Dynamic Gardner cross-over in a simple glass.

The criticality of the jamming transition responsible for amorphous solidification has been theoretically linked to the marginal stability of a thermodynamic Gardner phase. While the critical exponents of jamming appear independent of the preparation history, the pertinence of Gardner physics far from equilibrium is an open question. To fill this gap, we numerically study the nonequilibrium dynamics of hard disks compressed toward the jamming transition using a broad variety of protocols. We show that dynamic signatures of Gardner physics can be disentangled from the aging relaxation dynamics. We thus define a generic dynamic Gardner cross-over regardless of the history. Our results show that the jamming transition is always accessed by exploring increasingly complex landscape, resulting in anomalous microscopic relaxation dynamics that remains to be understood theoretically.

An adaptive shortest-solution guided decimation approach to sparse high-dimensional linear regression.

High-dimensional linear regression model is the most popular statistical model for high-dimensional data, but it is quite a challenging task to achieve a sparse set of regression coefficients. In this paper, we propose a simple heuristic algorithm to construct sparse high-dimensional linear regression models, which is adapted from the shortest-solution guided decimation algorithm and is referred to as ASSD. This algorithm constructs the support of regression coefficients under the guidance of the shortest least-squares solution of the recursively decimated linear models, and it applies an early-stopping criterion and a second-stage thresholding procedure to refine this support. Our extensive numerical results demonstrate that ASSD outperforms LASSO, adaptive LASSO, vector approximate message passing, and two other representative greedy algorithms in solution accuracy and robustness. ASSD is especially suitable for linear regression problems with highly correlated measurement matrices encountered in real-world applications.

[Expression of TGF-ß in bladder neck contracture after transurethral enucleation and resection of the prostate].

OBJECTIVE: To explore the role of transforming growth factor-ß (TGF-ß) in bladder neck contracture (BNC) after transurethral enucleation and resection of the prostate (TUERP). METHODS: This study included 300 BPH patients undergoing TUERP, aged 51－89 (69.19 ± 8.43) years, with the prostate volume of 14.4－355.8 (63.18 ± 47.63) ml and preoperative IPSS of 15－35 (26.07 ± 5.9), QOL score of 3－6 (4.43 ± 0.67), PSA content of 0.17－23.16 (2.94 ± 3.77) ug/L, urinary leukocyte increase in 50 cases, post-void residual urine volume (PVR) of 0－440 (83.53 ± 86.85) ml, and maximum urinary flow rate (Qmax) of 2.3－14.5 (7.77 ± 3.47) ml/s. During TUERP, we collected the tissues from the bladder neck at 5 and 7 o'clock as well as the BPH tissue and the tissue from the residual prostate for HE staining, immunohistochemistry (the SP method) and examination of the infiltration degree of inflammatory cells and expressions of TGF-ß1 and TGF-ß3. During the 6－24 months follow-up, 6 of the patients were confirmed with BNC based on the clinical symptoms and the results of uroflowmetry and cystoscopy, and underwent transurethral bladder neck incision and detection of the expressions of TGF-ß1 and TGF-ß3 in the bladder neck tissue with BNC. RESULTS: The bladder neck tissue without BNC was mainly composed of smooth muscle and fibrous tissues with local infiltration of inflammatory cells, and the residual prostate tissue primarily comprised fibrous and muscle tissues, mixed with a little prostatic epithelial tissue. The bladder neck tissue with BNC, compared with that harvested during the initial TUERP, exhibited significantly increased expression of TGF-ß1 (ï¼»68.20 ± 10.88ï¼½% vs ï¼»36.14 ± 7.62ï¼½%, P < 0.05), decreased expression of TGF-ß3 (ï¼»8.55 ± 4.73ï¼½% vs ï¼»20.77 ± 8.69ï¼½%, P < 0.05), and enhanced infiltration of inflammatory cells (P < 0.05). The bladder neck tissue without BNC, in comparison with the BPH tissue, showed dramatically up-regulated expressions of TGF-ß1 (ï¼»27.05 ± 8.21ï¼½% vs ï¼»1.61 ± 0.69ï¼½%, P < 0.001) and TGF-ß3 (ï¼»14.09 ± 4.19ï¼½% vs ï¼»0.32 ± 0.11ï¼½%, P < 0.001) and increased infiltration of inflammatory cells (P < 0.05). CONCLUSIONS: After TUERP, the expression of TGF-ß1 is increased, that of TGF-ß3 decreased and the infiltration of inflammatory cells enhanced in the bladder neck tissue with BNC, which suggests that BNC may be related to the expression of TGF-ß and that BNC after TUERP could be prevented by regulating the expression of TGF-ß.

