Effect of body mass index and waist circumference on renal function in hypertensive chronic kidney disease

AIM OF THE STUDY : The aim of the study is to investigate the association of Body Mass Index (BMI) and Waist Circumference(WC) with Hypertensive Chronic Kidney Disease. MATERIALS AND METHODS: 40 study group with Hypertensive Chronic Kidney Disease (HT-CKD; Stage I–II) in the age group of between 18-70 yrs and 40 control group of same age were included in this study. In the study group, group-1 included HT- CKD (stage I-II) patients with normal BMI, normal waist circumference, group-2 included patients with normal BMI, high waist circumference and group-3 included patients with normal waist circumference and high BMI. This case-control study was conducted in Thanjavur Medical College, Thanjavur. Patients with Chronic Kidney Disease (stage I-II) and Hypertension, patients who were non-diabetic and free from cardiovascular complications were included. Subjects with history of malignancies, or with inflammatory disorders, patients with the presence of major cardiovascular events during last 3 months prior to study, Diabetes Mellitus, heart failure and hereditary renal diseases were excluded from this study. Informed written consent from the study and control groups was obtained. Ethical committee approval was obtained before starting the study. For this study clinical history was recorded and physical examination including body weight, height, waist & hip circumferences were measured. Waist hip ratio (WHR) was calculated. Blood Pressure was recorded.24 hrs urine sample was collected for Albumin Excretion Rate (AER). Blood urea and Serum creatinine were estimated. Glomerular Filtration Rate (GFR) was estimated by using the Modification of Diet in Renal Disease (MDRD) formula. The results were analyzed by using student ‘t’ test and ANOVA study. Correlation of BMI and WC, WHR with various renal functions were done using Pearson’s Correlation test. P < 0.05 was considered as statistically significant. RESULTS: There was statistically significant (p < 0.05) correlation between BMI with e GFR decline and increased blood urea level and no significant correlation between BMI with serum creatinine level elevation and elevated AER level. However, statistically significant correlation exist with waist circumference (p < 0.01) and waist hip ratio (p < 0.01) for the parameters like e GFR, serum creatinine and AER. So WC and WHR (central obesity) were statistically significantly (p < 0.01) correlated with renal function decline. CONCLUSION: This study revealed that abdominal obesity was statistically significantly correlated with renal function decline than increase in BMI in hypertensive chronic kidney disease (stage I-II)

Evaluate Various Techniques of Data Warehouse and Data Mining with Web Based Tool

All enterprise has a crucial role to play proficiently and productively to maintain its survival in the market and increase its profitability shares. This challenge becomes more complicated with advancement in information technology along with increasing volume and complexity of information. Currently, success of an enterprise is not just the result of efforts by resources but also depends upon its ability to mine the data from the stored information. Data warehousing is a compilation of decision making procedure to integrate and manage the large variant data efficiently and scientifically. Data mining shores up organizations, scrutinize their data more effectively and proficiently to achieve valuable information, that can reward an intelligent and strategic decision making. Data mining has several techniques and maths algorithms which are used to mine large data to increase the organization performance and strategic decision-making. Clustering is a powerful and widely accepted data mining method used to segregate the large data sets into group of similar objects and provides to the end user a sophisticated view of database. This study discusses the basic concept of clustering; its meaning and applications, especially in business for division and selection of target market. This technique is useful in marketing or sales side and, for example, sends a promotion to the right target for that product or service. Association is a known data mining techniques. A pattern is inferred based on an affiliation between matter of same business transaction. It is also referred as relation technique. Large enterprises depend on this technique to research customer's buying preferences. For instance, to track people's buying behavior, retailers might categorize that a customer always buy sambar onion when they buy dal, and therefore suggest that the next time that they buy dal they might also want to buy onion. Classification – it is one of the data mining concept differs from the above in a way it is used on machine learning and makes use of techniques used in maths such as linear programming, decision trees, neural network. In classification, enterprises try to build tool that can learn how to classify the data items into groups. For instance, a company can define a classification in the application that “given all records of employees who offered to resign from the company, predict the number of individuals who are likely to resign from the company in future.” Under such a scenario, the company can classify the records of employees into two groups that namely “separate” and “retain”. It can use its data mining software to classify the employees into separate groups created earlier. Fuzzy logic resembles human reasoning greatly in handling of imperfect information and can be used as a flexibility tool for soften the boundaries in classification that suits the real problems more efficiently. The present study discusses the meaning of fuzzy logic, its applications and different features. A tool to be build to check data mining algorithms and algorithm behind the model, apply clustering method as a sample in tool to select the training data out of the large data base and reduce complexity and time while computing. K-nearest neighbor method can be used in many applications from general to specific to find the requested data out of huge data. Decision trees – A decision tree is a structure that includes a root node, branches, and leaf nodes. Every one interior node signify a test on an attribute, each branch denotes the result of a test, and each leaf node represents a class label. The topmost node in the tree is the root node. Within the decision tree, we start with a simple question that has multiple answers. Each respond show the way to a further query to help classify or identify the data so that it can be categorized, or so that a prediction can be made based on each answer. Regression analysis is the data mining method of identifying and analyzing the relationship between variables. It is used to identify the likelihood of a specific variable, given the presence of other variables. Outlier detection technique refers to observation of data items in the dataset which do not match an expected pattern or expected behaviour. This technique can be used in a variety of domains, such as intrusion, detection, fraud or fault detection, etc. Outer detection is also called Outlier Analysis or Outlier mining. Sequential Patterns technique helps to find out similar patterns or trends in transaction data for definite period

