Influence of short-term dietary measures on dioxin concentrations in human milk.

Breast-feeding may expose infants to high levels of toxic chlorinated dioxins. To diminish intake of these lipophilic compounds by the baby, two diets were tested for their ability to reduce concentrations of dioxins in human milk. The diets were a low-fat/high- carbohydrate/low-dioxin diet. (about 20% of energy intake derived from fat) and a high fat /low-carbohydrate/low-dioxin diet. These diets were tested in 16 and 18 breast-feeding women, respectively. The test diets were followed for 5 consecutive days in the fourth week after delivery. Milk was sampled before and at the end of the dietary regimen, and dioxin concentrations and fatty acid concentrations were determined. Despite significant influences of these diets on the fatty acid profiles, no significant influence on the dioxin concentrations in breast milk could be found. We conclude that short-term dietary measures will not reduce dioxin concentration in human milk

Discordance between reports of internalized symptoms in persons with Parkinson’s disease and informants: results from an online survey

BACKGROUND: Self-report of motor and non-motor symptoms is integral to understanding daily challenges of persons with Parkinson's disease (PwPD). Care partners are often asked to serve as informants regarding symptom severity, raising the question of concordance with PwPD self-reports, especially regarding internalized (not outwardly visible) symptoms. OBJECTIVES: Concordance between PwPD and informant ratings of motor and non-motor symptoms was evaluated across multiple domains. METHODS: In 60 PwPD-informant pairs, we compared ratings on 11 online self-report measures comprising 33 total scores, 2/3 of which represented purely internalized symptoms. For discordant scores, multiple regression analyses were used to examine demographic/clinical predictors. RESULTS: Though concordant on 85% of measures, PwPD endorsed more non-motor symptoms, bodily discomfort, stigma, and motor symptoms than informants. For PwPD, younger age, greater disease severity, and female gender predicted discordance. CONCLUSIONS: Discordance between PwPD and informants on measures assessing symptoms that cannot be outwardly observed may require targeted education.First author draf

Aortic dissection type I in a weightlifter with hypertension: A case report

Acute aortic dissection can occur at the time of intense physical exertion in strength-trained athletes like weightlifters, bodybuilders, throwers, and wrestlers

Adversarial Attack Vulnerability of Medical Image Analysis Systems: Unexplored Factors

Adversarial attacks are considered a potentially serious security threat for machine learning systems. Medical image analysis (MedIA) systems have recently been argued to be vulnerable to adversarial attacks due to strong financial incentives and the associated technological infrastructure. In this paper, we study previously unexplored factors affecting adversarial attack vulnerability of deep learning MedIA systems in three medical domains: ophthalmology, radiology, and pathology. We focus on adversarial black-box settings, in which the attacker does not have full access to the target model and usually uses another model, commonly referred to as surrogate model, to craft adversarial examples. We consider this to be the most realistic scenario for MedIA systems. Firstly, we study the effect of weight initialization (ImageNet vs. random) on the transferability of adversarial attacks from the surrogate model to the target model. Secondly, we study the influence of differences in development data between target and surrogate models. We further study the interaction of weight initialization and data differences with differences in model architecture. All experiments were done with a perturbation degree tuned to ensure maximal transferability at minimal visual perceptibility of the attacks. Our experiments show that pre-training may dramatically increase the transferability of adversarial examples, even when the target and surrogate's architectures are different: the larger the performance gain using pre-training, the larger the transferability. Differences in the development data between target and surrogate models considerably decrease the performance of the attack; this decrease is further amplified by difference in the model architecture. We believe these factors should be considered when developing security-critical MedIA systems planned to be deployed in clinical practice.Comment: First three authors contributed equall

A Unifying Framework for Mutual Information Methods for Use in Non-linear Optimisation

