Malignant melanoma in pregnancy: Rarity and paucity

Malignancy diagnosed during pregnancy is a rare coincidence and a taxing situation for the health care provider. The diagnosis and therapeutic management become laborious and it involves both the mother and fetus. One of the major cause of death among women of the childbearing age group is malignant melanoma in the western world. The literature vastly suggests that it has an ominous prognosis when diagnosed during pregnancy as it is known to rapidly metastasize to the placenta and fetus. Prompt diagnosis and appropriate treatment can avoid catastrophic events. We report a case of Indian women diagnosed with non- metastatic malignant melanoma in the first trimester of pregnancy with successful outcome.Keywords: Developing country; malignant melanoma; pregnanc

Automated Microfluidic Blood Lysis Protocol for Enrichment of Circulating Nucleated Cells

In this report the protocol for an automated microfluidic blood lysis device is detailed. Circulating nucleated cells (CNCs), including leukocytes and endothelial cells, provide an ideal platform for an updated status on the immune condition of an individual. The microfluidic protocol allows for enrichment of CNCs without selective cell loss and sample preparation variability due to user-mediated steps. Briefly, the protocol includes device fabrication, sample collection, device setup, and running blood through the microfluidic chamber. Within the device whole blood is rapidly mixed with deionized water for approximately 10 seconds in a 50 micron x 150 micron microfluidic channel. In this time span erythrocytes are lysed due to hypotonic conditions. Herringbone structures on the bottom of the channel ensure thorough mixing and exposure of cells to a constant environment. Remaining cells are returned to isotonic conditions at the exit of the device, fixed using 2% paraformaldehyde, centrifuged to separate erythrocyte debris from CNCs, and suspended in flow buffer for staining and analysis by flow cytometry. Results show clean flow cytometry scatter plots with CNC populations saved. Significance of this device and protocol comes in the study and understanding of disease pathogenesis by analysis of CNC populations. Hence, automation, effectiveness, and simplicity of the microfluidic protocol are demonstrated

Towards Personalized Prostate Cancer Therapy Using Delta-Reachability Analysis

Recent clinical studies suggest that the efficacy of hormone therapy for prostate cancer depends on the characteristics of individual patients. In this paper, we develop a computational framework for identifying patient-specific androgen ablation therapy schedules for postponing the potential cancer relapse. We model the population dynamics of heterogeneous prostate cancer cells in response to androgen suppression as a nonlinear hybrid automaton. We estimate personalized kinetic parameters to characterize patients and employ $\delta$-reachability analysis to predict patient-specific therapeutic strategies. The results show that our methods are promising and may lead to a prognostic tool for personalized cancer therapy.Comment: HSCC 201

Endometriosis fertility index at laparoscope: a ray of hope and lots of scope

Background: Endometriosis fertility index (EFI) is used to predict the fecundity in women with surgically and histologically confirmed endometriosis. Aim of the study is to evaluate the successful spontaneous pregnancy rates in patients with endometriosis after laparoscopic surgery in relation to EFI score.Methods: Observational cross-sectional study was conducted on 76 patients who desire to conceive with suspected endometriosis related infertility treated by laparoscopic surgery. EFI score was calculated and information on mode of conception (spontaneous or assisted reproductive technology-ART) was collected by contacting the patients.Results: In women who conceived spontaneously, mean age was 31.33+3.29 years. Factors found to be significant were age (pvalue-0.0001), time to achieve spontaneous pregnancy (median-9 months). Patients with higher EFI score (5-10) has good spontaneous conception rate (96.2%) compared to those with lower EFI score (0-4) that conceived better with ART (60%) women with lower least function score has better outcome for spontaneous pregnancy (p<0.001).Conclusions: EFI scoring system is effective in predicting postoperative successful spontaneous pregnancy rates in the patients with endometriosis. In our study patients with higher EFI score achieved successful spontaneous pregnancy

Improving the Feature Stability and Classification Performance of Bimodal Brain and Heart Biometrics

Electrical activities from brain (electroencephalogram, EEG) and heart (electrocardiogram, ECG) have been proposed as biometric modalities but the combined use of these signals appear not to have been studied thoroughly. Also, the feature stability of these signals has been a limiting factor for biometric usage. This paper presents results from a pilot study that reveal the combined use of brain and heart modalities provide improved classification performance and further-more, an improvement in the stability of the features over time through the use of binaural brain entrainment. The classification rate was increased, for the case of the neural network classifier from 92.4% to 95.1% and for the case of LDA, from 98.6% to 99.8%. The average standard deviation with binaural brain entrainment using all the inter-session features (from all the subjects) was 1.09, as compared to 1.26 without entrainment. This result suggests the improved stability of both the EEG and ECG features over time and hence resulting in higher classification performance. Overall, the results indicate that combining ECG and EEG gives improved classification performance and that through the use of binaural brain entrainment, both the ECG and EEG features are more stable over time

Effects of hidden unit sizes and autoregressive features in mental task classification

