The Early Sonographic Prediction of Gestational Diabetes in Women From India

2021 ◽  
pp. 875647932110298
Author(s):  
Shivani Gupta ◽  
Arjun Gupta ◽  
C. P. Swarnakar ◽  
Monika Rathore ◽  
Ramesh Beniwal ◽  
...  
Keyword(s):  
Adipose Tissue ◽  
Gestational Diabetes ◽  
Cost Effective ◽  
P Value ◽  
Antenatal Screening ◽  
Differential Distribution ◽  
Potential Marker ◽  
Cost Effective Method ◽  
Asian Indian Women ◽  
Patients At Risk

Objective: The purpose of this study was to look for the earliest, cost -effective method that can be added to the routine antenatal screening for identifying patients who might develop gestational diabetes mellitus (GDM) in a proactive manner, as opposed to the current reactive approach of screening and treating GDM, during the second trimester of pregnancy. Materials and Methods: 190 singleton pregnant women in the age group 18-35 years were selected for the study. On these women two step assessment was done. The current project was carried out to utilize sonography as an early, cost-effective method which could be added to routine antenatal screening for identifying patients, at risk for developing GDM. Results: Body mass index was found to have a significant association in those patients with GDM with a P < .001. There was a significant association between subcutaneous adipose tissue (SAT) depth and occurrence of GDM, with a P-value of <.001. Also, in the present study, the occurrence of GDM significantly increased with a rise in visceral adipose tissue (VAT), and there was a significant association between the two, with P < .001. It was noted that there were greater incidences of GDM as VAT depth increased. The existence of GDM greatly increased with a rise in total abdominal tissue (TAT), and there was a significant association between the two, with P < .001 Conclusion: The sonographic measurement of SAT, VAT, and TAT, could be potential marker to identify probable events for the development of GDM, among Asian Indian women who tend to have T2DM, due to differential distribution of fat.

scholarly journals Molecularly Imprinted Nanoparticles Based Sensor for Cocaine Detection

Biosensors ◽  
2020 ◽  
Vol 10 (3) ◽  
pp. 22 ◽  
Author(s):  
Roberta D’Aurelio ◽  
Iva Chianella ◽  
Jack A. Goode ◽  
Ibtisam E. Tothill
Keyword(s):  
Electrochemical Impedance ◽  
Limit Of Detection ◽  
Solid Phase ◽  
Cost Effective ◽  
Cross Reactivity ◽  
P Value ◽  
Sensing Element ◽  
Molecularly Imprinted ◽  
Cost Effective Method ◽  
Cocaine Detection

The development of a sensor based on molecularly imprinted polymer nanoparticles (nanoMIPs) and electrochemical impedance spectroscopy (EIS) for the detection of trace levels of cocaine is described in this paper. NanoMIPs for cocaine detection, synthesized using a solid phase, were applied as the sensing element. The nanoMIPs were first characterized by Transmission Electron Microscopy (TEM) and Dynamic Light Scattering and found to be ~148.35 ± 24.69 nm in size, using TEM. The nanoMIPs were then covalently attached to gold screen-printed electrodes and a cocaine direct binding assay was developed and optimized, using EIS as the sensing principle. EIS was recorded at a potential of 0.12 V over the frequency range from 0.1 Hz to 50 kHz, with a modulation voltage of 10 mV. The nanoMIPs sensor was able to detect cocaine in a linear range between 100 pg mL−1 and 50 ng mL−1 (R2 = 0.984; p-value = 0.00001) and with a limit of detection of 0.24 ng mL−1 (0.70 nM). The sensor showed no cross-reactivity toward morphine and a negligible response toward levamisole after optimizing the sensor surface blocking and assay conditions. The developed sensor has the potential to offer a highly sensitive, portable and cost-effective method for cocaine detection.

scholarly journals MassARRAY-based single nucleotide polymorphism analysis in breast cancer of north Indian population

BMC Cancer ◽  
2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Divya Bakshi ◽  
Ashna Nagpal ◽  
Varun Sharma ◽  
Indu Sharma ◽  
Ruchi Shah ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Mutations ◽  
Cost Effective ◽  
P Value ◽  
Polymorphism Analysis ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Cost Effective Method ◽  
Common Genetic Variants ◽  
Underlying Causes

