Progressive obesity leads to altered ovarian gene expression in the Lethal Yellow mouse: a microarray study

<p>Abstract</p> <p>Background</p> <p>Lethal yellow (LY; C57BL/6J <it>A</it>^<it>y</it>/<it>a</it>) mice exhibit adult-onset obesity, altered metabolic regulation, and early reproductive senescence. The present study was designed to test the hypothesis that obese LY mice possess differences in expression of ovarian genes relative to age-matched lean mice.</p> <p>Methods</p> <p>90- and 180-day-old LY and lean black (C57BL/6J <it>a/a</it>) mice were suppressed with GnRH antagonist (Antide^®), then stimulated with 5 IU eCG. cRNA derived from RNA extracts of whole ovarian homogenates collected 36 h post-eCG were run individually on Codelink Mouse Whole Genome Bioarrays (GE Healthcare Life Sciences).</p> <p>Results</p> <p>Fifty-two genes showed ≥ 2-fold differential (p < 0.05) expression between 180-day-old obese LY and lean black mice. LY mice exhibited elevated ovarian expression of agouti (350×), leptin (6.5×), and numerous genes involved in cholesterol/lipid transport and metabolism, e.g. lanosterol synthase, <it>Cyp51</it>, and steroidogenic acute regulatory protein (<it>Star</it>). Fewer genes showed lower expression in LY mice, e.g. angiotensinogen. In contrast, none of these genes showed differential expression in 90-day-old LY and black mice, which are of similar body weight. Interestingly, 180-day-old LY mice had a 2-fold greater expression of 11beta-hydroxysteroid dehydrogenase type 1 (<it>Hsd11b1</it>) and a 2-fold lesser expression of 11beta-hydroxysteroid dehydrogenase type 2 (<it>Hsd11b2</it>), differences not seen in 90-day-old mice. Consistent with altered <it>Hsd11b </it>gene expression, ovarian concentrations of corticosterone (C) were elevated in aging LY mice relative to black mice, but C levels were similar in young LY and black mice.</p> <p>Conclusion</p> <p>The data suggest that reproductive dysfunction in aging obese mice is related to modified intraovarian gene expression that is directly related to acquired obesity.</p

Occurrence of Anti-Drug Antibodies against Interferon-Beta and Natalizumab in Multiple Sclerosis: A Collaborative Cohort Analysis

Immunogenicity of biopharmaceutical products in multiple sclerosis is a frequent side effect which has a multifactorial etiology. Here we study associations between anti-drug antibody (ADA) occurrence and demographic and clinical factors. Retrospective data from routine ADA test laboratories in Sweden, Denmark, Austria and Germany (Dusseldorf group) and from one research study in Germany (Munich group) were gathered to build a collaborative multi-cohort dataset within the framework of the ABIRISK project. A subset of 5638 interferon-beta (IFN beta)-treated and 3440 natalizumab-treated patients having data on at least the first two years of treatment were eligible for interval-censored time-to-event analysis. In multivariate Cox regression, IFN beta-1a subcutaneous and IFN beta-1b subcutaneous treated patients were at higher risk of ADA occurrence compared to IFN beta-1a intramuscular-treated patients (pooled HR = 6.4, 95% CI 4.9-8.4 and pooled HR = 8.7, 95% CI 6.6-11.4 respectively). Patients older than 50 years at start of IFN beta therapy developed ADA more frequently than adult patients younger than 30 (pooled HR = 1.8, 95% CI 1.4-2.3). Men developed ADA more frequently than women (pooled HR = 1.3, 95% CI 1.1-1.6). Interestingly we observed that in Sweden and Germany, patients who started IFN beta in April were at higher risk of developing ADA (HR = 1.6, 95% CI 1.1-2.4 and HR = 2.4, 95% CI 1.5-3.9 respectively). This result is not confirmed in the other cohorts and warrants further investigations. Concerning natalizumab, patients older than 45 years had a higher ADA rate (pooled HR = 1.4, 95% CI 1.0-1.8) and women developed ADA more frequently than men (pooled HR = 1.4, 95% CI 1.0-2.0). We confirmed previously reported differences in immunogenicity of the different types of IFN beta. Differences in ADA occurrence by sex and age are reported here for the first time. These findings should be further investigated taking into account other exposures and biomarkers

Occurrence of Anti-Drug Antibodies against Interferon-Beta and Natalizumab in Multiple Sclerosis: A Collaborative Cohort Analysis