Controlled generation of self-sustained oscillations in complex artificial neural networks.

Spatially distinct, self-sustained oscillations in artificial neural networks are fundamental to information encoding, storage, and processing in these systems. Here, we develop a method to induce a large variety of self-sustained oscillatory patterns in artificial neural networks and a controlling strategy to switch between different patterns. The basic principle is that, given a complex network, one can find a set of nodes-the minimum feedback vertex set (mFVS), whose removal or inhibition will result in a tree-like network without any loop structure. Reintroducing a few or even a single mFVS node into the tree-like artificial neural network can recover one or a few of the loops and lead to self-sustained oscillation patterns based on these loops. Reactivating various mFVS nodes or their combinations can then generate a large number of distinct neuronal firing patterns with a broad distribution of the oscillation period. When the system is near a critical state, chaos can arise, providing a natural platform for pattern switching with remarkable flexibility. With mFVS guided control, complex networks of artificial neurons can thus be exploited as potential prototypes for local, analog type of processing paradigms.

Long-loop feedback vertex set and dismantling on bipartite factor graphs.

Network dismantling aims at breaking a network into disconnected components and attacking vertices that intersect with many loops has proven to be a most efficient strategy. Yet existing loop-focusing methods do not distinguish the short loops within densely connected local clusters (e.g., cliques) from the long loops connecting different clusters, leading to lowered performance of these algorithms. Here we propose a new solution framework for network dismantling based on a two-scale bipartite factor-graph representation, in which long loops are maintained while local dense clusters are simplistically represented as individual factor nodes. A mean-field spin-glass theory is developed for the corresponding long-loop feedback vertex set problem. The framework allows for the advancement of various existing dismantling algorithms; we developed the new version of two benchmark algorithms BPD (which uses the message-passing equations of the spin-glass theory as the solver) and CoreHD (which is fastest among well-performing algorithms). New solvers outperform current state-of-the-art algorithms by a considerable margin on networks of various sorts. Further improvement in dismantling performance is achievable by opting flexibly the choice of local clusters.

Circumventing spin-glass traps by microcanonical spontaneous symmetry breaking.

The planted p-spin interaction model is a paradigm of random-graph systems possessing both a ferromagnetic phase and a disordered phase with the latter splitting into many spin-glass states at low temperatures. Conventional simulated annealing dynamics is easily blocked by these low-energy spin-glass states. Here we demonstrate that actually this planted system is exponentially dominated by a microcanonical polarized phase at intermediate energy densities. There is a discontinuous microcanonical spontaneous symmetry breaking transition from the paramagnetic phase to the microcanonical polarized phase. This transition can serve as a mechanism to avoid all the spin-glass traps, and it is accelerated by the restart strategy of microcanonical random walk. We also propose an unsupervised learning problem on microcanonically sampled configurations for inferring the planted ground state.

Solving statistical mechanics on sparse graphs with feedback-set variational autoregressive networks.

We propose a method for solving statistical mechanics problems defined on sparse graphs. It extracts a small feedback vertex set (FVS) from the sparse graph, converting the sparse system to a much smaller system with many-body and dense interactions with an effective energy on every configuration of the FVS, then learns a variational distribution parametrized using neural networks to approximate the original Boltzmann distribution. The method is able to estimate free energy, compute observables, and generate unbiased samples via direct sampling without autocorrelation. Extensive experiments show that our approach is more accurate than existing approaches for sparse spin glasses. On random graphs and real-world networks, our approach significantly outperforms the standard methods for sparse systems, such as the belief-propagation algorithm; on structured sparse systems, such as two-dimensional lattices our approach is significantly faster and more accurate than recently proposed variational autoregressive networks using convolution neural networks.

Maximally flexible solutions of a random K-satisfiability formula.

Random K-satisfiability (K-SAT) is a paradigmatic model system for studying phase transitions in constraint satisfaction problems and for developing empirical algorithms. The statistical properties of the random K-SAT solution space have been extensively investigated, but most earlier efforts focused on solutions that are typical. Here we consider maximally flexible solutions which satisfy all the constraints only using the minimum number of variables. Such atypical solutions have high internal entropy because they contain a maximum number of null variables which are completely free to choose their states. Each maximally flexible solution indicates a dense region of the solution space. We estimate the maximum fraction of null variables by the replica-symmetric cavity method, and implement message-passing algorithms to construct maximally flexible solutions for single K-SAT instances.

