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| 1 | Over expression of resistin in adipose tissue of the obese induces insulin resistance显示文摘AIM: To compare resistin mRNA expression in subcutaneous adipose tissue (SAT) and its correlation with insulin resistance (IR) in postmenopausal obese women. METHODS: A total of 68 postmenopausal women (non obese = 34 and obese = 34) were enrolled for the study. The women of the two groups were age matched (49-70 years). Fasting blood samples were collected at admission and abdominal SAT was obtained during surgery for gall bladder stones or hysterectomy. Physical parameters [age, height, weight, body mass index (BMI)] were measured. Biochemical (plasma insulin and plasma glucose) parameters were estimated by enzymatic methods. RNA was isolated by the Trizol method.SAT resistin mRNA expression was done by real time- reverse transcription polymerase chain reaction (RT-PCR) by using Quanti Tect SYBR Green RT-PCR master mix. Data was analyzed using independent Student's t test, correlation and simple linear regression analysis. RESULTS: The mean weight (52.81 ± 8.04 kg vs 79.56 ± 9.91 kg; P < 0.001), BMI (20.23 ± 3.05 kg/m 2 vs 32.19 ± 4.86 kg/m 2 ; P < 0.001), insulin (8.47 ± 3.24 U/mL vs 14.67 ± 2.18 U/mL; P < 0.001), glucose (97.44 ± 11.31 mg/dL vs 109.67 ± 8.02 mg/dL; P < 0.001) and homeostasis model assessment index (2.01 ± 0.73 vs 3.96 ± 0.61; P < 0.001) were significantly higher in postmenopausal obese women compared to postmenopausal non obese women. The mean serum resistin level was also significantly higher in postmeno-pausal obese women compared to postmenopausal non obese women (9.05 ± 5.15 vs 13.92 ± 6.32, P < 0.001). Furthermore, the mean SAT resistin mRNA expression was also significantly (0.023 ± 0.008 vs 0.036 ± 0.009; P < 0.001) higher and over expressed 1.62 fold (upregulated) in postmenopausal obese women compared to postmenopausal non obese women. In postmeno-pausal obese women, the relative SAT resistin mRNA expression showed positive (direct) and significant correlation with BMI (r = 0.78, P < 0.001) and serum resistin (r = 0.76, P < 0.001). Furthermore, the SAT resistin mRNA expression in postmenopausal obese women also showed significant and direct association (r = 0.45, P < 0.01) with IR, while in postmenopausal non obese women it did not show any association (r = -0.04, P > 0.05). CONCLUSION: Increased SAT resistin mRNA expres-sion probably leads to inducing insulin resistance and thus may be associated with obesity-related disorders in postmenopausal obese women. | Sadashiv Sunita Tiwari S Dhananjai Bhola N Paul Sandeep Kumar Abhijit Chandra Mahendra PS Negi | 2012 | World Journal of Diabetes2012，3，7： | 10 |
| 2 | The GEON service-oriented architecture for Earth Science applications显示文摘The Geosciences Network(GEON)project has been developing cyberinfrastructure for data sharing in the Earth Science community based on a serviceoriented architecture.The layered architecture consists of Core,Middleware,and Applications services.Core services provide system-level functions(e.g.user authentication),Middleware services provide generic capabilities(e.g.catalog search),and Application services provide functions that users directly interact with,including applications that are specific to Earth Sciences.The GEON‘service stack’includes a standardized set of these services and the corresponding software modules.The GEON Portal provides Web-based access to these services via a set of portlets.This service-oriented approach has enabled GEON to expand to new partner sites and leverage GEON services for other projects.To facilitate interoperation in a distributed geoinformatics environment,GEON is focusing on standards for distributed search across federated catalogs. | Chaitan Baru Sandeep Chandra Kai Lin Ashraf Memon Choonhan Youn | 2009 | International Journal of Digital Earth2009，2，S01： | 3 |
