Coping with unpredictability: Dopaminergic and neurotrophic responses to omission of expected reward in Atlantic salmon (Salmo salar L.).

Comparative studies are imperative for understanding the evolution of adaptive neurobiological processes such as neural plasticity, cognition, and emotion. Previously we have reported that prolonged omission of expected rewards (OER, or 'frustrative nonreward') causes increased aggression in Atlantic salmon (Salmo salar). Here we report changes in brain monoaminergic activity and relative abundance of brain derived neurotrophic factor (BDNF) and dopamine receptor mRNA transcripts in the same paradigm. Groups of fish were initially conditioned to associate a flashing light with feeding. Subsequently, the expected food reward was delayed for 30 minutes during two out of three meals per day in the OER treatment, while the previously established routine was maintained in control groups. After 8 days there was no effect of OER on baseline brain stem serotonin (5-HT) or dopamine (DA) activity. Subsequent exposure to acute confinement stress led to increased plasma cortisol and elevated turnover of brain stem DA and 5-HT in all animals. The DA response was potentiated and DA receptor 1 (D1) mRNA abundance was reduced in the OER-exposed fish, indicating a sensitization of the DA system. In addition OER suppressed abundance of BDNF in the telencephalon of non-stressed fish. Regardless of OER treatment, a strong positive correlation between BDNF and D1 mRNA abundance was seen in non-stressed fish. This correlation was disrupted by acute stress, and replaced by a negative correlation between BDNF abundance and plasma cortisol concentration. These observations indicate a conserved link between DA, neurotrophin regulation, and corticosteroid-signaling pathways. The results also emphasize how fish models can be important tools in the study of neural plasticity and responsiveness to environmental unpredictability

Ebf1 or Pax5 haploinsufficiency synergizes with STAT5 activation to initiate acute lymphoblastic leukemia

STAT5 is abnormally activated in patients with acute lymphoblastic leukemia, and increased STAT5 activation synergizes with PAX5 and EBF1 to induce disease

Iron Behaving Badly: Inappropriate Iron Chelation as a Major Contributor to the Aetiology of Vascular and Other Progressive Inflammatory and Degenerative Diseases

The production of peroxide and superoxide is an inevitable consequence of aerobic metabolism, and while these particular "reactive oxygen species" (ROSs) can exhibit a number of biological effects, they are not of themselves excessively reactive and thus they are not especially damaging at physiological concentrations. However, their reactions with poorly liganded iron species can lead to the catalytic production of the very reactive and dangerous hydroxyl radical, which is exceptionally damaging, and a major cause of chronic inflammation. We review the considerable and wide-ranging evidence for the involvement of this combination of (su)peroxide and poorly liganded iron in a large number of physiological and indeed pathological processes and inflammatory disorders, especially those involving the progressive degradation of cellular and organismal performance. These diseases share a great many similarities and thus might be considered to have a common cause (i.e. iron-catalysed free radical and especially hydroxyl radical generation). The studies reviewed include those focused on a series of cardiovascular, metabolic and neurological diseases, where iron can be found at the sites of plaques and lesions, as well as studies showing the significance of iron to aging and longevity. The effective chelation of iron by natural or synthetic ligands is thus of major physiological (and potentially therapeutic) importance. As systems properties, we need to recognise that physiological observables have multiple molecular causes, and studying them in isolation leads to inconsistent patterns of apparent causality when it is the simultaneous combination of multiple factors that is responsible. This explains, for instance, the decidedly mixed effects of antioxidants that have been observed, etc...Comment: 159 pages, including 9 Figs and 2184 reference

Models for the preprocessing of reverse phase protein arrays

Reverse-phase protein lysate arrays (RPPA) are becoming important tools for the analysis of proteins in biological systems. RPPAs combine current assays for detecting and measuring proteins with the high-throughput technology of microarrays. Protein level assays have the ability to address questions about signaling pathways and post translational modifications that genomic assays alone cannot answer. The importance of preprocessing microarray data has been shown in a variety of contexts over the years and many of the same issues carry over to RPPAs including spot level correction, quantification, and normalization. In this thesis, we develop models and tools to improve upon the standard methods for preprocessing RPPA data. In particular, at the spot level, we suggest alternative methods for estimating background signal when the default estimates are compromised. Further, we introduce a multiplicative adjustment at the spot level, modeled with a smoothed surface of the positive control spots, that removes spatial bias better than additive-only models. When mutli-level information is available for the positive controls, a method that builds nested surfaces at the positive control levels further decreases spatial bias. At the quantification level, we outline a newly developed R-package called SuperCurve. This package uses a model that borrows strength from all samples on an array to estimate both an over all dose-response curve and individuals estimates of relative sample protein expression. SuperCurve is easy to implement and is compatible with the latest version of R. Finally, we introduce a normalization model called Variable Slope (VS) normalization that corrects for sample loading bias, taking into account the fact that expression estimates are computed separately for each array. Previous normalization models fail to account for this feature, potentially adding more variability to the expression measurements. VS normalization is shown to recover true correlation structure better than standard methods. As processing methods for RPPA data improve, this technology helps identify proteomic signatures that are unique to subtypes of disease and can eventually be applied to personalized therapy

COVID-19 Health Beliefs Regarding Mask Wearing and Vaccinations on Twitter: Deep Learning Approach

