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Odontogenic pain can be debilitating, and nonopioid analgesic options are limited. This randomized placebo-controlled clinical trial aimed to assess the effectiveness and safety of cannabidiol (CBD) as an analgesic for patients with emergency acute dental pain. Sixty-one patients with moderate to severe toothache were randomized into 3 groups: CBD10 (CBD 10 mg/kg), CBD20 (CBD 20 mg/kg), and placebo. We administered a single dose of respective oral solution and monitored the subjects for 3 h. The primary outcome measure was the numerical pain differences using a visual analog scale (VAS) from baseline within and among the groups. Secondary outcome measures included ordinal pain intensity differences, the onset of significant pain relief, maximum pain relief, changes in bite force within and among the groups, psychoactive effects, mood changes, and other adverse events. Both CBD groups resulted in significant VAS pain reduction compared to their baseline and the placebo group, with a maximum median VAS pain reduction of 73% from baseline pain at the 180-min time point (P < 0.05). CBD20 experienced a faster onset of significant pain relief than CBD10 (15 versus 30 min after drug administration), and both groups reached maximum pain relief at 180-min. Number needed to treat was 3.1 for CBD10 and 2.4 for CBD20. Intragroup comparisons showed a significant increase in bite forces in both CBD groups (P < 0.05) but not in the placebo group (P > 0.05). CBD20 resulted in a significant difference in mean percent bite force change in the 90- and 180-min time points compared to the placebo group (P < 0.05). Compared to placebo, sedation, diarrhea, and abdominal pain were significantly associated with the CBD groups (P < 0.05). There were no other significant psychoactive or mood change effects. This randomized trial provides the first clinical evidence that oral CBD can be an effective and safe analgesic for dental pain. [ABSTRACT FROM AUTHOR]

This article is a response to a letter to the editor regarding a clinical trial on the use of cannabidiol (CBD) for acute dental pain. The author of the letter expressed concerns about the efficacy of cannabinoids for dental pain, but the clinical trial focused specifically on CBD, which has different mechanisms of action compared to other cannabinoids. The article acknowledges the need for larger-scale clinical trials to further investigate the use of CBD for dental pain. The study provides the first evidence for the use of CBD in this context. [Extracted from the article]

Introduction: The monoclonal antibody therapies bamlanivimab (BAM) + etesevimab (ETE) received emergency use authorization (EUA) from the US Food and Drug Administration (February 9, 2021) for treatment of mild-to-moderate COVID-19. The EUA of BAM + ETE was revoked (December 14, 2023) due to the high prevalence of BAM + ETE-resistant variants of SARS-CoV-2. Efficacy and safety of 700/1400 mg and 2800/2800 mg BAM + ETE are well established and published; however, efficacy and safety of 350/700 mg BAM + ETE have not been disclosed to date., Methods: This portion of phase 3, BLAZE-1 trial (J2X-MC-PYAB) enrolled patients (between June 17, 2020 and April 9, 2021) with mild-to-moderate COVID-19 within 3 days of laboratory diagnosis of SARS-CoV-2 infection. In total, 354 patients with at least one risk factor for severe COVID-19 were enrolled, randomized (2:3), and infused with placebo (N = 141) or 350/700 mg BAM + ETE (N = 213), over ~ 8 min. Primary endpoint was to assess proportion of patients with persistently high SARS-CoV-2 viral load (PHVL) (log viral load > 5.27) 7 days after infusion., Results: Patients were aged (mean) 53 years, 49.7% female, and 82.7% White. Seven days after drug infusion, 10.8% (95% confidence interval: 6.6, 15.0; p < 0.001) of BAM + ETE-treated patients and 34.8% (26.9, 42.6) of placebo-treated patients had PHVL, and the viral load change from baseline (least square mean [standard error]) was - 3.50 (0.15; p < 0.001) in BAM + ETE-treated patients versus - 2.51 (0.19) in placebo-treated patients. The majority of treatment-emergent adverse events were considered mild or moderate in severity (BAM + ETE: 6.6%; placebo: 14.2%). No deaths were reported., Conclusions: Consistent with previous studies, patients treated with BAM + ETE (350/700 mg) had a significantly lower proportion of PHVL and greater reduction in viral load compared with placebo. The overall safety profile is consistent with higher doses of BAM + ETE. Infusions of over ~ 8 min did not result in meaningful increase in incidence of TEAEs compared to higher doses of BAM + ETE administered over 30-60 min., Trial Registration: Clinical trial.gov identifier, NCT04427501., (© 2024. The Author(s).)