| 3 | Gallbladder cancer with tumor thrombus in the superior vena cava显示文摘BACKGROUND:Gastrointestinal cancers,especially pancreatobiliary cancers,are frequently associated with or are complicated by thromboembolic phenomena due to hypercoagulability and/or altered venous drainage,especially of the abdomen and lower limbs.This report describes an unusual and interesting case of gallbladder carcinoma developing a viable tumor thrombus in the superior vena cava(SVC)with resultant SVC obstruction,while on gefitinibbased anti-epidermal growth factor receptor(EGFR)therapy.METHODS:A 60-year-old woman was incidentally diagnosed to have gallbladder cancer on cholecystectomy.She had disease recurrence and received systemic chemotherapy followed by gefitinib-based anti-EGFR therapy.Subsequently,while on gefitinib-based therapy,she presented with clinical signs and symptoms suggestive of SVC thrombosis.RESULTS:A whole body PET scan revealed a metabolically active tumor thrombus in the SVC,besides other sites of metabolically active disease inclusive of the lung parenchyma, lymph nodes and abdomen.She was treated with antithrombotics and external beam radiotherapy directed to the SVC thrombus leading to symptomatic relief.She continues to survive on the day of writing this report.CONCLUSIONS:This rare complication,though theoretically possible,is unreported because of the short overall survival of advanced gallbladder cancer patients.This highlights that with the availability of better chemotherapeutic/biotherapeutic agents for increasing in the lifespan of cancer patients,we may come across such cases more frequently in the future. | Sandeep Batra Dinesh Chandra Doval Ullas Batra Pandalanghat Suresh Amit Dhiman Vineet Talwar | 2010 | Hepatobiliary & Pancreatic Diseases International2010，9，3： | 2 |
| 4 | TEAM Network: Building Web-based Data Access and Analysis Environments for Ecosystem Services显示文摘 | Choonhan Youn Sandeep Chandra Eric H. Fegraus Kai Lin Chaitan Baru | 2011 | Procedia Computer Science2011，，： | 1 |
| 5 | Analysis and Predictions of Spread, Recovery, and Death Caused by COVID-19 in India显示文摘The novel coronavirus outbreak was first reported in late December 2019 and more than 7 million people were infected with this disease and over 0.40 million worldwide lost their lives. The first case was diagnosed on30 January 2020 in India and the figure crossed 0.24 million as of 6 June 2020. This paper presents a detailed study of recently developed forecasting models and predicts the number of confirmed, recovered, and death cases in India caused by COVID-19. The correlation coefficients and multiple linear regression applied for prediction and autocorrelation and autoregression have been used to improve the accuracy. The predicted number of cases shows a good agreement with 0.9992 R-squared score to the actual values. The finding suggests that lockdown and social distancing are two important factors that can help to suppress the increasing spread rate of COVID-19. | Rajani Kumari Sandeep Kumar Ramesh Chandra Poonia Vijander Singh Linesh Raja Vaibhav Bhatnagar Pankaj Agarwal | 2021 | Big Data Mining and Analytics2021，4，2： | 1 |
| 6 | Ranju ralhan:expression analysis of E-cadherin,slug and GSK3βin invasive ductal carcinoma of breast显示文摘 | Chandra P Prasad Gayatri Rath Sandeep Mathur | 2009 | BMC Cancer2009，18，： | 1 |
| 7 | Relation of Black Race Between High Density Lipoprotein Cholesterol Content, High Density Lipoprotein Particles and Coronary Events (from the Dallas Heart Study)显示文摘 | Alvin Chandra Ian J. Neeland Sandeep R. Das Amit Khera Aslan T. Turer Colby R. Ayers Darren K. McGuire Anand Rohatgi | 2015 | The American Journal of Cardiology2015，，7： | 1 |