Covering Problems and Core Percolations on Hypergraphs.

We introduce two generalizations of core percolation in graphs to hypergraphs, related to the minimum hyperedge cover problem and the minimum vertex cover problem on hypergraphs, respectively. We offer analytical solutions of these two core percolations for uncorrelated random hypergraphs whose vertex degree and hyperedge cardinality distributions are arbitrary but have nondiverging moments. We find that for several real-world hypergraphs their two cores tend to be much smaller than those of their null models, suggesting that covering problems in those real-world hypergraphs can actually be solved in polynomial time.

Kinked Entropy and Discontinuous Microcanonical Spontaneous Symmetry Breaking.

Spontaneous symmetry breaking (SSB) in statistical physics is a macroscopic collective phenomenon. For the paradigmatic Q-state Potts model it means a transition from the disordered color-symmetric phase to an ordered phase in which one color dominates. Existing mean field theories imply that SSB in the microcanonical statistical ensemble (with energy being the control parameter) should be a continuous process. Here we study microcanonical SSB on the random-graph Potts model and discover that the entropy is a kinked function of energy. This kink leads to a discontinuous phase transition at certain energy density value, characterized by a jump in the density of the dominant color and a jump in the microcanonical temperature. This discontinuous SSB in random graphs is confirmed by microcanonical Monte Carlo simulations, and it is also observed in bond-diluted finite-size lattice systems.

Core fucosylated glycan-dependent inhibitory effect of QSOX1-S on invasion and metastasis of hepatocellular carcinoma.

The goal of the present study was to identify glycoproteins associated with the postoperative relapse of hepatocellular carcinoma (HCC) and to investigate their potential role in HCC metastasis. A method for quantitating N-glycoproteome was used to screen for, and identify, recurrence-related N-linked glycoproteins from 100 serum samples taken from patients with early-stage HCC. The prognostic significance of candidate glycoproteins was then validated in 193 HCC tissues using immunohistochemical staining. Serum core fucosylated quiescin sulfhydryl oxidase 1 (cf-QSOX1) was identified as a leading prognostic glycoprotein that significantly correlated with HCC recurrence. Patients with high serum cf-QSOX1 levels had a significantly longer time to recurrence (TTR) as compared with those with low serum cf-QSOX1. As was seen with serum cf-QSOX1, QSOX1 in HCC tissues was further shown to be significantly associated with good patient outcome. Gain-functional and loss-functional analyses of QSOX1-S were performed in vitro and in vivo. QSOX1-S overexpression significantly increased in vitro apoptosis, but decreased the invasive capacity of HCC cells, and reduced lung metastasis in nude mice models bearing human HCC. Furthermore, overexpression of a mutant version of QSOX1-S, which had eliminated the core-fucosylated glycan at Asn-130, showed no demonstrable effect on invasion or metastasis of HCC cells. Our study suggests that serum cf-QSOX1-S and tumor QSOX1 levels are helpful for predicting recurrence in HCC patients, and its core-fucosylated glycan at Asn-130 is critical for the inhibitory effects of QSOX1-S on invasion and metastasis of HCC.

Controllability and maximum matchings of complex networks.

Previously, the controllability problem of a linear time-invariant dynamical system was mapped to the maximum matching (MM) problem on the bipartite representation of the underlying directed graph, and the sizes of MMs on random bipartite graphs were calculated analytically with the cavity method at zero temperature limit. Here we present an alternative theory to estimate MM sizes based on the core percolation theory and the perfect matching of cores. Our theory is much more simplified and easily interpreted, and can estimate MM sizes on random graphs with or without symmetry between out- and in-degree distributions. Our result helps to illuminate the fundamental connection between the controllability problem and the underlying structure of complex systems.

DCA for genome-wide epistasis analysis: the statistical genetics perspective.

Direct coupling analysis (DCA) is a now widely used method to leverage statistical information from many similar biological systems to draw meaningful conclusions on each system separately. DCA has been applied with great success to sequences of homologous proteins, and also more recently to whole-genome population-wide sequencing data. We here argue that the use of DCA on the genome scale is contingent on fundamental issues of population genetics. DCA can be expected to yield meaningful results when a population is in the quasi-linkage equilibrium (QLE) phase studied by Kimura and others, but not, for instance, in a phase of clonal competition. We discuss how the exponential (Potts model) distributions emerge in QLE, and compare couplings to correlations obtained in a study of about 3000 genomes of the human pathogen Streptococcus pneumoniae.

