Highly specific plasmonic biosensors for ultrasensitive microRNA detection in plasma from pancreatic cancer patients

MicroRNAs (miRs) are small noncoding RNAs that regulate mRNA stability and/or translation. Because of their release into the circulation and their remarkable stability, miR levels in plasma and other biological fluids can serve as diagnostic and prognostic disease biomarkers. However, quantifying miRs in the circulation is challenging due to issues with sensitivity and specificity. This Letter describes for the first time the design and characterization of a regenerative, solid-state localized surface plasmon resonance (LSPR) sensor based on highly sensitive nanostructures (gold nanoprisms) that obviates the need for labels or amplification of the miRs. Our direct hybridization approach has enabled the detection of subfemtomolar concentration of miR-X (X = 21 and 10b) in human plasma in pancreatic cancer patients. Our LSPR-based measurements showed that the miR levels measured directly in patient plasma were at least 2-fold higher than following RNA extraction and quantification by reverse transcriptase-polymerase chain reaction. Through LSPR-based measurements we have shown nearly 4-fold higher concentrations of miR-10b than miR-21 in plasma of pancreatic cancer patients. We propose that our highly sensitive and selective detection approach for assaying miRs in plasma can be applied to many cancer types and disease states and should allow a rational approach for testing the utility of miRs as markers for early disease diagnosis and prognosis, which could allow for the design of effective individualized therapeutic approaches

Label-Free Nanoplasmonic-Based Short Noncoding RNA Sensing at Attomolar Concentrations Allows for Quantitative and Highly Specific Assay of MicroRNA-10b in Biological Fluids and Circulating Exosomes

MicroRNAs are short noncoding RNAs consisting of 18-25 nucleotides that target specific mRNA moieties for translational repression or degradation, thereby modulating numerous biological processes. Although microRNAs have the ability to behave like oncogenes or tumor suppressors in a cell-autonomous manner, their exact roles following release into the circulation are only now being unraveled and it is important to establish sensitive assays to measure their levels in different compartments in the circulation. Here, an ultrasensitive localized surface plasmon resonance (LSPR)-based microRNA sensor with single nucleotide specificity was developed using chemically synthesized gold nanoprisms attached onto a solid substrate with unprecedented long-term stability and reversibility. The sensor was used to specifically detect microRNA-10b at the attomolar (10(-18) M) concentration in pancreatic cancer cell lines, derived tissue culture media, human plasma, and media and plasma exosomes. In addition, for the first time, our label-free and nondestructive sensing technique was used to quantify microRNA-10b in highly purified exosomes isolated from patients with pancreatic cancer or chronic pancreatitis, and from normal controls. We show that microRNA-10b levels were significantly higher in plasma-derived exosomes from pancreatic ductal adenocarcinoma patients when compared with patients with chronic pancreatitis or normal controls. Our findings suggest that this unique technique can be used to design novel diagnostic strategies for pancreatic and other cancers based on the direct quantitative measurement of plasma and exosome microRNAs, and can be readily extended to other diseases with identifiable microRNA signatures

Online Reviews System using Aspect Based Sentimental Analysis & Opinion Mining

Aspect extraction is the most critical and thoroughly researched process in SA (Sentiment Analysis) for conducting an accurate classification of feelings. Over the last decade, massive amounts of research have focused on identifying and removing elements. Products have centralized distribution channels, and certain apps may occasionally operate close to the most recent product to be created. Any e-commerce business enterprise must analyses user / customer feedback in order to provide better products and services to them. Because broad reviews frequently include remarks in a consolidated manner when a customer gives his thoughts on various product attributes within the same summary, it is difficult to determine the exact feeling. The key components of this software are included in their release, making it a valuable tool for management to improve the consistency of their own system's specifications. The goal was to categories the aspects of the target entities provided, as well as the feelings conveyed for each aspect. First, we are implementing a supervised classification framework that is tightly restricted and relies solely on training sets for knowledge. As a result, the key terms comes from associated at various elements of a thing within its entirety perform customer sentiment using certain elements. In contrast to current sentiment analysis approaches, synthetic and actual data set experiments yield positive results

Local Industrialization Based Lucrative Farming Using Machine Learning Technique

In recent times, agriculture have gained lot of attention of researchers. More precisely, crop prediction is trending topic for research as it leads agri-business to success or failure. Crop prediction totally rest on climatic and chemical changes. In the past which crop to promote was elected by rancher. All the decisions related to its cultivation, fertilizing, harvesting and farm maintenance was taken by rancher himself with his experience. But as we can see because of constant fluctuations in atmospheric conditions coming to any conclusion have become very tough. Picking correct crop to grow at right times under right circumstances can help rancher to make more business. To achieve what we cannot do manually we have started building machine learning models for it nowadays. To predict the crop deciding which parameters to consider and whose impact will be more on final decision is also equally important. For this we use feature selection models. This will alter the underdone data into more precise one. Though there have been various techniques to resolve this problem better performance is still desirable. In this research we have provided more precise & optimum solution for crop prediction keeping Satara, Sangli, Kolhapur region of Maharashtra. Along with crop & composts to increase harvest we are offering industrialization around so rancher can trade the yield & earn more profit. The proposed solution is using machine learning algorithms like KNN, Random Forest, Naïve Bayes where Random Forest outperforms others so we are using it to build our final framework to predict crop

