Nonparametric Learning of Two-Layer ReLU Residual Units

We describe an algorithm that learns two-layer residual units with rectified linear unit (ReLU) activation: suppose the input $\mathbf{x}$ is from a distribution with support space $\mathbb{R}^d$ and the ground-truth generative model is such a residual unit, given by $$\mathbf{y}= \boldsymbol{B}^\ast\left[\left(\boldsymbol{A}^\ast\mathbf{x}\right)^+ + \mathbf{x}\right]\text{,}$$ where ground-truth network parameters $\boldsymbol{A}^\ast \in \mathbb{R}^{d\times d}$ is a nonnegative full-rank matrix and $\boldsymbol{B}^\ast \in \mathbb{R}^{m\times d}$ is full-rank with $m \geq d$ and for $\mathbf{c} \in \mathbb{R}^d$, $[\mathbf{c}^{+}]_i = \max\{0, c_i\}$. We design layer-wise objectives as functionals whose analytic minimizers express the exact ground-truth network in terms of its parameters and nonlinearities. Following this objective landscape, learning residual units from finite samples can be formulated using convex optimization of a nonparametric function: for each layer, we first formulate the corresponding empirical risk minimization (ERM) as a positive semi-definite quadratic program (QP), then we show the solution space of the QP can be equivalently determined by a set of linear inequalities, which can then be efficiently solved by linear programming (LP). We further prove the statistical strong consistency of our algorithm, and demonstrate the robustness and sample efficiency of our algorithm by experiments

Sustained proliferation in cancer: mechanisms and novel therapeutic targets

Proliferation is an important part of cancer development and progression. This is manifest by altered expression and/or activity of cell cycle related proteins. Constitutive activation of many signal transduction pathways also stimulates cell growth. Early steps in tumor development are associated with a fibrogenic response and the development of a hypoxic environment which favors the survival and proliferation of cancer stem cells. Part of the survival strategy of cancer stem cells may manifested by alterations in cell metabolism. Once tumors appear, growth and metastasis may be supported by overproduction of appropriate hormones (in hormonally dependent cancers), by promoting angiogenesis, by undergoing epithelial to mesenchymal transition, by triggering autophagy, and by taking cues from surrounding stromal cells. A number of natural compounds (e.g., curcumin, resveratrol, indole-3-carbinol, brassinin, sulforaphane, epigallocatechin-3-gallate, genistein, ellagitannins, lycopene and quercetin) have been found to inhibit one or more pathways that contribute to proliferation (e.g., hypoxia inducible factor 1, nuclear factor kappa B, phosphoinositide 3 kinase/Akt, insulin-like growth factor receptor 1, Wnt, cell cycle associated proteins, as well as androgen and estrogen receptor signaling). These data, in combination with bioinformatics analyses, will be very important for identifying signaling pathways and molecular targets that may provide early diagnostic markers and/or critical targets for the development of new drugs or drug combinations that block tumor formation and progression

Metal Ion-dependent Heavy Chain Transfer Activity of TSG-6 Mediates Assembly of the Cumulus-Oocyte Matrix

The matrix polysaccharide hyaluronan (HA) has a critical role in the expansion of the cumulus cell-oocyte complex (COC), a process that is necessary for ovulation and fertilization in most mammals. Hyaluronan is organized into a cross-linked network by the cooperative action of three proteins, inter-α-inhibitor (IαI), pentraxin-3, and TNF-stimulated gene-6 (TSG-6), driving the expansion of the COC and providing the cumulus matrix with its required viscoelastic properties. Although it is known that matrix stabilization involves the TSG-6-mediated transfer of IαI heavy chains (HCs) onto hyaluronan (to form covalent HC·HA complexes that are cross-linked by pentraxin-3) and that this occurs via the formation of covalent HC·TSG-6 intermediates, the underlying molecular mechanisms are not well understood. Here, we have determined the tertiary structure of the CUB module from human TSG-6, identifying a calcium ion-binding site and chelating glutamic acid residue that mediate the formation of HC·TSG-6. This occurs via an initial metal ion-dependent, non-covalent, interaction between TSG-6 and HCs that also requires the presence of an HC-associated magnesium ion. In addition, we have found that the well characterized hyaluronan-binding site in the TSG-6 Link module is not used for recognition during transfer of HCs onto HA. Analysis of TSG-6 mutants (with impaired transferase and/or hyaluronan-binding functions) revealed that although the TSG-6-mediated formation of HC·HA complexes is essential for the expansion of mouse COCs in vitro, the hyaluronan-binding function of TSG-6 does not play a major role in the stabilization of the murine cumulus matrix