Aim: Paediatric patients with drug-resistant focal epilepsy (DRFE) who have no clear focal lesion identified on conventional structural magnetic resonance imaging (MRI) are a particularly challenging cohort to treat and form an increasing part of epilepsy surgery programs. A recently developed deep-learning-based MRI lesion detection algorithm, the Multicentre Lesion Detection (MELD) algorithm, has been shown to aid detection of focal cortical dysplasia (FCD). We applied this algorithm retrospectively to a cohort of MRI-negative children with refractory focal epilepsy who underwent stereoelectroencephalography (SEEG) to determine its accuracy in identifying unseen epileptic lesions, seizure onset zones and clinical outcomes., Methods: We retrospectively applied the MELD algorithm to a consecutive series of MRI-negative patients who underwent SEEG at our tertiary Paediatric Epilepsy Surgery centre. We assessed the extent to which the identified MELD cluster or lesion area corresponded with the clinical seizure hypothesis, the epileptic network, and the positron emission tomography (PET) focal hypometabolic area. In those who underwent resective surgery, we analysed whether the region of MELD abnormality corresponded with the surgical target and to what extent this was associated with seizure freedom., Results: We identified 37 SEEG studies in 28 MRI-negative children in whom we could run the MELD algorithm. Of these, 14 (50 %) children had clusters identified on MELD. Nine (32 %) children had clusters concordant with seizure hypothesis, 6 (21 %) had clusters concordant with PET imaging, and 5 (18 %) children had at least one cluster concordant with SEEG electrode placement. Overall, 4 MELD clusters in 4 separate children correctly predicted either seizure onset zone or irritative zone based on SEEG stimulation data. Sixteen children (57 %) went on to have resective or lesional surgery. Of these, only one patient (4 %) had a MELD cluster which co-localised with the resection cavity and this child had an Engel 1 A outcome., Conclusions: In our paediatric cohort of MRI-negative patients with drug-resistant focal epilepsy, the MELD algorithm identified abnormal clusters or lesions in half of cases, and identified one radiologically occult focal cortical dysplasia. Machine-learning-based lesion detection is a promising area of research with the potential to improve seizure outcomes in this challenging cohort of radiologically occult FCD cases. However, its application should be approached with caution, especially with regards to its specificity in detecting FCD lesions, and there is still work to be done before it adds to diagnostic utility., Competing Interests: Declaration of Competing Interest None, (Copyright © 2024 Elsevier B.V. All rights reserved.)

Diagnosing and treating people with bacteriologically-negative but radiologically-apparent tuberculosis (TB) may contribute to more effective TB care and reduce transmission. However, optimal treatment approaches for this group are unknown. It is important to understand peoples' preferences of treatment options for effective programmatic implementation of people-centred treatment approaches. We designed and implemented a discrete choice experiment (DCE) to solicit treatment preferences among adults (≥18 years) with TB symptoms attending a primary health clinic in Blantyre, Malawi. Treatment attributes included in the DCE were as follows: duration of treatment; number of tablets per dose; reduction in the risk of being unwell with TB disease; likelihood of infecting others; adverse effects from the treatment; frequency of follow up; and the annual travel cost to access care. Quantitative choice modelling with multinomial logit models estimated through frequentist and Bayesian approaches investigated preferences for the management of bacteriologically-negative, but radiographically-apparent TB. 128 participants were recruited (57% male, 43.8% HIV-positive, 8.6% previously treated for TB). Participants preferred to take any treatment compared to not taking treatment (odds ratio [OR] 5.78; 95% confidence interval [CI]: 2.40, 13.90). Treatments that reduced the relative risk of developing TB disease by 80% were preferred (OR: 2.97; 95% CI: 2.09, 4.21) compared to treatments that lead to a lower reduction in risk of 50%. However, there was no evidence for treatments that are 95% effective being preferred over those that are 80% effective. Participants strongly favoured the treatments that could completely stop transmission (OR: 7.87, 95% CI: 5.71, 10.84), and prioritised avoiding side effects (OR: 0.19, 95% CI: 0.12, 0.29). There was no evidence of an interaction between perceived TB disease risk and treatment preferences. In summary, participants were primarily concerned with the effectiveness of TB treatments and strongly preferred treatments that removed the risk of onward transmission. Person-centred approaches of preferences for treatment should be considered when designing new treatment strategies. Understanding treatment preferences will ensure that any recommended treatment for probable early TB disease is well accepted and utilized by the public., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: MQuai reports employment by Evidera, unrelated to tuberculosis and outside the submitted work. The other authors have declared that no competing interests exist., (Copyright: © 2024 Kamchedzera et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Proton magnetic resonance spectroscopy ( 1 H-MRS) is increasingly used for clinical brain tumour diagnosis, but suffers from limited spectral quality. This retrospective and comparative study aims at improving paediatric brain tumour classification by performing noise suppression on clinical 1 H-MRS. Eighty-three/forty-two children with either an ependymoma (ages 4.6 ± 5.3/9.3 ± 5.4), a medulloblastoma (ages 6.9 ± 3.5/6.5 ± 4.4), or a pilocytic astrocytoma (8.0 ± 3.6/6.3 ± 5.0), recruited from four centres across England, were scanned with 1.5T/3T short-echo-time point-resolved spectroscopy. The acquired raw 1 H-MRS was quantified by using Totally Automatic Robust Quantitation in NMR (TARQUIN), assessed by experienced spectroscopists, and processed with adaptive wavelet noise suppression (AWNS). Metabolite concentrations were extracted as features, selected based on multiclass receiver operating characteristics, and finally used for identifying brain tumour types with supervised machine learning. The minority class was oversampled through the synthetic minority oversampling technique for comparison purposes. Post-noise-suppression 1 H-MRS showed significantly elevated signal-to-noise ratios (P < .05, Wilcoxon signed-rank test), stable full width at half-maximum (P > .05, Wilcoxon signed-rank test), and significantly higher classification accuracy (P < .05, Wilcoxon signed-rank test). Specifically, the cross-validated overall and balanced classification accuracies can be improved from 81% to 88% overall and 76% to 86% balanced for the 1.5T cohort, whilst for the 3T cohort they can be improved from 62% to 76% overall and 46% to 56%, by applying Naïve Bayes on the oversampled 1 H-MRS. The study shows that fitting-based signal-to-noise ratios of clinical 1 H-MRS can be significantly improved by using AWNS with insignificantly altered line width, and the post-noise-suppression 1 H-MRS may have better diagnostic performance for paediatric brain tumours., (© 2024 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd.)

