Refine
Year of publication
Document Type
- Article (44)
- Postprint (9)
- Other (8)
- Conference Proceeding (2)
- Doctoral Thesis (1)
- Part of Periodical (1)
- Preprint (1)
- Review (1)
Is part of the Bibliography
- yes (67)
Keywords
- Alcohol dependence (6)
- fMRI (6)
- Pavlovian-to-instrumental transfer (4)
- Reinforcement learning (4)
- Working memory (3)
- alcohol (3)
- ventral striatum (3)
- working memory (3)
- Cognition (2)
- Cognitive impairment (2)
Institute
- Department Sport- und Gesundheitswissenschaften (28)
- Department Psychologie (10)
- Strukturbereich Kognitionswissenschaften (9)
- Institut für Biochemie und Biologie (5)
- Institut für Mathematik (4)
- Extern (2)
- Fakultät für Gesundheitswissenschaften (1)
- Humanwissenschaftliche Fakultät (1)
- Institut für Geowissenschaften (1)
- Institut für Informatik und Computational Science (1)
Importance Alcohol consumption (AC) leads to death and disability worldwide. Ongoing discussions on potential negative effects of the COVID-19 pandemic on AC need to be informed by real-world evidence.
Objective To examine whether lockdown measures are associated with AC and consumption-related temporal and psychological within-person mechanisms.
Design, Setting, and Participants This quantitative, intensive, longitudinal cohort study recruited 1743 participants from 3 sites from February 20, 2020, to February 28, 2021. Data were provided before and within the second lockdown of the COVID-19 pandemic in Germany: before lockdown (October 2 to November 1, 2020); light lockdown (November 2 to December 15, 2020); and hard lockdown (December 16, 2020, to February 28, 2021).
Main Outcomes and Measures Daily ratings of AC (main outcome) captured during 3 lockdown phases (main variable) and temporal (weekends and holidays) and psychological (social isolation and drinking intention) correlates.
Results Of the 1743 screened participants, 189 (119 [63.0%] male; median [IQR] age, 37 [27.5-52.0] years) with at least 2 alcohol use disorder (AUD) criteria according to the Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) yet without the need for medically supervised alcohol withdrawal were included. These individuals provided 14 694 smartphone ratings from October 2020 through February 2021. Multilevel modeling revealed significantly higher AC (grams of alcohol per day) on weekend days vs weekdays (β = 11.39; 95% CI, 10.00-12.77; P < .001). Alcohol consumption was above the overall average on Christmas (β = 26.82; 95% CI, 21.87-31.77; P < .001) and New Year’s Eve (β = 66.88; 95% CI, 59.22-74.54; P < .001). During the hard lockdown, perceived social isolation was significantly higher (β = 0.12; 95% CI, 0.06-0.15; P < .001), but AC was significantly lower (β = −5.45; 95% CI, −8.00 to −2.90; P = .001). Independent of lockdown, intention to drink less alcohol was associated with lower AC (β = −11.10; 95% CI, −13.63 to −8.58; P < .001). Notably, differences in AC between weekend and weekdays decreased both during the hard lockdown (β = −6.14; 95% CI, −9.96 to −2.31; P = .002) and in participants with severe AUD (β = −6.26; 95% CI, −10.18 to −2.34; P = .002).
Conclusions and Relevance This 5-month cohort study found no immediate negative associations of lockdown measures with overall AC. Rather, weekend-weekday and holiday AC patterns exceeded lockdown effects. Differences in AC between weekend days and weekdays evinced that weekend drinking cycles decreased as a function of AUD severity and lockdown measures, indicating a potential mechanism of losing and regaining control. This finding suggests that temporal patterns and drinking intention constitute promising targets for prevention and intervention, even in high-risk individuals.
Background
The metabolic syndrome (MetS) is a risk cluster for a number of secondary diseases. The implementation of prevention programs requires early detection of individuals at risk. However, access to health care providers is limited in structurally weak regions. Brandenburg, a rural federal state in Germany, has an especially high MetS prevalence and disease burden. This study aims to validate and test the feasibility of a setup for mobile diagnostics of MetS and its secondary diseases, to evaluate the MetS prevalence and its association with moderating factors in Brandenburg and to identify new ways of early prevention, while establishing a “Mobile Brandenburg Cohort” to reveal new causes and risk factors for MetS.
Methods
In a pilot study, setups for mobile diagnostics of MetS and secondary diseases will be developed and validated. A van will be equipped as an examination room using point-of-care blood analyzers and by mobilizing standard methods. In study part A, these mobile diagnostic units will be placed at different locations in Brandenburg to locally recruit 5000 participants aged 40-70 years. They will be examined for MetS and advice on nutrition and physical activity will be provided. Questionnaires will be used to evaluate sociodemographics, stress perception, and physical activity. In study part B, participants with MetS, but without known secondary diseases, will receive a detailed mobile medical examination, including MetS diagnostics, medical history, clinical examinations, and instrumental diagnostics for internal, cardiovascular, musculoskeletal, and cognitive disorders. Participants will receive advice on nutrition and an exercise program will be demonstrated on site. People unable to participate in these mobile examinations will be interviewed by telephone. If necessary, participants will be referred to general practitioners for further diagnosis.
