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.     

Melatonin induces apoptosis of colorectal cancer cells through HDAC4 nuclear import mediated by CaMKII inactivation

Melatonin induces apoptosis in many different cancer cell lines, including colorectal cancer. However, the precise mechanisms involved remain largely unresolved. In this study, we provide evidence to reveal a new mechanism by which melatonin induces apoptosis of colorectal cancer LoVo cells. Melatonin at pharmacological concentrations significantly suppressed cell proliferation and induced apoptosis in a dose‐dependent manner. The observed apoptosis was accompanied by the melatonin‐induced dephosphorylation and nuclear import of histone deacetylase 4 (HDAC4). Pretreatment with a HDAC4‐specific siRNA effectively attenuated the melatonin‐induced apoptosis, indicating that nuclear localization of HDAC4 is required for melatonin‐induced apoptosis. Moreover, constitutively active Ca²⁺/calmodulin‐dependent protein kinase II alpha (CaMKIIα) abrogated the melatonin‐induced HDAC4 nuclear import and apoptosis of LoVo cells. Furthermore, melatonin decreased H3 acetylation on bcl‐2 promoter, leading to a reduction of bcl‐2 expression, whereas constitutively active CaMKIIα(T286D) or HDAC4‐specific siRNA abrogated the effect of melatonin. In conclusion, the present study provides evidence that melatonin‐induced apoptosis in colorectal cancer LoVo cells largely depends on the nuclear import of HDAC4 and subsequent H3 deacetylation via the inactivation of CaMKIIα.     

From the Cover: Communication consumes 35 times more energy than computation in the human cortex,but both costs are needed to predict synapse number

Darwinian evolution tends to produce energy-efficient outcomes. On the other hand, energy limits computation, be it neural and probabilistic or digital and logical. Taking a particular energy-efficient viewpoint, we define neural computation and make use of an energy-constrained computational function. This function can be optimized over a variable that is proportional to the number of synapses per neuron. This function also implies a specific distinction between adenosine triphosphate (ATP)-consuming processes, especially computation per se vs. the communication processes of action potentials and transmitter release. Thus, to apply this mathematical function requires an energy audit with a particular partitioning of energy consumption that differs from earlier work. The audit points out that, rather than the oft-quoted 20 W of glucose available to the human brain, the fraction partitioned to cortical computation is only 0.1 W of ATP [L. Sokoloff, Handb. Physiol. Sect. I Neurophysiol. 3, 1843–1864 (1960)] and [J. Sawada, D. S. Modha, “Synapse: Scalable energy-efficient neurosynaptic computing” in Application of Concurrency to System Design (ACSD) (2013), pp. 14–15]. On the other hand, long-distance communication costs are 35-fold greater, 3.5 W. Other findings include 1) a 108-fold discrepancy between biological and lowest possible values of a neuron’s computational efficiency and 2) two predictions of N, the number of synaptic transmissions needed to fire a neuron (2,500 vs. 2,000).

