AI deployment on GBM diagnosis: a novel approach to analyze histopathological images using image feature-based analysis

Background: Glioblastoma (GBM) is one of the most common malignant primary brain tumors, which accounts for 60–70% of all gliomas. Conventional diagnosis and the decision of post-operation treatment plan for glioblastoma is mainly based on the feature-based qualitative analysis of hematoxylin and eosin-stained (H&amp;E) histopathological slides by both an experienced medical technologist and a pathologist. The recent development of digital whole slide scanners makes AI-based histopathological image analysis feasible and helps to diagnose cancer by accurately counting cell types and/or quantitative analysis. However, the technology available for digital slide image analysis is still very limited. This study aimed to build an image feature-based computer model using histopathology whole slide images to differentiate patients with glioblastoma (GBM) from healthy control (HC). Method: Two independent cohorts of patients were used. The first cohort was composed of 262 GBM patients of the Cancer Genome Atlas Glioblastoma Multiform Collection (TCGA-GBM) dataset from the cancer imaging archive (TCIA) database. The second cohort was composed of 60 GBM patients collected from a local hospital. Also, a group of 60 participants with no known brain disease were collected. All the H&amp;E slides were collected. Thirty-three image features (22 GLCM and 11 GLRLM) were retrieved from the tumor volume delineated by medical technologist on H&amp;E slides. Five machine-learning algorithms including decision-tree (DT), extreme-boost (EB), support vector machine (SVM), random forest (RF), and linear model (LM) were used to build five models using the image features extracted from the first cohort of patients. Models built were deployed using the selected key image features for GBM diagnosis from the second cohort (local patients) as model testing, to identify and verify key image features for GBM diagnosis. Results: All five machine learning algorithms demonstrated excellent performance in GBM diagnosis and achieved an overall accuracy of 100% in the training and validation stage. A total of 12 GLCM and 3 GLRLM image features were identified and they showed a significant difference between the normal and the GBM image. However, only the SVM model maintained its excellent performance in the deployment of the models using the independent local cohort, with an accuracy of 93.5%, sensitivity of 86.95%, and specificity of 99.73%. Conclusion: In this study, we have identified 12 GLCM and 3 GLRLM image features which can aid the GBM diagnosis. Among the five models built, the SVM model proposed in this study demonstrated excellent accuracy with very good sensitivity and specificity. It could potentially be used for GBM diagnosis and future clinical application.</p

A Theoretical Formation of Emotional Intelligence and Childhood Trauma among Adolescents

Problem Statement: Much has been documented on the impact of emotional intelligence (EI) on adolescents in terms of their problem-solving skills (Ajawani, 2012), creativity (Vijaykumar, 2012), and academic performance (Shenoy & Thingujam, 2012). Increasingly, emphasis has been paid on the effect of EI on health among this population. For example, EI has been shown to interact with personality traits to affect psychological well-being (Salami, 2012). EI, based on literature focusing on the adult population, shows that it is a protective factor and can buffer against psychological distress (e.g. Hunt & Evans, 2004; Schmidt & Andrykowski, 2004). However, little is known regarding the role that EI could play in influencing such outcome among traumatized adolescents. Whilst one study has shown that low EI predicted the likelihood for being bullied by peers (Lomas et.al, 2012), no research has focused on the effect of childhood trauma. To what extent EI could interact with the experience of childhood trauma in influencing different degrees of psychological distress among adolescents is unknown.Purpose of Study: The aim of this paper is twofold. Firstly, it aims to provide a brief review of literature pertaining to the relationship between psychological well-being and emotional intelligence among adolescents. Secondly, it aims to point out the gap in research looking at the link between EI and childhood trauma and to formulate a theoretical model for understanding the foregoing relationship. The theoretical postulate is integrated with theories from trauma and EI literature. In brief, it postulates that the experience of childhood trauma would have a significant impact on the development of traumatized self (Brewin, 2002) among these adolescents. This traumatized self is characterized by altered self-capacities of which interpersonal conflicts or difficulties with oneself and others are part (Briere & Spinazolli, 2005).Conclusions: This would hinder the development of EI which would in turn affect different degrees of psychological well-being. This theoretical model will be relevant for not only researchers investigating childhood trauma and posttraumatic stress disorder in general but also it will have significant clinical implications for counselor and psychotherapists who work with adolescent

Analysis of the vector and axialvector BcB_c mesons with QCD sum rules

In this article, we study the vector and axialvector $B_c$ mesons with the QCD sum rules, and make reasonable predictions for the masses and decay constants, then calculate the leptonic decay widths. The present predictions for the masses and decay constants can be confronted with the experimental data in the future. We can also take the masses and decay constants as basic input parameters and study other phenomenological quantities with the three-point vacuum correlation functions via the QCD sum rules.Comment: 14 pages, 16 figure

Current-spin-density functional study of persistent currents in quantum rings

We present a numerical study of persistent currents in quantum rings using current spin density functional theory (CSDFT). This formalism allows for a systematic study of the joint effects of both spin, interactions and impurities for realistic systems. It is illustrated that CSDFT is suitable for describing the physical effects related to Aharonov-Bohm phases by comparing energy spectra of impurity-free rings to existing exact diagonalization and experimental results. Further, we examine the effects of a symmetry-breaking impurity potential on the density and current characteristics of the system and propose that narrowing the confining potential at fixed impurity potential will suppress the persistent current in a characteristic way.Comment: 7 pages REVTeX, including 8 postscript figure

Neutrino masses from beta decays after KamLAND and WMAP (Updated including the NC enhanced SNO data)

