直肠癌淋巴结转移的深度神经网络评判研究进展

正目前,临床上对于直肠癌常用的影像评估方法有MRI、螺旋CT、PET-CT、直肠腔内超声(ERUS)等。而MRI作为首选检查方式,对肿瘤位置、浸润深度、淋巴结转移、血管侵犯、环周切缘及周围器官侵犯等方面的评估均具有明显优势~([1-2])。通过MRI诊断淋巴结的方法通常是影像科医师逐层浏览每一幅图像,从中识别淋巴结的形状、界限及密度来判断,这种传统方式耗时较长且存在主观偏倚,导致     

Rapid Increase in Neural Conduction Time in the Adult Human Auditory Brainstem Following Sudden Unilateral Deafness

Individuals with sudden unilateral deafness offer a unique opportunity to study plasticity of the binaural auditory system in adult humans. Stimulation of the intact ear results in increased activity in the auditory cortex. However, there are no reports of changes at sub-cortical levels in humans. Therefore, the aim of the present study was to investigate changes in sub-cortical activity immediately before and after the onset of surgically induced unilateral deafness in adult humans. Click-evoked auditory brainstem responses (ABRs) to stimulation of the healthy ear were recorded from ten adults during the course of translabyrinthine surgery for the removal of a unilateral acoustic neuroma. This surgical technique always results in abrupt deafferentation of the affected ear. The results revealed a rapid (within minutes) reduction in latency of wave V (mean pre = 6.55 ms; mean post = 6.15 ms; p < 0.001). A latency reduction was also observed for wave III (mean pre = 4.40 ms; mean post = 4.13 ms; p < 0.001). These reductions in response latency are consistent with functional changes including disinhibition or/and more rapid intra-cellular signalling affecting binaurally sensitive neurons in the central auditory system. The results are highly relevant for improved understanding of putative physiological mechanisms underlying perceptual disorders such as tinnitus and hyperacusis.     

Non-viral transfer of BDNF and uPA stimulates peripheral nerve regeneration

Peripheral nerves connect brain and spinal cord with the extremities and inner organs, and nerves injury can lead the disability and social exclusion. Growth factors and other natural stimulators of regeneration processes look very promising as future medicines. In our study, we tested the influence of genetic constructions that contain genes of brain-derived neurotrophic factor and urokinase plasminogen activator on nerve's structure and function after traumatic and ischemic injuries. Injection of pVax1-hBDNF and pVax1-muPA after traumatic injury led to better restoration of nerve's structure and function compared to similar parameters of control group mice. In ischemic injury model pVax1-hBDNF and pVax1-muPA slowed and reduced the damage progression and stimulated nerve regeneration as well. However, the treatment with pVax1-muPA was less effective after the traumatic injury. As we chose a non-viral method of gene delivery during our study the optimal conditions of plasmid intramuscular delivery were also determined.     

A Multi-Scale DNN Algorithm for Nonlinear Elliptic Equations with Multiple Scales

Algorithms based on deep neural networks (DNNs) have attracted increasing attention from the scientific computing community. DNN based algorithms are easy to implement, natural for nonlinear problems, and have shown great potential to overcome the curse of dimensionality. In this work, we utilize the multi-scale DNN-based algorithm (MscaleDNN) proposed by Liu, Cai and Xu (2020) to solve multi-scale elliptic problems with possible nonlinearity, for example, the p-Laplacian problem. We improve the MscaleDNN algorithm by a smooth and localized activation function. Several numerical examples of multi-scale elliptic problems with separable or non-separable scales in low-dimensional and high-dimensional Euclidean spaces are used to demonstrate the effectiveness and accuracy of the MscaleDNN numerical scheme.     

Convergence and attractivity of memristor-based cellular neural networks with time delays

This paper presents theoretical results on the convergence and attractivity of memristor-based cellular neural networks (MCNNs) with time delays. Based on a realistic memristor model, an MCNN is modeled using a differential inclusion. The essential boundedness of its global solutions is proven. The state of MCNNs is further proven to be convergent to a critical-point set located in saturated region of the activation function, when the initial state locates in a saturated region. It is shown that the state convergence time period is finite and can be quantitatively estimated using given parameters. Furthermore, the positive invariance and attractivity of state in non-saturated regions are also proven. The simulation results of several numerical examples are provided to substantiate the results.