Parametric Probability Distribution Functions for Axon Diameters of Corpus Callosum

Axon diameter is an important neuroanatomical characteristic of the nervous system that alters in the course of neurological disorders such as multiple sclerosis. Axon diameters vary, even within a fiber bundle, and are not normally distributed. An accurate distribution function is therefore beneficial, either to describe axon diameters that are obtained from a direct measurement technique (e.g., microscopy), or to infer them indirectly (e.g., using diffusion-weighted MRI). The gamma distribution is a common choice for this purpose (particularly for the inferential approach) because it resembles the distribution profile of measured axon diameters which has been consistently shown to be non-negative and right-skewed. In this study we compared a wide range of parametric probability distribution functions against empirical data obtained from electron microscopy images. We observed that the gamma distribution fails to accurately describe the main characteristics of the axon diameter distribution, such as location and scale of the mode and the profile of distribution tails. We also found that the generalized extreme value distribution consistently fitted the measured distribution better than other distribution functions. This suggests that there may be distinct subpopulations of axons in the corpus callosum, each with their own distribution profiles. In addition, we observed that several other distributions outperformed the gamma distribution, yet had the same number of unknown parameters; these were the inverse Gaussian, log normal, log logistic and Birnbaum-Saunders distributions

Regulation of B cell fate by chronic activity of the IgE B cell receptor.

IgE can trigger potent allergic responses, yet the mechanisms regulating IgE production are poorly understood. Here we reveal that IgE+ B cells are constrained by chronic activity of the IgE B cell receptor (BCR). In the absence of cognate antigen, the IgE BCR promoted terminal differentiation of B cells into plasma cells (PCs) under cell culture conditions mimicking T cell help. This antigen-independent PC differentiation involved multiple IgE domains and Syk, CD19, BLNK, Btk, and IRF4. Disruption of BCR signaling in mice led to consistently exaggerated IgE+ germinal center (GC) B cell but variably increased PC responses. We were unable to confirm reports that the IgE BCR directly promoted intrinsic apoptosis. Instead, IgE+ GC B cells exhibited poor antigen presentation and prolonged cell cycles, suggesting reduced competition for T cell help. We propose that chronic BCR activity and access to T cell help play critical roles in regulating IgE responses

Microbial conversion of major ginsenoside Rb1 to minor ginsenoside Rd by Indian fermented food bacteria

Ginsenoside Rb1 is the predominant secondary metabolite (saponin) in Panax ginseng. Hydrolysis of the sugar residues in Rb1 yields more pharmaceutically active ginsenosides like Rd, Rg3, F2, Rh2 andC-K. Among them, the minor ginsenoside Rd enhances the differentiation of neural stem cells, protects neurons from neurotoxic chemicals, decreases urea nitrogen and creatinine in kidney. It also protects the kidney from apoptosis and DNA fragmentation caused by cancer and chemical drugs and is more useful therapeutically than the major ginsenoside Rb1. Bacteria showing b-glucosidase activity were isolated from fermented Indian food using esculin-MRS agar. Bacteria from Amla in sugar syrup and Boiled Amla in jaggery syrup converted ginsenoside Rb1 to minor ginsenoside Rd. TLC and HPLC analysis showed that with increase in incubation time the conversion of Rb1 to Rd also increased. The 16s rDNA sequence was determined and the bacteria showed 93% sequence similarity to Brumimicrobium mesophilum

Blind spectra decomposition of MRSI of the brain with tumor by sparse component analysis

Magnetic Resonance Spectroscopy Imaging (MRSI) is suitable for analyzing brain tumor metabolites in vivo. Several tissue types may exist in the tumor lesion area, and thus the measured MR spectra are a linear superposition of the constituent spectra of each of the different tissues. In this abstract we describe a novel approach, based on sparse component analysis, to recover the constituent spectra from the measured mixtures. The method is applied to experimental MRSI data of a brain with tumor lesion, and promising result is obtained. Compared to the existing BSD and cNMF approaches, this method is relatively simple and very fast.published_or_final_versio

Controlling False Positive/Negative Rates for Deep-Learning-Based Prostate Cancer Detection on Multiparametric MR images

Prostate cancer (PCa) is one of the leading causes of death for men worldwide. Multi-parametric magnetic resonance (mpMR) imaging has emerged as a non-invasive diagnostic tool for detecting and localising prostate tumours by specialised radiologists. These radiological examinations, for example, for differentiating malignant lesions from benign prostatic hyperplasia in transition zones and for defining the boundaries of clinically significant cancer, remain challenging and highly skill-and-experience-dependent. We first investigate experimental results in developing object detection neural networks that are trained to predict the radiological assessment, using these high-variance labels. We further argue that such a computer-assisted diagnosis (CAD) system needs to have the ability to control the false-positive rate (FPR) or false-negative rate (FNR), in order to be usefully deployed in a clinical workflow, informing clinical decisions without further human intervention. However, training detection networks typically requires a multi-tasking loss, which is not trivial to be adapted for a direct control of FPR/FNR. This work in turn proposes a novel PCa detection network that incorporates a lesion-level cost-sensitive loss and an additional slice-level loss based on a lesion-to-slice mapping function, to manage the lesion- and slice-level costs, respectively. Our experiments based on 290 clinical patients concludes that 1) The lesion-level FNR was effectively reduced from 0.19 to 0.10 and the lesion-level FPR was reduced from 1.03 to 0.66 by changing the lesion-level cost; 2) The slice-level FNR was reduced from 0.19 to 0.00 by taking into account the slice-level cost; (3) Both lesion-level and slice-level FNRs were reduced with lower FP/FPR by changing the lesion-level or slice-level costs, compared with post-training threshold adjustment using networks without the proposed cost-aware training. For the PCa application of interest, the proposed CAD system is capable of substantially reducing FNR with a relatively preserved FPR, therefore is considered suitable for PCa screening applications

