Abstract
Prediction of disease risk is an essential part of preventative medicine, often guiding clinical management. Risk prediction typically includes risk factors such as age, sex, family history ...of disease and lifestyle (e.g. smoking status); however, in recent years, there has been increasing interest to include genomic information into risk models. Polygenic risk scores (PRS) aggregate the effects of many genetic variants across the human genome into a single score and have recently been shown to have predictive value for multiple common diseases. In this review, we summarize the potential use cases for seven common diseases (breast cancer, prostate cancer, coronary artery disease, obesity, type 1 diabetes, type 2 diabetes and Alzheimer’s disease) where PRS has or could have clinical utility. PRS analysis for these diseases frequently revolved around (i) risk prediction performance of a PRS alone and in combination with other non-genetic risk factors, (ii) estimation of lifetime risk trajectories, (iii) the independent information of PRS and family history of disease or monogenic mutations and (iv) estimation of the value of adding a PRS to specific clinical risk prediction scenarios. We summarize open questions regarding PRS usability, ancestry bias and transferability, emphasizing the need for the next wave of studies to focus on the implementation and health-economic value of PRS testing. In conclusion, it is becoming clear that PRS have value in disease risk prediction and there are multiple areas where this may have clinical utility.
Evolution is a blind fitting process by which organisms become adapted to their environment. Does the brain use similar brute-force fitting processes to learn how to perceive and act upon the world? ...Recent advances in artificial neural networks have exposed the power of optimizing millions of synaptic weights over millions of observations to operate robustly in real-world contexts. These models do not learn simple, human-interpretable rules or representations of the world; rather, they use local computations to interpolate over task-relevant manifolds in a high-dimensional parameter space. Counterintuitively, similar to evolutionary processes, over-parameterized models can be simple and parsimonious, as they provide a versatile, robust solution for learning a diverse set of functions. This new family of direct-fit models present a radical challenge to many of the theoretical assumptions in psychology and neuroscience. At the same time, this shift in perspective establishes unexpected links with developmental and ecological psychology.
To guide adaptive behavior and support predictions in real-life contexts, the brain may rely on opaque, over-parameterized models capable of directly fitting to the multidimensional world, while being blind—like evolution—to the underlying rules and causes.
•Laboratory experiments are often designed to isolate a handful of intuitive variables.•The brain, however, has evolved to navigate a complex, multidimensional world.•This creates a tension between ...experimental control and ecological generalizability.•Neuroscientific models should be developed and tested in ecological contexts.
Naturalistic experimental paradigms in neuroimaging arose from a pressure to test the validity of models we derive from highly-controlled experiments in real-world contexts. In many cases, however, such efforts led to the realization that models developed under particular experimental manipulations failed to capture much variance outside the context of that manipulation. The critique of non-naturalistic experiments is not a recent development; it echoes a persistent and subversive thread in the history of modern psychology. The brain has evolved to guide behavior in a multidimensional world with many interacting variables. The assumption that artificially decoupling and manipulating these variables will lead to a satisfactory understanding of the brain may be untenable. We develop an argument for the primacy of naturalistic paradigms, and point to recent developments in machine learning as an example of the transformative power of relinquishing control. Naturalistic paradigms should not be deployed as an afterthought if we hope to build models of brain and behavior that extend beyond the laboratory into the real world.
The relationship between pollution emissions and economic development matters greatly to sustainable growth goals. China has experienced rapid growth in pollution emissions, energy consumption, and ...the effects of climate change. To achieve pollution reduction and energy savings targets, China's green loan policy implements a financing–pollution emissions reduction strategy for Chinese firms. Employing a difference-in-difference estimation method, we use Jiangsu Province manufacturing firm data for the period 2005 to 2013 to evaluate the effect of financing–pollution emission reduction policy tools on firm performance. Our analysis yields the following results. First, the financing–emission reduction policy has a “punishment” effect on highly polluting firm performance, including total factor productivity, profitability, and sales growth. Second, we find that these negative effects are weakened in dynamic processes. Further, pollution emissions are significantly reduced. Third, financial constraints act as the mechanism through which firm performance is punished, via the financial–emission reduction policy. Short-term and long-term bank financing decrease, while working capital and trade credit are increased to finance investment. Finally, with regard to ownership structure, state-owned firm performance is more likely to be penalized than other forms of ownership.
•The financing–emission reduction policy has a “punishment” effect on polluting firm performance.•The financing–emission reduction policy makes pollution emissions reduced.•Financial constraints act as the mechanism through which firm performance is punished.•State-owned firm performance is more likely to be penalized than other forms of ownership.
