4,889 research outputs found
Information layering to de-clutter displays in emergency ambulance dispatch.
In this paper we report on a study to examine the usefulness of the MLD (Multi-Layered Display) as a device for creating physically distinct but visually overlapping information, what we refer to as 'information layering'. The technique was applied to emergency ambulance control, as a method for reducing visual clutter and information complexity in displays used by controllers. The results of the study show that participants completing simulated dispatch tasks in the MLD condition performed better on all categories of task difficulty compared to participants using a standard single layer display. However the improvements in performance were not significantly different
The Effects of Simple and Complex Carbohydrates on Mood
Carbohydrates can be differentiated into two categories, simple carbohydrates and complex carbohydrates. Our study looks at the effects of simple versus complex carbohydrates on mood. An anonymous online survey was administered through various social media platforms, such as GroupMe, Instagram, and Facebook, as well as sent to friends and family. The survey included basic demographics questions and questions on the frequency of food consumption, dietary patterns in relation to specific food groups, and mood. Pearson Correlation Coefficient was used to analyze data in SPSS version 25.0. Our results suggest there is an association between a positive mood and consumption of complex carbohydrates, with less consumption of simple carbohydrates. Higher levels of mood were found to be associated with healthier food groups and a less processed diet.https://orb.binghamton.edu/research_days_posters_2023/1099/thumbnail.jp
The product of C9orf72, a gene strongly implicated in neurodegeneration, is structurally related to DENN Rab-GEFs
Fronto-temporal dementia (FTD) and amyotrophic lateral sclerosis (ALS, also called motor neuron disease, MND) are severe neurodegenerative diseases that show considerable overlap at the clinical and cellular level. The most common single mutation in families with FTD or ALS has recently been mapped to a non-coding repeat expansion in the uncharacterized gene C9ORF72. Although a plausible mechanism for disease is that aberrant C9ORF72 mRNA poisons splicing, it is important to determine the cellular function of C9ORF72, about which nothing is known
Polypharmacy and Antidepressant Acceptability in Comorbid Depression and Type 2 Diabetes
BACKGROUND: Polypharmacy may increase the risk of drug interactions, side-effects and poor adherence. However, the impact of polypharmacy on antidepressant acceptability in individuals with type 2 diabetes (T2DM) is unknown. AIM: In adults with T2DM, to investigate the association between the number of prescribed medications and: i) early antidepressant discontinuation (<32 weeks); ii) switching antidepressant agents. DESIGN: Cohort study using UK primary care data from the years 2000-2018. METHODS: We used cox regression with penalised B-splines to describe the association between the number of concurrently prescribed medications at the time of starting antidepressant treatment, and each of our outcomes. RESULTS: We identified 73,808 individuals with comorbid depression and T2DM starting antidepressant treatment for the first time. The median number of concurrent medications prescribed was 7. Within 32 weeks, 44.26% of participants discontinued antidepressant treatment altogether, and 11.75% of participants switched antidepressant agents. We found an inverse relationship between the number of concurrent medications and discontinuing antidepressant treatment altogether. The median number of 7 concurrent medications was associated with a 65.06% decrease early antidepressant discontinuation HR 0.45, 95% CIs 0.37-0.55). We found no evidence of an association, in our main analysis, between the number of concurrent medications and switching antidepressant agents. CONCLUSIONS: Early discontinuation of antidepressants is common in adults with T2DM. However, individuals with higher levels of concurrent polypharmacy may be more adherent to treatment. These are likely to represent individuals with worse physical/mental health. Individuals with lower levels of concurrent polypharmacy may benefit from adherence support
Bipolar disorder prevalence and psychotropic medication utilisation in Hong Kong and the United Kingdom
PURPOSE: Bipolar disorder (BPD) is often an under-addressed mental disorder. Limited studies have investigated its epidemiology and drug utilisation in Hong Kong (HK) and the United Kingdom (UK) and thus local prescribing practices remain unclear. This study aimed to determine the prevalence of BPD and the prescribing of psychotropic medications as maintenance treatment from 2001-2018 in HK and the UK. METHOD: A retrospective study using the data from Clinical Data Analysis and Reporting System in HK and IQVIA Medical Research Data in the UK. RESULTS: The prevalence of BPD diagnosis in HK and the UK more than doubled during the study period. Some distinct changes in prescribing patterns over time were observed. Lithium use declined by 2.46% and 14.58% in HK and the UK, respectively. By 2018, patients were 4.6 times more likely to receive antidepressant monotherapy in the UK versus HK (15.62% vs. 3.42%). In HK, 38.41% of women of childbearing age were prescribed valproate in 2018 compared with 8.46% in the UK. CONCLUSION: The prevalence of BPD diagnosis has been increasing in HK and the UK. The disparity in prescribing patterns of BPD maintenance treatment in two regions reflected three major issues in clinical practice: (1) under-prescribing of lithium in both regions, (2) antidepressant monotherapy in the UK and (3) overprescribing of valproate to women of childbearing age in HK. A review of current clinical treatment guidelines and regulations of prescribing practice by local clinicians should be immediately implemented to ensure the safe use of medications in patients with BPD