Immunogenicity of biopharmaceutical products in multiple sclerosis is a frequent side effect which has a multifactorial etiology. Here we study associations between anti-drug antibody (ADA) occurrence and demographic and clinical factors. Retrospective data from routine ADA test laboratories in Sweden, Denmark, Austria and Germany (Dusseldorf group) and from one research study in Germany (Munich group) were gathered to build a collaborative multi-cohort dataset within the framework of the ABIRISK project. A subset of 5638 interferon-beta (IFN beta)-treated and 3440 natalizumab-treated patients having data on at least the first two years of treatment were eligible for interval-censored time-to-event analysis. In multivariate Cox regression, IFN beta-1a subcutaneous and IFN beta-1b subcutaneous treated patients were at higher risk of ADA occurrence compared to IFN beta-1a intramuscular-treated patients (pooled HR = 6.4, 95% CI 4.9-8.4 and pooled HR = 8.7, 95% CI 6.6-11.4 respectively). Patients older than 50 years at start of IFN beta therapy developed ADA more frequently than adult patients younger than 30 (pooled HR = 1.8, 95% CI 1.4-2.3). Men developed ADA more frequently than women (pooled HR = 1.3, 95% CI 1.1-1.6). Interestingly we observed that in Sweden and Germany, patients who started IFN beta in April were at higher risk of developing ADA (HR = 1.6, 95% CI 1.1-2.4 and HR = 2.4, 95% CI 1.5-3.9 respectively). This result is not confirmed in the other cohorts and warrants further investigations. Concerning natalizumab, patients older than 45 years had a higher ADA rate (pooled HR = 1.4, 95% CI 1.0-1.8) and women developed ADA more frequently than men (pooled HR = 1.4, 95% CI 1.0-2.0). We confirmed previously reported differences in immunogenicity of the different types of IFN beta. Differences in ADA occurrence by sex and age are reported here for the first time. These findings should be further investigated taking into account other exposures and biomarkers

People who use drugs show no increase in pre-existing T-cell cross-reactivity toward SARS-CoV-2 but develop a normal polyfunctional T-cell response after standard mRNA vaccination

People who use drugs (PWUD) are at a high risk of contracting and developing severe coronavirus disease 2019 (COVID-19) and other infectious diseases due to their lifestyle, comorbidities, and the detrimental effects of opioids on cellular immunity. However, there is limited research on vaccine responses in PWUD, particularly regarding the role that T cells play in the immune response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Here, we show that before vaccination, PWUD did not exhibit an increased frequency of preexisting cross-reactive T cells to SARS-CoV-2 and that, despite the inhibitory effects that opioids have on T-cell immunity, standard vaccination can elicit robust polyfunctional CD4+ and CD8+ T-cell responses that were similar to those found in controls. Our findings indicate that vaccination stimulates an effective immune response in PWUD and highlight targeted vaccination as an essential public health instrument for the control of COVID-19 and other infectious diseases in this group of high-risk patients

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

Chitin particles induce size-dependent but carbohydrate-independent innate eosinophilia

Large non-phagocytosable beads, independent of the chemical composition, induce innate eosinophilia and macrophage activation with high arginase I expression

High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 2: Spectroscopy, Chemical Exchange Saturation, Multiparametric Imaging, and Radiomics

Objective: To summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and to highlight the latest bench-to-bedside developments. Methods: The current evidence regarding the potential for monitoring biomarkers was reviewed and individual modalities of metabolism and/or chemical composition imaging discussed. Perfusion, permeability, and microstructure imaging were similarly analyzed in Part 1 of this two-part review article and are valuable reading as background to this article. We appraise the clinic readiness of all the individual modalities and consider methodologies involving machine learning (radiomics) and the combination of MRI approaches (multiparametric imaging). Results: The biochemical composition of high-grade gliomas is markedly different from healthy brain tissue. Magnetic resonance spectroscopy allows the simultaneous acquisition of an array of metabolic alterations, with choline-based ratios appearing to be consistently discriminatory in treatment response assessment, although challenges remain despite this being a mature technique. Promising directions relate to ultra-high field strengths, 2-hydroxyglutarate analysis, and the use of non-proton nuclei. Labile protons on endogenous proteins can be selectively targeted with chemical exchange saturation transfer to give high resolution images. The body of evidence for clinical application of amide proton transfer imaging has been building for a decade, but more evidence is required to confirm chemical exchange saturation transfer use as a monitoring biomarker. Multiparametric methodologies, including the incorporation of nuclear medicine techniques, combine probes measuring different tumor properties. Although potentially synergistic, the limitations of each individual modality also can be compounded, particularly in the absence of standardization. Machine learning requires large datasets with high-quality annotation; there is currently low-level evidence for monitoring biomarker clinical application. Conclusion: Advanced MRI techniques show huge promise in treatment response assessment. The clinical readiness analysis highlights that most monitoring biomarkers require standardized international consensus guidelines, with more facilitation regarding technique implementation and reporting in the clinic

