Estudio y desarrollo de modelos matemáticos de resistencia celular a la quimioterapia.

El cáncer es un conjunto de más de cien tipos de enfermedades relacionadas caracterizadas por la proliferación ininterrumpida de células y su capacidad de extenderse a otros tejidos, formando metástasis. Actualmente, se trata de una de las principales causas de mortalidad en todo el mundo. Por este motivo, se están llevando a cabo numerosos estudios para comprender mejor su comportamiento en el organismo y poder combatirlo de manera eficaz. Una línea interesante de investigación la representa el estudio de la resistencia a múltiples drogas (MDR), pues es la mayor causa de fracaso del tratamiento contra el cáncer. En los últimos años se está potenciando el interés por aplicar técnicas matemáticas en el análisis de problemas biológicos. Debido a la importancia de las enfermedades oncológicas, en este trabajo de investigación se ha desarrollado un modelo matemático de ecuaciones diferenciales que describe el proceso de transferencia de la resistencia a la quimioterapia en mezclas de dos poblaciones de células tumorales: resistentes y sensibles. Además, se han estimado los parámetros de dicho modelo utilizando los datos experimentales de ensayos de proliferación celular in vitro y se han realizado simulaciones numéricas para la validación del modelo, haciendo uso del software matemático Matlab. Como resultados de la investigación, hay que destacar que el modelo representa la proliferación in vitro de células cancerígenas sensibles, resistentes y de sus cultivos mixtos. Esto permitirá continuar con la investigación a niveles de complejidad superior, permitiendo la obtención de conclusiones de interés para la biología del cáncer.Cancer is an ensemble consisting of over a hundred kinds of related diseases characterized by the unrestrained proliferation of cells and their ability to spread to other tissues, forming metastases. It is one of the leading causes of mortality worldwide. For this reason, numerous studies are conducted for a better understanding of their behaviour in the body and to confront them effectively. The study of multidrug resistance (MDR) is an interesting line of research, as it is the major cause of failure of cancer treatment. In recent years, the interest in applying mathematical techniques to analyze biological problems has been boosted. Because of the importance of oncological diseases, this research has developed a mathematical model based on differential equations for describing the chemotherapy resistance transfer process in mixtures of two tumor cell populations: resistant and sensitive cells. Moreover, semi-empirical models parametrized with experimental data from cell proliferation essays and numerical simulations have been performed to validate the model, using the mathematical software Matlab. As a result of the investigation, it is not worthy that the model represents the in vitro proliferation of sensitive and resistant cancer cells and their mixed cultures. This will allow research to continue on higher levels of complexity and to draw relevant conclusions for Cancer Biology

Immunoassay for SARS-CoV-2 Humoral Response Monitorization: A Study of the Antibody Response in COVID-19 Patients with Different Clinical Profiles during the First and Second Waves in Cadiz, Spain

There is still a long way ahead regarding the COVID-19 pandemic, since emerging waves remain a daunting challenge to the healthcare system. For this reason, the development of new preventive tools and therapeutic strategies to deal with the disease have been necessary, among which serological assays have played a key role in the control of COVID-19 outbreaks and vaccine development. Here, we have developed and evaluated an immunoassay capable of simultaneously detecting multiple IgG antibodies against different SARS-CoV-2 antigens through the use of Bio- PlexTM technology. Additionally, we have analyzed the antibody response in COVID-19 patients with different clinical profiles in Cadiz, Spain. The multiplex immunoassay presented is a high-throughput and robust immune response monitoring tool capable of concurrently detecting anti-S1, anti-NC and anti-RBD IgG antibodies in serum with a very high sensitivity (94.34–97.96%) and specificity (91.84–100%). Therefore, the immunoassay proposed herein may be a useful monitoring tool for individual humoral immunity against SARS-CoV-2, as well as for epidemiological surveillance. In addition, we show the values of antibodies against multiple SARS-CoV-2 antigens and their correlation with the different clinical profiles of unvaccinated COVID-19 patients in Cadiz, Spain, during the first and second waves of the pandemic.Project grant number COV20-00173 of the 2020 Emergency Call for Research Projects about the SARS-CoV-2 virus and the COVID-19 disease of the Institute of Health “Carlos III” from the Spanish Ministry of Science and Innovation; Project grant number PECART-0096-2020, Consejería de Salud y Familias, Junta de Andalucía, Spain