Entropy Inflection and Invisible Low-Energy States: Defensive Alliance Example.

Lower temperature leads to a higher probability of visiting low-energy states. This intuitive belief underlies most physics-inspired strategies for addressing hard optimization problems. For instance, the popular simulated annealing (SA) dynamics is expected to approach a ground state if the temperature is lowered appropriately. Here, we demonstrate that this belief is not always justified. Specifically, we employ the cavity method to analyze the minimum strong defensive alliance problem and discover a bifurcation in the solution space, induced by an inflection point in the entropy-energy profile. While easily accessible configurations are associated with the lower-free-energy branch, the low-energy configurations are associated with the higher-free-energy branch within the same temperature range. There is a discontinuous phase transition between the high-energy configurations and the ground states, which generally cannot be followed by SA. We introduce an energy-clamping strategy to obtain superior solutions by following the higher-free-energy branch, overcoming the limitations of SA.

[Finasteride inhibits microvascular density and VEGF expression in the seminal vesicle of rats].

OBJECTIVE: To investigate the effect of finasteride on the microvascular density (MVD) and the expression of the vascular endothelial growth factor (VEGF) in the seminal vesicle of rats. METHODS: Forty male SD rats were randomly and equally divided into groups A, B, C and D, those in groups A and B fed with normal saline as the control and those in C and D with finasteride at 40 mg per kg of the body weight per day, A and C for 14 days and B and D for 28 days. Then the seminal vesicles of the animals were harvested for HE staining, measurement of MVD, determination of the expressions of CD34 and VEGF by immunohistochemistry, and observation of histomorphological changes in the seminal vesicle. RESULTS: The expressions of CD34 in groups C and D were decreased by 6.7% and 15.8% as compared with those in A and B (P<0.01), and that in group D decreased by 9.3% in comparison with that in C (P<0.01). The expression indexes of VEGF in groups C and D were decreased by 6.9% and 14.1% as compared with those in A and B (P<0.01), and that in group D decreased by 9.0% in comparison with that in C (P<0.01). CONCLUSIONS: Finasteride can inhibit the expression of VEGF in the seminal vesicle tissue of the rat and hence suppress the angiogenesis of microvessels of the seminal vesicle.

Co-emergence of multi-scale cortical activities of irregular firing, oscillations and avalanches achieves cost-efficient information capacity.

The brain is highly energy consuming, therefore is under strong selective pressure to achieve cost-efficiency in both cortical connectivities and activities. However, cost-efficiency as a design principle for cortical activities has been rarely studied. Especially it is not clear how cost-efficiency is related to ubiquitously observed multi-scale properties: irregular firing, oscillations and neuronal avalanches. Here we demonstrate that these prominent properties can be simultaneously observed in a generic, biologically plausible neural circuit model that captures excitation-inhibition balance and realistic dynamics of synaptic conductance. Their co-emergence achieves minimal energy cost as well as maximal energy efficiency on information capacity, when neuronal firing are coordinated and shaped by moderate synchrony to reduce otherwise redundant spikes, and the dynamical clusterings are maintained in the form of neuronal avalanches. Such cost-efficient neural dynamics can be employed as a foundation for further efficient information processing under energy constraint.

Behavioural effect of low-dose BPA on male zebrafish: Tuning of male mating competition and female mating preference during courtship process.

The ubiquity of environmental pollution by endocrine disrupting chemicals (EDCs) such as bisphenol A (BPA) is progressively considered as a major threat to aquatic ecosystems worldwide. Numerous toxicological studies have proved that BPA are hazardous to aquatic environment, along with alterations in the development and physiology of aquatic vertebrates. However, generally, there is a paucity in knowledge of behavioural and physiological effects of BPA with low concentration, for example, 0.22 nM (50 ng/L) and 2.2 nM (500 ng/L). Here we show that treatment of adult male zebrafish (Danio rerio) with 7 weeks low-dose (0.22 nM-2.2 nM) BPA, resulted in alteration in histological structure of testis tissue and abnormality in expression levels of genes involved in testicular steroidogenesis. Furthermore, low-dose BPA treatment decreased the male locomotion during courtship; and was associated with less courtship behaviours to female but more aggressive behaviours to mating competitor. Interestingly, during the courtship test, we observed that female preferred control male to male under low-dose BPA exposure. Subsequently, we found that the ability of female to chose optimal mating male through socially mutual interaction and dynamics of male zebrafish, which was based on visual discrimination. In sum, our results shed light on the potential behavioural and physiological effect of low-dose BPA exposure on courtship behaviours of zebrafish, which could exert profound consequences on natural zebrafish populations.

