Beginning with the simple question, "Why did audiences grow
silent?" Listening in Paris gives a spectator's-eye view
of opera and concert life from the Old Regime to the Romantic era,
describing the ...transformation in musical experience from social
event to profound aesthetic encounter. James H. Johnson recreates
the experience of audiences during these rich decades with brio and
wit. Woven into the narrative is an analysis of the political,
musical, and aesthetic factors that produced more engaged
listening. Johnson shows the gradual pacification of audiences from
loud and unruly listeners to the attentive public we know today.
Drawing from a wide range of sources-novels, memoirs, police files,
personal correspondence, newspaper reviews, architectural plans,
and the like-Johnson brings the performances to life: the hubbub of
eighteenth-century opera, the exuberance of Revolutionary
audiences, Napoleon's musical authoritarianism, the bourgeoisie's
polite consideration. He singles out the music of Gluck, Haydn,
Rossini, and Beethoven as especially important in forging new ways
of hearing. This book's theoretical edge will appeal to cultural
and intellectual historians in many fields and periods.
Identifying people at risk of cardiovascular diseases (CVD) is a cornerstone of preventative cardiology. Risk prediction models currently recommended by clinical guidelines are typically based on a ...limited number of predictors with sub-optimal performance across all patient groups. Data-driven techniques based on machine learning (ML) might improve the performance of risk predictions by agnostically discovering novel risk predictors and learning the complex interactions between them. We tested (1) whether ML techniques based on a state-of-the-art automated ML framework (AutoPrognosis) could improve CVD risk prediction compared to traditional approaches, and (2) whether considering non-traditional variables could increase the accuracy of CVD risk predictions.
Using data on 423,604 participants without CVD at baseline in UK Biobank, we developed a ML-based model for predicting CVD risk based on 473 available variables. Our ML-based model was derived using AutoPrognosis, an algorithmic tool that automatically selects and tunes ensembles of ML modeling pipelines (comprising data imputation, feature processing, classification and calibration algorithms). We compared our model with a well-established risk prediction algorithm based on conventional CVD risk factors (Framingham score), a Cox proportional hazards (PH) model based on familiar risk factors (i.e, age, gender, smoking status, systolic blood pressure, history of diabetes, reception of treatments for hypertension and body mass index), and a Cox PH model based on all of the 473 available variables. Predictive performances were assessed using area under the receiver operating characteristic curve (AUC-ROC). Overall, our AutoPrognosis model improved risk prediction (AUC-ROC: 0.774, 95% CI: 0.768-0.780) compared to Framingham score (AUC-ROC: 0.724, 95% CI: 0.720-0.728, p < 0.001), Cox PH model with conventional risk factors (AUC-ROC: 0.734, 95% CI: 0.729-0.739, p < 0.001), and Cox PH model with all UK Biobank variables (AUC-ROC: 0.758, 95% CI: 0.753-0.763, p < 0.001). Out of 4,801 CVD cases recorded within 5 years of baseline, AutoPrognosis was able to correctly predict 368 more cases compared to the Framingham score. Our AutoPrognosis model included predictors that are not usually considered in existing risk prediction models, such as the individuals' usual walking pace and their self-reported overall health rating. Furthermore, our model improved risk prediction in potentially relevant sub-populations, such as in individuals with history of diabetes. We also highlight the relative benefits accrued from including more information into a predictive model (information gain) as compared to the benefits of using more complex models (modeling gain).
Our AutoPrognosis model improves the accuracy of CVD risk prediction in the UK Biobank population. This approach performs well in traditionally poorly served patient subgroups. Additionally, AutoPrognosis uncovered novel predictors for CVD disease that may now be tested in prospective studies. We found that the "information gain" achieved by considering more risk factors in the predictive model was significantly higher than the "modeling gain" achieved by adopting complex predictive models.
ESCRTs are everywhere Hurley, James H
EMBO journal,
1 October 2015, Letnik:
34, Številka:
19
Journal Article
Recenzirano
Odprti dostop
The ESCRT proteins are an ancient system that buds membranes and severs membrane necks from their inner face. Three “classical” functions of the ESCRTs have dominated research into these proteins ...since their discovery in 2001: the biogenesis of multivesicular bodies in endolysosomal sorting; the budding of HIV‐1 and other viruses from the plasma membrane of infected cells; and the membrane abscission step in cytokinesis. The past few years have seen an explosion of novel functions: the biogenesis of microvesicles and exosomes; plasma membrane wound repair; neuron pruning; extraction of defective nuclear pore complexes; nuclear envelope reformation; plus‐stranded RNA virus replication compartment formation; and micro‐ and macroautophagy. Most, and perhaps all, of the functions involve the conserved membrane‐neck‐directed activities of the ESCRTs, revealing a remarkably widespread role for this machinery through a broad swath of cell biology.
