Lykkegaardrodriquez8858

Objective.Deep neural network (DNN) based methods have shown promising performances for low-dose computed tomography (LDCT) imaging. However, most of the DNN-based methods are trained on simulated labeled datasets, and the low-dose simulation algorithms are usually designed based on simple statistical models which deviate from the real clinical scenarios, which could lead to issues of overfitting, instability and poor robustness. To address these issues, in this work, we present a structure-preserved meta-learning uniting network (shorten as 'SMU-Net') to suppress noise-induced artifacts and preserve structure details in the unlabeled LDCT imaging task in real scenarios.Approach.Specifically, the presented SMU-Net contains two networks, i.e., teacher network and student network. The teacher network is trained on simulated labeled dataset and then helps the student network train with the unlabeled LDCT images via the meta-learning strategy. The student network is trained on real LDCT dataset with the pseudo-labels generated by the teacher network. Moreover, the student network adopts the Co-teaching strategy to improve the robustness of the presented SMU-Net.Main results.We validate the proposed SMU-Net method on three public datasets and one real low-dose dataset. The visual image results indicate that the proposed SMU-Net has superior performance on reducing noise-induced artifacts and preserving structure details. And the quantitative results exhibit that the presented SMU-Net method generally obtains the highest signal-to-noise ratio (PSNR), the highest structural similarity index measurement (SSIM), and the lowest root-mean-square error (RMSE) values or the lowest natural image quality evaluator (NIQE) scores.Significance.We propose a meta learning strategy to obtain high-quality CT images in the LDCT imaging task, which is designed to take advantage of unlabeled CT images to promote the reconstruction performance in the LDCT environments.In the drug development process, optimization of properties and biological activities of small molecules is an important task to obtain drug candidates with optimal efficacy when first applied in subsequent clinical studies. However, despite its importance, large-scale investigations of the optimization process in early drug discovery are lacking, likely due to the absence of historical records of different chemical series used in past projects. Here, we report a retrospective reconstruction of ∼3000 chemical series from the Novartis compound database, which allows us to characterize the general properties of chemical series as well as the time evolution of structural properties, ADMET properties, and target activities. Our data-driven approach allows us to substantiate common MedChem knowledge. learn more We find that size, fraction of sp3-hybridized carbon atoms (Fsp3), and the density of stereocenters tend to increase during optimization, while the aromaticity of the compounds decreases. On the ADMET side, solubility tends to increase and permeability decreases, while safety-related properties tend to improve. Importantly, while ligand efficiency decreases due to molecular growth over time, target activities and lipophilic efficiency tend to improve. This emphasizes the heavy-atom count and log D as important parameters to monitor, especially as we further show that the decrease in permeability can be explained with the increase in molecular size. We highlight overlaps, shortcomings, and differences of the computationally reconstructed chemical series compared to the series used in recent internal drug discovery projects and investigate the relation to historical projects.Adipose tissue dysfunction is a key mechanism that leads to adiposity-based chronic disease. This study aimed to investigate the reliability of the adiponectin/leptin ratio (AdipoQ/Lep) as an adipose tissue and metabolic function biomarker in adults with obesity, without diabetes. Data were collected from a clinical trial conducted in 28 adults with obesity (mean body mass index 35.4 ± 3.7 kg/m2) (NCT02169778). With the use of a forward stepwise multiple linear regression model to explore the relationship between AdipoQ/Lep and Homeostatic Model Assessment of Insulin Resistance (HOMA-IR), it was observed that 48.6% of HOMA-IR variance was explained by triacylglycerols, AdipoQ/Lep, and waist-to-hip ratio (P less then 0.001), AdipoQ/Lep being the strongest independent predictor (Beta = -0.449, P less then 0.001). A lower AdipoQ/Lep was correlated with higher body mass index (Rs = -0.490, P less then 0.001), body fat mass (Rs = -0.486, P less then 0.001), waist-to-height ratio (Rs = -0.290, P = 0.037), and plasma resistin (Rs = -0.365, P = 0.009). These data highlight the central role of adipocyte dysfunction in the pathogenesis of insulin resistance and emphasize that AdipoQ/Lep may be a promising early marker of insulin resistance development in adults with obesity.NEW & NOTEWORTHY Adiponectin/leptin ratio, triacylglycerols, and waist-to-hip ratio explained almost half of HOMA-IR variance in the context of obesity. This study provides evidence to support adipose tissue dysfunction as a central feature of the pathophysiology of obesity and insulin resistance. Early identification of individuals at higher risk of developing metabolic complications through adipose tissue dysfunction assessment and the staging of obesity and its transient phenotypes can contribute to improve therapeutic decision-making.In this study, we fabricate magnetic-fluorescent responsive Janus photonic crystal beads (JPCBs) based on poly(styrene-methyl methacrylate-acrylic acid) (p(St-MMA-AA)) colloidal nanoparticles, Fe3O4, and photobase generators used for self-destructive anti-counterfeiting. We synthesize two kinds of photobase generators that can react with fluorescamine to produce various fluorescence colors. A microfluidic method is used to obtain the Janus photonic crystal beads. The upper portions of the JPCBs are photonic crystals assembled with colloidal spheres, whereas the Fe3O4 settles down to the bottom of the JPCBs due to its higher density. Photobase generators