McMaster University

Aims: Magnetic resonance imaging (MRI) studies have identified brain structural predictors of treatment response in individuals with alcohol use disorder (AUD), but with varying findings and primarily in male veterans. The present study investigated cortical surface area and thickness (CT) as predictors of brief intervention response in community-based adults with AUD. Methods: Sixty-five non-treatment-seeking adults with AUD (44.6% male, aged 33.2±10.3 years) underwent an MRI and received a brief intervention comprising personalized feedback and motivational interviewing, with follow-up approximately 6-8 weeks later to quantify changes in drinks/week (DPW), the primary outcome. Eighteen bilateral a priori regions of interest (ROIs) were used to predict DPW at follow-up, adjusting for baseline drinking. Significant predictors were examined with secondary outcomes, percent drinking and heavy drinking days, and in relation to out-of-scanner measures of impulsivity and comorbidities. Results: Participants exhibited expected significant decreases in alcohol consumption in response to the brief intervention. Eight bilateral CT ROIs in the frontal, temporal, and occipital lobes, most notably medial orbitofrontal, middle temporal, and lateral occipital gyri, predicted DPW; however, only three predicted the secondary outcomes. Significant associations were observed between CT in frontal and occipital regions with impulsivity (delay discounting, lack of premeditation), executive functioning, anxiety, and stress. Conclusions: Thinner frontal, temporal, and occipital ROIs predicted poorer brief intervention response, with notable overlap with brain regions previously implicated in AUD. Clarifying whether these regions reflect premorbid or acquired differences and, if the latter, the potential for recovery of cortical gray matter following drinking reductions are future priorities.

In vitro selection methods are used to identify catalytic RNAs from pools of random sequences. We discuss the central concepts using experimental data and computational models. Experiments proceed in multiple rounds, each with a reaction step and a step in which reacted sequences are recovered. Sequences are enriched each round by a factor depending on combined reaction and recovery probability. In the first round, there are few functional sequences, and it is necessary to minimize the probability of losing these. In later rounds, the loss probability is negligible, and the procedure can be optimized to maximize the enrichment factor. Clusters of related sequences emerge which descend from separate sequences in the initial pool. The fitness of an RNA depends on how well it matches a structure with specified sequence and base-pair constraints. Sequences that exactly match the constraints may be rare, but sequences a few mutations away are much more common; hence it is likely that clusters descend from suboptimal sequences. There is a high probability that beneficial mutations arise during the experiment. This explains the experimental observation that there is little correlation between cluster frequencies and fitnesses, whereas correlation between enrichment factors and fitnesses is strong.

Periodic election is the hallmark of electoral democracy. In achieving this, continental groups such as the African Union (AU) have initiated interventions to allow nations to function and compare notes within a measurable framework. Tanzania is one of the signatories to the APRM document and has engaged several partners in recent presidential, parliamentary, and councillorship elections. The transitions were held despite the recurring socioeconomic challenges as well as the increased burden of the fight against the effects of insurgency, displacements, and the COVID-19 pandemic, which ravaged the resources of these countries. However, the country’s First-Past-the-Post electoral system was confronted by issues such as the adoption of technology, election management agencies, political participation, free press, independent candidacy, and election dispute resolution mechanisms. This study examines the role of partner institutions, especially the African Development Bank (AfDB), the United Nations Development Programme, and the United Nations Economic Commission for Africa (UNECA), in the democratization process of the member countries. The study relied on data from democratic partner agencies as well as existing data from relevant secondary sources and suggested ways to further strengthen democracy in these countries and other democracies across the world.

Eosinophilia is a hallmark of allergic disorders, including asthma, allergic rhinitis, and atopic dermatitis. The onset and maintenance of allergic inflammation in atopic adults involves the activation of selective hemopoietic processes and the migration of mature and immature eosinophils to allergic tissue, where these cells release mediators of inflammation that participate in the regulation of inflammation. Eosinophils function in close cooperation with basophils and mast cells in allergic tissue, where crosstalk between these central effector cells regulates the inflammatory process. This chapter will review the cellular events leading to the accumulation of eosinophils and their progenitors in the airways in allergic asthma, with a particular focus on models of allergen‐induced allergic inflammation. Inhaled allergen challenges in allergic asthmatics have advanced understanding of the pathogenesis of allergen exposure leading to early and late asthmatic responses and the associated airway hyperresponsiveness and type 2 airway inflammation. This chapter will also discuss the mechanisms of commonly used asthma therapies on allergen‐induced eosinophilia and compare the effects of novel therapies targeting specific immune pathways for a better understanding of how to regulate airway eosinophil levels in patients with asthma.

