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Extant literature implicates the role of glucagon-like peptide-1 (GLP-1) and GLP-1 receptor agonists (GLP-1RAs) on modulating alcohol-associated behaviours, with a particular emphasis of these agents on neural circuits subserving reward and appetite control. Herein, we explore the potential effects of GLP-1RAs on alcohol-associated behaviours in brain regions implicated in reward processing facilitating the repurposing of these agents for the treatment and prevention of problematic drinking. Understanding how GLP-1’s analogues interact with alcohol-related behaviours may underscore the development of therapeutic strategies for alcohol use disorder (AUD) and those with comorbid metabolic disorders.
Methods:
A systematic review was conducted, wherein relevant literature was identified through Web of Science, PubMed, and OVID (MedLINE, Embase, AMED, PsycInfo, JBI EBP) from database inception to October 27th, 2024. Preclinical and clinical studies examining the association between GLP-1RAs and alcohol-related behaviours were assessed.
Results:
Preclinical studies (n = 19) indicate that GLP-1RAs attenuate alcohol-related behaviours, with exenatide demonstrating significant dose-dependent effects in high alcohol-consuming phenotypes. Semaglutide and liraglutide are associated with reduced alcohol intake, though their effects were often transient. In human studies (n = 2) with AUD, semaglutide significantly reduced alcohol consumption, while exenatide showed mixed results, with reductions in alcohol drinking within high BMI subpopulations.
Discussion:
Extant preclinical and clinical literature provides preliminary support for the potential therapeutic role of GLP-1RAs in attenuating alcohol consumption and preference. There is a need for large well controlled studies evaluating the effect of GLP-1RAs as a treatment strategy for behavioural modifications in individuals living with alcohol use disorder.
Antidepressants are commonly prescribed for mood disorders. Epidemiological studies suggest antidepressant use may be associated with cataracts and glaucoma. We aim to investigate the association between antidepressants and cataracts and glaucoma.
Methods
Data was collected from the United States Food and Drug Administration Adverse Event Reporting System. Reporting odds ratio (ROR) and Bayesian information components (IC025) were calculated for antidepressants (ie, selective serotonin reuptake inhibitors [SSRIs], selective norepinephrine reuptake inhibitors [SNRIs], serotonin-norepinephrine-dopamine reuptake inhibitors, serotonin modulators and stimulators, serotonin antagonists and reuptake inhibitors [SARIs], norepinephrine reuptake inhibitors, norepinephrine-dopamine reuptake inhibitors, tricyclic antidepressants [TCAs], tetracyclic antidepressants [TeCAs], and monoamine oxidase inhibitors [MAOIs]). The reference agent was acetaminophen.
Results
TeCAs and MAOIs were significantly associated with a decreased risk of cataracts (ROR = 0.11-0.65 and 0.16-0.69, respectively). TCAs, brexanolone, esketamine, and opipramol reported an increased cataract risk (ROR = 1.31-12.81). For glaucoma, SSRIs, SNRIs, SARIs, TCAs, MAOIs, and other investigated antidepressants reported significant RORs ranging from 1.034 to 21.17. There was a nonsignificant association of angle closure glaucoma (ACG) and open angle glaucoma (OAG) with the investigated antidepressants.
Limitations
For adverse event cases, multiple suspected product names are listed, and as cases are not routinely verified, there may be a possibility of duplicate reports and causality cannot be established.
Conclusion
Most of the investigated antidepressants were associated with a lower risk of cataract reporting. TCAs, brexanolone, esketamine, and opipramol were associated with greater odds of cataract. For most antidepressants, there was an insignificant increase in reports of ACG and OAG.
The World Health Organization (WHO) has defined Post-COVID-19 Condition (PCC) as the onset of symptoms within three months after resolution of an acute SARS-CoV-2 infection, wherein symptoms persist for at least two months and cannot be explained by another medical/psychiatric condition. Persons living with PCC report debilitating symptoms including, but not limited to, depressive symptoms and motivational deficits. The aim of this post-hoc analysis was to evaluate the association between depressive symptoms and motivation in adults with PCC.
