97 research outputs found

    Temperature as a Circadian Marker in Older Human Subjects: Relationship to Metabolic Syndrome and Diabetes

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    Background: Circadian rhythms are characterized by approximate 24-hour oscillations in physiological and behavioral processes. Disruptions in these endogenous rhythms, most commonly associated with shift work and/or lifestyle, are recognized to be detrimental to health. Several studies have demonstrated a high correlation between disrupted circadian rhythms and metabolic disease. The aim of this study was to determine which metabolic parameters correlate with physiological measures of circadian temperature amplitude (TempAmp) and stability (TempStab). Methods: Wrist skin temperature was measured in 34 subjects (ages 50 to 70, including lean, obese, and diabetic subjects) every 10 minutes for 7 consecutive days. Anthropometric measures and fasting blood draws were conducted to obtain data on metabolic parameters: body mass index, hemoglobin A1C, triglycerides, cholesterol, high-density lipoprotein, and low-density lipoprotein. A history of hypertension and current blood pressure was noted. Results: Analysis of the data indicated a substantial reduction in TempAmp and TempStab in subjects with metabolic syndrome (three or more risk factors). To determine the impact of individual interdependent metabolic factors on temperature rhythms, stepwise multilinear regression analysis was conducted using metabolic syndrome measurements. Interestingly, only triglyceride level was consistently correlated by the analysis. Triglyceride level was shown to contribute to 33% of the variability in TempAmp and 23% of the variability in TempStab. Conclusion: Our results demonstrate that elevated triglycerides are associated with diminished TempAmp and TempStab in human subjects, and triglycerides may serve as a primary metabolic predictor of circadian parameters

    Diet quality in late midlife is associated with faster walking speed in later life in women, but not men

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    Healthy diet has been linked to better age-related physical functioning, but evidence on the relationship of overall diet quality in late midlife and clinically relevant measures of physical functioning in later life is limited. Research on potential sex differences in this relationship is scarce. The aim was to investigate the prospective association between overall diet quality, as assessed by the Healthy Eating Index-2015 at age 60-64y and measures of walking speed seven years later, among men and women from the Insight46, a neuroscience sub-study of the Medical Research Council National Survey of Health and Development. Diet was assessed at age 60-64y using five-day food diaries, from which total HEI-2015 was calculated. At age 69-71y, walking speed was estimated during four 10-meter walks at self-selected pace, using inertial measurement units. Multivariable linear regression models with sex as modifier, controlling for age, follow-up, lifestyle, health, social variables and physical performance were used. The final sample was 164 women and 167 men (n=331). Women had higher HEI-2015 scores and slower walking speed than men. A 10 point increase in HEI-2015 was associated with faster walking speed seven years later among women (B: 0.024, 95% CI: 0.006, 0.043), but not men. The association remained significant in the multivariable model (B: 0.021, 95% CI: 0.003, 0.040). In women in late midlife higher diet quality is associated with faster walking speed. A healthy diet in late midlife is likely to contribute towards better age-related physical capability and sex differences are likely to affect this relationship

    Implicit trust in clinical decision-making by multidisciplinary teams

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    In clinical practice, decision-making is not performed by individual knowers but by an assemblage of people and instruments in which no one member has full access to every piece of evidence. This is due to decision making teams consisting of members with different kinds of expertise, as well as to organisational and time constraints. This raises important questions for the epistemology of medicine, which is inherently social in this kind of setting, and implies epistemic dependence on others. Trust in these contexts is a highly complex social practice, involving different forms of relationships between trust and reasons for trust: based on reasons, and not based on reasons; based on reasons that are easily accessible to reflection and others that are not. In this paper, we focus on what it means to have reasons to trust colleagues in an established clinical team, collectively supporting or carrying out every day clinical decision-making. We show two important points about these reasons, firstly, they are not sought or given in advance of a situation of epistemic dependence, but are established within these situations; secondly they are implicit in the sense of being contained or nested within other actions that are not directly about trusting another person. The processes of establishing these reasons are directly about accomplishing a task, and indirectly about trusting someone else’s expertise or competence. These processes establish a space of reasons within which what it means to have reasons for trust, or not, gains a meaning and traction in these team-work settings. Based on a qualitative study of decision-making in image assisted diagnosis and treatment of a complex disease called pulmonary hypertension (PH), we show how an intersubjective framework, or ‘space of reasons’ is established through team members forging together a common way of identifying and dealing with evidence. In dealing with images as a central diagnostic tool, this also involves a common way of looking at the images, a common mode or style of perception. These frameworks are developed through many iterations of adjusting and calibrating interpretations in relation to those of others, establishing what counts as evidence, and ranking different kinds of evidence. Implicit trust is at work throughout this process. Trusting the expertise of others in clinical decision-making teams occurs while the members of the team are busy on other tasks, most importantly, building up a framework of common modes of seeing, and common ways of identifying and assessing evidence emerge. It is only in this way that trusting or mistrusting becomes meaningful in these contexts, and that a framework for epistemic dependence is established

