a solution of lignin in highly concentrated caustic potash, vanillic acid is almost exclusively obtained in yields up to 10.6 wt %. By altering the reaction parameters, the selectivity of the reaction can be shifted towards the demethylation product, protocatechuic acid, which is obtained in a yield of 6.9 wt %. Furthermore, the procedure was applicable to different types of Kraft and organosolv lignin. To create an economically feasible process, ion exchange resins were used for the work-up of the highly caustic reaction media without neutralizing the complete mixture. By the selective removal of the desired vanillic acid from the caustic potash, this alkaline media could directly be reused for at least 5 further lignin degradations without significant loss of yield., (© 2024 The Authors. ChemSusChem published by Wiley-VCH GmbH.)

Aim: To evaluate a lesion detection algorithm designed to detect focal cortical dysplasia (FCD) in children undergoing stereoelectroencephalography (SEEG) as part of their presurgical evaluation for drug-resistant epilepsy., Method: This was a prospective, single-arm, interventional study (Idea, Development, Exploration, Assessment, and Long-Term Follow-Up phase 1/2a). After routine SEEG planning, structural magnetic resonance imaging sequences were run through an FCD lesion detection algorithm to identify putative clusters. If the top three clusters were not already sampled, up to three additional SEEG electrodes were added. The primary outcome measure was the proportion of patients who had additional electrode contacts in the SEEG-defined seizure-onset zone (SOZ)., Results: Twenty patients (median age 12 years, range 4-18 years) were enrolled, one of whom did not undergo SEEG. Additional electrode contacts were part of the SOZ in 1 out of 19 patients while 3 out of 19 patients had clusters that were part of the SOZ but they were already implanted. A total of 16 additional electrodes were implanted in nine patients and there were no adverse events from the additional electrodes., Interpretation: We demonstrate early-stage prospective clinical validation of a machine learning lesion detection algorithm used to aid the identification of the SOZ in children undergoing SEEG. We share key lessons learnt from this evaluation and emphasize the importance of robust prospective evaluation before routine clinical adoption of such algorithms., What This Paper Adds: The focal cortical dysplasia detection algorithm collocated with the seizure-onset zone (SOZ) in 4 out of 19 patients. The algorithm changed the resection boundaries in 1 of 19 patients undergoing stereoelectroencephalography for drug-resistant epilepsy. The patient with an altered resection due to the algorithm was seizure-free 1 year after resective surgery. Overall, the algorithm did not increase the proportion of patients in whom SOZ was identified., (© 2023 The Authors. Developmental Medicine & Child Neurology published by John Wiley & Sons Ltd on behalf of Mac Keith Press.)