Abstract Background Breast Cancer (BC) is associated with inherited gene mutations. High throughput genotyping of BC samples has led to the identification and characterization of biomarkers for the diagnosis of BC. The most common genetic variants studied are SNPs (Single Nucleotide Polymorphisms) that determine susceptibility to an array of diseases thus serving as a potential tool for identifying the underlying causes of breast carcinogenesis. Methods SNP genotyping employing the Agena MassARRAY offers a robust, sensitive, cost-effective method to assess multiple SNPs and samples simultaneously. In this present study, we analyzed 15 SNPs of 14 genes in 550 samples (150 cases and 400 controls). We identified four SNPs of genes TCF21, SLC19A1, DCC, and ERCC1 showing significant association with BC in the population under study. Results The SNPs were rs12190287 (TCF21) having OR 1.713 (1.08–2.716 at 95% CI) p-value 0.022 (dominant), rs1051266 (SLC19A1) having OR 3.461 (2.136–5.609 at 95% CI) p-value 0.000000466 (dominant), rs2229080 (DCC) having OR 0.6867 (0.5123–0.9205 at 95% CI) p-value 0.0116 (allelic) and rs2298881 (ERCC1) having OR 0.669 (0.46–0.973 at 95% CI), p-value 0.035 (additive) respectively. The in-silico analysis was further used to fortify the above findings. Conclusion It is further anticipated that the variants should be evaluated in other population groups that may aid in understanding the genetic complexity and bridge the missing heritability.

scholarly journals Genetic Analysis of colorectal carcinoma using high throughput SNP genotyping technique within the population of Jammu and Kashmir

2021 ◽  
Author(s):  
Bhanu Sharma ◽  
Shabab Angurana ◽  
Amrita Bhat ◽  
Sonali Verma ◽  
Divya Bakshi ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
High Throughput ◽  
Cost Effective ◽  
Snp Genotyping ◽  
Colorectal Carcinogenesis ◽  
P Value ◽  
Jammu And Kashmir ◽  
Cost Effective Method ◽  
Underlying Causes ◽  
Multiple Samples

Abstract Background SNP genotyping has become increasingly more common place to understand the genetic basis of complex diseases like cancer. SNP-genotyping through massARRAY is a cost-effective method to quantitatively analyse the variation of gene expression in multiple samples, making it a potential tool to identify the underlying causes of colorectal carcinogenesis. Methods In the present study, SNP genotyping was carried out using Agena mass ARRAY, which is a cost-effective, robust, and sensitive method to analyse multiple SNPs simultaneously. We analysed 7 genes in 492 samples (100 cases and 392 controls) associated with CRC within the population of Jammu and Kashmir. These SNPs were selected based on their association with multiple cancers in literature. Results This is the first study to explore these SNPs with colorectal cancer within the J&K population.7 SNPs with a call rate of 90% were selected for the study. Out of these, one SNP i.e. rs2229080 of DCC was found to be significantly associated with the current study and 6 were non-significantly associated with CRC within the studied population. The allelic OR observed for the variant rs2229080 of DCC was 1.5 (1.1–2.3 at 95% CI), p value = 0.02. Conclusion This is the first study to find the relation of Genetic variants with the colorectal cancer within the studied population using high throughput mass ARRAY technology. It is further anticipated that the variants should be evaluated in other population groups that may aid in understanding the genetic complexity and bridge the missing heritability.

scholarly journals Genetic Analysis of colorectal carcinoma using high throughput SNP genotyping technique within the population of Jammu and Kashmir.

2021 ◽  
Author(s):  
Bhanu Sharma ◽  
Shabab Angurana ◽  
Amrita Bhat ◽  
Sonali Verma ◽  
Divya Bakshi ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
High Throughput ◽  
Cost Effective ◽  
Snp Genotyping ◽  
Colorectal Carcinogenesis ◽  
P Value ◽  
Jammu And Kashmir ◽  
Cost Effective Method ◽  
Underlying Causes ◽  
Multiple Samples

