Transition from regular to complex behaviour in a discrete deterministic asymmetric neural network model

We study the long time behaviour of the transient before the collapse on the periodic attractors of a discrete deterministic asymmetric neural networks model. The system has a finite number of possible states so it is not possible to use the term chaos in the usual sense of sensitive dependence on the initial condition. Nevertheless, at varying the asymmetry parameter, $k$, one observes a transition from ordered motion (i.e. short transients and short periods on the attractors) to a ``complex'' temporal behaviour. This transition takes place for the same value $k_{\rm c}$ at which one has a change for the mean transient length from a power law in the size of the system ($N$) to an exponential law in $N$. The ``complex'' behaviour during the transient shows strong analogies with the chaotic behaviour: decay of temporal correlations, positive Shannon entropy, non-constant Renyi entropies of different orders. Moreover the transition is very similar to that one for the intermittent transition in chaotic systems: scaling law for the Shannon entropy and strong fluctuations of the ``effective Shannon entropy'' along the transient, for $k > k_{\rm c}$.Comment: 18 pages + 6 figures, TeX dialect: Plain TeX + IOP macros (included

Relaxation, closing probabilities and transition from oscillatory to chaotic attractors in asymmetric neural networks

Attractors in asymmetric neural networks with deterministic parallel dynamics were shown to present a "chaotic" regime at symmetry eta < 0.5, where the average length of the cycles increases exponentially with system size, and an oscillatory regime at high symmetry, where the typical length of the cycles is 2. We show, both with analytic arguments and numerically, that there is a sharp transition, at a critical symmetry \e_c=0.33, between a phase where the typical cycles have length 2 and basins of attraction of vanishing weight and a phase where the typical cycles are exponentially long with system size, and the weights of their attraction basins are distributed as in a Random Map with reversal symmetry. The time-scale after which cycles are reached grows exponentially with system size $N$, and the exponent vanishes in the symmetric limit, where $T\propto N^{2/3}$. The transition can be related to the dynamics of the infinite system (where cycles are never reached), using the closing probabilities as a tool. We also study the relaxation of the function $E(t)=-1/N\sum_i |h_i(t)|$, where $h_i$ is the local field experienced by the neuron $i$. In the symmetric system, it plays the role of a Ljapunov function which drives the system towards its minima through steepest descent. This interpretation survives, even if only on the average, also for small asymmetry. This acts like an effective temperature: the larger is the asymmetry, the faster is the relaxation of $E$, and the higher is the asymptotic value reached. $E$ reachs very deep minima in the fixed points of the dynamics, which are reached with vanishing probability, and attains a larger value on the typical attractors, which are cycles of length 2.Comment: 24 pages, 9 figures, accepted on Journal of Physics A: Math. Ge

The challenges of containing SARS-CoV-2 via test-trace-and-isolate

Without a cure, vaccine, or proven long-term immunity against SARS-CoV-2, test-trace-and-isolate (TTI) strategies present a promising tool to contain its spread. For any TTI strategy, however, mitigation is challenged by pre- and asymptomatic transmission, TTI-avoiders, and undetected spreaders, who strongly contribute to hidden infection chains. Here, we studied a semi-analytical model and identified two tipping points between controlled and uncontrolled spread: (1) the behavior-driven reproduction number of the hidden chains becomes too large to be compensated by the TTI capabilities, and (2) the number of new infections exceeds the tracing capacity. Both trigger a self-accelerating spread. We investigated how these tipping points depend on challenges like limited cooperation, missing contacts, and imperfect isolation. Our model results suggest that TTI alone is insufficient to contain an otherwise unhindered spread of SARS-CoV-2, implying that complementary measures like social distancing and improved hygiene remain necessary