1 H-magnetic resonance spectroscopy (MRS) has the potential to improve the noninvasive diagnostic accuracy for paediatric brain tumours. However, studies analysing large, comprehensive, multicentre datasets are lacking, hindering translation to widespread clinical practice. Single-voxel MRS (point-resolved single-voxel spectroscopy sequence, 1.5 T: echo time [TE] 23-37 ms/135-144 ms, repetition time [TR] 1500 ms; 3 T: TE 37-41 ms/135-144 ms, TR 2000 ms) was performed from 2003 to 2012 during routine magnetic resonance imaging for a suspected brain tumour on 340 children from five hospitals with 464 spectra being available for analysis and 281 meeting quality control. Mean spectra were generated for 13 tumour types. Mann-Whitney U-tests and Kruskal-Wallis tests were used to compare mean metabolite concentrations. Receiver operator characteristic curves were used to determine the potential for individual metabolites to discriminate between specific tumour types. Principal component analysis followed by linear discriminant analysis was used to construct a classifier to discriminate the three main central nervous system tumour types in paediatrics. Mean concentrations of metabolites were shown to differ significantly between tumour types. Large variability existed across each tumour type, but individual metabolites were able to aid discrimination between some tumour types of importance. Complete metabolite profiles were found to be strongly characteristic of tumour type and, when combined with the machine learning methods, demonstrated a diagnostic accuracy of 93% for distinguishing between the three main tumour groups (medulloblastoma, pilocytic astrocytoma and ependymoma). The accuracy of this approach was similar even when data of marginal quality were included, greatly reducing the proportion of MRS excluded for poor quality. Children's brain tumours are strongly characterised by MRS metabolite profiles readily acquired during routine clinical practice, and this information can be used to support noninvasive diagnosis. This study provides both key evidence and an important resource for the future use of MRS in the diagnosis of children's brain tumours., (© 2024 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd.)

Background: The current study examined the role of avoidance in behavioral activation treatment compared to a supportive counseling condition targeting depressive symptoms in a sample comprised of Latinx individuals., Method: Depressed Latinx individuals with Spanish-speaking preference (LSSP; N = 46) were randomized to receive 10-weekly sessions of Brief Behavioral Activation Treatment for Depression (BATD) or supportive counseling. Participants completed weekly self-report measures of depressive symptoms and avoidance., Results: Avoidance levels decreased over the course of both treatments. However, decreases in depressive symptoms were associated with decreases in avoidance over time only for individuals who were randomized to BATD. Greater change in avoidance levels was related to post-treatment depression score, only for those who received BATD. Finally, greater avoidance prior to commencing treatment predicted lower depressive symptom change over the course of both treatments., Conclusions: This study provides preliminary evidence that avoidance may be a specific proposed mechanism of depression change in BATD among LSSP with depression. Pretreatment avoidance appears to be a useful construct to identify the trajectories of depressive symptoms over the course of psychotherapy among LSSP.

