Conditioning pain stimulation does not affect itch induced by intra-epidermal histamine pricks but aggravates neurogenic inflammation in healthy volunteers

This study investigated whether itch induced by intra-epidermal histamine is subjected to modulation by a standardized conditioned pain modulation (CPM) paradigm in 24 healthy volunteers. CPM was induced by computer-controlled cuff pressure algometry and histamine was introduced to the volar forearm by skin prick test punctures. Moreover, neurogenic inflammation and wheal reactions induced by histamine and autonomic nervous system responses (heart rate variability and skin conductance) were monitored. CPM did not modulate the intensity of histamine-induced itch suggesting that pruriceptive signaling is not inhibited by pain-recruited endogenous modulation, however, CPM was found to aggravate histamine-induced neurogenic inflammation, likely facilitated by efferent sympathetic fibers.     

New Anthracene‐Fused Nonfullerene Acceptors for High‐Efficiency Organic Solar Cells: Energy Level Modulations Enabling Match of Donor and Acceptor

Two new nonfullerene small molecule acceptors (NF‐SMAs) AT‐NC and AT‐4Cl based on heptacyclic anthracene(cyclopentadithiophene) (AT) core and different electron‐withdrawing end groups are designed and synthesized. Although the two new acceptor molecules use two different end groups, naphthyl‐fused indanone (NINCN) and chlorinated INCN (INCN‐2Cl) demonstrate similar light absorption. AT‐4Cl with chlorinated INCN as end groups are shifted significantly due to the strong electron‐withdrawing ability of chlorine atoms. Thus, desirable V_oc and photovoltaic performance are expected to be achieved when polymer PBDB‐T is used as the electron donor with AT‐NC as the acceptor, and fluorinated analog PBDB‐TF with down‐shifted energy levels is selected to blend with AT‐4Cl. Consequently, the device based on PBDB‐TF:AT‐4Cl yields a high power conversion efficiency of 13.27% with a slightly lower V_oc of 0.901 V, significantly enhanced J_sc of 19.52 mA cm^?2 and fill factor of 75.5% relative to the values based on PBDB‐T:AT‐NC. These results demonstrate that the use of a new electron‐rich AT core, together with energy levels modulations by end‐group optimizations enabling the match with polymer donors, is a successful strategy to construct high‐performance NF‐SMAs.     

‘Tailception’: using neural networks for assessing tail lesions on pictures of pig carcasses

Tail lesions caused by tail biting are a widespread welfare issue in pig husbandry. Determining their prevalence currently involves labour intensive, subjective scoring methods. Increased societal interest in tail lesions requires fast, reliable and cheap systems for assessing tail status. In the present study, we aimed to test the reliability of neural networks for assessing tail pictures from carcasses against trained human observers. Three trained observers scored tail lesions from automatically recorded pictures of 13 124 pigs. Nearly all pigs had been tail docked. Tail lesions were classified using a 4-point score (0=no lesion, to 3=severe lesion). In addition, total tail loss was recorded. Agreement between observers was tested prior and during the assessment in a total of seven inter-observer tests with 80 pictures each. We calculated agreement between observer pairs as exact agreement (%) and prevalence-adjusted bias-adjusted κ (PABAK; value 1=optimal agreement). Out of the 13 124 scored pictures, we used 80% for training and 20% for validating our neural networks. As the position of the tail in the pictures varied (high, low, left, right), we first trained a part detection network to find the tail in the picture and select a rectangular part of the picture which includes the tail. We then trained a classification network to categorise tail lesion severity using pictures scored by human observers whereby the classification network only analysed the selected picture parts. Median exact agreement between the three observers was 80% for tail lesions and 94% for tail loss. Median PABAK for tail lesions and loss were 0.75 and 0.87, respectively. The agreement between classification by the neural network and human observers was 74% for tail lesions and 95% for tail loss. In other words, the agreement between the networks and human observers were very similar to the agreement between human observers. The main reason for disagreement between observers and thereby higher variation in network training material were picture quality issues. Therefore, we expect even better results for neural network application to tail lesions if training is based on high quality pictures. Very reliable and repeatable tail lesion assessment from pictures would allow automated tail classification of all pigs slaughtered, which is something that some animal welfare labels would like to do.     

Neural Substrates of Drosophila Larval Anemotaxis

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老年人认知训练的神经机制研究

伴随老化,老年人的认知和脑功能会表现出一定的下降趋势.尽管如此,人类的大脑到老年期都会保有一定的可塑性,认知训练的方式是延缓认知和脑功能衰退的有效手段.本文回顾了以往针对老年人不同类型的认知训练研究,探讨了认知训练的理论基础(包括放大观和补偿观),深入分析了老年人认知训练的神经机制,并在此基础上指出以往研究中理论基础冲突的不足和对未来研究老年人训练任务适配性的展望.     

Proposing a Radial Basis Function and CSDM Indices to Predict the Traumatic Brain Injury Risk

BackgroundMany head injury indices and finite element (FE) head models have been proposed to predict traumatic brain injury (TBI). Although FE head models are suitable methods with high accuracy, they are computationally intensive. Head motion-based brain injury criteria are usually fast tools with lower accuracy. So, the objective of this study is to propose new criteria along with an artificial neural network model to predict TBI risks, which can be fast and accurate.MethodsFor this purpose, 250 FE head simulations have been carried out at 5 magnitudes and 50 rotational impact directions using the SIMon model. The effects of directions and magnitudes of rotational impacts were assessed for cumulative strain damage measure (CSDM) values. Next, statistical analysis and neural network were applied to predict CSDM values.ResultsThe results of the present research showed that the direction of rotation in the sagittal and frontal planes had a considerable effect on the CSDM values. Furthermore, new brain injury indices and a radial basis function neural network have been proposed to predict CSDM values which having high correlation coefficients with SIMon responses.ConclusionsThe results of this research demonstrated that rotational impact directions should be used to develop new head injury criteria being able to predict CSDM values. However, findings of present research proved that head motion-based brain injury criteria and RBF network can be used to predict FE head model responses with high speed and accuracy.     

Electrical Compartmentalization in Neurons

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Adhesive papillae on the brachiolar arms of brachiolaria larvae in two starfishes, Asterina pectinifera and Asterias amurensis, are sensors for metamorphic inducing factor(s)

It has been hypothesized by Barker that starfish brachiolaria larvae initiate metamorphosis by sensing of metamorphic inducing factor(s) with neural cells within the adhesive papillae on their brachiolar arms. We present evidence supporting Barker's hypothesis using brachiolaria larvae of the two species, Asterina pectinifera and Asterias amurensis. Brachiolaria larvae of these two species underwent metamorphosis in response to pebbles from aquaria in which adults were kept. Time-lapse analysis of A. pectinifera indicated that the pebbles were explored with adhesive papillae prior to establishment of a stable attachment for metamorphosis. Microsurgical dissections, which removed adhesive papillae, resulted in failure of the brachiolaria larvae to respond to the pebbles, but other organs such as the lateral ganglia, the oral ganglion, the adhesive disk or the adult rudiment were not required. Immunohistochemical analysis with a neuron-specific monoclonal antibody and transmission electron microscopy revealed that the adhesive papillae contained neural cells that project their processes towards the external surface of the adhesive papillae and they therefore qualify as sensory neural cells.