Effects of Copper Exchange Levels on Complexation of Ammonia in Cu (II)-exchanged X Zeolite

Copper (II)-exchanged faujasite-X zeolites at various loadings of copper per unit cell of zeolites were prepared and then exposed to ammonia. The copper ammine complexes of the various copper levels per unit cell were characterized and analyzed by a combination of diffuse reflectance, X-ray powder diffraction, FT-infrared spectroscopy, electron paramagnetic resonance and nuclear magnetic resonance spectroscopic methods. At low copper exchange levels (<5 copper atoms per unit cell), the major complex is [Cu(Ozeo)2(NH3)2]2+ and it is strongly bound to the zeolite framework walls at single four ring sites (site III). Above five copper atoms per unit cell, the major complex becomes [Cu(NH3)4]2+ and it is least interacting with the zeolite framework walls. The [Cu(NH3)4]2+ complex which was formed at higher copper levels per unit cell was most favoured by the presence of maximal amount of ammonia.Keywords: Cation Exchange, Catalysis, Copper, Complexation, Copper AmminesAttached PDF and Supplementary Fil

Collaborative Gaze Channelling for Improved Cooperation During Robotic Assisted Surgery

The use of multiple robots for performing complex tasks is becoming a common practice for many robot applications. When different operators are involved, effective cooperation with anticipated manoeuvres is important for seamless, synergistic control of all the end-effectors. In this paper, the concept of Collaborative Gaze Channelling (CGC) is presented for improved control of surgical robots for a shared task. Through eye tracking, the fixations of each operator are monitored and presented in a shared surgical workspace. CGC permits remote or physically separated collaborators to share their intention by visualising the eye gaze of their counterparts, and thus recovers, to a certain extent, the information of mutual intent that we rely upon in a vis-à-vis working setting. In this study, the efficiency of surgical manipulation with and without CGC for controlling a pair of bimanual surgical robots is evaluated by analysing the level of coordination of two independent operators. Fitts' law is used to compare the quality of movement with or without CGC. A total of 40 subjects have been recruited for this study and the results show that the proposed CGC framework exhibits significant improvement (p<0.05) on all the motion indices used for quality assessment. This study demonstrates that visual guidance is an implicit yet effective way of communication during collaborative tasks for robotic surgery. Detailed experimental validation results demonstrate the potential clinical value of the proposed CGC framework. © 2012 Biomedical Engineering Society.link_to_subscribed_fulltex

Numerical simulation of “sand-like” polymer flow during rotational moulding using smoothed particle hydrodynamics method

Rotational moulding is a versatile polymer shaping process used to create enclosed parts from powdered precursors using heat and multi-axis rotation. Controlling the heating process and mould motion is critical to producing high-quality parts, and failures due to incorrect mould coverage or variable wall thickness are common. To date, limited simulation tools exist to predict the motion of the powder within the mould, and operators rely on unreliable prior experience to avoid defects. This paper presents an SPH simulation framework to predict particle flow patterns and powder contact time within a rotating mould. The powder-to-wall contact time was derived from the transient rigid body force (RBF) of different sensors on the mould. The method was compared with the results of DEM simulation and validated by the particle flow pattern of two experimental results. Results showed that the SPH method was capable of simulating particle flow macroscopic properties. The great computing efficiency of SPH compared to DEM simulation was also demonstrated

Observation of the Fractional Quantum Hall Effect in Graphene

When electrons are confined in two dimensions and subjected to strong magnetic fields, the Coulomb interactions between them become dominant and can lead to novel states of matter such as fractional quantum Hall liquids. In these liquids electrons linked to magnetic flux quanta form complex composite quasipartices, which are manifested in the quantization of the Hall conductivity as rational fractions of the conductance quantum. The recent experimental discovery of an anomalous integer quantum Hall effect in graphene has opened up a new avenue in the study of correlated 2D electronic systems, in which the interacting electron wavefunctions are those of massless chiral fermions. However, due to the prevailing disorder, graphene has thus far exhibited only weak signatures of correlated electron phenomena, despite concerted experimental efforts and intense theoretical interest. Here, we report the observation of the fractional quantum Hall effect in ultraclean suspended graphene, supporting the existence of strongly correlated electron states in the presence of a magnetic field. In addition, at low carrier density graphene becomes an insulator with an energy gap tunable by magnetic field. These newly discovered quantum states offer the opportunity to study a new state of matter of strongly correlated Dirac fermions in the presence of large magnetic fields

Prenatal Lead Levels, Plasma Amyloid β Levels, and Gene Expression in Young Adulthood

Background: Animal studies suggest that early-life lead exposure influences gene expression and production of proteins associated with Alzheimer’s disease (AD)