Impact of CYP2C19 Variants on Clinical Efficacy of Clopidogrel and 1-Year Clinical Outcomes in Coronary Heart Patients Undergoing Percutaneous Coronary Intervention.

The impact of pharmacogenetic variants of cytochrome P450 2C19 (CYP2C19) on clopidogrel-mediated effects on platelet inhibition, inflammatory response and endothelial function, as well as risk of major adverse cardiovascular events (MACE), in coronary heart patients undergoing percutaneous coronary intervention (PCI) was investigated. To this end, we assessed the residual platelet aggregation rate (RPA), maximal aggregation rate (MAR) and plasma levels of sCD40L, sP-selectin, MMP-9, sVCAM-1 and sE-selectin after 24 h of PCI in 559 patients treated with clopidogrel and followed up for 1 year for evidence of MACE. CYP2C19*2 and *3 variants were identified using a clopidogrel-sensitive gene detection kit. Our results showed higher RPA and MAR as well as increased sE-selectin, sCD40L, sP-selectin, MMP-9, and sVCAM-1 levels in CYP2C19 intermediate metabolizer (IM, CYP2C19*1/*2, or *1/*3), poor metabolizer (PM, CYP2C19*2/*2, *2/*3, or *3/*3) and combined IM+PM groups, relative to those in extensive metabolizers (EM, CYP2C19*1/*1). In total, 519 patients completed 1 year of follow-up, among which 69 (13.3%) experienced MACE. The risk of MACE in CYP2C19 IM+PM patients was 2.664 times higher than that in CYP2C19 EM patients (OR = 2.664 (1.397-5.193), P = 0.004). The data suggest that CYP2C19*2 and *3 variants modulate the drug efficacy of clopidogrel in coronary heart patients undergoing PCI and further enhance the risk of MACE. Accordingly, CYP2C19 pharmacogenetic profiling may be beneficial for coronary heart patients undergoing PCI to predict the efficacy of treatment with clopidogrel. We propose that IM and PM patients should benefit from treatment with higher clopidogrel doses to improve efficacy and reduce the incidence of MACE.

Fast and simple decycling and dismantling of networks.

Decycling and dismantling of complex networks are underlying many important applications in network science. Recently these two closely related problems were tackled by several heuristic algorithms, simple and considerably sub-optimal, on the one hand, and involved and accurate message-passing ones that evaluate single-node marginal probabilities, on the other hand. In this paper we propose a simple and extremely fast algorithm, CoreHD, which recursively removes nodes of the highest degree from the 2-core of the network. CoreHD performs much better than all existing simple algorithms. When applied on real-world networks, it achieves equally good solutions as those obtained by the state-of-art iterative message-passing algorithms at greatly reduced computational cost, suggesting that CoreHD should be the algorithm of choice for many practical purposes.

Spin-glass phase transitions and minimum energy of the random feedback vertex set problem.

A feedback vertex set (FVS) of an undirected graph contains vertices from every cycle of this graph. Constructing a FVS of sufficiently small cardinality is very difficult in the worst cases, but for random graphs this problem can be efficiently solved by converting it into an appropriate spin-glass model [H.-J. Zhou, Eur. Phys. J. B 86, 455 (2013)EPJBFY1434-602810.1140/epjb/e2013-40690-1]. In the present work we study the spin-glass phase transitions and the minimum energy density of the random FVS problem by the first-step replica-symmetry-breaking (1RSB) mean-field theory. For both regular random graphs and Erdös-Rényi graphs, we determine the inverse temperature ß_{l} at which the replica-symmetric mean-field theory loses its local stability, the inverse temperature ß_{d} of the dynamical (clustering) phase transition, and the inverse temperature ß_{s} of the static (condensation) phase transition. These critical inverse temperatures all change with the mean vertex degree in a nonmonotonic way, and ß_{d} is distinct from ß_{s} for regular random graphs of vertex degrees K>60, while ß_{d} are identical to ß_{s} for Erdös-Rényi graphs at least up to mean vertex degree c=512. We then derive the zero-temperature limit of the 1RSB theory and use it to compute the minimum FVS cardinality.