Ventricular arrhythmias (VA), including ventricular tachycardia and fibrillation, are critical cardiac conditions that are often managed by catheter ablation among those unresponsive to pharmacologic therapy. The choice of anesthesia and sedation regimens for VA ablations may impact arrhythmia inducibility and hemodynamic stability, which can affect procedural success and complication rates. This systematic review and meta-analysis aimed to compare the efficacy and safety of sedation versus general anesthesia (GA) among patients undergoing VA ablation. The review was prospectively registered on PROSPERO (CRD42023441553). Database searches were conducted across five major databases from inception to March 9, 2024 to identify randomized trials or observational studies including adult patients undergoing ablations for VA. Screening and data extraction were completed in duplicate. Risk-of-bias assessments were conducted using ROBINS-I as all included studies were observational, and the quality of evidence was evaluated using the GRADE framework. Six observational studies (N = 16,435) were included. No significant differences were found between sedation and GA for total procedure time (MD: −14.16 minutes; 95%CI: −38.61 to 10.29 minutes), arrhythmia non-inducibility (RR: 0.73; 95% CI: 0.33–1.58), acute ablation success (RR: 1.06; 95% CI: 0.65–1.71), or procedural complications (RR: 0.72; 95% CI: 0.28–1.85). However, sedation was associated with significantly lower intraprocedural hemodynamic instability (RR: 0.28; 95% CI: 0.12–0.70). These findings indicate that while sedation and GA have comparable outcomes, sedation may be associated with less hemodynamic instability during VA ablation. However, more high-quality studies are needed to confirm these results.

Post-COVID-19 condition (PCC) is a serious debilitating condition that develops after the resolution of an acute infection of severe acute respiratory syndrome-associated coronavirus 2. Some commonly reported symptoms include fatigue and cognitive deficits. Multiple lines of evidence have indicated fatigue to be associated with cognitive deficits in the general population. Herein, we perform a secondary analysis of the effects of fatigue on subjective and objective cognition in persons with PCC using a generalized linear model. In this study, fatigue was measured using the Fatigue Severity Scale (FSS) and cognition was measured using the Digit-Symbol Substitution Test (DSST) and the Trails Making Test parts A and B (TMT-A/B). FSS had a statistically significant negative correlation with DSST and TMT-A/B scores. Fatigue serves as a possible target for the development of PCC therapeutics. Fatigue and cognition correlates should be further investigated for underlying neurobiological substrates in persons with PCC.

This study presents the modeling and simulation of carbon dioxide (CO₂) absorption in hybrid amine solutions using machine learning algorithms and response surface methodology (RSM). The process was governed by adjustable input parameters, including pressure (0.50–7.76 bar), temperature (292.8–343.1 K), time (0–1680 s), and solvent concentrations (1–5 wt% for N-methyl diethanolamine (MDEA), 1–5 wt% for sulfolane, and 1–5 wt% for piperazine (PZ)). The primary objective was to leverage the synergistic effects of chemical and physical solvents for enhanced CO₂ absorption. Seven machine learning models—MLP, RBF, LightGBM, XGBoost, Random Forest, ExtraTrees, and Adaboost—were employed for accurate prediction and parametric analysis. Among these, MLP with 147 neurons and RBF with 560 neurons demonstrated superior performance, achieving R² values of 0.9982 and 0.9975, respectively. A comparative analysis with RSM confirmed that neural networks exhibited superior predictive accuracy and generalization. The findings revealed that CO₂ absorption capacity increased with rising pressure and time but decreased with higher temperatures and solvent concentrations. Additionally, optimization through a genetic algorithm (GA) was employed to identify the best input parameters for maximizing CO₂ loading, achieving optimal conditions with a CO₂ loading of 0.62, 0.55, and 0.50 for RSM, MLP + GA, and RBF + GA, respectively.