Polarimetric imaging for the detection of synthetic models of SARS-CoV-2: A proof of concept

Objective: To conduct a proof-of-concept study of the detection of two synthetic models of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using polarimetric imaging. Approach: Two SARS-CoV-2 models were prepared as engineered lentiviruses pseudotyped with the G protein of the vesicular stomatitis virus, and with the characteristic Spike protein of SARS-CoV-2. Samples were prepared in two biofluids (saline solution and artificial saliva), in four concentrations, and deposited as 5-µL droplets on a supporting plate. The angles of maximal degree of linear polarization (DLP) of light diffusely scattered from dry residues were determined using Mueller polarimetry from87 samples at 405 nm and 514 nm. A polarimetric camera was used for imaging several samples under 380–420 nm illumination at angles similar to those of maximal DLP. Per-pixel image analysis included quantification and combination of polarization feature descriptors in 475 samples. Main results: The angles (from sample surface) of maximal DLP were 3° for 405 nm and 6° for 514 nm. Similar viral particles that differed only in the characteristic spike protein of the SARS-CoV-2, their corresponding negative controls, fluids, and the sample holder were discerned at 10-degree and 15-degree configurations. Significance: Polarimetric imaging in the visible spectrum may help improve fast, non-contact detection and identification of viral particles, and/or other microbes such as tuberculosis, in multiple dry fluid samples simultaneously, particularly when combined with other imaging modalities. Further analysis including realistic concentrations of real SARS-CoV-2 viral particles in relevant human fluids is required. Polarimetric imaging under visible light may contribute to a fast, cost-effective screening of SARS-CoV-2 and other pathogens when combined with other imaging modalities.12 página

Hyperspectral image processing for the identification and quantification of lentiviral particles in fluid samples

Optical spectroscopic techniques have been commonly used to detect the presence of biofilm-forming pathogens (bacteria and fungi) in the agro-food industry. Recently, near-infrared (NIR) spectroscopy revealed that it is also possible to detect the presence of viruses in animal and vegetal tissues. Here we report a platform based on visible and NIR (VNIR) hyperspectral imaging for non-contact, reagent free detection and quantification of laboratory-engineered viral particles in fluid samples (liquid droplets and dry residue) using both partial least square-discriminant analysis and artificial feed-forward neural networks. The detection was successfully achieved in preparations of phosphate buffered solution and artificial saliva, with an equivalent pixel volume of 4 nL and lowest concentration of 800 TU.mu L-1. This method constitutes an innovative approach that could be potentially used at point of care for rapid mass screening of viral infectious diseases and monitoring of the SARS-CoV- 2 pandemic.This research was funded by grants number COV20-00080 and COV20-00173 of the 2020 Emergency Call for Research Projects about the SARS-CoV-2 virus and the COVID-19 disease of the Institute of Health 'Carlos III', Spanish Ministry of Science and Innovation, and by grant number EQC2019-006240-P of the 2019 Call for Acquisition of Scientific Equipment, FEDER Program, Spanish Ministry of Science and Innovation. This work has been supported by the European Commission through the JRC HUMAINT project. ABR was supported by grant number RTI2018-094465-J funded by the Spanish National Agency of Research. The authors would like to gratefully acknowledge the assistance of the members of the EOD-CBRN Group of the Spanish National Police, whose identities cannot be disclosed, and who are represented here by JMNG. Authors thank continuous support from their institutions