Combinatorial Delivery of Docetaxel- and Erlotinib-Loaded Functionalized Nanostructured Lipid Carriers for the Treatment of Triple-Negative Breast Cancer Using Quality-by-Design Approach.

This study explored the combined administration of docetaxel (DOC) and erlotinib (ERL) using nanostructured lipid carriers (NLCs), with folic acid (FA) conjugation to enhance their synergistic anticancer efficacy against triple-negative breast cancer. NLCs were developed through hot melt homogenization-ultrasound dispersion, and optimized by a quality-by-design (QbD) approach using Plackett-Burman design and Box-Behnken design. Plots were generated based on maximum desirability.

Biogenic synthesis of gold nanoparticles using dual extract of tulsi- for breast cancer tumor regression in mice.

This work aims to synthesize the gold nanoparticles (GNPs) using a dual extract of tulsi and (T+V-Gold) for breast cancer tumor regression. The GNPs were synthesized and characterized for their microscopic, spectroscopic and crystalline properties. Further, the GNPs were investigated for and studies for the treatment of the 4T1-induced triple-negative breast cancer murine model.

Household food waste and theory of planned behavior: A systematic review and meta-analysis.

The darker side of food behavior is that millions of tons of food have been shown the doors of garbage. Therefore, food waste behavior needs an eye to look upon. The purpose of this research is to inculcate the concept of systematic literature review along with meta-analysis in order to examine the Theory of Planned Behavior (TPB) with respect to food waste behavior.

Chitosan reduced in-situ synthesis of gold nanoparticles on paper towards fabricating highly sensitive, stable uniform SERS substrates for sensing applications.

Surface-Enhanced Raman Spectroscopy (SERS) is a powerful surface-sensitive technique for molecular analysis. Its use is limited due to high cost, non-flexible rigid substrates such as silicon, alumina or glass and less reproducibility due to non-uniform surface. Recently, paper-based SERS substrates, a low-cost and highly flexible alternative, received significant attention.

State-of-the-art methods in healthcare text classification system: AI paradigm.

Machine learning has shown its importance in delivering healthcare solutions and revolutionizing the future of filtering huge amountd of textual content. The machine intelligence can adapt semantic relations among text to infer finer contextual information and language processing system can use this information for better decision support and quality of life care. Further, a learnt model can efficiently utilize written healthcare information in knowledgeable patterns.

Effect of incremental feature enrichment on healthcare text classification system: A machine learning paradigm.

Background And Objective: Healthcare tweets are particularly challenging due to its sparse layout and its limited character size. Compared to previous method based on "bag of words" (BOW) model, this study uniquely identifies the enrichment protocol and learns how semantically different aspects of feature selection such as BOW (feature F0), term frequency inverse document frequency (TF-IDF, feature F1), and latent semantic indexing (LSI, feature F2) when applied sequentially with classifier improves the overall performance.

Methods: To study this enrichment concept, our ML model is tested on two kinds of diverse data sets: (i) D1: Disease data with conjunctivitis, diarrhea, stomach ache, cough and nausea related tweets, and (ii) D2: WebKB4 dataset, while adapting three kind of classifiers (a) C1: support vector machine with radial basis function (SVMR), (b) C2: Multi-layer perceptron (MLP) and (c) C3: Random Forest (RF).

Fabrication of cost-effective and efficient paper-based device for viscosity measurement.

Use of paper-based devices for affordable diagnostics is gaining interest due to unique advantages such as affordability, portability, easy disposability and inherent capillarity. As capillary transportation is an integral component of paper-based devices, low sample volume with faster measurement becomes an additional advantage. We have developed a simple, paper-based microfluidic device suitable for measuring the viscosity of Newtonian fluids as well as a few non-Newtonian fluids with sample volume as little as 12-20 μL.

Healthcare Text Classification System and its Performance Evaluation: A Source of Better Intelligence by Characterizing Healthcare Text.

A machine learning (ML)-based text classification system has several classifiers. The performance evaluation (PE) of the ML system is typically driven by the training data size and the partition protocols used. Such systems lead to low accuracy because the text classification systems lack the ability to model the input text data in terms of noise characteristics.

A study of clinical presentation and delays in management of acute myocardial infarction in community.

To assess the medico social demographics of acute myocardial infarction (AMI) in our community we studied 609 patients presenting between January 2008 to December 2008 with a detailed questionnaire in four centres of UP. Medical attention was sought late (> 6 hours) in 316 (51.6%), thrombolysis was obtained in 45.