MEMS biosensor for detection of Escherichia coli O157:H7 in food products

Title from PDF of title page (University of Missouri--Columbia, viewed on May 24, 2012).The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file.Thesis advisor: Dr. Mahmoud AlmasriIncludes bibliographical references."July 2011"Escherichia coli O157:H7, is one of the most common pathogens that has caused several outbreaks in recent years. In 2010-11 there were 5 outbreaks of E.coli and thousands were victim of it. Thus there is an immediate need for sensors capable of rapid detection of this pathogenic strains of E.coli. To detect the presence of E.coli O157:H7 a MEMS based biosensor has been designed and fabricated. It consists of planar interdigitated array of microelectrodes (IDAM) and a microchannel. The surface of the microelectrodes is modified using goat anti-E.coli polyclonal IgG antibody. As the bacterium cells come in contact it binds to the antibody. This binding changes the dielectric property of the electrodes, resulting in an impedance change. This change is measured using an impedance analyzer. Another variation of this biosensor has been proposed in this thesis. This design consists of two arrays of 3-dimensional electrodes and a microchannel with multiple inlets and outlets. In this design dielectrophoresis is utilized to separate unwanted materials from the cells to increase the sensitivity of the biosensor. From the analysis it was found that the biosensor is sensitive to varying concentration of E.coli samples and the lowest detection limit of the biosensor is 3x103CFU/ml. Also it was established that the total detection time for this biosensor is less than 30 minutes which is rapid compared to the conventional ways of detection

Analysis of fetal growth restriction in pregnancy in subjects attending in an obstetric clinic of a tertiary care teaching hospital

Background: Intrauterine growth restriction (IUGR) is defined as fetal growth less than the normal growth potential of a specific infant because of genetic or environmental factors. Fetal growth restriction or intrauterine growth restriction is one of the leading causes of perinatal mortality and morbidity in newborns. Fetal growth restriction is a complex multifactorial condition resulting from several fetal and maternal disorders. Objective of present study was to find out incidence of IUGR and assessment and evaluation of different important changes in IUGR.Methods: Women who attended the Obstetric OPD in their 1st trimester of pregnancy and those who were thought would be able to visit the antenatal clinic for their fortnightly check-up regularly were screened for intrauterine foetal growth retardation. Women with irregular and uncertain menstrual history and where the 1st trimester USG foetal crown rump length did not corroborate with the menstrual gestational age were excluded from this study.Results: Incidence of IUGR was 18.2% and 84% were found to be asymmetrical. IUGR was found to be double among primigravids and women above 30 years. It had been observed that IUGR was associated with certain conditions like short stature (52%), pregnancy induced hypertension (24%) and anaemia (12%).Conclusions: Thus, early USG screening along with robust screening for maternal BMI, nutritional status, and anaemia can assist the obstetric team in providing early diagnosis, prompt intervention, and better outcome in pregnancy with fetal growth restriction

The effects of combined therapy of myo-inositol and D-chiro inositol in reduction of the individual components of metabolic syndrome in overweight PCOS patients compared to myo-inositol supplementation alone: a prospective randomised controlled trial

Background: Polycystic ovarian syndrome (PCOS) is one of the most common endocrine disorder affecting five to ten percent women of reproductive age group. Variability of signs and symptoms along with metabolic syndrome as one of the long term complications make it worthy of early diagnosis and treatment. Medical management of PCOS is aimed at the treatment of metabolic derangements, anovulation, hirsutism, and menstrual irregularities.Methods: 140 patients, using inclusion and exclusion criteria, were selected and randomly divided into two groups (seventy in each) and age, BMI, waist hip ratio, blood pressure (systolic, diastolic), serum fasting insulin, fasting blood sugar, total cholesterol, HDL, LDL, triglycerides were measured. Study group were given {Myo-inositol (550 mg) + D-chiro-inositol (13.8 mg)} (MI+DCI) twice daily and the control group were given Myo-inositol (1 gm) (MI) twice daily for six months. Same variables were measured at the end of three and six months and compared with repeated measurement ANOVA using SPSS (version 20).Results: Comparison between these two groups before study was non-contributory. Combined drug therapy has provided statistically significant decrease in BMI, W:H ratio, Diastolic BP, Fasting blood sugar at the end of both 3rd and 6th month but in case of LDL it was at the end of 3 months. Combined drug therapy also increased the HDL level significantly in both the occasions.Conclusions: Combined medical therapy by (MI+DCI) is very much helpful in reducing the metabolic complications of PCOS without any major side effects

Biomechanical and Biophysical Properties of Breast Cancer Cells under Varying Glycemic Regimens

Diabetes accelerates cancer cell proliferation and metastasis, particularly for cancers of the pancreas, liver, breast, colon, and skin. While pathways linking the 2 disease conditions have been explored extensively, there is a lack of information on whether there could be cytoarchitectural changes induced by glucose which predispose cancer cells to aggressive phenotypes. It was thus hypothesized that exposure to diabetes/high glucose alters the biomechanical and biophysical properties of cancer cells more than the normal cells, which aids in advancing the cancer. For this study, atomic force microscopy indentation was used through microscale probing of multiple human breast cancer cells (MCF-7, MDA-MB-231), and human normal mammary epithelial cells (MCF-10A), under different levels of glycemic stress. These were used to study both benign and malignant breast tissue behaviors. Benign cells (MCF-10A) recorded higher Young’s modulus values than malignant cells (MCF-7 and MDA-231) under normoglycemic conditions, which agrees with the current literature. Moreover, exposure to high glucose (for 48 hours) decreased Young’s modulus in both benign and malignant cells, to the effect that the cancer cells showed a complete loss in elasticity with high glucose. This provides a possible insight into a link between glycemic stress and cytoskeletal strength. This work suggests that reducing glycemic stress in cancer patients and those at risk can prove beneficial in restoring normal cytoskeletal structure