Methods
We conducted a post-hoc analysis of an 8-week, double-blind, randomized, placebo-controlled trial evaluating adults (18 years or older) in Canada with WHO-defined PCC and cognitive symptoms. This post-hoc analysis is comprised of baseline data that evaluates the association between depressive symptom severity measured by the 16-item Quick Inventory of Depressive Symptomatology-Self Report (QIDS-SR-16) and motivational systems measured by the Behavioral Inhibition System/Behavioral Activation System Questionnaire (BIS/BAS).
Results
There was a statistically significant association between depressive symptoms and BIS (β = -0.041 95% CI [-0.066, -0.016], p<0.05), BAS reward responsiveness (β = 0.043 95% CI [0.012, 0.074], p<0.05), sex (β = -0.137 95% CI [-0.266, -0.008], p<0.05), and confirmed COVID-19 infection (β = 0.196 95% CI [0.061, 0.332], p<0.05).
Conclusions
Depressive symptoms were associated with motivational deficits in persons living with PCC. Optimizing treatment for depressive symptoms may potentially improve aspects of motivational impairment amongst persons with PCC. All patients presenting with MDD and a history of COVID-19 infection should be assessed for the presence of PCC.
This study aimed to assess the relationship between COVID-19 infection-related conditions and depressive symptoms among medical staff after easing the zero-COVID policy in China, and to further examine the mediating role of professional burnout.
Methods
A total of 1716 medical staff from all levels of health care institutions in 16 administrative districts of Beijing, China, were recruited to participate at the end of 2022 in this cross-sectional study. Several multiple linear regressions and mediating effects tests were performed to analyze the data.
Results
At the beginning of the end of the zero-COVID policy in China, 91.84% of respondents reported infection with COVID-19. After adjusting for potential confounding variables, the severity of infection symptoms was significantly positively associated with high levels of depressive symptoms (β = 0.06, P < 0.001), and this association was partially mediated by professional burnout. Specifically, emotional exhaustion (95% CI, 0.131, 0.251) and depersonalization (95% CI, 0.009, 0.043) significantly mediated the association between the severity of infection symptoms and depressive symptoms.
Conclusions
The mental health of medical staff with more severe symptoms of COVID-19 infection should be closely monitored. Also, interventions aimed at reducing emotional exhaustion and depersonalization may effectively reduce their risk of developing depressive symptoms.
Many psychotropic drugs are highly associated with related weight gain. Glucagon-like peptide-1 receptor agonists (GLP-1RAs) are established anti-obesity and glucose-lowering agents. Preliminary evidence also indicates they are fit for purpose in mitigating psychotropic drug-related weight gain (PDWG). This systematic review aims to synthesize the extant evidence from randomized controlled trials (RCTs) on the effects of GLP-1RAs on weight change in persons experiencing PDWG.
Methods
Online databases (ie, PubMed, OVID Medline, Google Scholar) were searched to identify relevant studies from inception to January 1, 2024. Articles were screened by title, abstract, and full-text by three independent reviewers against inclusion and exclusion criteria.
Results
We identified six studies with participants aged ≥18 (n=374) that were eligible for inclusion in our systematic review. Most studies reported a significant and clinically meaningful effect of GLP-1RAs on anthropometrics and/or metabolics. All RCTs replicated the finding of modest or greater effects of GLP-1RAs; the most studied agents were liraglutide and exenatide. There was insufficient literature to conduct a meta-analysis.
Conclusion
Evidence suggests that GLP-1RAs are effective in mitigating weight gain in persons prescribed psychiatric medication. It is hypothesized that GLP-1RAs may moderate weight change in persons prescribed psychiatric medication through direct effects on metabolism and cognitive processes implicated in hunger/satiety. Future studies should aim to explore the long-term safety, tolerability, and efficacy profiles of various GLP-1RAs in the treatment and prevention of abnormal weight and metabolic homeostasis in psychiatric populations.
