Attention improves information flow between neuronal populations without changing the communication subspace

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Modelling HIV immune response and validation with clinical data

A system of ordinary differential equations is formulated to describe the pathogenesis of HIV infection, wherein certain features that have been shown to be important by recent experimental research are incorporated in the model. These include the role of CD4+memory cells that serve as a major reservoir of latently infected cells, a critical role for T-helper cells in the generation of CD8 memory cells capable of efficient recall response, and stimulation by antigens other than HIV. A stability analysis illustrates the capability of this model in admitting multiple locally asymptotically stable (locally a.s.) off-treatment equilibria. We show that this more biologically detailed model can exhibit the phenomenon of transient viremia experienced by some patients on therapy with viral load levels suppressed below the detection limit. We also show that the loss of CD4+T-cell help in the generation of CD8+memory cells leads to larger peak values for the viral load during transient viremia. Censored clinical data is used to obtain parameter estimates. We demonstrate that using a reduced set of 16 free parameters, obtained by fixing some parameters at their population averages, the model provides reasonable fits to the patient data and, moreover, that it exhibits good predictive capability. We further show that parameter values obtained for most clinical patients do not admit multiple locally a.s off-treatment equilibria. This suggests that treatment to move from a high viral load equilibrium state to an equilibrium state with a lower (or zero) viral load is not possible for these patients.     

中国繁缕属的一些分类问题

研究了36种中国产繁缕属(Stellaria)植物,根据模式材料或仅根据原描述,将已合格发表的1组、1系、12种、4变种和1变型首次归并到有关各类,依次列举入异名录中,其中有1移属。讨论了各种错误鉴定,同时对于选择性状、设想进化过程和分布记录均有讨论。     

Numerical simulation of thermal bone necrosis during cementation of femoral prostheses

The implant of a femoral prosthesis is a critical process because of the relatively high temperature values reached at the bone/cement interface during the cementation of the infibulum. In fact, the cement is actually a polymer that polymerizes in situ generating heat. Moreover, the conversion of monomer into polymer is never 100%; this is dangerous because of the toxicity of the monomer. In this paper, we present a 3-D axisymmetric mathematical model capable of taking into account both the geometry of the implant and the chemical/physical properties of the cement. This model, together with its numerical simulation, thus represents a useful tool to set up the optimal conditions for the new materials developed in this orthopaedic field. The real complex geometry is assumed to be a bone/cement/metallic system having cylindrical symmetry, thus allowing the model to be reduced to two space variables. The cementation process is described by the Fourier heat equation coupled with a suitable polymerization kinetics. The numerical approximation is accomplished by semi-implicit finite differences in time and finite elements in space with numerical quadrature. The full discrete scheme amounts to solve linear positive definite symmetric systems preceded by an elementwise algebraic computation. We present various numerical simulations which confirm some critical aspects of this orthopaedic fixing technique such as thermal bone necrosis and the presence of unreacted residual monomer.This work was partially supported by MURST (Fondi per la Ricerca Scientifica 40%) and CNR (IAN, Contract 880032601, and Progetto Finalizzato Sistemi Informatici e Calcolo Parallelo, Sottoprogetto Calcolo Scientifico per Grandi Sistemi) of Italy     

Six things Popper would like biologists not to ignore: In memoriam, Karl Raimund Popper, 1902–1994

To honour the memory of Sir Karl Popper, I put forward six elements of his philosophy which might be of particular interest to biologists and to philosophers of biology and which I think Popper would like them not to ignore, even if they disagree with him. They are: the primacy of problems; the criticizability of metaphysics (and thus the dubiousness of materialism); how downward causation might be real; how norms should matter to scientists; why dogmatism should be avoided; how genuine science is recognizable. I preface these six things with a brief discussion of Popper's early (but later recanted) mistakes concerning biology.     

造礁石珊瑚群落结构研究的概况,问题和前景

造礁石珊瑚作为珊瑚礁生态系统中的关键生物类群,其群落结构是珊瑚礁系统研究中的一个重 要方面。本文回顾了20余年以来世界各国对造礁石珊瑚群落结构研究所取得的主要进展和认识,指出了目前研究中存在的问题并分析了不同空间范围研究结论之间的缺乏一致性和中等干扰假说的不足。 最后,结合珊瑚礁生态系统基础理论和应用发展的需求,本文探讨了造礁石珊瑚群落结构研究的前景。     

Social problems in geriatric dentistry: an overview

Many studies have reported on the dental status of elderly patients. The results demonstrate consistent differences between normative and perceived needs in addition to varying levels of awareness of dental education among carers. This review article attempts to integrate a range of social factors which must be considered if holistic and comprehensive care is to be delivered to elderly patients.     

TTLL11 gene is associated with sustained attention performance and brain networks: A genome-wide association study of a healthy Chinese sample

Genetic studies on attention have mainly focused on children with attention-deficit/hyperactivity disorder (ADHD), so little systematic research has been conducted on genetic correlates of attention performance and their potential brain mechanisms among healthy individuals. The current study included a genome-wide association study (GWAS, N = 1145 healthy young adults) aimed to identify genes associated with sustained attention and an imaging genetics study (an independent sample of 483 healthy young adults) to examine any identified genes' influences on brain function. The GWAS found that TTLL11 showed genome-wide significant associations with sustained attention, with rs13298112 as the most significant SNP and the GG homozygotes showing more impulsive but also more focused responses than the A allele carriers. A retrospective examination of previously published ADHD GWAS results confirmed an un-reported, small but statistically significant effect of TTLL11 on ADHD. The imaging genetics study replicated this association and showed that the TTLL11 gene was associated with resting state activity and connectivity of the somatomoter network, and can be predicted by dorsal attention network connectivity. Specifically, the GG homozygotes showed lower brain activity, weaker brain network connectivity, and non-significant brain-attention association compared to the A allele carriers. Expression database showed that expression of this gene is enriched in the brain and that the G allele is associated with lower expression level than the A allele. These results suggest that TTLL11 may play a major role in healthy individuals' attention performance and may also contribute to the etiology of ADHD.     

Processing of global and local properties——An analysis with event-related brain potentials

The different processing of global and local properties of compound visual stimuli was studied with event-related brain potentials (ERPs) in the present experiment. It was found that, compared with the identification of global properties, the discrimination of local properties elicited longer RTs, lower accuracies, increased amplitudes of P1, decreased amplitudes of N1, and longer latencies of N2 and P3. The conflict of global and local properties increased the amplitudes of P2, decreased the amplitudes of P3, and prolonged latencies of N2 and P3. These results indicated that the advantage of global processing occurs at an early perceptual stage, and the attentional mechanisms for global and local processing may be different.     

DeepMHADTA: Prediction of Drug-Target Binding Affinity Using Multi-Head Self-Attention and Convolutional Neural Network

Drug-target interactions provide insight into the drug-side effects and drug repositioning. However, wet-lab biochemical experiments are time-consuming and labor-intensive, and are insufficient to meet the pressing demand for drug research and development. With the rapid advancement of deep learning, computational methods are increasingly applied to screen drug-target interactions. Many methods consider this problem as a binary classification task (binding or not), but ignore the quantitative binding affinity. In this paper, we propose a new end-to-end deep learning method called DeepMHADTA, which uses the multi-head self-attention mechanism in a deep residual network to predict drug-target binding affinity. On two benchmark datasets, our method outperformed several current state-of-the-art methods in terms of multiple performance measures, including mean square error (MSE), consistency index (CI), rm2, and PR curve area (AUPR). The results demonstrated that our method achieved better performance in predicting the drug–target binding affinity.