Abstract Background SNP genotyping has become increasingly more common place to understand the genetic basis of complex diseases like cancer. SNP-genotyping through massARRAY is a cost-effective method to quantitatively analyse the variation of gene expression in multiple samples, making it a potential tool to identify the underlying causes of colorectal carcinogenesis.Methods In the present study, SNP genotyping was carried out using Agena mass ARRAY, which is a cost-effective, robust, and sensitive method to analyse multiple SNPs simultaneously. We analysed 7 genes in 492 samples (100 cases and 392 controls) associated with CRC within the population of Jammu and Kashmir. These SNPs were selected based on their association with multiple cancers in literature.Results This is the first study to explore these SNPs with colorectal cancer within the J&K population.7 SNPs with a call rate of 90% were selected for the study. Out of these, one SNP i.e. rs2229080 of DCC was found to be significantly associated with the current study and 6 were non-significantly associated with CRC within the studied population. The allelic OR observed for the variant rs2229080 of DCC was 1.5 (1.1–2.3 at 95% CI), p value = 0.02.Conclusion This is the first study to find the relation of Genetic variants with the colorectal cancer within the studied population using high throughput mass ARRAY technology. It is further anticipated that the variants should be evaluated in other population groups that may aid in understanding the genetic complexity and bridge the missing heritability.

Statistical Analysis of Spectral Entropy Features for the Detection of Alcoholics Based on Elecroencephalogram (EEG) Signals

2012 ◽  
Vol 1 (2) ◽  
pp. 34-41 ◽  
Author(s):  
T.K. Padma Shri ◽  
N. Sriraam
Keyword(s):  
Statistical Analysis ◽  
Cost Effective ◽  
P Value ◽  
Band Pass Filter ◽  
Spectral Entropy ◽  
Pass Filter ◽  
Significance Level ◽  
Non Invasive ◽  
Cost Effective Method ◽  
Pattern Vep

EEG happens to be an important tool for brain study providing a non- invasive and cost effective method to detect the effects of alcohol on the human brain. This paper highlights the importance of statistical analysis to determine the usefulness of spectral entropy features for discriminating alcoholics from healthy subjects. The open source EEG database consisting of 10 alcoholic and 10 control subjects recordings under visual stimulus is considered for the study. The EEG signal is preprocessed to remove eye blink artefact using independent component analysis (ICA) and the gamma sub band is extracted by using an elliptic band pass filter to obtain the visually evoked pattern (VEP) signal. The spectral entropy (SEN) coefficients are computed on all the 61 VEP signals of each subject. To obtain a statistical measure of SEN coefficients suitability for classifying the alcoholic EEG, ANOVA tests are performed. Results show that the test exhibits interesting observations in the form of p-value <0.05 (accepted significance level) for most of the channels and p-value >0.05 for the remaining channels. This study may help in identifying those significant channels (p<0.05) which contribute to the classification of both the groups.

scholarly journals Role of O'sullivan's Test in Screening of Pregnant Women for Gestational Diabetes in Rural Area

2011 ◽  
Vol 3 (2) ◽  
pp. 86-88 ◽  
Author(s):  
Neema Acharya ◽  
Anil Inamdar
Keyword(s):  
Gestational Diabetes ◽  
Pregnant Women ◽  
Rural Area ◽  
Cost Effective ◽  
Perinatal Morbidity ◽  
Diabetes In Pregnancy ◽  
High Risk Factors ◽  
Cost Effective Method ◽  
Glucose Test

ABSTRACT Objective To study the role of O'sullivan's test in screening of pregnant women for gestational diabetes in rural area. Materials and methods A total of 1000 antenatal patients were screened for gestational diabetes with 50 gm glucose test (O'sullivan's test), 1-hour plasma glucose value more than 130 gm/dl was considered screen positive who were subjected to 3-hour GTT. Results The incidence of gestational diabetes in our study was 0.5%, the maternal and fetal high-risk factors in these patients were PROM, hydromnios and birth weight more than 3.5 kg. Conclusion O'sullivan's test is a cost-effective method of screening of diabetes in pregnancy which is associated with increased maternal and perinatal morbidity.

scholarly journals MassARRAY-based single nucleotide polymorphism analysis in breast cancer of North Indian Population.