Exploring the IL-21–STAT3 Axis as Therapeutic Target for Sézary Syndrome

Sézary syndrome is an aggressive cutaneous T-cell lymphoma. The malignant cells (Sézary cells) are present in skin, lymph nodes, and blood, and express constitutively activated signal transducer and activator of transcription (STAT)3. STAT3 can be activated by IL-21 in vitro and the IL-21 gene itself is a STAT3 target gene, thereby creating an autocrine positive feedback loop that might serve as a therapeutic target. Sézary cells underwent apoptosis when incubated with Stattic, a selective STAT3 inhibitor. STAT3 activation in Sézary cells did not affect expression of the supposed anti-apoptotic STAT3 target genes BCL2, BCL-xL, and SURVIVIN, whereas expression of (proto)oncogenes miR-21, TWIST1, MYC, and PIM1 was significantly increased. CD3/CD28-mediated activation of Sézary cells induced IL-21 expression, accompanied by STAT3 activation and increased proliferation. Blocking IL-21 in CD3/CD28-activated cells had no effects, whereas Stattic abrogated IL-21 expression and cell proliferation. Thus, specific inhibition of STAT3 is highly efficient in the induction of apoptosis of Sézary cells, likely mediated via the regulation of (proto)oncogenes. In contrast, blocking IL-21 alone seems insufficient to affect STAT3 activation, cell proliferation, or apoptosis. These data provide further insights into the pathogenic role of STAT3 in Sézary syndrome and strengthen the notion that STAT3 represents a promising therapeutic target in this disease

Transcriptional and Post-Transcriptional Mechanisms for Oncogenic Overexpression of Ether À Go-Go K+ Channel

The human ether-à-go-go-1 (h-eag1) K+ channel is expressed in a variety of cell lines derived from human malignant tumors and in clinical samples of several different cancers, but is otherwise absent in normal tissues. It was found to be necessary for cell cycle progression and tumorigenesis. Specific inhibition of h-eag1 expression leads to inhibition of tumor cell proliferation. We report here that h-eag1 expression is controlled by the p53−miR-34−E2F1 pathway through a negative feed-forward mechanism. We first established E2F1 as a transactivator of h-eag1 gene through characterizing its promoter region. We then revealed that miR-34, a known transcriptional target of p53, is an important negative regulator of h-eag1 through dual mechanisms by directly repressing h-eag1 at the post-transcriptional level and indirectly silencing h-eag1 at the transcriptional level via repressing E2F1. There is a strong inverse relationship between the expression levels of miR-34 and h-eag1 protein. H-eag1antisense antagonized the growth-stimulating effects and the upregulation of h-eag1 expression in SHSY5Y cells, induced by knockdown of miR-34, E2F1 overexpression, or inhibition of p53 activity. Therefore, p53 negatively regulates h-eag1 expression by a negative feed-forward mechanism through the p53−miR-34−E2F1 pathway. Inactivation of p53 activity, as is the case in many cancers, can thus cause oncogenic overexpression of h-eag1 by relieving the negative feed-forward regulation. These findings not only help us understand the molecular mechanisms for oncogenic overexpression of h-eag1 in tumorigenesis but also uncover the cell-cycle regulation through the p53−miR-34−E2F1−h-eag1 pathway. Moreover, these findings place h-eag1 in the p53−miR-34−E2F1−h-eag1 pathway with h-eag as a terminal effecter component and with miR-34 (and E2F1) as a linker between p53 and h-eag1. Our study therefore fills the gap between p53 pathway and its cellular function mediated by h-eag1

Adaptive Honeypot Engagement through Reinforcement Learning of Semi-Markov Decision Processes

A honeynet is a promising active cyber defense mechanism. It reveals the fundamental Indicators of Compromise (IoCs) by luring attackers to conduct adversarial behaviors in a controlled and monitored environment. The active interaction at the honeynet brings a high reward but also introduces high implementation costs and risks of adversarial honeynet exploitation. In this work, we apply infinite-horizon Semi-Markov Decision Process (SMDP) to characterize a stochastic transition and sojourn time of attackers in the honeynet and quantify the reward-risk trade-off. In particular, we design adaptive long-term engagement policies shown to be risk-averse, cost-effective, and time-efficient. Numerical results have demonstrated that our adaptive engagement policies can quickly attract attackers to the target honeypot and engage them for a sufficiently long period to obtain worthy threat information. Meanwhile, the penetration probability is kept at a low level. The results show that the expected utility is robust against attackers of a large range of persistence and intelligence. Finally, we apply reinforcement learning to the SMDP to solve the curse of modeling. Under a prudent choice of the learning rate and exploration policy, we achieve a quick and robust convergence of the optimal policy and value.Comment: The presentation can be found at https://youtu.be/GPKT3uJtXqk. arXiv admin note: text overlap with arXiv:1907.0139