Respiratory Syncytial Virus Matrix Protein Induces Lung Epithelial Cell Cycle Arrest through a p53 Dependent Pathway

Respiratory syncytial virus (RSV) is the major cause of viral respiratory infections in children. Our previous study showed that the RSV infection induced lung epithelial cell cycle arrest, which enhanced virus replication. To address the mechanism of RSV-induced cell cycle arrest, we examined the contribution of RSV-matrix (RSV-M) protein. In this report, we show that in both the A549 cell line and primary human bronchial epithelial (PHBE) cells, transfection with RSV-M protein caused the cells to proliferate at a slower rate than in control cells. The cell cycle analysis showed that RSV-M protein induced G1 phase arrest in A549 cells, and G1 and G2/M phase arrest in PHBE cells. Interestingly, RSV-M expression induced p53 and p21 accumulation and decreased phosphorylation of retinoblastoma protein (Rb). Further, induction of cell cycle arrest by RSV-M was not observed in a p53-deficient epithelial cell line (H1299). However, cell cycle arrest was restored after transfection of p53 cDNA into H1299 cells. Taken together, these results indicate that RSV-M protein regulates lung epithelial cell cycle through a p53-dependent pathway, which enhances RSV replication

Telomerase gene therapy ameliorates the effects of neurodegeneration associated to short telomeres in mice

Neurodegenerative diseases associated with old age such as Alzheimer's disease present major problems for society, and they currently have no cure. The telomere protective caps at the ends of chromosomes shorten with age, and when they become critically short, they can induce a persistent DNA damage response at chromosome ends, triggering secondary cellular responses such as cell death and cellular senescence. Mice and humans with very short telomeres owing to telomerase deficiencies have an earlier onset of pathologies associated with loss of the regenerative capacity of tissues. However, the effects of short telomeres in very low proliferative tissues such as the brain have not been thoroughly investigated. Here, we describe a mouse model of neurodegeneration owing to presence of short telomeres in the brain as the consequence of telomerase deficiency. Interestingly, we find similar signs of neurodegeneration in very old mice as the consequence of physiological mouse aging. Next, we demonstrate that delivery of telomerase gene therapy to the brain of these mice results in amelioration of some of these neurodegeneration phenotypes. These findings suggest that short telomeres contribute to neurodegeneration diseases with aging and that telomerase activation may have a therapeutic value in these diseases.We would like to thank the CNIO (Centro Nacional de Investigaciones Oncológicas or “Spanish National Cancer Centre” in Madrid Spain) confocal microscope core, histopathology core, particularly Alba de Martino and Patricia González García, molecular imaging core, and animal facility for all of their help and assistance. We also thank Manuel Valiente for suggestions and advice. The viral vectors were produced by the lab of Fàtima Bosc. Fàtima Bosch is an ICREA Academia recipient,Generalitat de Catalunya, SpainS

RHPS4 G-quadruplex ligand induces anti-proliferative effects in brain tumor cells

