Measures and Limits of Models of Fixation Selection

Models of fixation selection are a central tool in the quest to understand how the human mind selects relevant information. Using this tool in the evaluation of competing claims often requires comparing different models' relative performance in predicting eye movements. However, studies use a wide variety of performance measures with markedly different properties, which makes a comparison difficult. We make three main contributions to this line of research: First we argue for a set of desirable properties, review commonly used measures, and conclude that no single measure unites all desirable properties. However the area under the ROC curve (a classification measure) and the KL-divergence (a distance measure of probability distributions) combine many desirable properties and allow a meaningful comparison of critical model performance. We give an analytical proof of the linearity of the ROC measure with respect to averaging over subjects and demonstrate an appropriate correction of entropy-based measures like KL-divergence for small sample sizes in the context of eye-tracking data. Second, we provide a lower bound and an upper bound of these measures, based on image-independent properties of fixation data and between subject consistency respectively. Based on these bounds it is possible to give a reference frame to judge the predictive power of a model of fixation selection . We provide open-source python code to compute the reference frame. Third, we show that the upper, between subject consistency bound holds only for models that predict averages of subject populations. Departing from this we show that incorporating subject-specific viewing behavior can generate predictions which surpass that upper bound. Taken together, these findings lay out the required information that allow a well-founded judgment of the quality of any model of fixation selection and should therefore be reported when a new model is introduced

A user-centred approach to developing bWell, a mobile app for arm and shoulder exercises after breast cancer treatment

Purpose: The study aim was to develop a mobile application (app) supported by user preferences to optimise self-management of arm and shoulder exercises for upper-limb dysfunction (ULD) after breast cancer treatment. Methods: Focus groups with breast cancer patients were held to identify user needs and requirements. Behaviour change techniques were explored by researchers and discussed during the focus groups. Concepts for content were identified by thematic analysis. A rapid review was conducted to inform the exercise programme. Preliminary testing was carried out to obtain user feedback from breast cancer patients who used the app for 8 weeks post-surgery. Results: Breast cancer patients’ experiences with ULD and exercise advice and routines varied widely. They identified and prioritised several app features: tailored information, video demonstrations of the exercises, push notifications, and tracking and progress features. An evidence-based programme was developed with a physiotherapist with progressive exercises for passive and active mobilisation, stretching and strengthening. The exercise demonstration videos were filmed with a breast cancer patient. Early user testing demonstrated ease of use, and clear and motivating app content. Conclusions: bWell, a novel app for arm and shoulder exercises was developed by breast cancer patients, health care professionals and academics. Further research is warranted to confirm its clinical effectiveness. Implications for Cancer Survivors: Mobile health has great potential to provide patients with information specific to their needs. bWell is a promising way to support breast cancer patients with exercise routines after treatment and may improve future self-management of clinical care

Proteasomal Degradation of TRIM5α during Retrovirus Restriction

The host protein TRIM5α inhibits retroviral infection at an early post-penetration stage by targeting the incoming viral capsid. While the detailed mechanism of restriction remains unclear, recent studies have implicated the activity of cellular proteasomes in the restriction of retroviral reverse transcription imposed by TRIM5α. Here, we show that TRIM5α is rapidly degraded upon encounter of a restriction-susceptible retroviral core. Inoculation of TRIM5α-expressing human 293T cells with a saturating level of HIV-1 particles resulted in accelerated degradation of the HIV-1-restrictive rhesus macaque TRIM5α protein but not the nonrestrictive human TRIM5α protein. Exposure of cells to HIV-1 also destabilized the owl monkey restriction factor TRIMCyp; this was prevented by addition of the inhibitor cyclosporin A and was not observed with an HIV-1 virus containing a mutation in the capsid protein that relieves restriction by TRIMCyp IVHIV. Likewise, human TRIM5α was rapidly degraded upon encounter of the restriction-sensitive N-tropic murine leukemia virus (N-MLV) but not the unrestricted B-MLV. Pretreatment of cells with proteasome inhibitors prevented the HIV-1-induced loss of both rhesus macaque TRIM5α and TRIMCyp proteins. We also detected degradation of endogenous TRIM5α in rhesus macaque cells following HIV-1 infection. We conclude that engagement of a restriction-sensitive retrovirus core results in TRIM5α degradation by a proteasome-dependent mechanism

Single Nucleotide Polymorphism in Gene Encoding Transcription Factor Prep1 Is Associated with HIV-1-Associated Dementia

