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

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

Approximate probabilistic verification of hybrid systems

Hybrid systems whose mode dynamics are governed by non-linear ordinary differential equations (ODEs) are often a natural model for biological processes. However such models are difficult to analyze. To address this, we develop a probabilistic analysis method by approximating the mode transitions as stochastic events. We assume that the probability of making a mode transition is proportional to the measure of the set of pairs of time points and value states at which the mode transition is enabled. To ensure a sound mathematical basis, we impose a natural continuity property on the non-linear ODEs. We also assume that the states of the system are observed at discrete time points but that the mode transitions may take place at any time between two successive discrete time points. This leads to a discrete time Markov chain as a probabilistic approximation of the hybrid system. We then show that for BLTL (bounded linear time temporal logic) specifications the hybrid system meets a specification iff its Markov chain approximation meets the same specification with probability $1$. Based on this, we formulate a sequential hypothesis testing procedure for verifying -approximately- that the Markov chain meets a BLTL specification with high probability. Our case studies on cardiac cell dynamics and the circadian rhythm indicate that our scheme can be applied in a number of realistic settings

A family case of fertile human 45,X,psu dic(15;Y) males

We report on a familial case including four male probands from three generations with a 45,X,psu dic(15;Y)(p11.2;q12) karyotype. 45,X is usually associated with a female phenotype and only rarely with maleness, due to translocation of small Y chromosomal fragments to autosomes. These male patients are commonly infertile because of missing azoospermia factor regions from the Y long arm. In our familial case we found a pseudodicentric translocation chromosome, that contains almost the entire chromosomes 15 and Y. The translocation took place in an unknown male ancestor of our probands and has no apparent effect on fertility and phenotype of the carrier. FISH analysis demonstrated the deletion of the pseudoautosomal region 2 (PAR2) from the Y chromosome and the loss of the nucleolus organizing region (NOR) from chromosome 15. The formation of the psu dic(15;Y) chromosome is a reciprocal event to the formation of the satellited Y chromosome (Yqs). Statistically, the formation of 45,X,psu dic(15;Y) (p11.2;q12) is as likely as the formation of Yqs. Nevertheless, it has not been described yet. This can be explained by the dicentricity of this translocation chromosome that usually leads to mitotic instability and meiotic imbalances. A second event, a stable inactivation of one of the two centromeres is obligatory to enable the transmission of the translocation chromosome and thus a stably reduced chromosome number from father to every son in this family

Inter-hemispheric EEG coherence analysis in Parkinson's disease : Assessing brain activity during emotion processing

Parkinson’s disease (PD) is not only characterized by its prominent motor symptoms but also associated with disturbances in cognitive and emotional functioning. The objective of the present study was to investigate the influence of emotion processing on inter-hemispheric electroencephalography (EEG) coherence in PD. Multimodal emotional stimuli (happiness, sadness, fear, anger, surprise, and disgust) were presented to 20 PD patients and 30 age-, education level-, and gender-matched healthy controls (HC) while EEG was recorded. Inter-hemispheric coherence was computed from seven homologous EEG electrode pairs (AF3–AF4, F7–F8, F3–F4, FC5–FC6, T7–T8, P7–P8, and O1–O2) for delta, theta, alpha, beta, and gamma frequency bands. In addition, subjective ratings were obtained for a representative of emotional stimuli. Interhemispherically, PD patients showed significantly lower coherence in theta, alpha, beta, and gamma frequency bands than HC during emotion processing. No significant changes were found in the delta frequency band coherence. We also found that PD patients were more impaired in recognizing negative emotions (sadness, fear, anger, and disgust) than relatively positive emotions (happiness and surprise). Behaviorally, PD patients did not show impairment in emotion recognition as measured by subjective ratings. These findings suggest that PD patients may have an impairment of inter-hemispheric functional connectivity (i.e., a decline in cortical connectivity) during emotion processing. This study may increase the awareness of EEG emotional response studies in clinical practice to uncover potential neurophysiologic abnormalities

MIRO-1 Determines Mitochondrial Shape Transition upon GPCR Activation and Ca^(2+) Stress

Mitochondria shape cytosolic calcium ([Ca^(2+)]_c) transients and utilize the mitochondrial Ca_2^+ ([Ca^(2+)]_m) in exchange for bioenergetics output. Conversely, dysregulated [Ca^(2+)]_c causes [Ca^(2+)]_m overload and induces permeability transition pore and cell death. Ablation of MCU-mediated Ca^(2+) uptake exhibited elevated [Ca^(2+)]_c and failed to prevent stress-induced cell death. The mechanisms for these effects remain elusive. Here, we report that mitochondria undergo a cytosolic Ca^(2+)-induced shape change that is distinct from mitochondrial fission and swelling. [Ca^(2+)]_c elevation, but not MCU-mediated Ca^(2+) uptake, appears to be essential for the process we term mitochondrial shape transition (MiST). MiST is mediated by the mitochondrial protein Miro1 through its EF-hand domain 1 in multiple cell types. Moreover, Ca^(2+)-dependent disruption of Miro1/KIF5B/tubulin complex is determined by Miro1 EF1 domain. Functionally, Miro1-dependent MiST is essential for autophagy/mitophagy that is attenuated in Miro1 EF1 mutants. Thus, Miro1 is a cytosolic Ca^(2+) sensor that decodes metazoan Ca^(2+) signals as MiST