are distributed in photonic crystal gaps. Because of the magnetism of the Fe3O4, the JPCBs could be flipped from one side to the other in the presence of a magnet. After being exposed to UVC light and fluorescamine, the JPCBs can fluoresce under UVA light. Then, we create Janus microbeads arrays with various types of beads and apply them to the visitor card, bracelet, and box label to provide irreversible and self-destructive anti-counterfeiting. The JPCBs are capable of being encoded and angle-independently displayed, which are crucial to their applications in anti-counterfeiting, information coding, and array display.Phenomenon To increase racial diversity in medical school classes, many institutions have created underrepresented minority (URM) application streams. However, many URM students experience overt and passive marginalization throughout their training and this may be related to how matriculants from URM streams are perceived by their peers. Approach We conducted a discourse analysis of online discussion forums to explore how URM streams across Canada and the United States are perceived. We analyzed 850 posts from 13 discussion threads published between 2015 and 2020. We used inductive content analysis to develop a data-driven coding scheme from which we identified common themes. Findings Despite an overall appreciation of the benefits of a diverse workforce, participants engaged in prominent discussions surrounding the merits of URM streams. We identified perceptions that students admitted from URM streams are less academically and clinically competent, with URM applicants reporting feeling unworthy for admission in the eyes of non-URM applicants. Users felt that the influence of socioeconomic status was under-appreciated, and that admissions officers inadequately addressed this barrier. There were some applicants who perceived the admissions process as "broken" with non-URMs displaying a fear of social change, and URMs fearing that the system defines them by their racialized status. Insights Online discussion forums provide unique insight into perceptions surrounding URM streams. We identified potentially harmful misconceptions about URM students applying to these streams and highlight that actionable measures to reduce marginalization against URM matriculants must begin before medical school.Quantum chemical calculations on quantum computers have been focused mostly on simulating molecules in the gas phase. Molecules in liquid solution are, however, most relevant for chemistry. Continuum solvation models represent a good compromise between computational affordability and accuracy in describing solvation effects within a quantum chemical description of solute molecules. In this work, we extend the variational quantum eigensolver to simulate solvated systems using the polarizable continuum model. To account for the state dependent solute-solvent interaction we generalize the variational quantum eigensolver algorithm to treat non-linear molecular Hamiltonians. We show that including solvation effects does not impact the algorithmic efficiency. Numerical results of noiseless simulations for molecular systems with up to 12 spin-orbitals (qubits) are presented. Furthermore, calculations performed on a simulated noisy quantum hardware (IBM Q, Mumbai) yield computed solvation free energies in fair agreement with the classical calculations.This work describes the development and testing of a method for the identification and classification of conserved water molecules and their networks from molecular dynamics (MD) simulations. The conserved waters in the active sites of proteins influence protein-ligand binding. Recently, several groups have argued that a water network formed from conserved waters can be used to interpret the thermodynamic signature of the binding site. We implemented a novel methodology in which we apply the complex approach to categorize water molecules extracted from the MD simulation trajectories using clustering approaches. The main advantage of our methodology as compared to current state of the art approaches is the inclusion of the information on the orientation of hydrogen atoms to further inform the clustering algorithm and to classify the conserved waters into different subtypes depending on how strongly certain orientations are preferred. This information is vital for assessing the stability of water networks. The newly developed approach is described in detail as well as validated against known results from the scientific literature including comparisons with the experimental data on thermolysin, thrombin, and Haemophilus influenzae virulence protein SiaP as well as with the previous computational results on thermolysin. We observed excellent agreement with the literature and were also able to provide additional insights into the orientations of the conserved water molecules, highlighting the key interactions which stabilize them. The source code of our approach, as well as the utility tools used for visualization, are freely available on GitHub.

Sociological research has linked racism and discrimination among children to poorer health outcomes and social conditions later in life.

Given the change in the political climate in the United States, highly publicized deaths of Black men and women by police, and the rise in hate crimes against Asian Americans from 2016 through 2020, our primary objective was to assess trends in racial or ethnic discrimination among children in the United States.

We conducted a cross-sectional analysis of the National Survey of Children's Health (NSCH), a nationally representative survey, utilizing data from 2016 to 2020. We calculated yearly population estimates of whether a child had experienced discrimination based on race/ethnicity via a parent-reported item. We further divided the estimates by race/ethnicity and plotted linear trends over time.

Data from the NSCH show that racial/ethnic discrimination reported by parents of children who are minorities increased from 6.7% in 2016 to approximately 9.3% in 2020. Indigenous children were reported to experience discrimination at high rates ranging from 10.