BACKGROUND: Infection with HIV-1 may result in severe cognitive and motor impairment, referred to as HIV-1-associated dementia (HAD). While its prevalence has dropped significantly in the era of combination antiretroviral therapy, milder neurocognitive disorders persist with a high prevalence. To identify additional therapeutic targets for treating HIV-associated neurocognitive disorders, several candidate gene polymorphisms have been evaluated, but few have been replicated across multiple studies. METHODS: We here tested 7 candidate gene polymorphisms for association with HAD in a case-control study consisting of 86 HAD cases and 246 non-HAD AIDS patients as controls. Since infected monocytes and macrophages are thought to play an important role in the infection of the brain, 5 recently identified single nucleotide polymorphisms (SNPs) affecting HIV-1 replication in macrophages in vitro were also tested. RESULTS: The CCR5 wt/Δ32 genotype was only associated with HAD in individuals who developed AIDS prior to 1991, in agreement with the observed fading effect of this genotype on viral load set point. A significant difference in genotype distribution among all cases and controls irrespective of year of AIDS diagnosis was found only for a SNP in candidate gene PREP1 (p = 1.2 × 10(-5)). Prep1 has recently been identified as a transcription factor preferentially binding the -2,518 G allele in the promoter of the gene encoding MCP-1, a protein with a well established role in the etiology of HAD. CONCLUSION: These results support previous findings suggesting an important role for MCP-1 in the onset of HIV-1-associated neurocognitive disorders

Gender differences in the use of cardiovascular interventions in HIV-positive persons; the D:A:D Study

Peer reviewe

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Development and Validation of a Risk Score for Chronic Kidney Disease in HIV Infection Using Prospective Cohort Data from the D:A:D Study

Ristola M. on työryhmien DAD Study Grp ; Royal Free Hosp Clin Cohort ; INSIGHT Study Grp ; SMART Study Grp ; ESPRIT Study Grp jäsen.Background Chronic kidney disease (CKD) is a major health issue for HIV-positive individuals, associated with increased morbidity and mortality. Development and implementation of a risk score model for CKD would allow comparison of the risks and benefits of adding potentially nephrotoxic antiretrovirals to a treatment regimen and would identify those at greatest risk of CKD. The aims of this study were to develop a simple, externally validated, and widely applicable long-term risk score model for CKD in HIV-positive individuals that can guide decision making in clinical practice. Methods and Findings A total of 17,954 HIV-positive individuals from the Data Collection on Adverse Events of Anti-HIV Drugs (D:A:D) study with >= 3 estimated glomerular filtration rate (eGFR) values after 1 January 2004 were included. Baseline was defined as the first eGFR > 60 ml/min/1.73 m2 after 1 January 2004; individuals with exposure to tenofovir, atazanavir, atazanavir/ritonavir, lopinavir/ritonavir, other boosted protease inhibitors before baseline were excluded. CKD was defined as confirmed (>3 mo apart) eGFR In the D:A:D study, 641 individuals developed CKD during 103,185 person-years of follow-up (PYFU; incidence 6.2/1,000 PYFU, 95% CI 5.7-6.7; median follow-up 6.1 y, range 0.3-9.1 y). Older age, intravenous drug use, hepatitis C coinfection, lower baseline eGFR, female gender, lower CD4 count nadir, hypertension, diabetes, and cardiovascular disease (CVD) predicted CKD. The adjusted incidence rate ratios of these nine categorical variables were scaled and summed to create the risk score. The median risk score at baseline was -2 (interquartile range -4 to 2). There was a 1: 393 chance of developing CKD in the next 5 y in the low risk group (risk score = 5, 505 events), respectively. Number needed to harm (NNTH) at 5 y when starting unboosted atazanavir or lopinavir/ritonavir among those with a low risk score was 1,702 (95% CI 1,166-3,367); NNTH was 202 (95% CI 159-278) and 21 (95% CI 19-23), respectively, for those with a medium and high risk score. NNTH was 739 (95% CI 506-1462), 88 (95% CI 69-121), and 9 (95% CI 8-10) for those with a low, medium, and high risk score, respectively, starting tenofovir, atazanavir/ritonavir, or another boosted protease inhibitor. The Royal Free Hospital Clinic Cohort included 2,548 individuals, of whom 94 individuals developed CKD (3.7%) during 18,376 PYFU (median follow-up 7.4 y, range 0.3-12.7 y). Of 2,013 individuals included from the SMART/ESPRIT control arms, 32 individuals developed CKD (1.6%) during 8,452 PYFU (median follow-up 4.1 y, range 0.6-8.1 y). External validation showed that the risk score predicted well in these cohorts. Limitations of this study included limited data on race and no information on proteinuria. Conclusions Both traditional and HIV-related risk factors were predictive of CKD. These factors were used to develop a risk score for CKD in HIV infection, externally validated, that has direct clinical relevance for patients and clinicians to weigh the benefits of certain antiretrovirals against the risk of CKD and to identify those at greatest risk of CKD.Peer reviewe