A Low-Power and High-Speed Frequency Multiplier for DLL-Based Clock Generator

A low-power and high-speed frequency multiplier for a delay-locked loop-based clock generator is proposed to generate a multiplied clock with different range of frequencies. The modified edge combiner consumes low power and achieves a high-speed operation. The proposed frequency multiplier overcomes a deterministic jitter problem by reducing the delay difference between positive- and negative-edge generation paths. The proposed frequency multiplier is implemented in a 0.13-µm CMOS process technology achieved power consumption to a frequency ratio of 2.9 µW/MHz, and has the multiplication ratios of 16, and an output range of 100 MHz–3.3 GHz

Cicatricial alopecia: Clinical, dermascopy and histopathological study

INTRODUCTION: Cicatricial alopecia is a scarring form of Alopecia due to permanent destruction of hair follicles. It can be of Primary or Secondary cause. Cicatricial alopecia leads to considerable disfigurement of the scalp which can be a major psychosocial burden. This study is conducted to emphasize on the early diagnostic features based on clinical, dermascopic and histopathological findings and identifying the underlying cause of cicatricial alopecia. AIM OF THE STUDY: To determine in the cases of cicatricial alopecia the following: 1. To study the clinical pattern of the disease. 2. To study the dermascopic features of the disease. 3. To study the histopathological findings of the disease. 4. To identify various etiological causes of the disease. MATERIALS AND METHODS: Study Design : Prospective cohort study. Sample : 50 cases. METHODS: This study was carried from November 2016 to September 2017 in Rajiv Gandhi Govt. General Hospital. Detailed clinical history was obtained.Clinical and Dermascopy examination was done. Scalp biopsy was done and sent for histopathology. Routine investigations of all patients were performed for all. RESULTS: In my study, it was seen that maximum number of cases of cicatrical alopecia were of LPP (30%) followed by 26% of DLE. Amongst the less frequent causes were Non specific cicatricial alopecia (8%)and Pseudo pelade of Brocq (6%) acne keloidalis nuchae (4%), keratosis spinulosa declavans and systemic lupus erythematoses 2% each. Amongst the secondary causes of cicatricial alopecia trauma was the most common (4%) followed by 2% each of radiation, lipoid proteinosis, Gunthers disease, and scalp tumors. In dermascopic features absent follicular opening was seen in almost all patients. Commonest histopathological feature of cicatricial alopecia was follicular plugging (18%) followed by basal cell vacuolization and hyperkeratosis (16%) each. CONCLUSION: Scalp hair is a significant cosmetic element and prompt diagnosis and aggressive management is crucial in preventing permanent disfigurement. Dermatoscopy provides a useful aid for the diagnosis of cicatricial alopecia

An IOT based smart metering development for energy management system

The worldwide energy demand is increasing and hence necessity measures need to be taken to reduce the energy wastage with proper metering infrastructure in the buildings. A Smart meter can be used to monitor electricity consumption of customers in the smart grid technology. For allocating the available resources proper energy demand management is required. During the past years, various methods are being utilized for energy demand management to precisely calculate the requirements of energy that is yet to come. A large system presents a potential esteem to execute energy conservation as well as additional services linked to energy services, extended as a competent with end user is executed. The supervising system at the utilities determines the interface of devices with significant advantages, while the communication with the household is frequently proposing particular structures for appropriate buyer-oriented implementation of a smart meter network. Also, this paper concentrates on the estimation of vitality utilization. In this paper energy is measured in units and also product arrangement is given to create bill for energy consumption and implementing in LabVIEW software. An IOT based platform is created for remote monitoring of the metering infrastructure in the real time. The data visualization is also carried out in webpage and the data packet loss is investigated in the remote monitoring of the parameters

Cent CORE: Centralized Cloud Oriented Requirement Engineering Strategy for Tracking and Elicitation of Dynamic Requirements

