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"Field, Matt"
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Do daily fluctuations in inhibitory control predict alcohol consumption? An ecological momentary assessment study
Rationale
Deficient inhibitory control is predictive of increased alcohol consumption in the laboratory; however, little is known about this relationship in naturalistic, real-world settings.
Objectives
In the present study, we implemented ecological momentary assessment methods to investigate the relationship between inhibitory control and alcohol consumption in the real world.
Methods
Heavy drinkers who were motivated to reduce their alcohol consumption (
N
= 100) were loaned a smartphone which administered a stop signal task twice per day at random intervals between 10 a.m. and 6 p.m. for 2 weeks. Each day, participants also recorded their planned and actual alcohol consumption and their subjective craving and mood. We hypothesised that day-to-day fluctuations in inhibitory control (stop signal reaction time) would predict alcohol consumption, over and above planned consumption and craving.
Results
Multilevel modelling demonstrated that daily alcohol consumption was predicted by planned consumption (
β
= .816; 95% CI .762–.870) and craving (
β
= .022; 95% CI .013–.031), but inhibitory control did not predict any additional variance in alcohol consumption. However, secondary analyses demonstrated that the magnitude of deterioration in inhibitory control across the day was a significant predictor of increased alcohol consumption on that day (
β
= .007; 95% CI .004–.011), after controlling for planned consumption and craving.
Conclusions
These findings demonstrate that short-term fluctuations in inhibitory control predict alcohol consumption, which suggests that transient fluctuations in inhibition may be a risk factor for heavy drinking episodes.
Journal Article
Alcohol consumers’ attention to warning labels and brand information on alcohol packaging: Findings from cross-sectional and experimental studies
Background
Alcohol warning labels have a limited effect on drinking behavior, potentially because people devote minimal attention to them. We report findings from two studies in which we measured the extent to which alcohol consumers attend to warning labels on alcohol packaging, and aimed to identify if increased attention to warning labels is associated with motivation to change drinking behavior.
Methods
Study 1 (
N
= 60) was an exploratory cross-sectional study in which we used eye-tracking to measure visual attention to brand and health information on alcohol and soda containers. In study 2 (
N
= 120) we manipulated motivation to reduce drinking using an alcohol brief intervention (vs control intervention) and measured heavy drinkers’ attention to branding and warning labels with the same eye-tracking paradigm as in study 1. Then, in a separate task we experimentally manipulated attention by drawing a brightly colored border around health (or brand) information before measuring participants’ self-reported drinking intentions for the subsequent week.
Results
Study 1 showed that participants paid minimal attention to warning labels (7% of viewing time). Participants who were motivated to reduce drinking paid less attention to alcohol branding and alcohol warning labels. Results from study 2 showed that the alcohol brief intervention decreased attention to branding compared to the control condition, but it did not affect attention to warning labels. Furthermore, the experimental manipulation of attention to health or brand information did not influence drinking intentions for the subsequent week.
Conclusions
Alcohol consumers allocate minimal attention to warning labels on alcohol packaging and even if their attention is directed to these warning labels, this has no impact on their drinking intentions. The lack of attention to warning labels, even among people who actively want to cut down, suggests that there is room for improvement in the content of health warnings on alcohol packaging.
Journal Article
A literature review of dispersal pathways of Aedes albopictus across different spatial scales: implications for vector surveillance
Background
Aedes albopictus
is a highly invasive species and an important vector of dengue and chikungunya viruses. Indigenous to Southeast Asia,
Ae. albopictus
has successfully invaded every inhabited continent, except Antarctica, in the past 80 years. Vector surveillance and control at points of entry (PoE) is the most critical front line of defence against the introduction of
Ae. albopictus
to new areas. Identifying the pathways by which
Ae. albopictus
are introduced is the key to implementing effective vector surveillance to rapidly detect introductions and to eliminate them.
Methods
A literature review was conducted to identify studies and data sources reporting the known and suspected dispersal pathways of human-mediated
Ae. albopictus
dispersal between 1940–2020. Studies and data sources reporting the first introduction of
Ae. albopictus
in a new country were selected for data extraction and analyses.