Background Telomeric 3’ overhangs can fold into a four-stranded DNA structure termed G-quadruplex (G4), a formation which inhibits telomerase. As telomerase activation is crucial for telomere maintenance in most cancer cells, several classes of G4 ligands have been designed to directly disrupt telomeric structure. Methods We exposed brain tumor cells to the G4 ligand 3,11-difluoro-6,8,13-trimethyl-8H-quino[4,3,2-kl]acridinium methosulfate (RHPS4) and investigated proliferation, cell cycle dynamics, telomere length, telomerase activity and activated c-Myc levels. Results Although all cell lines tested were sensitive to RHPS4, PFSK-1 central nervous system primitive neuroectodermal cells, DAOY medulloblastoma cells and U87 glioblastoma cells exhibited up to 30-fold increased sensitivity compared to KNS42 glioblastoma, C6 glioma and Res196 ependymoma cells. An increased proportion of S-phase cells were observed in medulloblastoma and high grade glioma cells whilst CNS PNET cells showed an increased proportion of G1-phase cells. RHPS4-induced phenotypes were concomitant with telomerase inhibition, manifested in a telomere length-independent manner and not associated with activated c-Myc levels. However, anti-proliferative effects were also observed in normal neural/endothelial cells in vitro and ex vivo. Conclusion This study warrants in vivo validation of RHPS4 and alternative G4 ligands as potential anti-cancer agents for brain tumors but highlights the consideration of dose-limiting tissue toxicities

Generation in vivo of peptide-specific cytotoxic T cells and presence of regulatory T cells during vaccination with hTERT (class I and II) peptide-pulsed DCs

Optimal techniques for DC generation for immunotherapy in cancer are yet to be established. Study aims were to evaluate: (i) DC activation/maturation milieu (TNF-α +/- IFN-α) and its effects on CD8+ hTERT-specific T cell responses to class I epitopes (p540 or p865), (ii) CD8+ hTERT-specific T cell responses elicited by vaccination with class I alone or both class I and II epitope (p766 and p672)-pulsed DCs, prepared without IFN-α, (iii) association between circulating T regulatory cells (Tregs) and clinical responses

Ageing, adipose tissue, fatty acids and inflammation

A common feature of ageing is the alteration in tissue distribution and composition, with a shift in fat away from lower body and subcutaneous depots to visceral and ectopic sites. Redistribution of adipose tissue towards an ectopic site can have dramatic effects on metabolic function. In skeletal muscle, increased ectopic adiposity is linked to insulin resistance through lipid mediators such as ceramide or DAG, inhibiting the insulin receptor signalling pathway. Additionally, the risk of developing cardiovascular disease is increased with elevated visceral adipose distribution. In ageing, adipose tissue becomes dysfunctional, with the pathway of differentiation of preadipocytes to mature adipocytes becoming impaired; this results in dysfunctional adipocytes less able to store fat and subsequent fat redistribution to ectopic sites. Low grade systemic inflammation is commonly observed in ageing, and may drive the adipose tissue dysfunction, as proinflammatory cytokines are capable of inhibiting adipocyte differentiation. Beyond increased ectopic adiposity, the effect of impaired adipose tissue function is an elevation in systemic free fatty acids (FFA), a common feature of many metabolic disorders. Saturated fatty acids can be regarded as the most detrimental of FFA, being capable of inducing insulin resistance and inflammation through lipid mediators such as ceramide, which can increase risk of developing atherosclerosis. Elevated FFA, in particular saturated fatty acids, maybe a driving factor for both the increased insulin resistance, cardiovascular disease risk and inflammation in older adults

CrypTFlow2: Practical 2-Party Secure Inference

We present CrypTFlow2, a cryptographic framework for secure inference over realistic Deep Neural Networks (DNNs) using secure 2-party computation. CrypTFlow2 protocols are both correct -- i.e., their outputs are bitwise equivalent to the cleartext execution -- and efficient -- they outperform the state-of-the-art protocols in both latency and scale. At the core of CrypTFlow2, we have new 2PC protocols for secure comparison and division, designed carefully to balance round and communication complexity for secure inference tasks. Using CrypTFlow2, we present the first secure inference over ImageNet-scale DNNs like ResNet50 and DenseNet121. These DNNs are at least an order of magnitude larger than those considered in the prior work of 2-party DNN inference. Even on the benchmarks considered by prior work, CrypTFlow2 requires an order of magnitude less communication and 20x-30x less time than the state-of-the-art