ESCRT complexes are required for membrane remodeling and scission; this review highlights their role in cellular processes ranging from exosome generation to the reformation of the nuclear envelope.
Advances in optical manipulation and observation of neural activity have set the stage for widespread implementation of closed-loop and activity-guided optical control of neural circuit dynamics. ...Closing the loop optogenetically (i.e., basing optogenetic stimulation on simultaneously observed dynamics in a principled way) is a powerful strategy for causal investigation of neural circuitry. In particular, observing and feeding back the effects of circuit interventions on physiologically relevant timescales is valuable for directly testing whether inferred models of dynamics, connectivity, and causation are accurate in vivo. Here we highlight technical and theoretical foundations as well as recent advances and opportunities in this area, and we review in detail the known caveats and limitations of optogenetic experimentation in the context of addressing these challenges with closed-loop optogenetic control in behaving animals.
Grosenick et al. highlight advances in simultaneous read-write, all-optical, and optoelectronic technologies enabling closed-loop control of neurons and projections in behaving animals. The authors emphasize bridging the biological and engineering literatures to study, understand, and control neural dynamics and behavior.
The brain-age paradigm is proving increasingly useful for exploring aging-related disease and can predict important future health outcomes. Most brain-age research uses structural neuroimaging to ...index brain volume. However, aging affects multiple aspects of brain structure and function, which can be examined using multimodality neuroimaging. Using UK Biobank, brain-age was modeled in n = 2205 healthy people with T1-weighted MRI, T2-FLAIR, T2∗, diffusion-MRI, task fMRI, and resting-state fMRI. In a held-out healthy validation set (n = 520), chronological age was accurately predicted (r = 0.78, mean absolute error = 3.55 years) using LASSO regression, higher than using any modality separately. Thirty-four neuroimaging phenotypes were deemed informative by the regression (after bootstrapping); predominantly gray-matter volume and white-matter microstructure measures. When applied to new individuals from UK Biobank (n = 14,701), significant associations with multimodality brain-predicted age difference (brain-PAD) were found for stroke history, diabetes diagnosis, smoking, alcohol intake and some, but not all, cognitive measures (corrected p < 0.05). Multimodality neuroimaging can improve brain-age prediction, and derived brain-PAD values are sensitive to biomedical and lifestyle factors that negatively impact brain and cognitive health.
•Brain-age was predicted from 6 different neuroimaging modalities.•Combined multi-modality brain-age was more accurate than any single modality.•Thirty-four neuroimaging measures were informative for brain-age prediction.•Informative measures generally reflect brain volume and white-matter microstructure.•Brain-age was associated with stroke, diabetes, smoking, alcohol and cognition.
Abstract Dietary guidelines continue to recommend restricting intake of saturated fats. This recommendation follows largely from the observation that saturated fats can raise levels of total serum ...cholesterol (TC), thereby putatively increasing the risk of atherosclerotic coronary heart disease (CHD). However, TC is only modestly associated with CHD, and more important than the total level of cholesterol in the blood may be the number and size of low-density lipoprotein (LDL) particles that contain it. As for saturated fats, these fats are a diverse class of compounds; different fats may have different effects on LDL and on broader CHD risk based on the specific saturated fatty acids (SFAs) they contain. Importantly, though, people eat foods, not isolated fatty acids. Some food sources of SFAs may pose no risk for CHD or possibly even be protective . Advice to reduce saturated fat in the diet without regard to nuances about LDL, SFAs, or dietary sources could actually increase people's risk of CHD. When saturated fats are replaced with refined carbohydrates, and specifically with added sugars (like sucrose or high fructose corn syrup), the end result is not favorable for heart health. Such replacement leads to changes in LDL, high-density lipoprotein (HDL), and triglycerides that may increase the risk of CHD. Additionally, diets high in sugar may induce many other abnormalities associated with elevated CHD risk, including elevated levels of glucose, insulin, and uric acid, impaired glucose tolerance, insulin and leptin resistance, non-alcoholic fatty liver disease, and altered platelet function. A diet high in added sugars has been found to cause a 3-fold increased risk of death due to cardiovascular disease, but sugars, like saturated fats, are a diverse class of compounds. The monosaccharide, fructose, and fructose-containing sweeteners (e.g., sucrose) produce greater degrees of metabolic abnormalities than does glucose (either isolated as a monomer, or in chains as starch) and may present greater risk of CHD. This paper reviews the evidence linking saturated fats and sugars to CHD, and concludes that the latter is more of a problem than the former. Dietary guidelines should shift focus away from reducing saturated fat, and from replacing saturated fat with carbohydrates, specifically when these carbohydrates are refined. To reduce the burden of CHD, guidelines should focus particularly on reducing intake of concentrated sugars, specifically the fructose-containing sugars like sucrose and high-fructose corn syrup in the form of ultra-processed foods and beverages.