The purpose of the brain is to process information, but that leaves us with the problem of finding appropriate definitions of information processing. We assume that given enough time and given a sufficiently stable environment (e.g., the common internals of the mammalian brain), then Nature’s constructions approach an optimum. The problem is to find which function or combined set of functions is optimal when incorporating empirical values into these function(s). The initial example in neuroscience is ref. 1, which shows that information capacity is far from optimized, especially in comparison to the optimal information per joule which is in much closer agreement with empirical values. Whenever we find such an agreement between theory and experiment, we conclude that this optimization, or near optimization, is Nature’s perspective. Using this strategy, we and others seek quantified relationships with particular forms of information processing and require that these relationships are approximately optimal (1–7). At the level of a single neuron, a recent theoretical development identifies a potentially optimal computation (8). To apply this conjecture requires understanding certain neuronal energy expenditures. Here the focus is on the energy budget of the human cerebral cortex and its primary neurons. The energy audit here differs from the premier earlier work (9) in two ways: The brain considered here is human not rodent, and the audit here uses a partitioning motivated by the information-efficiency calculations rather than the classical partitions of cell biology and neuroscience (9). Importantly, our audit reveals greater energy use by communication than by computation. This observation in turn generates additional insights into the optimal synapse number. Specifically, the bits per joule optimized computation must provide sufficient bits per second to the axon and presynaptic mechanism to justify the great expense of timely communication. Simply put from the optimization perspective, we assume evolution would not build a costly communication system and then not supply it with appropriate bits per second to justify its costs. The bits per joule are optimized with respect to N, the number of synaptic activations per interpulse interval (IPI) for one neuron, where N happens to equal the number of synapses per neuron times the success rate of synaptic transmission (below).To measure computation, and to partition out its cost, requires a suitable definition at the single-neuron level. Rather than the generic definition “any signal transformation” (3) or the neural-like “converting a multivariate signal to a scalar signal,” we conjecture a more detailed definition (8). To move toward this definition, note two important brain functions: estimating what is present in the sensed world and predicting what will be present, including what will occur as the brain commands manipulations. Then, assume that such macroscopic inferences arise by combining single-neuron inferences. That is, conjecture a neuron performing microscopic estimation or prediction. Instead of sensing the world, a neuron’s sensing is merely its capacitive charging due to recently active synapses. Using this sampling of total accumulated charge over a particular elapsed time, a neuron implicitly estimates the value of its local latent variable, a variable defined by evolution and developmental construction (8). Applying an optimization perspective, which includes implicit Bayesian inference, a sufficient statistic, and maximum-likelihood unbiasedness, as well as energy costs (8), produces a quantified theory of single-neuron computation. This theory implies the optimal IPI probability distribution. Motivating IPI coding is this fact: The use of constant amplitude signaling, e.g., action potentials, implies that all information can only be in IPIs. Therefore, no code can outperform an IPI code, and it can equal an IPI code in bit rate only if it is one to one with an IPI code. In neuroscience, an equivalent to IPI codes is the instantaneous rate code where each message is IPI−1. In communication theory, a discrete form of IPI coding is called differential pulse position modulation (10); ref. 11 explicitly introduced a continuous form of this coding as a neuron communication hypothesis, and it receives further development in ref. 12.Results recall and further develop earlier work concerning a certain optimization that defines IPI probabilities (8). An energy audit is required to use these developments. Combining the theory with the audit leads to two outcomes: 1) The optimizing N serves as a consistency check on the audit and 2) future energy audits for individual cell types will predict N for that cell type, a test of the theory. Specialized approximations here that are not present in earlier work (9) include the assumptions that 1) all neurons of cortex are pyramidal neurons, 2) pyramidal neurons are the inputs to pyramidal neurons, 3) a neuron is under constant synaptic bombardment, and 4) a neuron’s capacitance must be charged 16 mV from reset potential to threshold to fire.Following the audit, the reader is given a perspective that may be obvious to some, but it is rarely discussed and seemingly contradicts the engineering literature (but see ref. 6). In particular, a neuron is an incredibly inefficient computational device in comparison to an idealized physical analog. It is not just a few bits per joule away from optimal predicted by the Landauer limit, but off by a huge amount, a factor of 108. The theory here resolves the efficiency issue using a modified optimization perspective. Activity-dependent communication and synaptic modification costs force upward optimal computational costs. In turn, the bit value of the computational energy expenditure is constrained to a central limit like the result: Every doubling of N can produce no more than 0.5 bits. In addition to 1) explaining the 108 excessive energy use, other results here include 2) identifying the largest “noise” source limiting computation, which is the signal itself, and 3) partitioning the relevant costs, which may help engineers redirect focus toward computation and communication costs rather than the 20-W total brain consumption as their design goal.     

白藜芦醇联合顺铂对神经胶质瘤细胞的作用*

目的： 探讨白藜芦醇联合顺铂对神经胶质瘤细胞C6 的作用。方法：不同浓度的白藜芦醇与顺铂单独联合 作用于神经胶质瘤细胞C6，24、48 h 和72 h 后，CCK8法检测增殖，并选出合适浓度进行后续试验；不同浓度的 药物作用于细胞24 h 后，吖啶橙法观察细胞形态变化、流式细胞仪检测细胞凋亡、细胞周期和免疫印迹检测蛋白 Bax、Bcl-2 和p-Erk1/2 变化。结果：白藜芦醇与顺铂能协同抑制神经胶质瘤细胞C6 的增殖。联合用药后细胞周 期抑制在S 期。免疫印迹结果显示凋亡蛋白Bax 的表达量增加，而凋亡抑制蛋白Bcl-2 的表达量减少，细胞外调 节蛋白激酶p-Erk1/2 的表达量减少。结论：白藜芦醇与顺铂联合对神经胶质瘤细胞具有相互增敏作用，能够协同 抑制细胞增殖，并通过Ras-Raf-MEK-Erk 信号通路促进其凋亡。     