Association between polypharmacy and depression relapse in individuals with comorbid depression and type 2 diabetes: a UK electronic health record study
BACKGROUND: Individuals with physical comorbidities and polypharmacy may be at higher risk of depression relapse, however, they are not included in the 'high risk of relapse' group for whom longer antidepressant treatment durations are recommended. AIMS: In individuals with comorbid depression and type 2 diabetes (T2DM), we aimed to investigate the association and interaction between depression relapse and (a) polypharmacy, (b) previous duration of antidepressant treatment. METHOD: This was a cohort study using primary care data from the UK Clinical Practice Research Datalink (CPRD) from years 2000 to 2018. We used Cox regression models with penalised B-splines to describe the association between restarting antidepressants and our two exposures. RESULTS: We identified 48 001 individuals with comorbid depression and T2DM, who started and discontinued antidepressant treatment during follow-up. Within 1 year of antidepressant discontinuation, 35% of participants restarted treatment indicating depression relapse. As polypharmacy increased, the rate of restarting antidepressants increased until a maximum of 18 concurrent medications, where individuals were more than twice as likely to restart antidepressants (hazard ratio (HR) = 2.15, 95% CI 1.32-3.51). As the duration of previous antidepressant treatment increased, the rate of restarting antidepressants increased - individuals with a previous duration of ≥25 months were more than twice as likely to restart antidepressants than those who previously discontinued in <7 months (HR = 2.36, 95% CI 2.25-2.48). We found no interaction between polypharmacy and previous antidepressant duration. CONCLUSIONS: Polypharmacy and longer durations of previous antidepressant treatment may be associated with depression relapse following the discontinuation of antidepressant treatment
Prevalence and characteristics of antidepressant prescribing in adults with comorbid depression and type 2 diabetes mellitus: A systematic review and meta-analysis
Background: Treatment guidelines do not provide specific recommendations for antidepressant prescribing in people with type 2 diabetes mellitus (T2DM). It is important to understand the prevalence of antidepressant prescribing and associated patient characteristics, to recognise safety issues or inequalities related to treatment access. Methods and Results: Seven databases were searched using terms related to depression, T2DM and antidepressant medication. From 14,389 reports retrieved, 9 met inclusion criteria. The prevalence of antidepressant prescribing varied considerably between studies from 18% to 87%. Where meta-analyses were possible, the pooled odds ratio for receiving an antidepressant were 1.52 (95% confidence intervals (CIs) 1.28 - 1.82) in women compared to men, 0.53 (95% CIs 0.23-1.20%) in Black and Ethnic Minorities compared to White ethnicity and 1.29 (95% CIs 0.92-1.80) in insulin users compared to individuals with non-insulin controlled T2DM. Conclusions: Antidepressant prescribing is more common in women with T2DM compared to men, however, the difference is less than in the general population. Insulin users, representing individuals with more advanced T2DM, were as likely to be prescribed antidepressants as those who did not use insulin. There is a gap in the literature concerning which antidepressant agents are being prescribed, and alongside which concurrent medications and comorbidities
Privacy Risks of Securing Machine Learning Models against Adversarial Examples
The arms race between attacks and defenses for machine learning models has
come to a forefront in recent years, in both the security community and the
privacy community. However, one big limitation of previous research is that the
security domain and the privacy domain have typically been considered
separately. It is thus unclear whether the defense methods in one domain will
have any unexpected impact on the other domain.
In this paper, we take a step towards resolving this limitation by combining
the two domains. In particular, we measure the success of membership inference
attacks against six state-of-the-art defense methods that mitigate the risk of
adversarial examples (i.e., evasion attacks). Membership inference attacks
determine whether or not an individual data record has been part of a model's
training set. The accuracy of such attacks reflects the information leakage of
training algorithms about individual members of the training set. Adversarial
defense methods against adversarial examples influence the model's decision
boundaries such that model predictions remain unchanged for a small area around
each input. However, this objective is optimized on training data. Thus,
individual data records in the training set have a significant influence on
robust models. This makes the models more vulnerable to inference attacks.
To perform the membership inference attacks, we leverage the existing
inference methods that exploit model predictions. We also propose two new
inference methods that exploit structural properties of robust models on
adversarially perturbed data. Our experimental evaluation demonstrates that
compared with the natural training (undefended) approach, adversarial defense
methods can indeed increase the target model's risk against membership
inference attacks.Comment: ACM CCS 2019, code is available at
https://github.com/inspire-group/privacy-vs-robustnes
- …