Most of the global population is deficient in long-chain marine omega-3s. In particular, docosahexaenoic acid (DHA), a long-chain omega-3 fatty acid, is important for brain and eye development. ...Additionally, DHA plays a significant role in mental health throughout early childhood and even into adulthood. In the brain, DHA is important for cellular membrane fluidity, function and neurotransmitter release. Evidence indicates that a low intake of marine omega-3s increases the risk for numerous mental health issues, including Attention Deficit Hyperactivity Disorder (ADHD), autism, bipolar disorder, depression and suicidal ideation. Studies giving supplemental marine omega-3s have shown promise for improving numerous mental health conditions. This paper will review the evidence surrounding marine omega-3s and mental health conditions.
Intravenous infusions of angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) in experimental animals increase the numbers of angiotensin-converting enzyme 2 ...(ACE2) receptors in the cardiopulmonary circulation. ACE2 receptors serve as binding sites for SARS-CoV-2 virions in the lungs. Patients who take ACEIs and ARBS may be at increased risk of severe disease outcomes due to SARS-CoV-2 infections.
Most countries, including the United States, have an array of greenhouse gas mitigation policies, which provide subsidies or restrictions typically aimed at specific technologies or sectors. Such ...climate policies range from automobile fuel economy standards, to gasoline taxes, to mandating that a certain amount of electricity in a state comes from renewables, to subsidizing solar and wind electrical generation, to mandates requiring the blending of biofuels into the surface transportation fuel supply, to supply-side restrictions on fossil fuel extraction. This paper reviews the costs of various technologies and actions aimed at reducing greenhouse gas emissions. Our aim is twofold. First, we seek to provide an up-to-date summary of costs of actions that can be taken now using currently available technology. These costs focus on expenditures and emissions reductions over the life of a project compared to some business-as-usual benchmark—for example, replacing coal-fired electricity generation with wind, or weatherizing a home. We refer to these costs as static because they are costs over the life of a specific project undertaken now, and they ignore spillovers. Our second aim is to distinguish between dynamic and static costs and to argue that some actions taken today with seemingly high static costs can have low dynamic costs, and vice versa. We make this argument at a general level and through two case studies, of solar panels and of electric vehicles, technologies whose costs have fallen sharply. Under the right circumstances, dynamic effects will offer a justification for policies that have high costs according to a myopic calculation.
Between 1730 and 1750, Domingos Alvares traversed the colonial Atlantic world like few Africans of his time--from Africa to South America to Europe. By tracing the steps of this powerful African ...healer and vodun priest, James Sweet finds dramatic means for unfolding a history of the eighteenth-century Atlantic world in which healing, religion, kinship, and political subversion were intimately connected.Alvares treated many people across the Atlantic, yet healing was rarely a simple matter of remedying illness and disease. Through the language of health and healing, Alvares also addressed the profound alienation of warfare, capitalism, and the African slave trade. As a result, he and other African healers frequently ran afoul of imperial power brokers. Nevertheless, even the powerful suffered isolation in the Atlantic world and often turned to African healers for answers. In this way, healers simultaneously became fierce critics of Atlantic imperialism and expert translators of it, adapting their therapeutic strategies in order to secure social relevance and even power. By tracing Alvares' frequent uprooting and border crossing, Sweet illuminates how African healing practices evolved in the diaspora, contesting the social and political hierarchies of imperialism while also making profound impacts on the intellectual discourse of the "modern" Atlantic world.
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