Aquaculture is the fastest-growing farmed food sector and will soon become the primary source of fish and shellfish for human diets. In contrast to crop and livestock production, aquaculture ...production is derived from numerous, exceptionally diverse species that are typically in the early stages of domestication. Genetic improvement of production traits via well-designed, managed breeding programmes has great potential to help meet the rising seafood demand driven by human population growth. Supported by continuous advances in sequencing and bioinformatics, genomics is increasingly being applied across the broad range of aquaculture species and at all stages of the domestication process to optimize selective breeding. In the future, combining genomic selection with biotechnological innovations, such as genome editing and surrogate broodstock technologies, may further expedite genetic improvement in aquaculture.
Background
Jeffrey A. Norton could have been a professional football player but instead he chose to pursue a career in medicine and in the process became an outstanding academic surgeon. This story ...recounts his ascent from a small town in Massachusetts to the pinnacle of academic surgery.
Methods
After graduating from high school in Albany, New York, Jeff continued his education at Dartmouth University, the State University of New York Upstate Medical University at Syracuse (SUNY Upstate Medical University), and the Department of Surgery at the Duke University School of Medicine. When he completed the surgical residency, he spent 10 years at the National Cancer Institute (NCI) where he and his colleagues made significant contributions to the diagnosis and treatment of patients with endocrine tumors. After leaving the NCI, he had highly productive years as a Professor in Departments of Surgery at Washington University, the University of California at San Francisco, and Stanford University. He became a member of every major academic surgical society and won numerous awards for his accomplishments in research. His expertise in educating medical students and surgical residents is legendary.
Results
In addition to his academic accomplishments, Jeff trained legions of young surgeons who subsequently made significant contributions in surgical investigation and clinical surgery.
Conclusion
It is most fitting that the Stanford University School of Medicine has assembled a group of Jeffrey Norton’s colleagues in academic medicine and surgery to pay tribute to his achievements as a surgical scientist.
Various studies have been done over a number of years to develop strengthening techniques which will improve the performance of masonry structures. Many unreinforced masonry structures are ...seismically deficient and several research studies have been conducted to improve the seismic performance of these structures. Strengthening methods such as the addition of new structural elements, steel plate bonding, external post tensioning, steel bracing and many more have been applied with some degree of success. However, an innovative retrofitting technique using Fiber Reinforced Polymer (FRP) has gained recognition and acceptance. FRP materials have light weight, excellent durability, and high strength, yet are lightweight and are easy and quick to install. All these properties make FRP materials attractive for strengthening and rehabilitating of reinforced and unreinforced masonry structures. Different strengthening techniques are available to increase the flexural and shear strength and ductility of masonry structures using FRP materials. This paper reviews these strengthening techniques, their advantages, disadvantages and limitations.
Mitophagy pathways in health and disease Killackey, Samuel A; Philpott, Dana J; Girardin, Stephen E
The Journal of cell biology,
11/2020, Letnik:
219, Številka:
11
Journal Article
Recenzirano
Odprti dostop
Mitophagy is an evolutionarily conserved process involving the autophagic targeting and clearance of mitochondria destined for removal. Recent insights into the complex nature of the overlapping ...pathways regulating mitophagy illustrate mitophagy's essential role in maintaining the health of the mitochondrial network. In this review, we highlight recent studies that have changed the way mitophagy is understood, from initiation through lysosomal degradation. We outline the numerous mitophagic receptors and triggers, with a focus on basal and physiologically relevant cues, offering insight into why they lead to mitochondrial removal. We also explore how mitophagy maintains mitochondrial homeostasis at the organ and system levels and how a loss of mitophagy may play a role in a diverse group of diseases, including cardiovascular, metabolic, and neurodegenerative diseases. With disrupted mitophagy affecting such a wide array of physiological processes, a deeper understanding of how to modulate mitophagy could provide avenues for numerous therapies.
The reaction-diffusion master equation (RDME) is a lattice stochastic reaction-diffusion model that has been used to study spatially distributed cellular processes. The RDME is often interpreted as ...an approximation to spatially continuous models in which molecules move by Brownian motion and react by one of several mechanisms when sufficiently close. In the limit that the lattice spacing approaches zero, in two or more dimensions, the RDME has been shown to lose bimolecular reactions. The RDME is therefore not a convergent approximation to any spatially continuous model that incorporates bimolecular reactions. In this work we derive a new convergent RDME (CRDME) by finite volume discretization of a spatially continuous stochastic reaction-diffusion model popularized by Doi. We demonstrate the numerical convergence of reaction time statistics associated with the CRDME. For sufficiently large lattice spacings or slow bimolecular reaction rates, we also show that the reaction time statistics of the CRDME may be approximated by those from the RDME. The original RDME may therefore be interpreted as an approximation to the CRDME in several asymptotic limits.
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