Topological, or Non-topological? A Deep Learning Based Prediction

Prediction and discovery of new materials with desired properties are at the forefront of quantum science and technology research. A major bottleneck in this field is the computational resources and time complexity related to finding new materials from ab initio calculations. In this work, an effective and robust deep learning-based model is proposed by incorporating persistent homology and graph neural network which offers an accuracy of 91.4% and an F1 score of 88.5% in classifying topological vs. non-topological materials, outperforming the other state-of-the-art classifier models. The incorporation of the graph neural network encodes the underlying relation between the atoms into the model based on their own crystalline structures and thus proved to be an effective method to represent and process non-euclidean data like molecules with a relatively shallow network. The persistent homology pipeline in the suggested neural network is capable of integrating the atom-specific topological information into the deep learning model, increasing robustness, and gain in performance. It is believed that the presented work will be an efficacious tool for predicting the topological class and therefore enable the high-throughput search for novel materials in this field.Comment: 13 pages, 8 figure

Barriers Faced by Women with Physical Disabilities for Reproductive Health Care Services Utilization

Women with physical disabilities are often marginalized from mainstream healthcare services, and their reproductive health needs are not often met. The study aimed to explore the barriers faced by women with physical disabilities in reproductive health care utilization. This descriptive cross-sectional study was conducted between January to December 2021 among 83 conveniently selected women with physical disabilities of the reproductive age group (18-49 years). Data were obtained through face-to-face interviews from the participants using a pre-tested, semi-structured, interviewer-administered questionnaire. Among participants, the mean age was 29.3 years. All individuals reported that they experienced some sort of barrier to reproductive healthcare utilization. The Majority (50.6%) of the participants reported that disease was the cause of their disability. Traditional hurdles prevented 57% of participants from accessing reproductive healthcare, whereas 32.5% lacked familial support. Most (78.3%) of them said that accessing healthcare was expensive. More than half of the participants seeking reproductive healthcare found no wheelchair ramp or transfer aid. No service provider educated 69.9% of participants about reproductive healthcare services and rights. When asked about healthcare hurdles, individuals reported fear of poor care (75.9%), negative healthcare provider attitudes (68.7%), and communication issues with providers (67.5%). Some barriers to accessing reproductive health care services include high expenses, lack of family support, poor physical accessibility, lack of information, fear of poor care, negative attitudes of providers, and communication difficulties. Improving access to reproductive healthcare for women with physical disabilities requires addressing barriers and implementing necessary interventions

PHYTOCHEMICALS IN THE TREATMENT OF ARTHRITIS: CURRENT KNOWLEDGE

The objective of the present review is to evaluate the therapeutic potential of phytochemicals against arthritis, which is asymptomatic disorder of chronic joint inflammation followed by swelling and pain. Here, we discussed about the anti-arthritic activity of many phytomolecules such as Norisoboldine, Berberine, Triptolide, Hesperidin Hesperidin, Madecassocide, Hydroxy napthoquinone, Ginsenoside, Cryptotanshinone, Kirenol, Thymoquinone, Chlorogenic acid, Curcumin, Bromelain, Andrographolide and Allicin. These compounds are able to control inflammatory responses, proinflammatory cytokines, osteoclast differentiation and to prevent bone erosion in the joints. In this article, we reviewed anti-arthritic activities of phytichemicals from 2011-2019, using various scientific websites like PubMed, Google Scholar, Science Direct etc. Till date clinical trials conducted with anti-arthritic phytomolecules are very less. Hence, more clinical trials are needed to bring plant molecules as safe and effective anti-arthritic drugs in the market, either alone or in combination with other anti-arthritic agents

Combined dielectrophoretic and impedance system for on-chip controlled bacteria concentration: Application to Escherichia coli

The present paper reports a bacteria autonomous controlled concentrator prototype with a user-friendly interface for bench-top applications. It is based on a micro-fluidic lab-on-a-chip and its associated custom instrumentation, which consists in a dielectrophoretic actuator, to pre-concentrate the sample, and an impedance analyser, to measure concentrated bacteria levels. The system is composed by a single micro-fluidic chamber with interdigitated electrodes and a instrumentation with custom electronics. The prototype is supported by a real-time platform connected to a remote computer, which automatically controls the system and displays impedance data used to monitor the status of bacteria accumulation on-chip. The system automates the whole concentrating operation. Performance has been studied for controlled volumes of Escherichia coli (E. coli) samples injected into the micro-fluidic chip at constant flow rate of 10 μL/min. A media conductivity correcting protocol has been developed, as the preliminary results showed distortion of the impedance analyser measurement produced by bacterial media conductivity variations through time. With the correcting protocol, the measured impedance values were related to the quantity of bacteria concentrated with a correlation of 0.988 and a coefficient of variation of 3.1%. Feasibility of E. coli on-chip automated concentration, using the miniaturized system, has been demonstrated. Furthermore, the impedance monitoring protocol had been adjusted and optimized, to handle changes in the electrical properties of the bacteria media over time