    Implicit trust in clinical decision-making by multidisciplinary teams

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    In clinical practice, decision-making is not performed by individual knowers but by an assemblage of people and instruments in which no one member has full access to every piece of evidence. This is due to decision making teams consisting of members with different kinds of expertise, as well as to organisational and time constraints. This raises important questions for the epistemology of medicine, which is inherently social in this kind of setting, and implies epistemic dependence on others. Trust in these contexts is a highly complex social practice, involving different forms of relationships between trust and reasons for trust: based on reasons, and not based on reasons; based on reasons that are easily accessible to reflection and others that are not. In this paper, we focus on what it means to have reasons to trust colleagues in an established clinical team, collectively supporting or carrying out every day clinical decision-making. We show two important points about these reasons, firstly, they are not sought or given in advance of a situation of epistemic dependence, but are established within these situations; secondly they are implicit in the sense of being contained or nested within other actions that are not directly about trusting another person. The processes of establishing these reasons are directly about accomplishing a task, and indirectly about trusting someone else’s expertise or competence. These processes establish a space of reasons within which what it means to have reasons for trust, or not, gains a meaning and traction in these team-work settings. Based on a qualitative study of decision-making in image assisted diagnosis and treatment of a complex disease called pulmonary hypertension (PH), we show how an intersubjective framework, or ‘space of reasons’ is established through team members forging together a common way of identifying and dealing with evidence. In dealing with images as a central diagnostic tool, this also involves a common way of looking at the images, a common mode or style of perception. These frameworks are developed through many iterations of adjusting and calibrating interpretations in relation to those of others, establishing what counts as evidence, and ranking different kinds of evidence. Implicit trust is at work throughout this process. Trusting the expertise of others in clinical decision-making teams occurs while the members of the team are busy on other tasks, most importantly, building up a framework of common modes of seeing, and common ways of identifying and assessing evidence emerge. It is only in this way that trusting or mistrusting becomes meaningful in these contexts, and that a framework for epistemic dependence is established

    Endomembrane targeting of human OAS1 p46 augments antiviral activity

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    Many host RNA sensors are positioned in the cytosol to detect viral RNA during infection. However, most positive-strand RNA viruses replicate within a modified organelle co-opted from intracellular membranes of the endomembrane system, which shields viral products from cellular innate immune sensors. Targeting innate RNA sensors to the endomembrane system may enhance their ability to sense RNA generated by viruses that use these compartments for replication. Here, we reveal that an isoform of oligoadenylate synthetase 1, OAS1 p46, is prenylated and targeted to the endomembrane system. Membrane localization of OAS1 p46 confers enhanced access to viral replication sites and results in increased antiviral activity against a subset of RNA viruses including flaviviruses, picornaviruses, and SARS-CoV-2. Finally, our human genetic analysis shows that the OAS1 splice-site SNP responsible for production of the OAS1 p46 isoform correlates with protection from severe COVID-19. This study highlights the importance of endomembrane targeting for the antiviral specificity of OAS1 and suggests that early control of SARS-CoV-2 replication through OAS1 p46 is an important determinant of COVID-19 severity

    Discovery of Q203, a potent clinical candidate for the treatment of tuberculosis

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    New therapeutic strategies are needed to combat the tuberculosis pandemic and the spread of multidrug-resistant (MDR) and extensively drug-resistant (XDR) forms of the disease, which remain a serious public health challenge worldwide1, 2. The most urgent clinical need is to discover potent agents capable of reducing the duration of MDR and XDR tuberculosis therapy with a success rate comparable to that of current therapies for drug-susceptible tuberculosis. The last decade has seen the discovery of new agent classes for the management of tuberculosis3, 4, 5, several of which are currently in clinical trials6, 7, 8. However, given the high attrition rate of drug candidates during clinical development and the emergence of drug resistance, the discovery of additional clinical candidates is clearly needed. Here, we report on a promising class of imidazopyridine amide (IPA) compounds that block Mycobacterium tuberculosis growth by targeting the respiratory cytochrome bc1 complex. The optimized IPA compound Q203 inhibited the growth of MDR and XDR M. tuberculosis clinical isolates in culture broth medium in the low nanomolar range and was efficacious in a mouse model of tuberculosis at a dose less than 1 mg per kg body weight, which highlights the potency of this compound. In addition, Q203 displays pharmacokinetic and safety profiles compatible with once-daily dosing. Together, our data indicate that Q203 is a promising new clinical candidate for the treatment of tuberculosis

