AN ALTERNATIVE WAY TO BREAK THE MATRIX BARRIER: AN EXPERIMENTAL STUDY OF A LIFU-MEDIATED, VISUALIZABLE TARGETED NANOPARTICLE SYNERGISTIC AMPLIFICATION FOR THE TREATMENT OF MALIGNANT FIBROBLASTS

An alternative way to break the matrix barrier: an experimental study of a LIFU-mediated, visualizable targeted nanoparticle synergistic amplification for the treatment of malignant fibroblasts

Malignant fibroblasts (MFs) are widely present in various diseases and are characterized by connective tissue proliferation; these cells act as a physical barrier that severely limits drug delivery and affects disease outcomes.Based on this, Fan Shop - CFL - Hats we constructed the smart, integrated, theranostic, targeted lipid nanoprobe HMME-RG3@P

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SISTEM PENDUKUNG KEPUTUSAN PENDUGAAN UMUR SIMPAN & TANGGAL KADALUARSA PRODUK PANGAN DENGAN METODE ARRHENIUS BERBASIS WEB

The concept of Kids clothes Decision Support Systems is one branch of artificial intelligence which is widely used.There are many methods that can be used by decision makers to find the optimum solution or alternative to a problem.One such method is the method of Arrhenius.This method will help decision makers where many alternative decisions with

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Anemia in pregnancy in Western Jamaica

Saidah Wright,1 Dominique Earland,1 Swati Sakhuja,1 Anna Junkins,1 Sarah Franklin,1 Luz Padilla,1 Maung Aung,2 Pauline E Jolly1 1Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA; 2Western Region Health Authority, Cornwall Regional Hospital, Ministry of Health, Montego Bay, Jamaica Backgro

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Spatio-temporal monitoring of vegetation phenology in the dry sub-humid region of Nigeria using time series of AVHRR NDVI and TAMSAT datasets

Time series data are of great importance for monitoring vegetation phenology in the dry sub-humid regions where change in land cover has influence on biomass productivity.However few studies have inquired into examining the impact of rainfall and land cover change on vegetation phenology.This study explores Seasonal Trend Analysis (STA) approach in

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