Role of Endothelial Nitric Oxide Synthase in Breast Cancer

Breast cancer (BC) is the most common form of carcinoma and a primary cause of morbidity and mortality globally. Oxidative stress represents as an important factor in carcinogenesis and may play a role in initiation and progression of tumors. Oxidative stress–induced NO• damage to DNA includes a multitude of lesions, many of which are mutagenic and have multiple roles in cancer and aging. It is caused by an unfavorable balance between reactive oxygen species/reactive nitrogen species (ROS/RNS) and antioxidant defenses. ROS/RNS are generated during normal cellular metabolism, as a result of the influence of various environmental factors, as well as during pathological processes. Nitric oxide (NO•) is a ubiquitous, short-lived free radical produced from L-arginine by nitric oxide synthases (NOSs), and isoforms of NOS exist, depending on the site of origin: endothelial (eNOS), neuronal (nNOS), mitochondrial (mtNOS), and inducible (iNOS). eNOS is responsible for the endothelial synthesis of NO• and has shown to modulate cancer-related events such as inflammation, angiogenesis, apoptosis, cell cycle, invasion, and metastasis. Genetic studies also showed that eNOS gene polymorphisms are associated with the development of breast cancer. Therefore, selective targeting of eNOS may prove a potential strategy for prevention and treatment of breast cancer

Differential Evolution Biogeography Based Optimization for Linear Phase Fir Low Pass Filter Design

This paper presents an efficient way of designing Linear Phase Finite Impulse Response (FIR) Filter using hybrid Differential Evolution (DE) and Biogeography based optimization (BBO) algorithms. DE is a fast and robust evolutionary algorithm tool for global optimization. On the other hand, BBO uses migration operator to share information among solutions. FIR filter of order 20 is designed using fitness function that is based on minimization of maximum ripples in pass band and stop band of the filter response. The result obtained from Differential Evolution Biogeography Based Optimization (DEBBO) for the FIR low pass filter is good in convergence speed and solution quality in terms of pass band ripple, stop band ripple, transition width. Keywords: DE, BBO, DEBBO, Convergence, FIR Filter

BATTERY LESS, WSN-BASED HEALTH CARE UNIT THAT DRIVES A BACKSCATTERING TRANSMITTER

A potential means to fix minimize power consumption is using asynchronous sensor architectures that sample and transmit data only if a celebration is detected. A celebration-driven sensor consumes minimal power unless of course a celebration is detected. This paper presents the style of asynchronous ECG monitoring and knowledge transmission that cuts down on the circuitry power use of the sensor node without using power gating and requiring neither exterior energy storage devices nor a very like a time reference. The offset calibration is really a typical foreground calibration that's enabled during system startup or manual resetting. The sensor node that is remotely operated by the hub is really a peripheral device from the network that transmits data towards the hub in the recognition of the event. The information processing and memory allocation will be performed through the hub. Therefore, the sensor node can operate from hardly any power. The Two-output items of the ADC are combined and transmitted concurrently, otherwise information could be lost. Employing pulse duration modulation (PDM), the two-bit data stream is combined to create pulses with various time duration for upward conversion and downward conversion. Which means that the transmitter creates a pulse when LT signifies a conversion and U/D defines the time period of this pulse? Within the circuit created for backscattering data transmission, the pulsed signal modulates the 402 MHz RF signal received within the LC network, applying ON-OFF-Keying modulation through transistor. The LC-ADC has both magnitude resolution and time resolution. As time resolution is incorporated within the measurement, the general SNDR is degraded when compared to standalone LNA SNDR

Fine mapping and sequence analysis reveal a promising candidate gene encoding a novel NB-ARC domain derived from wild rice (Oryza officinalis) that confers bacterial blight resistance

Bacterial blight disease of rice caused by Xanthomonas oryzae pv. oryzae (Xoo) is one of the most serious constraints in rice production. The most sustainable strategy to combat the disease is the deployment of host plant resistance. Earlier, we identified an introgression line, IR 75084-15-3-B-B, derived from Oryza officinalis possessing broad-spectrum resistance against Xoo. In order to understand the inheritance of resistance in the O. officinalis accession and identify genomic region(s) associated with resistance, a recombinant inbred line (RIL) mapping population was developed from the cross Samba Mahsuri (susceptible to bacterial blight) × IR 75084-15-3-B-B (resistant to bacterial blight). The F2 population derived from the cross segregated in a phenotypic ratio of 3: 1 (resistant susceptible) implying that resistance in IR 75084-15-3-B-B is controlled by a single dominant gene/quantitative trait locus (QTL). In the F7 generation, a set of 47 homozygous resistant lines and 47 homozygous susceptible lines was used to study the association between phenotypic data obtained through screening with Xoo and genotypic data obtained through analysis of 7K rice single-nucleotide polymorphism (SNP) chip. Through composite interval mapping, a major locus was detected in the midst of two flanking SNP markers, viz., Chr11.27817978 and Chr11.27994133, on chromosome 11L with a logarithm of the odds (LOD) score of 10.21 and 35.93% of phenotypic variation, and the locus has been named Xa48t. In silico search in the genomic region between the two markers flanking Xa48t identified 10 putatively expressed genes located in the region of interest. The quantitative expression and DNA sequence analysis of these genes from contrasting parents identified the Os11g0687900 encoding an NB-ARC domain-containing protein as the most promising gene associated with resistance. Interestingly, a 16-bp insertion was noticed in the untranslated region (UTR) of the gene in the resistant parent, IR 75084-15-3-B-B, which was absent in Samba Mahsuri. The association of Os11g0687900 with resistance phenotype was further established by sequence-based DNA marker analysis in the RIL population. A co-segregating PCR-based INDEL marker, Marker_Xa48, has been developed for use in the marker-assisted breeding of Xa48t

Hierarchical Decision Model (HDM) for selecting a Microcontroller (MCU) for Smart Water Meter IoT

We’re entering a new era of computing technology that many are calling the Internet of Things (IoT) and its foundation is the intelligence that embedded processing provides. Integrated Microcontroller devices, which can provide the “real-time” embedded processing is a key requirement of most IoT applications. However the task of selecting the appropriate Microcontroller for an IoT application is more difficult than it seems. Traditional microcontroller selection and management practices are inadequate. This paper proposes a new methodology of selecting a Microcontroller for an IoT application. A hierarchical decision model (HDM) is utilized in the decision making activity and qualified expert\u27s opinions are used as measurements. There are four levels in the hierarchy: objective, criteria, sub-criteria, and alternatives. Expert panel is formed based on their background and expertise in order to minimize and balance any possible biases among the members. The criteria, sub-criteria and alternatives are evaluated and prioritized, according to their contribution to the objective, by quantifying the expert’s judgments. The results are validated using Inconsistency measure for the reliability of the experts and group agreement. The final decision from this new model will help in better selection methodology for assisting embedded designers to make the right decision and select the most suitable Microcontroller required for the design from the large pool of the Microcontrollers available in the market. This model can be improved in any future work by including other criteria maintainability, flexibility, Scalability, adding more alternatives and more expert panels