Requirement Engineering is one of the most important stages of Software Engineering. Eliciting requirements is highly critical and a complex process as the software end product totally depends on the quality of requirements that were collected. The property of the requirements is dynamic that keeps changing and constantly evolving. The Traditional Strategies for Requirement Engineering lacked organization and change management was entirely manual which consumed a lot of time and skilled labor. A centralized strategy for Elicitation of Dynamic Requirements using the concept of Requirement Cloud is proposed with high level of organization and structuring. A novel idea of using Cloud Storage Service for Requirement Engineering is implemented using a heuristics approach. Change management is incorporated and a few activities like requirements document generation is automated in this approach. Finally a survey between the Traditional Requirement Engineering and Proposed Cloud Methodology is conducted to prove the proposed methodology is better than the traditional strategies of Requirement Engineering

Discovery of ST1 centers in natural diamond

The ST1 center is a point defect in diamond with bright fluorescence and a mechanism for optical spin initialization and readout. The center has impressive potential for applications in diamond quantum computing as a quantum bus to a register of nuclear spins. This is because it has an exceptionally high readout contrast and, unlike the well-known nitrogen-vacancy center, it does not have a ground state electronic spin that decoheres the nuclear spins. However, its chemical structure is unknown and there are large gaps in our understanding of its properties. We present the discovery of ST1 centers in natural diamond. Our experiments identify interesting power dependence of the center's optical dynamics and reveal new electronic structure. We also present a theory of its electron-phonon interactions, which we combine with previous experiments, to shortlist likely candidates for its chemical structure

Clinical Benefit from Docetaxel +/- Ramucirumab Is Not Associated with Mutation Status in Metastatic Non-Small-Cell Lung Cancer Patients Who Progressed on Platinum Doublets and Immunotherapy

Docetaxel +/- ramucirumab remains the standard-of-care therapy for patients with metastatic non-small-cell lung cancer (NSCLC) after progression on platinum doublets and immune checkpoint inhibitors (ICIs). The aim of our study was to investigate whether the cancer gene mutation status was associated with clinical benefits from docetaxel +/- ramucirumab. We also investigated whether platinum/taxane-based regimens offered a better clinical benefit in this patient population. A total of 454 patients were analyzed (docetaxel +/- ramucirumab n=381; platinum/taxane-based regimens n=73). Progression-free survival (PFS) and overall survival (OS) were compared among different subpopulations with different cancer gene mutations and between patients who received docetaxel +/- ramucirumab versus platinum/taxane-based regimens. Among patients who received docetaxel +/- ramucirumab, the top mutated cancer genes included TP53 (n=167), KRAS (n=127), EGFR (n=65), STK11 (n=32), ERBB2 (HER2) (n=26), etc. None of these cancer gene mutations or PD-L1 expression was associated with PFS or OS. Platinum/taxane-based regimens were associated with a significantly longer mQS (13.00 m, 95% Cl: 11.20-14.80 m versus 8.40 m, 95% Cl: 7.12-9.68 m, LogRank P=0.019) than docetaxel +/- ramcirumab. Key prognostic factors including age, histology, and performance status were not different between these two groups. In conclusion, in patients with metastatic NSCLC who have progressed on platinum doublets and ICIs, the clinical benefit from docetaxel +/- ramucirumab is not associated with the cancer gene mutation status. Platinum/taxane-based regimens may offer a superior clinical benefit over docetaxel +/- ramucirumab in this patient population

Maturation-Dependent Licensing of Naive T Cells for Rapid TNF Production

The peripheral naïve T cell pool is comprised of a heterogeneous population of cells at various stages of development, which is a process that begins in the thymus and is completed after a post-thymic maturation phase in the periphery. One hallmark of naïve T cells in secondary lymphoid organs is their unique ability to produce TNF rapidly after activation and prior to acquiring other effector functions. To determine how maturation influences the licensing of naïve T cells to produce TNF, we compared cytokine profiles of CD4+ and CD8+ single positive (SP) thymocytes, recent thymic emigrants (RTEs) and mature-naïve (MN) T cells during TCR activation. SP thymocytes exhibited a poor ability to produce TNF when compared to splenic T cells despite expressing similar TCR levels and possessing comparable activation kinetics (upregulation of CD25 and CD69). Provision of optimal antigen presenting cells from the spleen did not fully enable SP thymocytes to produce TNF, suggesting an intrinsic defect in their ability to produce TNF efficiently. Using a thymocyte adoptive transfer model, we demonstrate that the ability of T cells to produce TNF increases progressively with time in the periphery as a function of their maturation state. RTEs that were identified in NG-BAC transgenic mice by the expression of GFP showed a significantly enhanced ability to express TNF relative to SP thymocytes but not to the extent of fully MN T cells. Together, these findings suggest that TNF expression by naïve T cells is regulated via a gradual licensing process that requires functional maturation in peripheral lymphoid organs