Psoriatic disease is a lifelong chronic illness for which there is no cure. It is well established that psoriasis leads to a major impairment of health-related quality-of-life and wellbeing. Most people with psoriasis live together with partners, bringing along a major burden for them. The FamilyPso was created to measure this burden in psoriasis. The aim of the FamilyPso international study was to validate this tool and to show feasibility for the use of the FamilyPso across multiple countries. A prospective cohort study was conducted in 11 centers in Austria, Canada, Germany, Italy, Spain, and Turkey. The factor structure of the FamiliyPso was examined by confirmatory factor analysis (CFA) including tests of measurement invariance for gender and language. Subgroups (e.g., countries and gender) were tested for significant differences, and the relationship between the severity of illness and FamilyPso scores was tested for differences between countries using a mixed regression model. Descriptive statistics for items and scores are presented herein. The cohort consisted of 556 people with psoriasis and their partners. Patients agreed that their partners would answer the questionnaire in their absence and return the forms to the centers. The mean age of patients and partners was 51 years. Psoriasis severity was mild in 57.6%, moderate in 31.5%, and severe in 10.9% of cases, and 91.3% received treatment. The results of the CFA confirmed the original factor structure with minor modifications. Self-assessed high severity of psoriasis was a predictor for a higher burden in 4/5 FamilyPso domains. There was an increased burden to partners related to the severity of psoriasis particularly in the domain “general emotional strain,” including items such as a “feeling of helplessness.” The results of the study showed that the FamilyPso could assess the burden of partners of people with psoriasis and can be used across different countries. The data can improve management of psoriatic disease and should be considered in shared decision-making.

Psychological stress changes both behaviour and metabolism to protect organisms. Adrenaline is an important driver of this response. Anxiety correlates with circulating free fatty acid levels and can be alleviated by a peripherally restricted β-blocker, suggesting a peripheral signal linking metabolism with behaviour. Here we show that adrenaline, the β3 agonist CL316,243 and acute restraint stress induce growth differentiation factor 15 (GDF15) secretion in white adipose tissue of mice. Genetic inhibition of adipose triglyceride lipase or genetic deletion of β-adrenergic receptors blocks β-adrenergic-induced increases in GDF15. Increases in circulating GDF15 require lipolysis-induced free fatty acid stimulation of M2-like macrophages within white adipose tissue. Anxiety-like behaviour elicited by adrenaline or restraint stress is eliminated in mice lacking the GDF15 receptor GFRAL. These data provide molecular insights into the mechanisms linking metabolism and behaviour and suggest that inhibition of GDF15–GFRAL signalling might reduce acute anxiety.

Introduction This study describes baseline and clinical characteristics, treatment patterns, survival, and safety outcomes of patients with acute myeloid leukemia (AML) who received oral azacitidine (oral‐AZA) maintenance therapy in Canada following its approval in 2021. Methods A retrospective, observational medical record review was conducted of patients with AML in remission after induction therapy and who initiated treatment with oral‐AZA between March 2021 and July 2023 in Canada. Real‐world relapse‐free survival and overall survival outcomes were estimated using Kaplan–Meier methodology. Results Data from 119 patients were analyzed. The median age at oral‐AZA initiation was 62.5 years. Most patients had favorable (39.5%) or intermediate (39.5%) genetic risk per the 2017/2022 European LeukemiaNet classification. Nearly all patients (99.2%) received cytarabine‐based induction regimens. A total of 55.5% of patients received consolidation therapy, with a median of two cycles. After a median follow‐up of 9.4 months, 68.1% of all patients were still receiving oral‐AZA at last follow‐up. After oral‐AZA treatment, 21.0% of patients relapsed. Rates of real‐world relapse‐free survival and overall survival at 12 months from oral‐AZA initiation were 66.9% and 74.5%, respectively. During oral‐AZA treatment, 67.2% of patients experienced ≥1 adverse event. Concomitant antiemetic treatment was received by 78.2% of patients. Conclusion These findings provide real‐world evidence further supporting the use of oral‐AZA as a standard‐of‐care maintenance therapy in current routine clinical practice for patients with AML in remission who do not receive hematopoietic stem cell transplantation. These results may inform a broader clinical audience because of the inclusion of patients with diverse demographic and clinical characteristics.

In this article, we present the response to authors who had concerns on our article (recently published in the December 12, 2024, issue of the Indian Journal of Psychiatry)[1] with interest.

Inflammatory myofibroblastic tumor (IMT) of the heart is a very rare tumor, constituting less than 5% of primary heart tumors. This case report describes the unexpected finding of IMT of the heart causing pulmonary artery obstruction in an asymptomatic toddler.