The practical implementation of machine learning in flow control is limited due to its significant training expenses. In the present study the convolutional neural network (CNN) trained with the data of the restricted nonlinear (RNL) model is used to predict the normal velocity on a detection plane at $y^+=10$ in a turbulent channel flow, and the predicted velocity is used as wall blowing and suction for drag reduction. An active control test is carried out by using the well-trained CNN in direct numerical simulation (DNS). Substantial drag reduction rates up to 19 % and 16 % are obtained based on the spanwise and streamwise wall shear stresses, respectively. Furthermore, we explore the online control of wall turbulence by combining the RNL model with reinforcement learning (RL). The RL is constructed to determine the optimal wall blowing and suction based on its observation of the wall shear stresses without using the label data on the detection plane for training. The controlling and training processes are conducted synchronously in a RNL flow field. The control strategy discovered by RL has similar drag reduction rates with those obtained previously by the established method. Also, the training cost decreases by over thirty times at $Re_{\tau }=950$ compared with the DNS-RL model. The present results provide a perspective that combining the RNL model with machine learning control for drag reduction in wall turbulence can be effective and computationally economical. Also, this approach can be easily extended to flows at higher Reynolds numbers.
Chemical defoliants are widely used in cotton (Gossypium L.) to accelerate leaf abscission and boll maturation, as well as, to facilitate mechanical harvesting. The current study was conducted to determine the interactive effect of cotton cultivars and spraying time of defoliant on defoliation, boll opening, fibre yield and quality. An experiment was performed with four cultivars and three defoliant spraying time during 2019 and 2020 in split plot design with three replications. At harvest, the defoliation and boll opening rate of all treatments after spraying defoliant was 94.6 and 85.4%, while the blank control (water) was 73.9 and 79.1%, respectively. After spraying defoliant, the effects of defoliation rate, boll opening rate, fibre yield and quality were different among cultivars, indicating that different cultivars had different responses to defoliant. Among them, L7619 was the most sensitive to defoliant, with the average defoliation rate of 95.6% and a seed cotton yield reduction of 882.9 kg/ha. Among the different time of applications, late spraying (17 September, B3) of defoliant recorded the highest defoliation rate (97.3%), boll opening rate (89.8%), seed cotton yield (3991 kg/ha) and steadily increased the fibre strength by 0.59 cN/tex compared with the control. Late spraying of defoliant had little or even no adverse effect on the remaining fibre quality traits (length, uniformity, micronaire and elongation). In general, these results suggested that the appropriate time for spraying defoliant can be determined based on the sensitivity of the cotton cultivar, the weather conditions at the field and the harvest time.
Based on the chemical reaction model proposed by Park, the ‘blackout’ of a reentry vehicle is studied in this paper. The temperature, pressure and electron density distribution characteristics around the reentry vehicle were simulated at various flight speeds and altitudes by USim. Subsequently, the scattering matrix method was used to study the transmission characteristics of terahertz waves in ‘blackout’. The simulation results show that the temperature around the aircraft is mainly affected by speed, the pressure is mainly affected by the altitude and electron density is affected by both of these factors. The calculation results show that the transmission characteristics of terahertz waves in plasma are mainly affected by electron density, while the effects of temperature and pressure cannot be ignored either.
We offer a new social approach to investment decision making and asset prices. Investors discuss their strategies and convert others to their strategies with a probability that increases in investment returns. The conversion rate is shown to be convex in realized returns. Unconditionally, active strategies (e.g., high variance and skewness) dominate, although investors have no inherent preference for these characteristics. The model has strong predictions for how the adoption of active strategies depends on investors’ social networks. In contrast with nonsocial approaches, sociability, self-enhancing transmission, and other features of the communication process determine the popularity and pricing of active investment strategies.
It was reported that about 10% of people suffer from painful knee arthritis, and a quarter of them were severely disabled. The core activities of daily living were severely limited by knee osteoarthritis (KOA). In order to reduce knee pain and prolong the life of the knee joint, there has been an increasing demand on the development of exoskeletons, for prevention and treatment. The course of KOA was closely related to the biomechanics of knee joint, and the pathogenesis was summarized based on the biomechanics of knee joint. For the prevention and clinical treatment, exoskeletons are classified into three categories: prevention, treatment, and rehabilitation after the operation. Furthermore, the design concepts, actuators, sensors, control strategies, and evaluation criteria were presented. Finally, the shortcomings and limitations were summarized. It is useful for researchers to develop suitable exoskeletons in the future.