Discussion
The mobile diagnostics approach enables early detection of individuals at risk, and their targeted referral to local health care providers. Evaluation of the MetS prevalence, its relation to risk-increasing factors, and the “Mobile Brandenburg Cohort” create a unique database for further longitudinal studies on the implementation of home-based prevention programs to reduce mortality, especially in rural regions.
Trial registration
German Clinical Trials Register, DRKS00022764; registered 07 October 2020—retrospectively registered.
Background
The metabolic syndrome (MetS) is a risk cluster for a number of secondary diseases. The implementation of prevention programs requires early detection of individuals at risk. However, access to health care providers is limited in structurally weak regions. Brandenburg, a rural federal state in Germany, has an especially high MetS prevalence and disease burden. This study aims to validate and test the feasibility of a setup for mobile diagnostics of MetS and its secondary diseases, to evaluate the MetS prevalence and its association with moderating factors in Brandenburg and to identify new ways of early prevention, while establishing a “Mobile Brandenburg Cohort” to reveal new causes and risk factors for MetS.
Methods
In a pilot study, setups for mobile diagnostics of MetS and secondary diseases will be developed and validated. A van will be equipped as an examination room using point-of-care blood analyzers and by mobilizing standard methods. In study part A, these mobile diagnostic units will be placed at different locations in Brandenburg to locally recruit 5000 participants aged 40-70 years. They will be examined for MetS and advice on nutrition and physical activity will be provided. Questionnaires will be used to evaluate sociodemographics, stress perception, and physical activity. In study part B, participants with MetS, but without known secondary diseases, will receive a detailed mobile medical examination, including MetS diagnostics, medical history, clinical examinations, and instrumental diagnostics for internal, cardiovascular, musculoskeletal, and cognitive disorders. Participants will receive advice on nutrition and an exercise program will be demonstrated on site. People unable to participate in these mobile examinations will be interviewed by telephone. If necessary, participants will be referred to general practitioners for further diagnosis.
Discussion
The mobile diagnostics approach enables early detection of individuals at risk, and their targeted referral to local health care providers. Evaluation of the MetS prevalence, its relation to risk-increasing factors, and the “Mobile Brandenburg Cohort” create a unique database for further longitudinal studies on the implementation of home-based prevention programs to reduce mortality, especially in rural regions.
Trial registration
German Clinical Trials Register, DRKS00022764; registered 07 October 2020—retrospectively registered.
Stripe rust (Pst) is a major disease of wheat crops leading untreated to severe yield losses. The use of fungicides is often essential to control Pst when sudden outbreaks are imminent. Sensors capable of detecting Pst in wheat crops could optimize the use of fungicides and improve disease monitoring in high-throughput field phenotyping. Now, deep learning provides new tools for image recognition and may pave the way for new camera based sensors that can identify symptoms in early stages of a disease outbreak within the field. The aim of this study was to teach an image classifier to detect Pst symptoms in winter wheat canopies based on a deep residual neural network (ResNet). For this purpose, a large annotation database was created from images taken by a standard RGB camera that was mounted on a platform at a height of 2 m. Images were acquired while the platform was moved over a randomized field experiment with Pst-inoculated and Pst-free plots of winter wheat. The image classifier was trained with 224 x 224 px patches tiled from the original, unprocessed camera images. The image classifier was tested on different stages of the disease outbreak. At patch level the image classifier reached a total accuracy of 90%. To test the image classifier on image level, the image classifier was evaluated with a sliding window using a large striding length of 224 px allowing for fast test performance. At image level, the image classifier reached a total accuracy of 77%. Even in a stage with very low disease spreading (0.5%) at the very beginning of the Pst outbreak, a detection accuracy of 57% was obtained. Still in the initial phase of the Pst outbreak with 2 to 4% of Pst disease spreading, detection accuracy with 76% could be attained. With further optimizations, the image classifier could be implemented in embedded systems and deployed on drones, vehicles or scanning systems for fast mapping of Pst outbreaks.
One of the major risk factors for global death and disability is alcohol, tobacco, and illicit drug use. While there is increasing knowledge with respect to individual factors promoting the initiation and maintenance of substance use disorders (SUDs), disease trajectories involved in losing and regaining control over drug intake (ReCoDe) are still not well described. Our newly formed German Collaborative Research Centre (CRC) on ReCoDe has an interdisciplinary approach funded by the German Research Foundation (DFG) with a 12-year perspective. The main goals of our research consortium are (i) to identify triggers and modifying factors that longitudinally modulate the trajectories of losing and regaining control over drug consumption in real life, (ii) to study underlying behavioral, cognitive, and neurobiological mechanisms, and (iii) to implicate mechanism-based interventions. These goals will be achieved by: (i) using mobile health (m-health) tools to longitudinally monitor the effects of triggers (drug cues, stressors, and priming doses) and modify factors (eg, age, gender, physical activity, and cognitive control) on drug consumption patterns in real-life conditions and in animal models of addiction; (ii) the identification and computational modeling of key mechanisms mediating the effects of such triggers and modifying factors on goal-directed, habitual, and compulsive aspects of behavior from human studies and animal models; and (iii) developing and testing interventions that specifically target the underlying mechanisms for regaining control over drug intake.