Many variants of MI exist in the literature. These vary primarily in how the joint histogram is populated. This paper places the four main variants of MI: Standard sampling, Partial Volume Estimation (PVE), In-Parzen Windowing and Post-Parzen Windowing into a single mathematical framework. Jacobians and Hessians are derived in each case. A particular contribution is that the non-linearities implicit to standard sampling and post-Parzen windowing are explicitly dealt with. These non-linearities are a barrier to their use in optimisation. Side-by-side comparison of the MI variants is made using eight diverse data-sets, considering computational expense and convergence. In the experiments, PVE was generally the best performer, although standard sampling often performed nearly as well (if a higher sample rate was used). The widely used sum of squared differences metric performed as well as MI unless large occlusions and non-linear intensity relationships occurred. The binaries and scripts used for testing are available online

spot 003 thymidylate synthase maintains the undifferentiated state of aggressive breast cancers

Introduction De-differentiation is a highly lethal feature of aggressive breast cancers (BC), and is achieved through the epithelial-to-mesenchymal transition (EMT) and the cancer stem cell (CSC) programs. Targeting the mechanisms controlling BC de-differentiation can lead to more effective therapeutics. Recent studies indicated that nucleotide metabolism can regulate cancer stemness and EMT. Here we investigated the expression of the nucleotide metabolism enzyme and drug target thymidylate synthase (TS) in the BC subtypes and analysed its impact on BC de-differentiation. Material and methods Cells with TS knockdown and overexpression were tested in vitro and in vivo. Proteins were analysed by western blot, FACS and ELISA. Differential gene expression in TS-deficient cells was determined by RNA-seq. Immunohistochemistry (IHC) was used to stain samples from patients with different BC subtypes. Results and discussions TS mRNA expression was found to be significantly differentially expressed among the BC subtypes, exhibiting the highest levels in aggressive triple-negative BC (TNBC). shRNA-mediated TS knockdown in TNBC cell lines (n=3) increased the population of differentiated cells (CD24high) and strongly attenuated the stem-like phenotype, like the formation of mammospheres from single cells and the migration in a cell culture wound. TS-deficient cells also showed an altered ability to form metastasis in vivo, consistent with previous observations in EMT-repressed BC cells. A rescue experiment performed by overexpressing either a wild-type or catalytically inactive TS indicated that the enzymatic activity was essential for the maintenance of the BCSC phenotype. Along with a strong repression of EMT-signature genes, RNA-seq profiling indicated a reduction of inflammatory and NF-κB signalling pathways in TS deficient cells, which dramatically reduced IL-1β production and secretion. A TS-specific gene signature was generated, which significantly associated with worst survival in BC patients. IHC staining on FFPE samples from a series of BC patients (n=120) confirmed higher TS expression in tumours that were poorly differentiated and in TNBC. Conclusion We discovered a novel role for the TS enzyme in the maintenance of a de-differentiated and stem-like state of BC. These findings may not only open the possibility to study in-depth the role of nucleotide metabolism at the crossroad between proliferation and differentiation, but may provide the rationale for novel drug combinations with TS-inhibiting agents for the treatment of BC

Parallel mutual information estimation for inferring gene regulatory networks on GPUs

<p>Abstract</p> <p>Background</p> <p>Mutual information is a measure of similarity between two variables. It has been widely used in various application domains including computational biology, machine learning, statistics, image processing, and financial computing. Previously used simple histogram based mutual information estimators lack the precision in quality compared to kernel based methods. The recently introduced B-spline function based mutual information estimation method is competitive to the kernel based methods in terms of quality but at a lower computational complexity.</p> <p>Results</p> <p>We present a new approach to accelerate the B-spline function based mutual information estimation algorithm with commodity graphics hardware. To derive an efficient mapping onto this type of architecture, we have used the Compute Unified Device Architecture (CUDA) programming model to design and implement a new parallel algorithm. Our implementation, called CUDA-MI, can achieve speedups of up to 82 using double precision on a single GPU compared to a multi-threaded implementation on a quad-core CPU for large microarray datasets. We have used the results obtained by CUDA-MI to infer gene regulatory networks (GRNs) from microarray data. The comparisons to existing methods including ARACNE and TINGe show that CUDA-MI produces GRNs of higher quality in less time.</p> <p>Conclusions</p> <p>CUDA-MI is publicly available open-source software, written in CUDA and C++ programming languages. It obtains significant speedup over sequential multi-threaded implementation by fully exploiting the compute capability of commonly used CUDA-enabled low-cost GPUs.</p