Understanding how an animal's ability to learn relates to neural activity or is altered by lesions, different attentional states, pharmacological interventions, or genetic manipulations are central questions in neuroscience. Although learning is a dynamic process, current analyses do not use dynamic estimation methods, require many trials across many animals to establish the occurrence of learning, and provide no consensus as how best to identify when learning has occurred. We develop a state-space model paradigm to characterize learning as the probability of a correct response as a function of trial number (learning curve). We compute the learning curve and its confidence intervals using a state-space smoothing algorithm and define the learning trial as the first trial on which there is reasonable certainty (Ͼ0.95) that a subject performs better than chance for the balance of the experiment. For a range of simulated learning experiments, the smoothing algorithm estimated learning curves with smaller mean integrated squared error and identified the learning trials with greater reliability than commonly used methods. The smoothing algorithm tracked easily the rapid learning of a monkey during a single session of an association learning experiment and identified learning 2 to 4 d earlier than accepted criteria for a rat in a 47 d procedural learning experiment. Our state-space paradigm estimates learning curves for single animals, gives a precise definition of learning, and suggests a coherent statistical framework for the design and analysis of learning experiments that could reduce the number of animals and trials per animal that these studies require.

BACKGROUND L-type calcium channel (LTCC) mutations have been associated with Brugada syndrome (BrS), short QT (SQT) syndrome, and Timothy syndrome (LQT8). Little is known about the extent to which LTCC mutations contribute to the J-wave syndromes associated with sudden cardiac death. OBJECTIVE The purpose of this study was to identify mutations in the α1, β2, and α2δ subunits of LTCC (Cav1.2) among 205 probands diagnosed with BrS, idiopathic ventricular fibrillation (IVF), and early repolarization syndrome (ERS). CACNA1C, CACNB2b, and CACNA2D1 genes of 162 probands with BrS and BrS+SQT, 19 with IVF, and 24 with ERS were screened by direct sequencing. METHODS/RESULTS Overall, 23 distinct mutations were identified. A total of 12.3%, 5.2%, and 16% of BrS/BrS+SQT, IVF, and ERS probands displayed mutations in α1, β2, and α2δ subunits of LTCC, respectively. When rare polymorphisms were included, the yield increased to 17.9%, 21%, and 29.1% for BrS/BrS+SQT, IVF, and ERS probands, respectively. Functional expression of two CACNA1C mutations associated with BrS and BrS+SQT led to loss of function in calcium channel current. BrS probands displaying a normal QTc had additional variations known to prolong the QT interval. CONCLUSION The study results indicate that mutations in the LTCCs are detected in a high percentage of probands with J-wave syndromes associated with inherited cardiac arrhythmias, suggesting that genetic screening of Cav genes may be a valuable diagnostic tool in identifying individuals at risk. These results are the first to identify CACNA2D1 as a novel BrS susceptibility gene and CACNA1C, CACNB2, and CACNA2D1 as possible novel ERS susceptibility genes.

The mouse protein Qa-1 (HLA-E in humans) is essential for immunological protection and immune regulation. Although Qa-1 has been linked to CD8 T cell-dependent suppression, the physiological relevance of this observation is unclear. We generated mice deficient in Qa-1 to develop an understanding of this process. Qa-1-deficient mice develop exaggerated secondary CD4 responses to foreign and self peptides. Enhanced responses to proteolipid protein self peptide were associated with resistance of Qa-1-deficient CD4 T cells to Qa-1-restricted CD8 T suppressor activity and increased susceptibility to experimental autoimmune encephalomyelitis. These findings delineate a Qa-1-dependent T cell-T cell inhibitory interaction that prevents the pathogenic expansion of autoreactive CD4 T cell populations and consequent autoimmune disease.

It has been hypothesized that topological structures of biological transport networks are consequences of energy optimization. Motivated by experimental observation, we propose that adaptation dynamics may underlie this optimization. In contrast to the global nature of optimization, our adaptation dynamics responds only to local information and can naturally incorporate fluctuations in flow distributions. The adaptation dynamics minimizes the global energy consumption to produce optimal networks, which may possess hierarchical loop structures in the presence of strong fluctuations in flow distribution. We further show that there may exist a new phase transition as there is a critical open probability of sinks, above which there are only trees for network structures whereas below which loops begin to emerge.

SARS coronavirus (SARS-CoV), the causative agent of the large SARS outbreak in 2003, originated in bats. Many SARS-like coronaviruses (SL-CoVs) have been detected in bats, particularly those that reside in China, Europe, and Africa. To further understand the evolutionary relationship between SARS-CoV and its reservoirs, 334 bats were collected from Zhoushan city, Zhejiang province, China, between 2015 and 2017. PCR amplification of the conserved coronaviral protein RdRp detected coronaviruses in 26.65% of bats belonging to this region, and this number was influenced by seasonal changes. Full genomic analyses of the two new SL-CoVs from Zhoushan (ZXC21 and ZC45) showed that their genomes were 29,732 nucleotides (nt) and 29,802 nt in length, respectively, with 13 open reading frames (ORFs). These results revealed 81% shared nucleotide identity with human/civet SARS CoVs, which was more distant than that observed previously for bat SL-CoVs in China. Importantly, using pathogenic tests, we found that the virus can reproduce and cause disease in suckling rats, and further studies showed that the virus-like particles can be observed in the brains of suckling rats by electron microscopy. Thus, this study increased our understanding of the genetic diversity of the SL-CoVs carried by bats and also provided a new perspective to study the possibility of cross-species transmission of SL-CoVs using suckling rats as an animal model.

This in vivo time-lapse imaging study in zebrafish reveals how changes to brain blood flow drive vessel pruning via endothelial cell migration, and how pruning leads to the simplification of the brain vasculature during development.

Atherogenesis, the formation of atherosclerotic plaques, is a complex process that involves several mechanisms, including endothelial dysfunction, neovascularization, vascular proliferation, apoptosis, matrix degradation, inflammation, and thrombosis. The pathogenesis and progression of atherosclerosis are explained differently by different scholars. One of the most common theories is the destruction of well-balanced homeostatic mechanisms, which incurs the oxidative stress. And oxidative stress is widely regarded as the redox status realized when an imbalance exists between antioxidant capability and activity species including reactive oxygen (ROS), nitrogen (RNS) and halogen species, non-radical as well as free radical species. This occurrence results in cell injury due to direct oxidation of cellular protein, lipid, and DNA or via cell death signaling pathways responsible for accelerating atherogenesis. This paper discusses inflammation, mitochondria, autophagy, apoptosis, and epigenetics as they induce oxidative stress in atherosclerosis, as well as various treatments for antioxidative stress that may prevent atherosclerosis.

Small beginnings: Metal nanoparticle/CNT nanohybrids are synthesized from carbon nanotubes (CNTs) functionalized with an ionic-liquid polymer. The Pt and PtRu nanoparticles with narrow size distribution (average diameter: (1.3+/-0.4) nm for PtRu, (1.9+/-0.5) nm for Pt) are dispersed uniformly on the CNTs (see images) and show good performance in methanol electrooxidation.