The role of androgens in fetal growth: observational study in two genetic models of disordered androgen signalling.

OBJECTIVE: To examine the role of androgens on birth weight in genetic models of altered androgen signalling. SETTING: Cambridge Disorders of Sex Development (DSD) database and the Swedish national screening programme for congenital adrenal hyperplasia (CAH). PATIENTS: (1) 29 girls with XY karyotype and mutation positive complete androgen insensitivity syndrome (CAIS); (2) 43 girls and 30 boys with genotype confirmed CAH. MAIN OUTCOME MEASURES: Birth weight, birth weight-for-gestational-age (birth weight standard deviation score (SDS)) calculated by comparison with national references. RESULTS: Mean birth weight SDS in CAIS XY infants was higher than the reference for girls (mean, 95% CI: 0.4, 0.1 to 0.7; p=0.02) and was similar to the national reference for boys (0.1, -0.2 to 0.4). Birth weight SDS in CAH girls was similar to the national reference for girls (0.0, -0.2 to 0.2) and did not vary by severity of gene mutation. Birth weight SDS in CAH boys was also similar to the national reference for boys (0.2, -0.2 to 0.6). CONCLUSION: CAIS XY infants have a birth weight distribution similar to normal male infants and birth weight is not increased in infants with CAH. Alterations in androgen signalling have little impact on birth weight. Sex dimorphism in birth size is unrelated to prenatal androgen exposure.

Neuro-Fuzzy genetic system for selection of construction project managers

Choosing a project manager for a construction project—particularly, large projects—is a critical project decision. The selection process involves different criteria and should be in accordance with company policies and project specifications. Traditionally, potential candidates are interviewed and the most qualified are selected in compliance with company priorities and project conditions. Precise computing models that could take various candidates’ information into consideration and then pinpoint the most qualified person with a high degree of accuracy would be beneficial. On the basis of the opinions of experienced construction company managers, this paper, through presenting a fuzzy system, identifies the important criteria in selecting a project manager. The proposed fuzzy system is based on IF-THEN rules; a genetic algorithm improves the overall accuracy as well as the functions used by the fuzzy system to make initial estimates of the cluster centers for fuzzy c-means clustering. Moreover, a back-propagation neutral network method was used to train the system. The optimal measures of the inference parameters were identified by calculating the system’s output error and propagating this error within the system. After specifying the system parameters, the membership function parameters—which by means of clustering and projection were approximated—were tuned with the genetic algorithm. Results from this system in selecting project managers show its high capability in making high-quality personnel predictions

A neuro-inspired method for data rate limited feedback control

The nervous system implements a networked control system in which the plants take the form of limbs, the controller is the brain, and neurons form the communication channels. Unlike standard networked control architectures, there is no periodic sampling, and the fundamental units of communication contain little numerical information. This paper describes a novel communication channel, modeled after spiking neurons, in which the transmitter integrates an input signal and sends out a spike when the integral reaches a threshold value. The reciever then filters the sequence of spikes to approximately reconstruct the input signal. It is shown that for appropriate choices of channel parameters, stable feedback control over these spiking channels is possible. Furthermore, good tracking performance can be achieved. The data rate of the channel increases linearly with the size of the inputs. Thus, when placed in a feedback loop, small loop gains imply a low data rate. ©2010 IEEE.

Towards the formation of neuro-transistor artificial chemical synapse

Highly sensitive biosensor for detection of acetylcholine (ACh) and competitive acetylcholinesterase (AChE) inhibitor, eserine, is investigated. Peculiar microelectronic configuration of an ion-sensitive field-effect transistor (ISFET) in addition to a right choice of the pH-transducing nanolayers allows recording a response of the enzyme-modified ISFET (EnFET) to a wide range of ACh concentrations. We demonstrate a remarkable improvement of at least three orders of magnitude in dose response to ACh. Described bioelectronic system reveals clear response, when the catalytic activity of the immobilized AChE is inhibited in a reversible manner by eserine, competitive inhibitor of AChE. ©2007 IEEE.

Single event molecular signalling for estimation and control

Cell biology is characterised by low molecule numbers and coupled stochastic chemical reactions with intrinsic noise permeating and dominating the interactions between molecules. Recent work [9] has shown that in such environments there are hard limits on the accuracy with which molecular populations can be controlled and estimated. These limits are predicated on a continuous diffusion approximation of the target molecule (although the remainder of the system is non-linear and discrete). The principal result of [9] assumes that the birth rate of the signalling species is linearly dependent on the target molecule population size. In this paper, we investigate the situation when the entire system is kept discrete, and arbitrary non-linear coupling is allowed between the target molecule and downstream signalling molecules. In this case it is possible, by relying solely on the event triggered nature of control and signalling reactions, to define non-linear reaction rate modulation schemes that achieve improved performance in certain parameter regimes. These schemes would not appear to be biologically relevant, raising the question of what are an appropriate set of assumptions for obtaining biologically meaningful results. © 2013 EUCA.