Results
Between 1940–2020,
Ae. albopictus
was reported via various dispersal pathways into 86 new countries. Two main dispersal pathways were identified: (1) at global and continental spatial scales, maritime sea transport was the main dispersal pathway for
Ae. albopictus
into new countries in the middle to late 20th Century, with ships carrying used tyres of particular importance during the 1980s and 1990s, and (2) at continental and national spatial scales, the passive transportation of
Ae. albopictus
in ground vehicles and to a lesser extent the trade of used tyres and maritime sea transport appear to be the major drivers of
Ae. albopictus
dispersal into new countries, especially in Europe. Finally, the dispersal pathways for the introduction and spread of
Ae. albopictus
in numerous countries remains unknown, especially from the 1990s onwards.
Conclusions
This review identified the main known and suspected dispersal pathways of human-mediated
Ae. albopictus
dispersal leading to the first introduction of
Ae. albopictus
into new countries and highlighted gaps in our understanding of
Ae. albopictus
dispersal pathways. Relevant advances in vector surveillance and genomic tracking techniques are presented and discussed in the context of improving vector surveillance.
Graphical Abstract
Journal Article
Bioinformatic Challenges Detecting Genetic Variation in Precision Medicine Programs
Precision medicine programs to identify clinically relevant genetic variation have been revolutionized by access to increasingly affordable high-throughput sequencing technologies. A decade of continual drops in per-base sequencing costs means it is now feasible to sequence an individual patient genome and interrogate all classes of genetic variation for < $1,000 USD. However, while advances in these technologies have greatly simplified the ability to obtain patient sequence information, the timely analysis and interpretation of variant information remains a challenge for the rollout of large-scale precision medicine programs. This review will examine the challenges and potential solutions that exist in identifying predictive genetic biomarkers and pharmacogenetic variants in a patient and discuss the larger bioinformatic challenges likely to emerge in the future. It will examine how both software and hardware development are aiming to overcome issues in short read mapping, variant detection and variant interpretation. It will discuss the current state of the art for genetic disease and the remaining challenges to overcome for complex disease. Success across all types of disease will require novel statistical models and software in order to ensure precision medicine programs realize their full potential now and into the future.
Journal Article
Increasing pathogenic germline variant diagnosis rates in precision medicine: current best practices and future opportunities
The accurate diagnosis of pathogenic variants is essential for effective clinical decision making within precision medicine programs. Despite significant advances in both the quality and quantity of molecular patient data, diagnostic rates remain suboptimal for many inherited diseases. As such, prioritisation and identification of pathogenic disease-causing variants remains a complex and rapidly evolving field. This review explores the latest technological and computational options being used to increase genetic diagnosis rates in precision medicine programs.
While interpreting genetic variation via standards such as ACMG guidelines is increasingly being recognized as a gold standard approach, the underlying datasets and algorithms recommended are often slow to incorporate additional data types and methodologies. For example, new technological developments, particularly in single-cell and long-read sequencing, offer great opportunity to improve genetic diagnosis rates, however, how to best interpret and integrate increasingly complex multi-omics patient data remains unclear. Further, advances in artificial intelligence and machine learning applications in biomedical research offer enormous potential, however they require careful consideration and benchmarking given the clinical nature of the data. This review covers the current state of the art in available sequencing technologies, software methodologies for variant annotation/prioritisation, pedigree-based strategies and the potential role of machine learning applications. We describe a key set of design principles required for a modern multi-omic precision medicine framework that is robust, modular, secure, flexible, and scalable. Creating a next generation framework will ensure we realise the full potential of precision medicine into the future.
Journal Article
Lost in translation: why genomic breakthroughs are not reaching patients
Despite revolutionary advances in genomic technologies, a persistent disconnect exists between research discoveries and clinical implementation. This translational gap stems from misaligned incentive and funding structures: researchers prioritise publications over clinical uptake, with funding ending at proof-of-concept; clinicians face time constraints and integration challenges; regulators struggle with rapidly evolving technologies and genomics-specific complexities including variant classification and data governance. We propose that dedicated translational medicine centres are essential to bridge this divide. These centres require multidisciplinary teams spanning clinician-scientists, regulatory affairs specialists, health economists, biostatisticians and bioinformaticians, providing end-to-end support from feasibility assessment through to regulatory approval. Success requires government investment, explicit health equity assessments and measuring achievement through clinical uptake rather than traditional academic metrics.