Classification of electroencephalogram (EEG) signals extracted during mental tasks is a technique that is actively pursued for Brain Computer Interfaces (BCI) designs. In this paper, we compared the classification performances of univariateautoregressive (AR) and multivariate autoregressive (MAR) models for representing EEG signals that were extracted during different mental tasks. Multilayer Perceptron (MLP) neural network (NN) trained by the backpropagation (BP) algorithm was used to classify these features into the different categories representing the mental tasks. Classification performances were also compared across different mental task combinations and 2 sets of hidden units (HU): 2 to 10 HU in steps of 2 and 20 to 100 HU in steps of 20. Five different mental tasks from 4 subjects were used in the experimental study and combinations of 2 different mental tasks were studied for each subject. Three different feature extraction methods with 6th order were used to extract features from these EEG signals: AR coefficients computed with Burg-s algorithm (ARBG), AR coefficients computed with stepwise least square algorithm (ARLS) and MAR coefficients computed with stepwise least square algorithm. The best results were obtained with 20 to 100 HU using ARBG. It is concluded that i) it is important to choose the suitable mental tasks for different individuals for a successful BCI design, ii) higher HU are more suitable and iii) ARBG is the most suitable feature extraction method

Head and neck target delineation using a novel PET automatic segmentation algorithm

Purpose To evaluate the feasibility and impact of using a novel advanced PET auto-segmentation method in Head and Neck (H&N) radiotherapy treatment (RT) planning. Methods ATLAAS, Automatic decision Tree-based Learning Algorithm for Advanced Segmentation, previously developed and validated on pre-clinical data, was applied to 18F-FDG-PET/CT scans of 20 H&N patients undergoing Intensity Modulated Radiation Therapy. Primary Gross Tumour Volumes (GTVs) manually delineated on CT/MRI scans (GTVpCT/MRI), together with ATLAAS-generated contours (GTVpATLAAS) were used to derive the RT planning GTV (GTVpfinal). ATLAAS outlines were compared to CT/MRI and final GTVs qualitatively and quantitatively using a conformity metric. Results The ATLAAS contours were found to be reliable and useful. The volume of GTVpATLAAS was smaller than GTVpCT/MRI in 70% of the cases, with an average conformity index of 0.70. The information provided by ATLAAS was used to grow the GTVpCT/MRI in 10 cases (up to 10.6 mL) and to shrink the GTVpCT/MRI in 7 cases (up to 12.3 mL). ATLAAS provided complementary information to CT/MRI and GTVpATLAAS contributed to up to 33% of the final GTV volume across the patient cohort. Conclusions ATLAAS can deliver operator independent PET segmentation to augment clinical outlining using CT and MRI and could have utility in future clinical studies

Heat Transfer Analysis of Flat Plate Subjected to Multi-Jet Air Impingement using Principal Component Analysis and Computational Technique

The aim of this work is to investigate experimentally the variation in temperature, heat transfer coefficient and Nusselt number of a hot plate subjected to multi-jet air impingement cooling to use the multi-objective optimization technique to arrive at optimum conditions. A flat plate of 15 cm x 10 cm is heated through a heating foil with a constant heat flux of 7667 W/m2. Air jets with and without swirling action are considered, fixing the distance of target surface from nozzle exit at 2D, 4D and 6D. Reynolds numbers 18000, 20000and 22000 and pipe diameters 8mm, 10mm and 12 mm have been considered for investigation. Experiments are designed and analyzed using Taguchi’s technique, coupled with principal component analysis for multi-variate optimization by calculating multi-response performance index (MRPI). Based on the observations made, it is concluded that lower H/D ratio and higher Reynolds number result in higher heat transfer coefficient, in accordance with the first principles. Heat transfer coefficient obtained for jets with swirl is compared with that of jet without swirling for the same Reynolds number and H/D ratio. Furthermore, it is concluded that introducing swirl results in increase of heat transfer coefficients for all the test conditions for 10mm and 12mm diameter jets. However for 8mm jet, introduction of swirl reduced the heat transfer rate for all the test conditions. From Analysis of Variance (ANOVA), it is found that significant contributions on outputs are due to the effect of H/D ratio and Reynolds number. Confirmation experiments with optimum condition result in improved heat transfer coefficient and Nusselt number. Numerical simulation has also been performed with the optimum condition. It is observed that the simulation results are in consistence with the experimental results

Mechanical properties of phormium tenax reinforced natural rubber composites

The introduction of natural fibers as a filler in a natural rubber (NR) matrix can be of relevance for their eco-friendly and sustainable nature as the substitute for carbon-based fillers. In this work, short Phormium tenax fibers were introduced in random orientation into a NR matrix in different lengths (6, 10, and 14 mm) and various amounts (10, 20, and 30%, taking 100 as the NR weight). The composite was fabricated using a two-roll mill according to American Society for Testing and Materials (ASTM) D3184-11 standard. Several properties were determined, namely tensile and tear characteristics, hardness, and abrasion resistance. The results suggest that the shortest fiber length used, 6 mm, offered the best combination between loss of mechanical (tensile and tear) properties and hardness and the most acceptable resistance to abrasion, with the properties increasing with the amount of fibers present in NR. As a consequence, it is indicated that a higher amount of fibers could be possibly introduced, especially to achieve harder composites, though this would require a more controlled mixing process not excessively reducing tensile elongation at break