Effect of Statistical Fluctuation in Monte Carlo Based Photon Beam Dose Calculation on Gamma Index Evaluation

The gamma-index test has been commonly adopted to quantify the degree of agreement between a reference dose distribution and an evaluation dose distribution. Monte Carlo (MC) simulation has been widely used for the radiotherapy dose calculation for both clinical and research purposes. The goal of this work is to investigate both theoretically and experimentally the impact of the MC statistical fluctuation on the gamma-index test when the fluctuation exists in the reference, the evaluation, or both dose distributions. To the first order approximation, we theoretically demonstrated in a simplified model that the statistical fluctuation tends to overestimate gamma-index values when existing in the reference dose distribution and underestimate gamma-index values when existing in the evaluation dose distribution given the original gamma-index is relatively large for the statistical fluctuation. Our numerical experiments using clinical photon radiation therapy cases have shown that 1) when performing a gamma-index test between an MC reference dose and a non-MC evaluation dose, the average gamma-index is overestimated and the passing rate decreases with the increase of the noise level in the reference dose; 2) when performing a gamma-index test between a non-MC reference dose and an MC evaluation dose, the average gamma-index is underestimated when they are within the clinically relevant range and the passing rate increases with the increase of the noise level in the evaluation dose; 3) when performing a gamma-index test between an MC reference dose and an MC evaluation dose, the passing rate is overestimated due to the noise in the evaluation dose and underestimated due to the noise in the reference dose. We conclude that the gamma-index test should be used with caution when comparing dose distributions computed with Monte Carlo simulation

A randomised controlled trial to examine the effectiveness of group cognitive behavioural therapy for the treatment of unipolar depression in Malaysia

Malaysia has been experiencing a dearth in mental health resources. Group Cognitive Behavioural Therapy (GCBT) has been an established form of treatment for unipolar depression. The objectives of the current study were to examine the effectiveness of using GCBT for the treatment of depression in Malaysia. A total of 174 participants suffering from unipolar depression were recruited and randomly allocated to one of GCBT+Treatment as Usual (TAU), Relaxation training+TAU, or TAU only treatment groups. The participants were between 18-60 years of age. The participants in the GCBT+TAU group received eight Group CBT sessions of over a span of two months. The participants receiving Relaxation+TAU treatment received eight relaxation training sessions over a span of two months. The participants in the TAU only treatment group received treatment as usual from their psychiatrists. The BDI-M, ATQ-M, ATQP-M and DAS-M were administered at pre-treatment, mid-treatment (week 4) and post-treatment. Repeated Measures MANOVA showed a significant interaction effect between treatment group and time for BDI-M, ATQ-M, ATQP-M and DAS-M. Results showed that GCBT+TAU was able to significantly reduce depressive symptoms, negative cognitions and beliefs. Moderate effect sizes for the BDI-M scores, as well as significantly reliable and clinical change, were also found. The current study was limited by geographical boundaries, where only hospitals in and around the greater Klang Valley area were sampled. Results from the current study suggest that GCBT is effective in reducing the symptoms of depression in a Malaysian setting

Towards quantum enhanced adversarial robustness in machine learning

Machine learning algorithms are powerful tools for data driven tasks such as image classification and feature detection, however their vulnerability to adversarial examples - input samples manipulated to fool the algorithm - remains a serious challenge. The integration of machine learning with quantum computing has the potential to yield tools offering not only better accuracy and computational efficiency, but also superior robustness against adversarial attacks. Indeed, recent work has employed quantum mechanical phenomena to defend against adversarial attacks, spurring the rapid development of the field of quantum adversarial machine learning (QAML) and potentially yielding a new source of quantum advantage. Despite promising early results, there remain challenges towards building robust real-world QAML tools. In this review we discuss recent progress in QAML and identify key challenges. We also suggest future research directions which could determine the route to practicality for QAML approaches as quantum computing hardware scales up and noise levels are reduced.Comment: 10 Pages, 4 Figure

PCA-based lung motion model

Organ motion induced by respiration may cause clinically significant targeting errors and greatly degrade the effectiveness of conformal radiotherapy. It is therefore crucial to be able to model respiratory motion accurately. A recently proposed lung motion model based on principal component analysis (PCA) has been shown to be promising on a few patients. However, there is still a need to understand the underlying reason why it works. In this paper, we present a much deeper and detailed analysis of the PCA-based lung motion model. We provide the theoretical justification of the effectiveness of PCA in modeling lung motion. We also prove that under certain conditions, the PCA motion model is equivalent to 5D motion model, which is based on physiology and anatomy of the lung. The modeling power of PCA model was tested on clinical data and the average 3D error was found to be below 1 mm.Comment: 4 pages, 1 figure. submitted to International Conference on the use of Computers in Radiation Therapy 201

Explicit hypoxia targeting with tumor suppression by creating an “obligate” anaerobic Salmonella Typhimurium strain

Using bacteria as therapeutic agents against solid tumors is emerging as an area of great potential in the treatment of cancer. Obligate and facultative anaerobic bacteria have been shown to infiltrate the hypoxic regions of solid tumors, thereby reducing their growth rate or causing regression. However, a major challenge for bacterial therapy of cancer with facultative anaerobes is avoiding damage to normal tissues. Consequently the virulence of bacteria must be adequately attenuated for therapeutic use. By placing an essential gene under a hypoxia conditioned promoter, Salmonella Typhimurium strain SL7207 was engineered to survive only in anaerobic conditions (strain YB1) without otherwise affecting its functions. In breast tumor bearing nude mice, YB1 grew within the tumor, retarding its growth, while being rapidly eliminated from normal tissues. YB1 provides a safe bacterial vector for anti-tumor therapies without compromising the other functions or tumor fitness of the bacterium as attenuation methods normally do