Dispersive order is used to compare the variability in probability distributions, while star order is used to compare the skewness of probability distributions. In this paper, we discuss dispersive and star orders of the smallest and largest order statistics from dependent unit gamma Gompertz random variables. We also use the Archimedean copula for representing the joint distribution of the underlying random variables. Several numerical examples are presented in order to illustrate all the results established here.

Low-dose computed tomography (LDCT) is increasingly adopted in medical imaging to minimize radiation exposure. However, the diagnostic accuracy is primarily affected by different noise sources, e.g., quantum, electronic, and reconstruction. Moreover, conventional denoising methods struggle with the non-uniform noise distributions in LDCT images and often require complex projection data, which limits their effectiveness and generalizability. Herein, we propose an AI-based denoising approach using an Attention Residual U-Net (ARU-Net) architecture integrated into the CycleGAN framework named Attention Residual U-Net CycleGAN (ARUC-GAN). The proposed framework outperforms state-of-theart denoising models, such as RED-CNN, EDCNN, and CTformer, according to experimental evaluation on the Mayo Clinic abdominal CT dataset. The model exhibits a peak signal-to-noise ratio (PSNR) of 34.82 dB, a structural similarity index (SSIM) of 0.85, and an RMSE of 0.018. Furthermore, the model successfully maintains edge structures with an Edge Keeping Index (EKI) of 0.835. The visual examination validates ARUC-GAN’s superior texture and detail preservation. The results indicate that the suggested method has great promise as a smart health tool for improving diagnosis accuracy in LDCT scans.

When intersecting non-matching three dimensional lattices, one needs to calculate the intersections of tetrahedra. The authors’ previously published two dimensional triangle-triangle intersection algorithm suggests a novel approach in three dimensions based on parsimony. The algorithm presented here expands on this two dimensional algorithm and introduces new strategies necessitated by the increase in dimension. An extensive proof is given for the consistency of the algorithm. Thus, the algorithm is shown to be robust to numerical error arising from floating-point arithmetic. Example problems demonstrate its use and effectiveness.

Background During the recent COVID-19 pandemic, reports of long-term persistence or recurrence of symptoms after SARS-CoV-2 infection emerged, which are now collectively referred to as ‘long COVID’. Most descriptions of long COVID originate from patients residing in high-income countries. We set out to characterise long COVID in a large-scale clinical trial that was conducted in low-middle, high-middle and high-income countries. Methods The Anti-Coronavirus Therapies trials enrolled 6528 adult patients with symptomatic COVID-19 in Argentina, Brazil, Canada, Colombia, Ecuador, Egypt, India, Nepal, Pakistan, Philippines, Russia, Saudi Arabia, South Africa and the United Arab Emirates. Long COVID was defined as the presence of patient-reported symptoms at 180 days after enrolment. Multivariable logistic regression was used to evaluate associations of baseline characteristics with long COVID. Results Of 4697 included participants, 1181 (25.1%) reported long COVID symptoms. The most frequently reported symptoms were sleeping disorders (n=601; 12.8%), joint pain (n=461; 9.8%), fatigue (n=410; 8.7%) and headaches (n=382; 8.1%). Long COVID prevalence was higher in participants from lower middle-income compared with high-income countries (29.8% (850/2854) vs 14.4% (102/706); adjusted OR (aOR) 1.53 (1.10 to 2.14); p=0.012). Prevalence also varied between participants of different ethnic backgrounds and was highest (36.1% (775/2145)) for patients of Arab/North African ethnicity. Patients requiring inpatient admission were at increased risk of long COVID (aOR: 2.04 (1.63 to 2.54); p<0.001). Other independent predictors of long COVID were male sex, older age and hypertension. Vaccination, prior lung disease, smoking and diabetes mellitus conferred protective effects. Conclusion Symptoms of long COVID are reported in a quarter of cases of symptomatic COVID-19 in this study and were significantly more prevalent in participants from countries with lower income status and in patients of Arab/North African ethnicity. Research to further assess the health burden posed by long COVID in low- and middle-income countries is urgently needed.

Highlights Addressing equity meaningfully helps reduce disease burden and improve health outcomes for all, including populations experiencing inequities, as highlighted in the commentaries by Persaud, Dewidar and colleagues. Guiding principles and tools, such as the GIN‐McMaster equity extension checklist, support the systematic consideration of equity in the guideline enterprise, ensuring recommendations remain adaptable, impactful, and responsive to evolving evidence and varying resource contexts.