妊娠期糖尿病中胎盘外泌体对滋养细胞增殖、细胞周期及凋亡的影响*

目的：探讨妊娠期糖尿病（GDM）中胎盘外泌体对滋养细胞增殖、细胞周期及细胞凋亡的影响。方法： 选取2018 年3 月至2019 年4 月间重庆市第七人民医院50 例诊断为GDM患者（GDM组），另选取50 例正常孕产 妇作为对照组。分离纯化GDM组和对照组孕产妇外周血血浆中的胎盘外泌体，通过透射电镜观察外泌体的形 态，纳米粒径分析检测外泌体的直径，免疫印迹检测外泌体标志性蛋白CD63、TSG101 及胎盘标志性分子胎盘 碱性磷酸酶（PLAP）的表达。PKH67染色后荧光共聚焦显微镜观察体外培养滋养细胞系对外泌体的摄取情况； 应用MTT实验检测外泌体对滋养细胞增殖能力的影响，流式细胞术检测外泌体对滋养细胞周期的影响，Annexin V-FITC/PI 双染色结合流式细胞术检测外泌体对滋养细胞凋亡的影响。结果：成功从外周血中分离获得了胎盘外 泌体，形态呈典型的杯状或双凹状，直径为40 ～ 120 nm，CD63、TSG101、PLAP 表达呈阳性；与对照组相比， GDM组胎盘外泌体以浓度依赖性促进滋养细胞的增殖、细胞周期进展，并抑制滋养细胞的凋亡。结论：GDM中 胎盘外泌体可能通过促进滋养细胞的增殖、细胞周期进展，抑制滋养细胞凋亡等参与GDM的发生和发展。     

Adaptive dynamic surface control using neural networks for hypersonic flight vehicle with input nonlinearities

This study proposes an effective adaptive dynamic surface control (DSC) method based on the radial basis function neural networks and the auxiliary system for hypersonic flight vehicle (HFV) systems in the presence of system uncertainties, external disturbances, and state variable and control input constraints. Firstly, to enhance the robustness of the system, the neural network is combined with the robust term to deal with the uncertainties and external disturbances of the system. Secondly, to prevent the deterioration of the dynamic performance of the system due to the over-adaptation of the neural networks and the robust terms caused by the state and control input constraints, the auxiliary system is added at each step in the DSC design to adjust the dynamic process of the reference signal and virtual control. Furthermore, the variable structure control is used to solve the problem of dead zone in the control input. Using the Lyapunov analysis method, all signals of the closed-loop system are semi-globally uniformly ultimate bounded. The simulation results illustrate the effectiveness of the proposed control scheme for the HFVs.     

The effect of painful laser stimuli on EEG gamma-band activity in migraine patients and healthy controls

ObjectiveGamma-band oscillations (GBOs) induced by nociceptive stimuli were compared between migraine patients and controls in order to further characterize interictal pain processing in the brain of migraineurs. GBOs were related to subjective pain intensity, years of migraine history and migraine attack frequency and the sources of GBOs were investigated.MethodsTwenty-three migraine patients without aura and 23 controls received a series of laser stimulations on their right forehead and right hand while recording electroencephalographic data (61 electrodes). After each series they indicated the perceived pain. A multitaper time-frequency method was used on artifact-cleaned scalp data and frequency domain beamforming was used to localize the GBOs.ResultsIn both groups we observed increases in GBOs around central electrodes, which were not significantly different between groups. The central GBOs were positively associated with the subjective pain ratings in the control group, in accordance with previous studies, but not in the migraine group. Increases in gamma power were observed in the midcingulate cortex.ConclusionsNo evidence was found that GBOs differ between interictal migraine and controls nor that central GBOs represent a neurophysiological correlate of subjective pain in migraine.SignificanceWe shed light on observations of GBOs during pain processing in interictal migraine.