Vinsonmccray1705

The International Brain Laboratory (IBL) is a collaboration of ∼20 laboratories dedicated to developing a standardized mouse decision-making behavior, coordinating measurements of neural activity across the mouse brain, and utilizing theoretical approaches to formalize the neural computations that support decision-making. In contrast to traditional neuroscientific practice, in which individual laboratories each probe different behaviors and record from a few select brain areas, IBL aims to deliver a standardized, high-density approach to behavioral and neural assays. This approach relies on a highly distributed, collaborative network of ∼50 researchers - postdocs, graduate students, and scientific staff - who coordinate the intellectual, administrative, and sociological aspects of the project. In this article, we examine this network, extract some lessons learned, and consider how IBL may represent a template for other team-based approaches in neuroscience, and beyond.Diffusion magnetic resonance imaging (dMRI) provides a noninvasive method for measuring brain tissue microstructure. find more q-Space deep learning(q-DL) methods have been developed to accurately estimate tissue microstructure from dMRI scans acquired with a reduced number of diffusion gradients. In these methods, deep networks are trained to learn the mapping directly from diffusion signals to tissue microstructure. However, the quality of tissue microstructure estimation can be limited not only by the reduced number of diffusion gradients but also by the low spatial resolution of typical dMRI acquisitions. Therefore, in this work we extend q-DL to super-resolved tissue microstructure estimation and propose super-resolvedq-DL (SR-q-DL), where deep networks are designed to map low-resolution diffusion signals undersampled in the q-space to high-resolution tissue microstructure. Specifically, we use a patch-based strategy, where a deep network takes low-resolution patches of diffusion signals as input and outputs high-stimates. Then, multiple deep networks are trained and their results are fused for the final prediction of high-resolution tissue microstructure and uncertainty quantification. The proposed method was evaluated on two independent datasets of brain dMRI scans. Results indicate that our approach outperforms competing methods in terms of estimation accuracy. In addition, uncertainty measures provided by our method correlate with estimation errors, which indicates potential application of the proposed uncertainty quantification method in brain studies.Long-term trends of artificial radionuclides, from 2003 to 2018, in two abundant species of macrophytes, shining pondweed, Potamogeton lucens, and water moss, Fontinalis antipyretica, have been analyzed to estimate the indicative reliability of these two species as biomonitors of radioactive contamination in a river system and to quantify the decrease in the content of artificial radionuclides in the Yenisei River. Time-dependent trends of artificial radionuclides in the biomass of these species were similar, resulting in estimates of effective half-lives for 54Mn, 58Co, 60Co, 65Zn, 137Cs, and 152Eu similar for both species. Concentrations of artificial radionuclides in biomass of shining pondweed and water moss correlated with annual discharges of the radionuclides to the Yenisei at different levels of significance, and the strongest (R2 > 0.7) positive correlation (p less then 0.05) was obtained for 60Co, 65Zn, and 152Eu. Concentrations of 60Co, 137Cs, and 152Eu in water moss were 2-7.5 times higher than in shining pondweed, and considerable percentages of those isotopes were recorded in extracellular particulate matter, which was largely represented by epiphytic diatoms. Higher concentrations of artificial radionuclides in the biomass of water moss can be considered as an advantage of water moss as a monitor of radioactive contamination of the Yenisei, while shining pondweed is more useful for estimation of annual deposits of radionuclides in vegetation of the Yenisei and spatial transfer of radionuclides downstream of the discharge site. Despite differences in concentrations of artificial radionuclides, both species can be considered as reliable indicators of radioactive contamination of the river on a long-term scale.

For the past few decades, numerous theoretical perspectives have predicted a negative association between adolescent sexual debut and the probability of college entrance. The present article extends the literature by using nationally representative longitudinal data from South Korea to assess these perspectives.

Drawing on longitudinal data from South Korea, this article examined the impact of becoming sexually active between 8th and 12th grades on the probability of college entrance. We controlled for a wide array of confounding variables by using logit models that account for longitudinal attrition and school-based sampling design.

Analytical results showed that the initiation of sexual intercourse during adolescence predicted a statistically significant decrease in the probability of college entrance for both boys and girls. Gender-specific analyses suggested that, on average, sexual debut in adolescence was associated with a decrease of 10.3 percentage points in the probability of college entrance for boys and a decrease of 14.7 percentage points for girls.

These findings strongly support the theoretical perspectives of age norm theory and sexual double standards in South Korea, where strictly conservative attitudes toward sexuality and sexual behaviors are dominant.

These findings strongly support the theoretical perspectives of age norm theory and sexual double standards in South Korea, where strictly conservative attitudes toward sexuality and sexual behaviors are dominant.

Surveillance for Middle East Respiratory Syndrome (MERS) has been undertaken in the UK since September 2012. This study describes the surveillance outcomes in England from 2012 to 2018.

This was a descriptive study using surveillance data.

Local health protection teams in England report possible MERS cases to the National Infection Service with clinical and laboratory data.

A total of 1301 possible MERS cases were identified in the study period. Five cases were laboratory-confirmed MERS. The majority of cases had travelled to Saudi Arabia (56.7%) and United Arab Emirates (25.9%). Fifty-four percent of cases were men and 43.7% were women. The majority of cases (65.1%) were aged 45 years or older. The number of tests increased in the period after Hajj each year. Laboratory-confirmed alternative diagnoses were available for 513 (39.4%) cases; influenza was the most common virus detected (n=255, 52.4%).

Our study highlights the importance of differential diagnosis of influenza and other respiratory pathogens and early influenza antiviral treatment.