The Science of Sungrazers, Sunskirters, and Other Near-Sun Comets

This review addresses our current understanding of comets that venture close to the Sun, and are hence exposed to much more extreme conditions than comets that are typically studied from Earth. The extreme solar heating and plasma environments that these objects encounter change many aspects of their behaviour, thus yielding valuable information on both the comets themselves that complements other data we have on primitive solar system bodies, as well as on the near-solar environment which they traverse. We propose clear definitions for these comets: We use the term near-Sun comets to encompass all objects that pass sunward of the perihelion distance of planet Mercury (0.307 AU). Sunskirters are defined as objects that pass within 33 solar radii of the Sun’s centre, equal to half of Mercury’s perihelion distance, and the commonly-used phrase sungrazers to be objects that reach perihelion within 3.45 solar radii, i.e. the fluid Roche limit. Finally, comets with orbits that intersect the solar photosphere are termed sundivers. We summarize past studies of these objects, as well as the instruments and facilities used to study them, including space-based platforms that have led to a recent revolution in the quantity and quality of relevant observations. Relevant comet populations are described, including the Kreutz, Marsden, Kracht, and Meyer groups, near-Sun asteroids, and a brief discussion of their origins. The importance of light curves and the clues they provide on cometary composition are emphasized, together with what information has been gleaned about nucleus parameters, including the sizes and masses of objects and their families, and their tensile strengths. The physical processes occurring at these objects are considered in some detail, including the disruption of nuclei, sublimation, and ionisation, and we consider the mass, momentum, and energy loss of comets in the corona and those that venture to lower altitudes. The different components of comae and tails are described, including dust, neutral and ionised gases, their chemical reactions, and their contributions to the near-Sun environment. Comet-solar wind interactions are discussed, including the use of comets as probes of solar wind and coronal conditions in their vicinities. We address the relevance of work on comets near the Sun to similar objects orbiting other stars, and conclude with a discussion of future directions for the field and the planned ground- and space-based facilities that will allow us to address those science topics

Diffractive J/ψJ/\psi production through color-octet mechanism in resolved photon processes at HERA

We use the color-octet mechanism combined with the two gluon exchange model for the diffractive $J/\psi$ production in resolved photon processes. In the leading logarithmic approximation in QCD, we find that the diffractive $J/\psi$ production cross section is related to the off-diagonal gluon density of the proton, the gluon density of the photon and to the nonperturbative color-octet $^3 S_{1}^{(8)}$ matrix element of $J/\psi$. The cross section is found to be very sensitive to the gluon density of the photon. As a result, this process may provide a wide window for testing the two-gluon exchange model, studying the nature of hard diffractive factorization breaking and may be particularly useful in studying the gluon distribution of the photon. And it may also be a golden place to test the color-octet mechanism proposed by solving the $\psi'(J/\psi)$ surplus problem at the Tevatron.Comment: Revtex, 10 pages, 4 PS figure

A Pivotal Role of Vitamin B9 in the Maintenance of Regulatory T Cells In Vitro and In Vivo

Dietary factors regulate immunological function, but the underlying mechanisms remain elusive. Here we show that vitamin B9 is a survival factor for regulatory T (Treg) cells expressing high levels of vitamin B9 receptor (folate receptor 4). In vitamin B9-reduced condition in vitro, Treg cells could be differentiated from naïve T cells but failed to survive. The impaired survival of Treg cells was associated with decreased expression of anti-apoptotic Bcl2 and independent of IL-2. In vivo depletion of dietary vitamin B9 resulted in the reduction of Treg cells in the small intestine, a site for the absorption of dietary vitamin B9. These findings provide a new link between diet and the immune system, which could maintain the immunological homeostasis in the intestine

A Comprehensive Association Analysis of Homocysteine Metabolic Pathway Genes in Singaporean Chinese with Ischemic Stroke

10.1371/journal.pone.0024757PLoS ONE69

Dynein-Dynactin Complex Is Essential for Dendritic Restriction of TM1-Containing Drosophila Dscam

BACKGROUND: Many membrane proteins, including Drosophila Dscam, are enriched in dendrites or axons within neurons. However, little is known about how the differential distribution is established and maintained. METHODOLOGY/PRINCIPAL FINDINGS: Here we investigated the mechanisms underlying the dendritic targeting of Dscam[TM1]. Through forward genetic mosaic screens and by silencing specific genes via targeted RNAi, we found that several genes, encoding various components of the dynein-dynactin complex, are required for restricting Dscam[TM1] to the mushroom body dendrites. In contrast, compromising dynein/dynactin function did not affect dendritic targeting of two other dendritic markers, Nod and Rdl. Tracing newly synthesized Dscam[TM1] further revealed that compromising dynein/dynactin function did not affect the initial dendritic targeting of Dscam[TM1], but disrupted the maintenance of its restriction to dendrites. CONCLUSIONS/SIGNIFICANCE: The results of this study suggest multiple mechanisms of dendritic protein targeting. Notably, dynein-dynactin plays a role in excluding dendritic Dscam, but not Rdl, from axons by retrograde transport