High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 1: Perfusion and Diffusion Techniques

Objective: Summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and highlight the latest bench-to-bedside developments. Methods: Experts in advanced MRI techniques applied to high-grade glioma treatment response assessment convened through a European framework. Current evidence regarding the potential for monitoring biomarkers in adult high-grade glioma is reviewed, and individual modalities of perfusion, permeability, and microstructure imaging are discussed (in Part 1 of two). In Part 2, we discuss modalities related to metabolism and/or chemical composition, appraise the clinic readiness of the individual modalities, and consider post-processing methodologies involving the combination of MRI approaches (multiparametric imaging) or machine learning (radiomics). Results: High-grade glioma vasculature exhibits increased perfusion, blood volume, and permeability compared with normal brain tissue. Measures of cerebral blood volume derived from dynamic susceptibility contrast-enhanced MRI have consistently provided information about brain tumor growth and response to treatment; it is the most clinically validated advanced technique. Clinical studies have proven the potential of dynamic contrast-enhanced MRI for distinguishing post-treatment related effects from recurrence, but the optimal acquisition protocol, mode of analysis, parameter of highest diagnostic value, and optimal cut-off points remain to be established. Arterial spin labeling techniques do not require the injection of a contrast agent, and repeated measurements of cerebral blood flow can be performed. The absence of potential gadolinium deposition effects allows widespread use in pediatric patients and those with impaired renal function. More data are necessary to establish clinical validity as monitoring biomarkers. Diffusion-weighted imaging, apparent diffusion coefficient analysis, diffusion tensor or kurtosis imaging, intravoxel incoherent motion, and other microstructural modeling approaches also allow treatment response assessment; more robust data are required to validate these alone or when applied to post-processing methodologies. Conclusion: Considerable progress has been made in the development of these monitoring biomarkers. Many techniques are in their infancy, whereas others have generated a larger body of evidence for clinical application

High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 1: Perfusion and Diffusion Techniques

OBJECTIVE: Summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and highlight the latest bench-to-bedside developments. METHODS: Experts in advanced MRI techniques applied to high-grade glioma treatment response assessment convened through a European framework. Current evidence regarding the potential for monitoring biomarkers in adult high-grade glioma is reviewed, and individual modalities of perfusion, permeability, and microstructure imaging are discussed (in Part 1 of two). In Part 2, we discuss modalities related to metabolism and/or chemical composition, appraise the clinic readiness of the individual modalities, and consider post-processing methodologies involving the combination of MRI approaches (multiparametric imaging) or machine learning (radiomics). RESULTS: High-grade glioma vasculature exhibits increased perfusion, blood volume, and permeability compared with normal brain tissue. Measures of cerebral blood volume derived from dynamic susceptibility contrast-enhanced MRI have consistently provided information about brain tumor growth and response to treatment; it is the most clinically validated advanced technique. Clinical studies have proven the potential of dynamic contrast-enhanced MRI for distinguishing post-treatment related effects from recurrence, but the optimal acquisition protocol, mode of analysis, parameter of highest diagnostic value, and optimal cut-off points remain to be established. Arterial spin labeling techniques do not require the injection of a contrast agent, and repeated measurements of cerebral blood flow can be performed. The absence of potential gadolinium deposition effects allows widespread use in pediatric patients and those with impaired renal function. More data are necessary to establish clinical validity as monitoring biomarkers. Diffusion-weighted imaging, apparent diffusion coefficient analysis, diffusion tensor or kurtosis imaging, intravoxel incoherent motion, and other microstructural modeling approaches also allow treatment response assessment; more robust data are required to validate these alone or when applied to post-processing methodologies. CONCLUSION: Considerable progress has been made in the development of these monitoring biomarkers. Many techniques are in their infancy, whereas others have generated a larger body of evidence for clinical application