Journal Article
Bot or Not? Detecting and Managing Participant Deception When Conducting Digital Research Remotely: Case Study of a Randomized Controlled Trial
Evaluating digital interventions using remote methods enables the recruitment of large numbers of participants relatively conveniently and cheaply compared with in-person methods. However, conducting research remotely based on participant self-report with little verification is open to automated \"bots\" and participant deception.
This paper uses a case study of a remotely conducted trial of an alcohol reduction app to highlight and discuss (1) the issues with participant deception affecting remote research trials with financial compensation; and (2) the importance of rigorous data management to detect and address these issues.
We recruited participants on the internet from July 2020 to March 2022 for a randomized controlled trial (n=5602) evaluating the effectiveness of an alcohol reduction app, Drink Less. Follow-up occurred at 3 time points, with financial compensation offered (up to £36 [US $39.23]). Address authentication and telephone verification were used to detect 2 kinds of deception: \"bots,\" that is, automated responses generated in clusters; and manual participant deception, that is, participants providing false information.
Of the 1142 participants who enrolled in the first 2 months of recruitment, 75.6% (n=863) of them were identified as bots during data screening. As a result, a CAPTCHA (Completely Automated Public Turing Test to Tell Computers and Humans Apart) was added, and after this, no more bots were identified. Manual participant deception occurred throughout the study. Of the 5956 participants (excluding bots) who enrolled in the study, 298 (5%) were identified as false participants. The extent of this decreased from 110 in November 2020, to a negligible level by February 2022 including a number of months with 0. The decline occurred after we added further screening questions such as attention checks, removed the prominence of financial compensation from social media advertising, and added an additional requirement to provide a mobile phone number for identity verification.
Data management protocols are necessary to detect automated bots and manual participant deception in remotely conducted trials. Bots and manual deception can be minimized by adding a CAPTCHA, attention checks, a requirement to provide a phone number for identity verification, and not prominently advertising financial compensation on social media.
ISRCTN Number ISRCTN64052601; https://doi.org/10.1186/ISRCTN64052601.
Journal Article
The clinical relevance of attentional bias in substance use disorders
Individuals with substance use disorders typically show an “attentional bias” for substance-related cues: Those cues are able to grab and hold the attention, in preference to other cues in the environment. We discuss the theoretical context for this work before reviewing the measurement of attentional bias, and its relationship to motivational state and relapse to substance use after a period of abstinence. Finally, we discuss the implications of this research for the treatment of substance use disorders. We conclude that attentional bias is associated with subjective craving, and that moment-by-moment fluctuations in attentional bias may precede relapse to substance use. The evidence regarding the predictive relationship between attentional bias assessed in treatment contexts and subsequent relapse is inconsistent. Furthermore, there is currently insufficient evidence to endorse attentional bias modification as a treatment for substance use disorders. Clinical implications and suggestions for future research are highlighted.
Journal Article
CD8+ T cells sustain vaccination-induced immunity against dissemination of contained tuberculosis in immunosuppressed hosts
About two billion people are latently infected with
Mycobacterium tuberculosis
(
Mtb
), which can reside in multiple organs, including the lymphatics. The risk of latent
Mtb
infection (LTBI) reactivation increases with immunosuppression, such as HIV coinfection, yet the immunological correlates that maintain LTBI remain largely elusive. Using a mouse model of contained lymphatic
Mtb
infection we dissect the drivers of containment versus reactivation. We show that immunosuppression-induced dissemination of lymphatic
Mtb
and ensuing progressive disease can be prevented by vaccination with BCG or recombinant BCG even in the absence of CD4
+
T cells. Multi-parameter imaging, spatial transcriptomics and network analysis reveal that anti-CD4-mediated immunosuppression triggers distinct repositioning of non-CD4 immune cells at the edge of TB lesions in cervical lymph nodes. Although B cell numbers increase, they prove dispensable for
Mtb
containment during CD4
+
T cell loss. Using immune cell-deficient mice, cell depletion and adoptive transfers, we reveal that CD8
+
T cells mediate vaccination-induced prevention of
Mtb
dissemination in the absence of CD4
+
T cells, informing LTBI management in immunocompromised individuals.
The immunological events that correlate with latent
Mycobacterium tuberculosis
(
Mtb
) infection (LTBI) containment in immune suppressed hosts remain to be explored. The authors here show that CD8
+
T cells are critical for BCG vaccination-induced prevention of Mtb dissemination in the absence of CD4
+
T cells in a mouse model of contained tuberculosis.
Journal Article