    Class II Transactivator (CIITA) Enhances Cytoplasmic Processing of HIV-1 Pr55Gag

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    The Pr55(gag) (Gag) polyprotein of HIV serves as a scaffold for virion assembly and is thus essential for progeny virion budding and maturation. Gag localizes to the plasma membrane (PM) and membranes of late endosomes, allowing for release of infectious virus directly from the cell membrane and/or upon exocytosis. The host factors involved in Gag trafficking to these sites are largely unknown. Upon activation, CD4+ T cells, the primary target of HIV infection, express the class II transcriptional activator (CIITA) and therefore the MHC class II isotype, HLA-DR. Similar to Gag, HLA-DR localizes to the PM and at the membranes of endosomes and specialized vesicular MHC class II compartments (MIICs). In HIV producer cells, transient HLA-DR expression induces intracellular Gag accumulation and impairs virus release.Here we demonstrate that both stable and transient expression of CIITA in HIV producer cells does not induce HLA-DR-associated intracellular retention of Gag, but does increase the infectivity of virions. However, neither of these phenomena is due to recapitulation of the class II antigen presentation pathway or CIITA-mediated transcriptional activation of virus genes. Interestingly, we demonstrate that CIITA, apart from its transcriptional effects, acts cytoplasmically to enhance Pr160(gag-pol) (Gag-Pol) levels and thereby the viral protease and Gag processing, accounting for the increased infectivity of virions from CIITA-expressing cells.This study demonstrates that CIITA enhances HIV Gag processing, and provides the first evidence of a novel, post-transcriptional, cytoplasmic function for a well-known transactivator

    Phylogenomics of the Reproductive Parasite Wolbachia pipientis wMel: A Streamlined Genome Overrun by Mobile Genetic Elements

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    The complete sequence of the 1,267,782 bp genome of Wolbachia pipientis wMel, an obligate intracellular bacteria of Drosophila melanogaster, has been determined. Wolbachia, which are found in a variety of invertebrate species, are of great interest due to their diverse interactions with different hosts, which range from many forms of reproductive parasitism to mutualistic symbioses. Analysis of the wMel genome, in particular phylogenomic comparisons with other intracellular bacteria, has revealed many insights into the biology and evolution of wMel and Wolbachia in general. For example, the wMel genome is unique among sequenced obligate intracellular species in both being highly streamlined and containing very high levels of repetitive DNA and mobile DNA elements. This observation, coupled with multiple evolutionary reconstructions, suggests that natural selection is somewhat inefficient in wMel, most likely owing to the occurrence of repeated population bottlenecks. Genome analysis predicts many metabolic differences with the closely related Rickettsia species, including the presence of intact glycolysis and purine synthesis, which may compensate for an inability to obtain ATP directly from its host, as Rickettsia can. Other discoveries include the apparent inability of wMel to synthesize lipopolysaccharide and the presence of the most genes encoding proteins with ankyrin repeat domains of any prokaryotic genome yet sequenced. Despite the ability of wMel to infect the germline of its host, we find no evidence for either recent lateral gene transfer between wMel and D. melanogaster or older transfers between Wolbachia and any host. Evolutionary analysis further supports the hypothesis that mitochondria share a common ancestor with the α-Proteobacteria, but shows little support for the grouping of mitochondria with species in the order Rickettsiales. With the availability of the complete genomes of both species and excellent genetic tools for the host, the wMel–D. melanogaster symbiosis is now an ideal system for studying the biology and evolution of Wolbachia infections

    Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury

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    Objective: We aimed to explore the added value of common machine learning (ML) algorithms for prediction of outcome for moderate and severe traumatic brain injury. Study Design and Setting: We performed logistic regression (LR), lasso regression, and ridge regression with key baseline predictors in the IMPACT-II database (15 studies, n = 11,022). ML algorithms included support vector machines, random forests, gradient boosting machines, and artificial neural networks and were trained using the same predictors. To assess generalizability of predictions, we performed internal, internal-external, and external validation on the recent CENTER-TBI study (patients with Glasgow Coma Scale <13, n = 1,554). Both calibration (calibration slope/intercept) and discrimination (area under the curve) was quantified. Results: In the IMPACT-II database, 3,332/11,022 (30%) died and 5,233(48%) had unfavorable outcome (Glasgow Outcome Scale less than 4). In the CENTER-TBI study, 348/1,554(29%) died and 651(54%) had unfavorable outcome. Discrimination and calibration varied widely between the studies and less so between the studied algorithms. The mean area under the curve was 0.82 for mortality and 0.77 for unfavorable outcomes in the CENTER-TBI study. Conclusion: ML algorithms may not outperform traditional regression approaches in a low-dimensional setting for outcome prediction after moderate or severe traumatic brain injury. Similar to regression-based prediction models, ML algorithms should be rigorously validated to ensure applicability to new populations
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