Modelling the Geographical Origin of Rice Cultivation in Asia Using the Rice Archaeological Database

We have compiled an extensive database of archaeological evidence for rice across Asia, including 400 sites from mainland East Asia, Southeast Asia and South Asia. This dataset is used to compare several models for the geographical origins of rice cultivation and infer the most likely region(s) for its origins and subsequent outward diffusion. The approach is based on regression modelling wherein goodness of fit is obtained from power law quantile regressions of the archaeologically inferred age versus a least-cost distance from the putative origin(s). The Fast Marching method is used to estimate the least-cost distances based on simple geographical features. The origin region that best fits the archaeobotanical data is also compared to other hypothetical geographical origins derived from the literature, including from genetics, archaeology and historical linguistics. The model that best fits all available archaeological evidence is a dual origin model with two centres for the cultivation and dispersal of rice focused on the Middle Yangtze and the Lower Yangtze valleys

Genome-Wide Association Study of Copy Number Variants Suggests LTBP1 and FGD4 Are Important for Alcohol Drinking

Alcohol dependence (AD) is a complex disorder characterized by psychiatric and physiological dependence on alcohol. AD is reflected by regular alcohol drinking, which is highly inheritable. In this study, to identify susceptibility genes associated with alcohol drinking, we performed a genome-wide association study of copy number variants (CNVs) in 2,286 Caucasian subjects with Affymetrix SNP6.0 genotyping array. We replicated our findings in 1,627 Chinese subjects with the same genotyping array. We identified two CNVs, CNV207 (combined p-value 1.91E-03) and CNV1836 (combined p-value 3.05E-03) that were associated with alcohol drinking. CNV207 and CNV1836 are located at the downstream of genes LTBP1 (870 kb) and FGD4 (400 kb), respectively. LTBP1, by interacting TGFB1, may down-regulate enzymes directly participating in alcohol metabolism. FGD4 plays a role in clustering and trafficking GABAA receptor and subsequently influence alcohol drinking through activating CDC42. Our results provide suggestive evidence that the newly identified CNV regions and relevant genes may contribute to the genetic mechanism of alcohol dependence

CCAAT/Enhancer Binding Protein alpha uses distinct domains to prolong pituitary cells in the Growth 1 and DNA Synthesis phases of the cell cycle

BACKGROUND: A number of transcription factors coordinate differentiation by simultaneously regulating gene expression and cell proliferation. CCAAT/enhancer binding protein alpha (C/EBPα) is a basic/leucine zipper transcription factor that integrates transcription with proliferation to regulate the differentiation of tissues involved in energy balance. In the pituitary, C/EBPα regulates the transcription of a key metabolic regulator, growth hormone. RESULTS: We examined the consequences of C/EBPα expression on proliferation of the transformed, mouse GHFT1-5 pituitary progenitor cell line. In contrast to mature pituitary cells, GHFT1-5 cells do not contain C/EBPα. Ectopic expression of C/EBPα in the progenitor cells resulted in prolongation of both growth 1 (G1) and the DNA synthesis (S) phases of the cell cycle. Transcription activation domain 1 and 2 of C/EBPα were required for prolongation of G1, but not of S. Some transcriptionally inactive derivatives of C/EBPα remained competent for G1 and S phase prolongation. C/EBPα deleted of its leucine zipper dimerization functions was as effective as full-length C/EBPα in prolonging G1 and S. CONCLUSION: We found that C/EBPα utilizes mechanistically distinct activities to prolong the cell cycle in G1 and S in pituitary progenitor cells. G1 and S phase prolongation did not require that C/EBPα remained transcriptionally active or retained the ability to dimerize via the leucine zipper. G1, but not S, arrest required a domain overlapping with C/EBPα transcription activation functions 1 and 2. Separation of mechanisms governing proliferation and transcription permits C/EBPα to regulate gene expression independently of its effects on proliferation

Adaptation-Dependent Synchronous Activity Contributes to Receptive Field Size Change of Bullfrog Retinal Ganglion Cell

Nearby retinal ganglion cells of similar functional subtype have a tendency to discharge spikes in synchrony. The synchronized activity is involved in encoding some aspects of visual input. On the other hand, neurons always continuously adjust their activities in adaptation to some features of visual stimulation, including mean ambient light, contrast level, etc. Previous studies on adaptation were primarily focused on single neuronal activity, however, it is also intriguing to investigate the adaptation process in population neuronal activities. In the present study, by using multi-electrode recording system, we simultaneously recorded spike discharges from a group of dimming detectors (OFF-sustained type ganglion cells) in bullfrog retina. The changes in receptive field properties and synchronization strength during contrast adaptation were analyzed. It was found that, when perfused using normal Ringer's solution, single neuronal receptive field size was reduced during contrast adaptation, which was accompanied by weakening in synchronization strength between adjacent neurons' activities. When dopamine (1 µM) was applied, the adaptation-related receptive field area shrinkage and synchronization weakening were both eliminated. The activation of D1 receptor was involved in the adaptation-related modulation of synchronization and receptive field. Our results thus suggest that the size of single neuron's receptive field is positively related to the strength of its synchronized activity with its neighboring neurons, and the dopaminergic pathway is responsible for the modulation of receptive field property and synchronous activity of the ganglion cells during the adaptation process

Computing CNN loss and gradients for pose estimation with Riemannian geometry

Pose estimation, i.e. predicting a 3D rigid transformation with respect to a fixed co-ordinate frame in, SE(3), is an omnipresent problem in medical image analysis. Deep learning methods often parameterise poses with a representation that separates rotation and translation. As commonly available frameworks do not provide means to calculate loss on a manifold, regression is usually performed using the L2-norm independently on the rotation’s and the translation’s parameterisations. This is a metric for linear spaces that does not take into account the Lie group structure of SE(3). In this paper, we propose a general Riemannian formulation of the pose estimation problem, and train CNNs directly on SE(3) equipped with a left-invariant Riemannian metric. The loss between the ground truth and predicted pose (elements of the manifold) is calculated as the Riemannian geodesic distance, which couples together the translation and rotation components. Network weights are updated by back-propagating the gradient with respect to the predicted pose on the tangent space of the manifold SE(3). We thoroughly evaluate the effectiveness of our loss function by comparing its performance with popular and most commonly used existing methods, on tasks such as image-based localisation and intensity-based 2D/3D registration. We also show that hyper-parameters, used in our loss function to weight the contribution between rotations and translations, can be intrinsically calculated from the dataset to achieve greater performance margins