To assess the consumption of sugar-sweetened beverages (SSB) and other energy-dense nutrient-poor (EDNP) foods in two Southern low-income communities targeted by the Balance Calories Initiative, a campaign by the top-three American beverage companies intended to reduce the consumption of sugary beverages by 20 % over 10 years.
Design:
We conducted self-administered intercept surveys in front of food retail outlets between August and November 2016. We recruited adults with children <18 years living at home and adolescents aged 10–17 years with parental consent.
Setting:
Retail food outlets in Mississippi and Alabama, USA.
Participants:
Adults (n 11 311) and adolescents (n 3460).
Results:
The percentage of high SSB consumers (≥4 servings/d) was 40·9 % among adult males, 32·3 % among adult females, 43·0 % among adolescent males and 34·4 % among adolescent females (male – female difference, P < 0·0001). In aggregate, respondents also reported consuming a mean of 3 servings of salty snacks, cookies and/or candy in the past 24 h, with adolescent males reporting 4 servings.
Conclusions:
SSB should be a primary target of future interventions to improve dietary intake, but EDNP foods likely contribute as many daily kilojoules as SSB among this population. Future campaigns should aim to limit the consumption of all EDNP foods.
To explore whether and how group cognitive-behavioural therapy (GCBT) plus medication differs from medication alone for the treatment of generalised anxiety disorder (GAD).
Methods:
Hundred and seventy patients were randomly assigned to the GCBT plus duloxetine (n=89) or duloxetine group (n=81). The primary outcomes were Hamilton Anxiety Scale (HAMA) response and remission rates. The explorative secondary measures included score reductions from baseline in the HAMA total, psychic, and somatic anxiety subscales (HAMA-PA, HAMA-SA), the Hamilton Depression Scale, the Severity Subscale of Clinical Global Impression Scale, Global Assessment of Functioning, and the 12-item Short-Form Health Survey. Assessments were conducted at baseline, 4-week, 8-week, and 3-month follow-up.
Results:
At 4 weeks, HAMA response (GCBT group 57.0% vs. control group 24.4%, p=0.000, Cohen’s d=0.90) and remission rates (GCBT group 21.5% vs. control group 6.2%, p=0.004; d=0.51), and most secondary outcomes (all p<0.05, d=0.36−0.77) showed that the combined therapy was superior. At 8 weeks, all the primary and secondary significant differences found at 4 weeks were maintained with smaller effect sizes (p<0.05, d=0.32−0.48). At 3-month follow-up, the combined therapy was only significantly superior in the HAMA total (p<0.045, d=0.43) and HAMA-PA score reductions (p<0.001, d=0.77). Logistic regression showed superiority of the combined therapy for HAMA response rates [odds ratio (OR)=2.12, 95% confidence interval (CI) 1.02−4.42, p=0.04] and remission rates (OR=2.80, 95% CI 1.27−6.16, p=0.01).
Conclusions:
Compared with duloxetine alone, GCBT plus duloxetine showed significant treatment response for GAD over a shorter period of time, particularly for psychic anxiety symptoms, which may suggest that GCBT was effective in changing cognitive style.
Underground Nuclear Astrophysics in China (JUNA) will take the advantage of the ultra-low background in Jinping underground lab. High current accelerator with an ECR source and detectors were commissioned. JUNA plans to study directly a number of nuclear reactions important to hydrostatic stellar evolution at their relevant stellar energies. At the first period, JUNA aims at the direct measurements of 25Mg(p,γ)26 Al, 19F(p,α) 16 O, 13C(α, n) 16O and 12C(α,γ) 16O near the Gamow window. The current progress of JUNA will be given.