BackgroundAmid the global COVID-19 pandemic, a worldwide infodemic also emerged with large amounts of COVID-19–related information and misinformation spreading through social media channels. Various organizations, including the World Health Organization (WHO) and the Centers for Disease Control and Prevention (CDC), and other prominent individuals issued high-profile advice on preventing the further spread of COVID-19. ObjectiveThe purpose of this study is to leverage machine learning and Twitter data from the pandemic period to explore health beliefs regarding mask wearing and vaccines and the influence of high-profile cues to action. MethodsA total of 646,885,238 COVID-19–related English tweets were filtered, creating a mask-wearing data set and a vaccine data set. Researchers manually categorized a training sample of 3500 tweets for each data set according to their relevance to Health Belief Model (HBM) constructs and used coded tweets to train machine learning models for classifying each tweet in the data sets. ResultsIn total, 5 models were trained for both the mask-related and vaccine-related data sets using the XLNet transformer model, with each model achieving at least 81% classification accuracy. Health beliefs regarding perceived benefits and barriers were most pronounced for both mask wearing and immunization; however, the strength of those beliefs appeared to vary in response to high-profile cues to action. ConclusionsDuring both the COVID-19 pandemic and the infodemic, health beliefs related to perceived benefits and barriers observed through Twitter using a big data machine learning approach varied over time and in response to high-profile cues to action from prominent organizations and individuals

Functional and behavioral restoration of vision by gene therapy in the guanylate cyclase-1 (GC1) knockout mouse.

Recessive mutations in guanylate cyclase-1 (Gucy2d) are associated with severe, early onset Leber congenital amaurosis-1(LCA1). Gucy2d encodes guanylate cyclase (GC1) is expressed in photoreceptor outer segment membranes and produces cGMP in these cells. LCA1 patients present in infancy with severely impaired vision and extinguished electroretinogram (ERG) but retain some photoreceptors in both their macular and peripheral retina for years. Like LCA1 patients, loss of cone function in the GC1 knockout (GC1KO) mouse precedes cone degeneration. The purpose of this study was to test whether delivery of functional GC1 to cone cells of the postnatal GC1KO mouse could restore function to these cells.Serotype 5 AAV vectors containing either a photoreceptor-specific, rhodopsin kinase (hGRK1) or ubiquitous (smCBA) promoter driving expression of wild type murine GC1 were subretinally delivered to one eye of P14 GC1KO mice. Visual function (ERG) was analyzed in treated and untreated eyes until 3 months post injection. AAV-treated, isogenic wild type and uninjected control mice were evaluated for restoration of visual behavior using optomotor testing. At 3 months post injection, all animals were sacrificed, and their treated and untreated retinas assayed for expression of GC1 and localization of cone arrestin. Cone-mediated function was restored to treated eyes of GC1KO mice (ERG amplitudes were approximately 45% of normal). Treatment effect was stable for at least 3 months. Robust improvements in cone-mediated visual behavior were also observed, with responses of treated mice being similar or identical to that of wild type mice. AAV-vectored GC1 expression was found in photoreceptors and cone cells were preserved in treated retinas.This is the first demonstration of gene-based restoration of both visual function/vision-elicited behavior and cone preservation in a mammalian model of GC1 deficiency. Importantly, results were obtained using a well characterized, clinically relevant AAV vector. These results lay the ground work for the development of an AAV-based gene therapy vector for the treatment of LCA1

Cerebral Volume Loss, Cognitive Deficit and Neuropsychological Performance: Comparative Measures of Brain Atrophy - I. Dementia

There are several magnetic resonance (MR) imaging methods to measure brain volume and cerebral atrophy; however, the best measure for examining potential relationships between such measures and neuropsychological performance has not been established. Relationships between seven measures of MR derived brain volume or indices of atrophy and neuropsychological performance in the elderly subjects of the population-based Cache County, Utah Study of Aging and Memory (n = 195) were evaluated. The seven MR measures included uncorrected total brain volume (TBV), TBV corrected by total intracranial volume (TICV), TBV corrected by the ratio of the individuals TICV by group TICV (TBVC), a ventricle-to-brain ratio (VBR), total ventricular volume (TVV), TVV corrected by TICV, and a measure of parenchymal volume loss. The cases from the Cache County Study were comprised of elderly individuals classified into one of four subject groups based on a consensus diagnostic process, independent of quantitative MR imaging findings. The groups included subjects with Alzheimer\u27s disease (AD, n = 85), no dementia but mild/ambiguous (M/A) deficits (n = 30), a group of subjects with non-AD dementia or neuropsychiatric disorder including vascular dementia (n = 60), and control subjects (n = 20). Neuropsychological performance was based on the Mini-Mental Status Exam (MMSE) and an expanded neuropsychological test battery (consortium to establish a registry for Alzheimer\u27s disease (CERAD). The results demonstrated that the various quantitative MR measures were highly interrelated and no single measure was statistically superior. However, TBVC, TBV/TICV and VBR consistently exhibited the more robust relationships with neuropsychological performance. These results suggest that a single corrected brain volume measure or index is sufficient in studies examining global MR indicators of cerebral atrophy in relation to cognitive function and recommends use of either TBVC, TBV/TICV, or VBR. (JINS, 2004, 10, 442–452.