2020 ◽  
Author(s):  
Divya Bakshi ◽  
Ashna Nagpal ◽  
Varun Sharma ◽  
Indu Sharma ◽  
Ruchi Shah ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Mutations ◽  
Cost Effective ◽  
P Value ◽  
Polymorphism Analysis ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Cost Effective Method ◽  
Common Genetic Variants ◽  
Underlying Causes

Abstract Background Breast Cancer (BC) is associated with inherited gene mutations. High throughput genotyping of BC samples has led to the identification and characterization of biomarkers for the diagnosis of BC. The most common genetic variants studied are SNPs (Single Nucleotide Polymorphisms) that determine susceptibility to an array of diseases thus serving as a potential tool for identifying the underlying causes of breast carcinogenesis. Methods SNP genotyping employing the Agena MassARRAY offers a robust, sensitive, cost-effective method to assess multiple SNPs and samples simultaneously. In this present study, we analyzed 15 SNPs of 14 genes in 550 samples (150 cases and 400 controls). We identified four SNPs of genes TCF21, SLC19A1, DCC, and ERCC1 showing significant association with BC in the population under study. Results The SNPs were rs12190287 (TCF21) having OR 1.713 (1.08-2.716 at 95% CI) p-value 0.022 (dominant), rs1051266 (SLC19A1) having OR 3.461 (2.136-5.609 at 95% CI) p-value 0.000000466 (dominant), rs2229080 (DCC) having OR 0.6867 (0.5123 -0.9205 at 95% CI) p-value 0.0116 (allelic) and rs2298881 (ERCC1) having OR 0.669 (0.46-0.973 at 95% CI), p-value 0.035 (additive) respectively. The in-silico analysis was further used to fortify the above findings. Conclusion It is further anticipated that the variants should be evaluated in other population groups that may aid in understanding the genetic complexity and bridge the missing heritability.

scholarly journals Color Doppler Ultrasound of Carotid and Vertebral Vessels: Anatomy, Technique and Reporting

2016 ◽  
Vol 5 ◽  
pp. 24-35
Author(s):  
Mehrzad Lotfi
Keyword(s):  
Color Doppler ◽  
Cost Effective ◽  
Color Doppler Ultrasound ◽  
Flow Mapping ◽  
Color Flow ◽  
Vertebral Arteries ◽  
Doppler Study ◽  
Cost Effective Method ◽  
Patients At Risk ◽  
Carotid And Vertebral Arteries

Color Doppler study of carotid and vertebral arteries is a non-invasive, reliable and also easily available, cost-effective method for screening and follows up of patients at risk of stroke to differentiate patients need surgery or intervention from whom could be followed by medical management. I   reviewed anatomy of cervical arteries and different techniques such as B- mode or gray scale scanning, color flow mapping and spectral analysis for evaluation of both carotid and vertebral arteries.

scholarly journals Single nucleotide polymorphism analysis in breast cancer using MassARRAY from Jammu and Kashmir, India

2020 ◽  
Author(s):  
Divya Bakshi ◽  
Ashna Nagpal ◽  
Varun Sharma ◽  
Indu Sharma ◽  
Ruchi Shah ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Mutations ◽  
Cost Effective ◽  
P Value ◽  
Polymorphism Analysis ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Jammu And Kashmir ◽  
Cost Effective Method ◽  
Common Genetic Variants

Abstract BackgroundBreast Cancer (BC) is associated with inherited gene mutations. High throughput genotyping of BC samples has led to the identification and characterization of biomarkers for diagnosis of BC. The most common genetic variants studied are SNPs (Single Nucleotide Polymorphisms) that determine susceptibility to an array of diseases thus serving as a potential tool for identifying the underlying causes of breast carcinogenesis. MethodsSNP genotyping employing the Agena MassARRAY offers a robust, sensitive, cost-effective method to assess multiple SNPs and samples simultaneously. In this present study, we analyzed 15 SNPs of 14 genes in 550 samples (150 cases and 400 controls). We identified four SNPs of genes TCF21, SLC19A1, DCC, and ERCC1 showing significant association with BC in the population under study. ResultsThe SNPs were rs12190287 (TCF21) having OR 1.713 (1.08-2.716 at 95% CI) p-value 0.022 (dominant), rs1051266 (SLC19A1) having OR 3.461 (2.136-5.609 at 95% CI) p-value 0.000000466 (dominant), rs2229080 (DCC) having OR 0.6867 (0.5123 -0.9205 at 95% CI) p-value 0.0116 (allelic) and rs2298881 (ERCC1) having OR 0.669 (0.46-0.973 at 95% CI), p-value 0.035 (additive) respectively. The in-silico analysis was further used to fortify the above findings. ConclusionIt is further anticipated that the variants should be evaluated in other population groups that may aid in understanding the genetic complexity and bridge the missing heritability.

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