The study of the relationship among the manufacturing process, the structure and the property of materials can help to develop the new materials. The material images contain the microstructures of materials, therefore, the quantitative analysis for the material images is the important means to study the characteristics of material structures. Generally, the quantitative analysis for the material microstructures is based on the exact segmentation of the materials images. However, most material microstructures are shown with various shapes and complex textures in images, and they seriously hinder the exact segmentation of the component elements. In this research, machine learning method and complex networks method are adopted to the challenge of automatic material image segmentation. Two segmentation tasks are completed: on the one hand, the images of the titanium alloy are segmented based on the pixel-level classification through feature extraction and machine learning algorithm; on the other hand, the ceramic images are segmented with the complex networks theory. In the first task, texture and shape features near each pixel in titanium alloy image are calculated, such as Gabor filters, Hu moments and GLCM (Gray-Level Co-occurrence Matrix) etc.. The feature vector for the pixel can be obtained by arraying these features. Then, classification is performed with the random forest model. Once each pixel is classified, the image segmentation is completed. In the second task, a complex network structure is built for the ceramic image. Then, a clustering algorithm of complex network is used to obtain network connection area. Finally, the clustered network structure is mapped back to the image and getting the contours among the component elements. The experimental results demonstrate that these methods can accurately segment material images.
In a model where investors disagree about the fundamentals of two stocks, the state-price density depends on investor disagreements for both stocks, especially the larger stock. This implies that disagreement among investors in a large firm has a spillover effect on the pricing of other stocks owned by these investors. The pricing effects of investor disagreements crucially depend on the average belief biases. Empirical findings support the novel model prediction of a disagreement spillover effect and help reconcile some mixed evidence in the literature.
The aim of this study was to determine whether vitamin D supplementation and maintaining vitamin D sufficiency are associated with changes in inflammatory and metabolic biomarkers in patients with knee osteoarthritis (OA) and vitamin D deficiency. A total of 413 participants with symptomatic knee OA and vitamin D deficiency were enrolled in a randomised, placebo-controlled trial and received 1·25 mg vitamin D3 or placebo monthly for 24 months across two sites. In this post hoc analysis, 200 participants from one site (ninety-four from the placebo group and 106 from the vitamin D group; mean age 63·1 (sd 7·3) years, 53·3 % women) were randomly selected for measurement of serum levels of inflammatory and metabolic biomarkers at baseline and 24 months using immunoassays. In addition, participants were classified into two groups according to serum 25-hydroxyvitamin D (25(OH)D) levels at months 3 and 24: (1) not consistently sufficient (25(OH)D≤50 nmol/l at either month 3 or 24, n 61), and (2) consistently sufficient (25(OH)D>50 nmol/l at both months 3 and 24, n 139). Compared with placebo, vitamin D supplementation had no significant effect on change in serum high-sensitive C-reactive protein, IL-6, IL-8, IL-10, leptin, adiponectin, resistin, adipsin and apelin. Being consistently vitamin D sufficient over 2 years was also not associated with changes in these biomarkers compared with not being consistently sufficient. Vitamin D supplementation and maintaining vitamin D sufficiency did not alter serum levels of inflammatory and metabolic biomarkers over 2 years in knee OA patients who were vitamin D insufficient, suggesting that they may not affect systemic inflammation in knee OA patients.
Monosized spherical Cu–20% Sn (wt%) alloy particles with diameter ranging from 70.6 to 334.0 μm were prepared by the pulsated orifice ejection method (termed “POEM”). Fully dense without pores and bulk inclusions, the cross-sectional micrographs of the spherical alloy particles indicate an even distribution of Cu and Sn. These spherical Cu–Sn alloy particles exhibit a good spherical shape and a narrow size distribution, suggesting that the liquid Cu–Sn alloy can completely break the balance between the surface tension and the liquid static pressure in the crucible micropores and accurately control the volume of the droplets. Furthermore, the cooling rate of spherical Cu–20% Sn alloy particles is estimated by a Newton’s cooling model. The cooling rate of the Cu–20% Sn alloy particle decreases gradually with the particle diameter increasing. Smaller particles have higher cooling rates and when the particle diameter is less than 70 μm, the cooling rate of particles can reach more than 3.3 × 104 K/s. The secondary dendrite arm spacing has strong dependence on particle diameter which increases gradually with the increase of particle diameter. The results demonstrate that POEM is an effective route for fabrication of high-quality monosized Cu–20% Sn alloy particles.