The first data released by the KamLAND collaboration have confirmed the strong evidence in favour of the LMA solution of the solar neutrino problem. Taking into account the ranges for the oscillation parameters allowed by the global analysis of the solar, CHOOZ and KamLAND data, we update the limits on the neutrinoless double beta decay effective neutrino mass parameter and analyze the impact of all the available data from neutrinoless double beta decay experiments on the neutrino mass bounds, in view of the latest WMAP results. For the normal neutrino mass spectrum the range (0.05-0.23) eV is obtained for the lightest neutrino mass if one takes into account the Heidelberg-Moscow evidence for neutrinoless double beta decay and the cosmological bound. It is also shown that under the same conditions the mass of the lightest neutrino may not be bounded from below if the spectrum is of the inverted type. Finnaly, we discuss how future experiments can improve the present bounds on the lightest neutrino mass set by the Troitsk, Mainz and WMAP results. In the addendum we update the allowed ranges for the effective Majorana neutrino mass parameter in view of the latest NC enhanced SNO data.Comment: Updated including the recent NC enhanced SNO data. Refferences added and typos correcte

Impact of CP phases on neutrinoless double beta decay

We highlight in a model independent way the dependence of the effective Majorana mass parameter, relevant for neutrinoless double beta decay, on the CP phases of the PMNS matrix, using the most recent neutrino data including the cosmological WMAP measurement. We perform our analysis with three active neutrino flavours in the context of three kinds of mass spectra: quasi-degenerate, normal hierarchical and inverted hierarchical. If a neutrinoless double beta decay experiment records a positive signal, then assuming that Majorana masses of light neutrinos are responsible for it, we show how it might be possible to discriminate between the three kinds of spectra.Comment: 10 pages, latex, 9 eps figs, version to appear in Phys Rev

Bimaximal Neutrino Mixings from Lopsided Mass Matrices

Current solar and atmospheric neutrino oscillation data seem to favor a bimaximal pattern for neutrino mixings where the matrix elements U_{e2} and U_{\mu 3} are of order one, while U_{e3} is much smaller. We show that such a pattern can be obtained quite easily in theories with ``lopsided'' mass matrices for the charged leptons and the down type quarks. A relation connecting the solar and atmospheric neutrino mixing angles is derived, \tan^2\theta_{atm} \simeq 1+ \tan^2\theta_{sol}, which predicts \sin^2 2\theta_{atm} \simeq 0.97 corresponding to the best fit LMA solution for solar neutrinos. Predictive schemes in SO(10) realizing these ideas are presented. A new class of SO(10) models with lopsided mass matrices is found which makes use of an adjoint VEV along the I_{3R} direction, rather than the traditional B-L direction.Comment: 12 pages in LaTeX, no figure

Diagonalization of the neutralino mass matrix and boson-neutralino interaction

We analyze a connection between neutralino mass sign, parity and structure of the neutralino-boson interaction. Correct calculation of spin-dependent and spin-independent contributions to neutralino-nuclear scattering should consider this connection. A convenient diagonalization procedure, based on the exponetial parametrization of unitary matrix, is suggested.Comment: 21 pages, RevTex

Emergence of Anti-Cancer Drug Resistance: Exploring the Importance of the Microenvironmental Niche via a Spatial Model

Practically, all chemotherapeutic agents lead to drug resistance. Clinically, it is a challenge to determine whether resistance arises prior to, or as a result of, cancer therapy. Further, a number of different intracellular and microenvironmental factors have been correlated with the emergence of drug resistance. With the goal of better understanding drug resistance and its connection with the tumor microenvironment, we have developed a hybrid discrete-continuous mathematical model. In this model, cancer cells described through a particle-spring approach respond to dynamically changing oxygen and DNA damaging drug concentrations described through partial differential equations. We thoroughly explored the behavior of our self-calibrated model under the following common conditions: a fixed layout of the vasculature, an identical initial configuration of cancer cells, the same mechanism of drug action, and one mechanism of cellular response to the drug. We considered one set of simulations in which drug resistance existed prior to the start of treatment, and another set in which drug resistance is acquired in response to treatment. This allows us to compare how both kinds of resistance influence the spatial and temporal dynamics of the developing tumor, and its clonal diversity. We show that both pre-existing and acquired resistance can give rise to three biologically distinct parameter regimes: successful tumor eradication, reduced effectiveness of drug during the course of treatment (resistance), and complete treatment failure

Elevated plasma TGF-β1 levels in patients with chronic obstructive pulmonary disease

SummaryBackgroundTransforming growth factor-β1 (TGF-β1), a multifunctional cytokine, has been implicated to be responsible for the increased deposition of extracellular matrix in the airways, and increased submucosal collagen expression in chronic obstructive pulmonary disease (COPD). We determined plasma TGF-β1 levels in patients with COPD and explored its association with common functional polymorphisms of TGF-β1 gene at C-509T and T869C in the development of COPD in a case–control study.MethodsStable COPD patients who were ever smokers, and age and pack-years smoked matched healthy controls (n = 205 in each group) were recruited for measurement of plasma TGF-β1 levels using commercially available ELISA kit, and genotyped at C-509T and T869C functional polymorphisms of TGF-β1 gene using polymerase chain reaction and restriction fragment length polymorphism (PCR–RFLP).ResultsCOPD patients had significantly elevated plasma TGF-β1 levels in comparison to healthy controls irrespective of the genotypes. Allele frequencies and genotype distributions at both polymorphic sites were not different among COPD patients or controls. TGF-β1 levels were inversely correlated (Pearson's correlation analysis) with FEV1 (% predicted) (p < 0.001) and FVC (% predicted) (p < 0.001).ConclusionThe findings of elevated plasma TGF-β1 levels in patients with COPD suggest that TGF-β1 may play a role in COPD pathogenesis. The C-509T and T869C functional polymorphisms of TGF-β1 gene do not represent a genetic predisposition to COPD susceptibility in Hong Kong Chinese patients