| 8 | Plant Identification Using Fitness-Based Position Update in Whale Optimization Algorithm显示文摘Since the beginning of time,humans have relied on plants for food,energy,and medicine.Plants are recognized by leaf,flower,or fruit and linked to their suitable cluster.Classification methods are used to extract and select traits that are helpful in identifying a plant.In plant leaf image categorization,each plant is assigned a label according to its classification.The purpose of classifying plant leaf images is to enable farmers to recognize plants,leading to the management of plants in several aspects.This study aims to present a modified whale optimization algorithm and categorizes plant leaf images into classes.This modified algorithm works on different sets of plant leaves.The proposed algorithm examines several benchmark functions with adequate performance.On ten plant leaf images,this classification method was validated.The proposed model calculates precision,recall,F-measurement,and accuracy for ten different plant leaf image datasets and compares these parameters with other existing algorithms.Based on experimental data,it is observed that the accuracy of the proposed method outperforms the accuracy of different algorithms under consideration and improves accuracy by 5%. | Ayman Altameem Sandeep Kumar Ramesh Chandra Poonia Abdul Khader Jilani Saudagar | 2022 | Computers, Materials & Continua2022，，6： | 0 |
| 9 | Performance Analysis of Machine Learning Algorithms for Classifying Hand Motion-Based EEG Brain Signals显示文摘Brain-computer interfaces (BCIs) records brain activity using electroencephalogram (EEG) headsets in the form of EEG signals;these signals can berecorded, processed and classified into different hand movements, which can beused to control other IoT devices. Classification of hand movements will beone step closer to applying these algorithms in real-life situations using EEGheadsets. This paper uses different feature extraction techniques and sophisticatedmachine learning algorithms to classify hand movements from EEG brain signalsto control prosthetic hands for amputated persons. To achieve good classificationaccuracy, denoising and feature extraction of EEG signals is a significant step. Wesaw a considerable increase in all the machine learning models when the movingaverage filter was applied to the raw EEG data. Feature extraction techniques likea fast fourier transform (FFT) and continuous wave transform (CWT) were usedin this study;three types of features were extracted, i.e., FFT Features, CWTCoefficients and CWT scalogram images. We trained and compared differentmachine learning (ML) models like logistic regression, random forest, k-nearestneighbors (KNN), light gradient boosting machine (GBM) and XG boost onFFT and CWT features and deep learning (DL) models like VGG-16, DenseNet201 and ResNet50 trained on CWT scalogram images. XG Boost with FFTfeatures gave the maximum accuracy of 88%. | Ayman Altameem Jaideep Singh Sachdev Vijander Singh Ramesh Chandra Poonia Sandeep Kumar Abdul Khader Jilani Saudagar | 2022 | Computer Systems Science & Engineering2022，42，9： | 0 |
| 10 | Anterior Versus Posterior Fixation in Thoracic Tubercular Spine显示文摘 | Amit Agarwal Harish Chandra Anubhav Agarwal Namit Singhal Sandeep Kumar | 2015 | Journal of US-China Medical Science2015，12，1： | 0 |
| 11 | Isolated breast metastasis mimicking as second primary cancer-a case report显示文摘Primary carcinoma of breast is common but breast is a rare site of metastasis and metastases from extramammary sites are even rarer.Metastasis to breast from rectal carcinoma is very unusual and till now 19 cases of breast secondaries from colorectal carcinoma have been reported in literature which include 14 cases where the primary site was colon and remaining 5 were from the rectum.Here the authors report a case of adenocarcinoma anorectum who had completed treatment and after 4 months developed a lump in her left breast which was metastatic.Metastatic lesions of breast are usually part of a widely disseminated disease but this case presented as a solitary breast metastasis which mimicked as second primary cancer of the breast. | Manjari Shah Umang Mithal Sandeep Agarwal Sweety Gupta Disha Tiwari Shashank Srinivasan Asheesh Jain Ritu Chandra | 2016 | Journal of Cancer Metastasis and Treatment2016，2，1： | 0 |
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