A REVIEW OF AUTOMATIC DETECTION OF MICRO ANEURYSM AND DIABETIC RETINOPATHY GRADING IN FUNDUS RETINAL IMAGES

 From an image processing standpoint, the automatic detection of micro aneurysms is a challenging task, since their color and size are same as the vessels, they have a variable size and often they are so small that can be easily mystified with the image noise. It is also difficult to discriminate whether a red lesion is a micro aneurysm or small dot hemorrhage. This problem increases the number of false candidates that naturally deteriorates the overall accuracy of the detectors. Automatic early detection could limit the severity of the disease and assist ophthalmologists in investigating and treating the disease more effectively and efficiently. Therefore, time required for examination and effect of the disease on the patient could be reduced if the detection system could succeed on images taken from patients with non-dilated pupils. &nbsp

AUTOMATIC DETECTION OF MICRO ANEURYSM AND DIABETIC RETINOPATHY GRADING IN FUNDUS RETINAL IMAGES

Image processing founds the applications in various medical fields. A cluster of research has been carried out in last decade and images processing is found to be superior to other environments in medical field. In a research it has been proven that the chances of blindness are 25 times more in the patients of diabetes than that of non-diabetic person. Automatic detection of the micro aneurysms is really challenging. Diabetic retinopathy (DR) has severe effects on retina and results in loss of eye sight. The research is carried out to understand the diabetes disease in India and it is found that, this disease is increasing rapidly. The percentage of people dead due to diabetes is also very high. Most of the times, this disease is neglected by patient and in some cases the people are unaware that they have diabetes. In this paper, authors have implemented the automatic detection of micro-aneurysm and diabetic retinopathy grading in fundus retinal images

A Review Of Automatic Detection Of Micro Aneurysm And Diabetic Retinopathy Grading In Fundus Retinal Images

 From an image processing standpoint, the automatic detection of micro aneurysms is a challenging task, since their color and size are same as the vessels, they have a variable size and often they are so small that can be easily mystified with the image noise. It is also difficult to discriminate whether a red lesion is a micro aneurysm or small dot hemorrhage. This problem increases the number of false candidates that naturally deteriorates the overall accuracy of the detectors. Automatic early detection could limit the severity of the disease and assist ophthalmologists in investigating and treating the disease more effectively and efficiently. Therefore, time required for examination and effect of the disease on the patient could be reduced if the detection system could succeed on images taken from patients with non-dilated pupils. &nbsp

Formulation and Evaluation of Herbal Face Pack

Majority of the cosmetic products available in market are of synthetic origin and causes numerous side effects when used for longer period of time. One of the solutions for this problem is use of herbal cosmetics. Herbal cosmetics are considered safe for routine use with minimal side effects. Acne, redness, wrinkles, dark circles, pimples, dry and dead skin is some of the major skin issues. All these problems can be minimized by using herbal cosmetics such as face pack, scrub, cream, etc. Present work focused on preparation of powder based herbal face pack using natural ingredient like orange peel, neem, tulsi, sandalwood, rose oil, etc. Orange peel was used as core ingredient for its ability to reduce acne, wrinkle and also to control excessive secretion of oil is known as natural or herbal cosmetics. Formulation was evaluated for its appearance, spreadability, smoothness, irritability, pH etc. from the results obtained from evaluation parameters, it can be concluded that the prepared face pack can be safely used. Keywords: herbal cosmetics, scrub, softening, cleansing, moisturizing and fairnes

Cryo-EM structure of SARS-CoV-2 ORF3a in lipid nanodiscs.

SARS-CoV-2 ORF3a is a putative viral ion channel implicated in autophagy inhibition, inflammasome activation and apoptosis. 3a protein and anti-3a antibodies are found in infected patient tissues and plasma. Deletion of 3a in SARS-CoV-1 reduces viral titer and morbidity in mice, suggesting it could be an effective target for vaccines or therapeutics. Here, we present structures of SARS-CoV-2 3a determined by cryo-EM to 2.1-Å resolution. 3a adopts a new fold with a polar cavity that opens to the cytosol and membrane through separate water- and lipid-filled openings. Hydrophilic grooves along outer helices could form ion-conduction paths. Using electrophysiology and fluorescent ion imaging of 3a-reconstituted liposomes, we observe Ca2+-permeable, nonselective cation channel activity, identify mutations that alter ion permeability and discover polycationic inhibitors of 3a activity. 3a-like proteins are found across coronavirus lineages that infect bats and humans, suggesting that 3a-targeted approaches could treat COVID-19 and other coronavirus diseases