One of the major risk factors for global death and disability is alcohol, tobacco, and illicit drug use. While there is increasing knowledge with respect to individual factors promoting the initiation and maintenance of substance use disorders (SUDs), disease trajectories involved in losing and regaining control over drug intake (ReCoDe) are still not well described. Our newly formed German Collaborative Research Centre (CRC) on ReCoDe has an interdisciplinary approach funded by the German Research Foundation (DFG) with a 12-year perspective. The main goals of our research consortium are (i) to identify triggers and modifying factors that longitudinally modulate the trajectories of losing and regaining control over drug consumption in real life, (ii) to study underlying behavioral, cognitive, and neurobiological mechanisms, and (iii) to implicate mechanism-based interventions. These goals will be achieved by: (i) using mobile health (m-health) tools to longitudinally monitor the effects of triggers (drug cues, stressors, and priming doses) and modify factors (eg, age, gender, physical activity, and cognitive control) on drug consumption patterns in real-life conditions and in animal models of addiction; (ii) the identification and computational modeling of key mechanisms mediating the effects of such triggers and modifying factors on goal-directed, habitual, and compulsive aspects of behavior from human studies and animal models; and (iii) developing and testing interventions that specifically target the underlying mechanisms for regaining control over drug intake.
Dysregulation of physiological stress reactivity plays a key role in the development and relapse risk of alcohol dependence. This article reviews studies investigating physiological responses to experimentally induced acute stress in patients with alcohol dependence. A systematic search from electronic databases resulted in 3641 articles found and after screening 62 articles were included in our review. Studies are analyzed based on stress types (i.e., social stress tasks and nonsocial stress tasks) and physiological markers (i.e., the nervous system, the endocrine system, somatic responses and the immune system). In studies applying nonsocial stress tasks, alcohol-dependent patients were reported to show a blunted stress response compared with healthy controls in the majority of studies applying markers of adrenocorticotropic hormone and cortisol. In studies applying social stress tasks, findings are inconsistent, with less than half of the studies reporting altered physiological stress responses in patients. We discuss the impact of duration of abstinence, comorbidities, baseline physiological arousal and intervention on the discrepancy of study findings. Furthermore, we review evidence for an associationbetween blunted physiological stress responses and the relapse risk among patients with alcohol dependence. (c) 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Forecasting and early warning systems are important investments to protect lives, properties, and livelihood. While early warning systems are frequently used to predict the magnitude, location, and timing of potentially damaging events, these systems rarely provide impact estimates, such as the expected amount and distribution of physical damage, human consequences, disruption of services, or financial loss. Complementing early warning systems with impact forecasts has a twofold advantage: It would provide decision makers with richer information to take informed decisions about emergency measures and focus the attention of different disciplines on a common target. This would allow capitalizing on synergies between different disciplines and boosting the development of multihazard early warning systems. This review discusses the state of the art in impact forecasting for a wide range of natural hazards. We outline the added value of impact-based warnings compared to hazard forecasting for the emergency phase, indicate challenges and pitfalls, and synthesize the review results across hazard types most relevant for Europe.
Pavlovian-to-instrumental transfer (PIT) tasks examine the influence of Pavlovian stimuli on ongoing instrumental behaviour. Previous studies reported associations between a strong PIT effect, high-risk drinking and alcohol use disorder. This study investigated whether susceptibility to interference between Pavlovian and instrumental control is linked to risky alcohol use in a community sample of 18-year-old male adults. Participants (N = 191) were instructed to 'collect good shells' and 'leave bad shells' during the presentation of appetitive (monetary reward), aversive (monetary loss) or neutral Pavlovian stimuli. We compared instrumental error rates (ER) and functional magnetic resonance imaging (fMRI) brain responses between the congruent and incongruent conditions, as well as among high-risk and low-risk drinking groups. On average, individuals showed a substantial PIT effect, that is, increased ER when Pavlovian cues and instrumental stimuli were in conflict compared with congruent trials. Neural PIT correlates were found in the ventral striatum and the dorsomedial and lateral prefrontal cortices (lPFC). Importantly, high-risk drinking was associated with a stronger behavioural PIT effect, a decreased lPFC response and an increased neural response in the ventral striatum on the trend level. Moreover, high-risk drinkers showed weaker connectivity from the ventral striatum to the lPFC during incongruent trials. Our study links interference during PIT to drinking behaviour in healthy, young adults. High-risk drinkers showed higher susceptibility to Pavlovian cues, especially when they conflicted with instrumental behaviour, indicating lower interference control abilities. Increased activity in the ventral striatum (bottom-up), decreased lPFC response (top-down), and their altered interplay may contribute to poor interference control in the high-risk drinkers.