Hairpin structures formed by alpha satellite DNA of human centromeres are cleaved by human topoisomerase IIα

Although centromere function has been conserved through evolution, apparently no interspecies consensus DNA sequence exists. Instead, centromere DNA may be interconnected through the formation of certain DNA structures creating topological binding sites for centromeric proteins. DNA topoisomerase II is a protein, which is located at centromeres, and enzymatic topoisomerase II activity correlates with centromere activity in human cells. It is therefore possible that topoisomerase II recognizes and interacts with the alpha satellite DNA of human centromeres through an interaction with potential DNA structures formed solely at active centromeres. In the present study, human topoisomerase IIα-mediated cleavage at centromeric DNA sequences was examined in vitro. The investigation has revealed that the enzyme recognizes and cleaves a specific hairpin structure formed by alpha satellite DNA. The topoisomerase introduces a single-stranded break at the hairpin loop in a reaction, where DNA ligation is partly uncoupled from the cleavage reaction. A mutational analysis has revealed, which features of the hairpin are required for topoisomerease IIα-mediated cleavage. Based on this a model is discussed, where topoisomerase II interacts with two hairpins as a mediator of centromere cohesion

Micro-computed tomography and histology to explore internal morphology in decapod larvae

Traditionally, the internal morphology of crustacean larvae has been studied using destructive techniques such as dissection and microscopy. The present study combines advances in microcomputed tomography (micro-CT) and histology to study the internal morphology of decapod larvae, using the common spider crab (Maja brachydactyla Balss, 1922) as a model and resolving the individual limitations of these techniques. The synergy of micro-CT and histology allows the organs to be easily identified, revealing simultaneously the gross morphology (shape, size, and location) and histological organization (tissue arrangement and cell identification). Micro-CT shows mainly the exoskeleton, musculature, digestive and nervous systems, and secondarily the circulatory and respiratory systems, while histology distinguishes several cell types and confirms the organ identity. Micro-CT resolves a discrepancy in the literature regarding the nervous system of crab larvae. The major changes occur in the metamorphosis to the megalopa stage, specifically the formation of the gastric mill, the shortening of the abdominal nerve cord, the curving of the abdomen beneath the cephalothorax, and the development of functional pereiopods, pleopods, and lamellate gills. The combination of micro-CT and histology provides better results than either one alone.Financial support was provided by the Spanish Ministry of Economy and Competitiveness through the INIA project (grant number RTA2011-00004-00-00) to G.G. and a pre-doctoral fellowship to D.C. (FPI-INIA)

Rapid Internalization of the Oncogenic K+ Channel KV10.1

KV10.1 is a mammalian brain voltage-gated potassium channel whose ectopic expression outside of the brain has been proven relevant for tumor biology. Promotion of cancer cell proliferation by KV10.1 depends largely on ion flow, but some oncogenic properties remain in the absence of ion permeation. Additionally, KV10.1 surface populations are small compared to large intracellular pools. Control of protein turnover within cells is key to both cellular plasticity and homeostasis, and therefore we set out to analyze how endocytic trafficking participates in controlling KV10.1 intracellular distribution and life cycle. To follow plasma membrane KV10.1 selectively, we generated a modified channel of displaying an extracellular affinity tag for surface labeling by α-bungarotoxin. This modification only minimally affected KV10.1 electrophysiological properties. Using a combination of microscopy and biochemistry techniques, we show that KV10.1 is constitutively internalized involving at least two distinct pathways of endocytosis and mainly sorted to lysosomes. This occurs at a relatively fast rate. Simultaneously, recycling seems to contribute to maintain basal KV10.1 surface levels. Brief KV10.1 surface half-life and rapid lysosomal targeting is a relevant factor to be taken into account for potential drug delivery and targeting strategies directed against KV10.1 on tumor cells