The Role of microRNAs in Development of Colitis-Associated Colorectal Cancer

Colorectal cancer (CRC) is the third most deadly cancer worldwide, and inflammatory bowel disease (IBD) is one of the critical factors in CRC carcinogenesis. IBD is responsible for an unphysiological and sustained chronic inflammation environment favoring the transformation. MicroRNAs (miRNAs) belong to a class of highly conserved short single-stranded segments (18–25 nucleotides) non-coding RNA and have been extensively discussed in both CRC and IBD. However, the role of miRNAs in the development of colitis-associated CRC (CAC) is less clear. The aim of this review is to summarize the major upregulated (miR-18a, miR-19a, miR-21, miR-31, miR-155 and miR-214) and downregulated (miR-124, miR-193a-3p and miR-139-5p) miRNAs in CAC, and their roles in genes’ expression modulation in chronic colonic-inflammation-induced carcinogenesis, including programmed cell-death pathways. These miRNAs dysregulation could be applied for early CAC diagnosis, to predict therapy efficacy and for precision treatment.     

A Case Report of Germline Compound Heterozygous Mutations in the BRCA1 Gene of an Ovarian and Breast Cancer Patient

The germline carrier of the BRCA1 pathogenic mutation has been well proven to confer an increased risk of breast and ovarian cancer. Despite BRCA1 biallelic pathogenic mutations being extremely rare, they have been reported to be embryonically lethal or to cause Fanconi anemia (FA). Here we describe a patient who was a 48-year-old female identified with biallelic pathogenic mutations of the BRCA1 gene, with no or very subtle FA-features. She was diagnosed with ovarian cancer and breast cancer at the ages of 43 and 44 and had a strong family history of breast and gynecological cancers.     

Analysis and optimization of DS-CDMA systems with time-limited partial response chip waveforms

Conventional direct sequence code division multiple access systems (DS-CDMA) using offset quadrature phase shift key (OQPSK) usually employ a strictly bandlimited partial response square-root raised cosine pulse as the chip waveform. They have the disadvantage of large envelope fluctuation that will incur performance degradation due to the intermodulation and bandwidth enlargement caused by post nonlinear processing. To improve the performance of DS-CDMA systems, the chip waveform and receiver should be properly selected. This paper presents a systematic performance analysis of a matched filter receiver and zero-forcing filter (ZF) receiver for DS-CDMA using a time-limited partial response chip waveform. Nevertheless the systematic performance analysis is applicable to bandlimited chip pulse as well. For the zero-forcing filters, we propose to select the frequency responses that satisfy the first Nyquist criterion. With this class of filters, we can choose the roll-off factor to minimize the total power of multiple access interference and noise power. The zero-forcing filter with proper choice of roll-off factor, referred to as optimum ZF, yields a performance better than the matched filter counterpart. The bit error rate (BER) performance of the optimum ZF with superposed quadrature amplitude modulation signal as the time pulse waveform is evaluated. It is shown that the optimum ZF provides better BER performance than conventional OQPSK and minimum shift keying, and its envelope uniformity is much better than that of OQPSK.     

Derivation of a second-order switching surface in the boundary control of buck converters

A second-order switching surface in the boundary control of buck converters is derived in this letter. The formulated switching surface can make the overall converter exhibit better steady-state and transient behaviors than the one with a first-order switching surface. The switching surface is derived by estimating the state trajectory movement after a switching action, resulting in a high state trajectory velocity along the switching surface. This phenomenon accelerates the trajectory moving toward the target operating point. The proposed control scheme has been successfully applied to a 120-W buck converter. The large-signal performance and a comparison with the first-order switching surface have been studied.     

On the capacities of bipartite Hamiltonians and unitary gates

We consider interactions as bidirectional channels. We investigate the capacities for interaction Hamiltonians and nonlocal unitary gates to generate entanglement and transmit classical information. We give analytic expressions for the entanglement generating capacity and entanglement-assisted one-way classical communication capacity of interactions, and show that these quantities are additive, so that the asymptotic capacities equal the corresponding 1-shot capacities. We give general bounds on other capacities, discuss some examples, and conclude with some open questions.     

Assessment of Anger and Aggression in Male Offenders With Developmental Disabilities.

Systematic assessment of anger among people with developmental disabilities has been lacking, especially for hospital inpatients. Reliability and validity of anger self-report psychometric scales were investigated with 129 male patients, mostly forensic. Anger prevalence and its relationship to demographic, cognitive, and personality variables and to hospital assaultive behavior were examined. High internal and intermeasure consistency, and some concurrent validity with staff ratings, were found. Retrospective validity regarding physically assaultive behavior in the hospital was obtained. Hierarchical regressions revealed that patient-reported anger was a significant predictor of assaults postadmission, controlling for age, length of stay, IQ, violence offense history, and personality variables. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Classification of audio radar signals using radial basis function neural networks

Radial basis function (RBF) neural networks are used to classify real-life audio radar signals that are collected by a ground surveillance radar mounted on a tank. Currently, a human operator is required to operate the radar system to discern among signals bouncing off tanks, vehicles, planes, and so on. The objective of this project is to investigate the possibility of using a neural network to perform this target recognition task, with the aim of reducing the number of personnel required in a tank. Different signal classification methods in the neural net literature are considered. The first method employs a linear autoregressive (AR) model to extract linear features of the audio data, and then perform classification on these features, i.e, the AR coefficients. AR coefficient estimations based on least squares and higher order statistics are considered in this study. The second approach uses nonlinear predictors to model the audio data and then classifies the signals according to the prediction errors. The real-life audio radar data set used here was collected by an AN/PPS-15 ground surveillance radar and consists of 13 different target classes, which include men marching, a man walking, airplanes, a man crawling, and boats, etc. It is found that each classification method has some classes which are difficult to classify. Overall, the AR feature extraction approach is most effective and has a correct classification rate of 88% for the training data and 67% for data not used for training.