Background: The malignant childhood brain tumour, medulloblastoma, is classified clinically into molecular groups which guide therapy. DNA-methylation profiling is the current classification 'gold-standard', typically delivered 3-4 weeks post-surgery. Pre-surgery non-invasive diagnostics thus offer significant potential to improve early diagnosis and clinical management. Here, we determine tumour metabolite profiles of the four medulloblastoma groups, assess their diagnostic utility using tumour tissue and potential for non-invasive diagnosis using in vivo magnetic resonance spectroscopy (MRS)., Methods: Metabolite profiles were acquired by high-resolution magic-angle spinning NMR spectroscopy (MAS) from 86 medulloblastomas (from 59 male and 27 female patients), previously classified by DNA-methylation array (WNT (n = 9), SHH (n = 22), Group3 (n = 21), Group4 (n = 34)); RNA-seq data was available for sixty. Unsupervised class-discovery was performed and a support vector machine (SVM) constructed to assess diagnostic performance. The SVM classifier was adapted to use only metabolites (n = 10) routinely quantified from in vivo MRS data, and re-tested. Glutamate was assessed as a predictor of overall survival., Findings: Group-specific metabolite profiles were identified; tumours clustered with good concordance to their reference molecular group (93%). GABA was only detected in WNT, taurine was low in SHH and lipids were high in Group3. The tissue-based metabolite SVM classifier had a cross-validated accuracy of 89% (100% for WNT) and, adapted to use metabolites routinely quantified in vivo, gave a combined classification accuracy of 90% for SHH, Group3 and Group4. Glutamate predicted survival after incorporating known risk-factors (HR = 3.39, 95% CI 1.4-8.1, p = 0.025)., Interpretation: Tissue metabolite profiles characterise medulloblastoma molecular groups. Their combination with machine learning can aid rapid diagnosis from tissue and potentially in vivo. Specific metabolites provide important information; GABA identifying WNT and glutamate conferring poor prognosis., Funding: Children with Cancer UK, Cancer Research UK, Children's Cancer North and a Newcastle University PhD studentship., Competing Interests: Declaration of interests HR holds stock options in Healx (AI drug discovery in rare diseases). PSM is unpaid co-chair of SIOP-Europe Brain Tumour Group Imaging Group. We declare no other competing interests., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Introduction: Treatment with monoclonal antibodies provides rapid, passive immunity and may stop COVID-19 disease progression. The study evaluated the effect of bamlanivimab (BAM) or BAM + etesevimab (ETE)/sotrovimab compared to placebo on SARS-CoV-2 viral load in patients with COVID-19., Methods: The phase 2, randomized, single-dose study included patients aged between ≥ 18 and < 65 years, not hospitalized at the time of randomization, and had ≥ 1 mild or moderate COVID-19 symptoms. Study included arms 1-6 (placebo, BAM 175 mg + ETE 350 mg, BAM 700 mg + ETE 1400 mg, BAM 2800 mg + ETE 2800 mg, BAM 700 mg alone, and BAM 350 mg + ETE 700 mg, respectively), BAM 700 mg + ETE 700 mg unintentional dosing; and arms 7 and 8 (BAM 700 mg + sotrovimab 500 mg and placebo, respectively). The primary endpoint was proportion of patients with SARS-CoV-2 log viral load > 5.27 on day 7 (persistently high viral load [PHVL]) who received BAM or BAM + (ETE or sotrovimab)., Results: A total of 725 patients, mean age 39.6 years (range 18-75 years), 50.2% male were randomized and infused with study drug in arms 1-6; and a total 202 patients, mean age 38 years (range 18-63 years), 53.5% female were randomized and infused with study drug in arms 7 and 8. A significantly lower proportion of patients in arms 2-6 and arm 7 experienced PHVL on day 7 compared to placebo. On day 7, patients in arms 2, 3, and 6 consistently experienced significantly greater reduction in viral load than placebo. Significant improvement was observed in time to viral load clearance and time to symptom improvement by day 29 in some arms compared to placebo. No new safety concerns were observed with drug combinations., Conclusion: The study demonstrated that a significantly lower proportion of patients with mild-to-moderate COVID-19 treated with BAM or BAM + (ETE or sotrovimab) experienced a PHVL at day 7., Trial Registration: ClinicalTrials.gov identifier, NCT04634409., (© 2024. Eli Lilly and Co.)