The ErbB2ΔEx16 splice variant is a major oncogenic driver in breast cancer that promotes a pro-metastatic tumor microenvironment.

Amplification and overexpression of erbB2/neu proto-oncogene is observed in 20-30% human breast cancer and is inversely correlated with the survival of the patient. Despite this, somatic activating mutations within erbB2 in human breast cancers are rare. However, we have previously reported that a splice isoform of erbB2, containing an in-frame deletion of exon 16 (herein referred to as ErbB2ΔEx16), results in oncogenic activation of erbB2 because of constitutive dimerization of the ErbB2 receptor. Here, we demonstrate that the ErbB2ΔEx16 is a major oncogenic driver in breast cancer that constitutively signals from the cell surface. We further show that inducible expression of the ErbB2ΔEx16 variant in mammary gland of transgenic mice results in the rapid development of metastatic multifocal mammary tumors. Genetic and biochemical characterization of the ErbB2ΔEx16-derived mammary tumors exhibit several unique features that distinguish this model from the conventional ErbB2 ones expressing the erbB2 proto-oncogene in mammary epithelium. Unlike the wild-type ErbB2-derived tumors that express luminal keratins, ErbB2ΔEx16-derived tumors exhibit high degree of intratumoral heterogeneity co-expressing both basal and luminal keratins. Consistent with these distinct pathological features, the ErbB2ΔEx16 tumors exhibit distinct signaling and gene expression profiles that correlate with activation of number of key transcription factors implicated in breast cancer metastasis and cancer stem cell renewal

IoT Device Identification Using Deep Learning

The growing use of IoT devices in organizations has increased the number of attack vectors available to attackers due to the less secure nature of the devices. The widely adopted bring your own device (BYOD) policy which allows an employee to bring any IoT device into the workplace and attach it to an organization's network also increases the risk of attacks. In order to address this threat, organizations often implement security policies in which only the connection of white-listed IoT devices is permitted. To monitor adherence to such policies and protect their networks, organizations must be able to identify the IoT devices connected to their networks and, more specifically, to identify connected IoT devices that are not on the white-list (unknown devices). In this study, we applied deep learning on network traffic to automatically identify IoT devices connected to the network. In contrast to previous work, our approach does not require that complex feature engineering be applied on the network traffic, since we represent the communication behavior of IoT devices using small images built from the IoT devices network traffic payloads. In our experiments, we trained a multiclass classifier on a publicly available dataset, successfully identifying 10 different IoT devices and the traffic of smartphones and computers, with over 99% accuracy. We also trained multiclass classifiers to detect unauthorized IoT devices connected to the network, achieving over 99% overall average detection accuracy

Glucocorticoid-induced cell death is mediated through reduced glucose metabolism in lymphoid leukemia cells

Malignant cells are known to have increased glucose uptake and accelerated glucose metabolism. Using liquid chromatography and mass spectrometry, we found that treatment of acute lymphoblastic leukemia (ALL) cells with the glucocorticoid (GC) dexamethasone (Dex) resulted in profound inhibition of glycolysis. We thus demonstrate that Dex reduced glucose consumption, glucose utilization and glucose uptake by leukemic cells. Furthermore, Dex treatment decreased the levels of the plasma membrane-associated glucose transporter GLUT1, thus revealing the mechanism for the inhibition of glucose uptake. Inhibition of glucose uptake correlated with induction of cell death in ALL cell lines and in leukemic blasts from ALL patients cultured ex vivo. Addition of di-methyl succinate could partially overcome cell death induced by Dex in RS4;11 cells, thereby further supporting the notion that inhibition of glycolysis contributes to the induction of apoptosis. Finally, Dex killed RS4;11 cells significantly more efficiently when cultured in lower glucose concentrations suggesting that modulation of glucose levels might influence the effectiveness of GC treatment in ALL. In summary, our data show that GC treatment blocks glucose uptake by leukemic cells leading to inhibition of glycolysis and that these effects play an important role in the induction of cell death by these drugs

Idiopathic Male Infertility Is Strongly Associated with Aberrant Promoter Methylation of Methylenetetrahydrofolate Reductase (MTHFR)

Abnormal germline DNA methylation in males has been proposed as a possible mechanism compromising spermatogenesis of some men currently diagnosed with idiopathic infertility. Previous studies have been focused on imprinted genes with DNA methylation in poor quality human sperms. However, recent but limited data have revealed that sperm methylation abnormalities may involve large numbers of genes or shown that genes that are not imprinted are also affected.Using the methylation-specific polymerase chain reaction and bisulfite sequencing method, we examined methylation patterns of the promoter of methylenetetrahydrofolate reductase (MTHFR) gene (NG_013351: 1538-1719) in sperm DNA obtained from 94 idiopathic infertile men and 54 normal fertile controls. Subjects with idiopathic infertility were further divided into groups of normozoospermia and oligozoospermia. Overall, 45% (41/94) of idiopathic infertile males had MTHFR hypermethylation (both hemimethylation and full methylation), compared with 15% of fertile controls (P<0.05). Subjects with higher methylation level of MTHFR were more likely to have idiopathic male infertility (P-value for trend  = 0.0007). Comparing the two groups of idiopathic infertile subjects with different sperm concentrations, a higher methylation pattern was found in the group with oligozoospermia.Hypermethylation of the promoter of MTHFR gene in sperms is associated with idiopathic male infertility. The functional relevance of hypermathylation of MTHFR to male fertility warrants further investigation

A Search for Dark Higgs Bosons

Recent astrophysical and terrestrial experiments have motivated the proposal of a dark sector with GeV-scale gauge boson force carriers and new Higgs bosons. We present a search for a dark Higgs boson using 516 fb-1 of data collected with the BABAR detector. We do not observe a significant signal and we set 90% confidence level upper limits on the product of the Standard Model-dark sector mixing angle and the dark sector coupling constant.Comment: 7 pages, 5 postscript figures, published version with improved plots for b/w printin

Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO

Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO