Modelo de atención a estudiantes becarios de la Universidad Nacional Autónoma de México

La Universidad Nacional Autónoma de México (UNAM), es considerada la principal opción educativa de muchos jóvenes para mejorar sus condiciones de vida. Su población estudiantil cuenta con una gran diversidad, alumnos locales y migrantes, algunos provenientes de diversas poblaciones rurales y urbanas de la República Mexicana que tienen que adaptarse a un nuevo estilo y ritmo de vida, así como algunos jóvenes de otros países, con diferencias en el nivel cultural y problemáticas personales que junto con el cúmulo de problemas sociales que el país enfrenta, da por resultado una población diversa en riesgo de abandonar sus estudios. Para poder atender esta situación, se han puesto en marcha algunos programas de becas, que amén de apoyar económicamente a los estudiantes en desventaja, se busca sobre todo, aumentar la permanencia escolar y reducir su deserción. Este trabajo tiene como objetivo describir el impacto que tiene el modelo de atención a estudiantes de licenciatura de la UNAM, a través de indicadores cuantitativos y cualitativos diseñados para explicar un conjunto de acciones que favorecen el desempeño del joven. Se concluye que la población de estudiantes becarios cuenta con un soporte económico importante para apoyar sus estudios, sin embargo, no es suficiente, es fundamental atenderlos de manera integral, haciendo un trabajo interdisciplinario que abarque el apoyo de los profesionistas que se encuentran en contacto directo con ellos, como son los profesores a través de los programas de tutoría, así como de la orientación educativa para mejorar el rendimiento académico y la permanencia universitaria

SPITFIR(e): a supermaneuverable image restoration algorithm for 2D, 3D and 3D+Time microscopy images

International audienc

A sequential algorithm to detect diffusion switching along intracellular particle trajectories

Recent advances in molecular biology and fluorescence microscopy imaging have made possible the inference of the dynamics of single molecules in living cells. When we observe a long trajectory (more than 100 points), it is possible that the particle switches mode of motion over time. Then, an issue is to estimate the temporal change-points that is the times at which a change of dynamics occurs. We propose a non-parametric procedure based on test statistics [Briane et al., 2018] computed on local windows along the trajectory to detect the change-points. This algorithm controls the number of false change-point detections in the case where the trajectory is fully Brownian. A Monte Carlo study is proposed to demonstrate the performances of the method and also to compare the procedure to two competitive algorithms. At the end, we illustrate the efficacy of the method on real data in 2D and 3D, depicting the motion of mRNA complexes-called mRNP-in neuronal dendrites, Galectin-3 endocytosis and trafficking within the cell. A user-friendly Matlab package containing examples and the code of the simulations used in the paper is available at http://serpico.rennes.inria.fr/doku.php?id=software:cpanalysis: index

BioImageIT: Integration of image data-management with analysis

International audienceOpen science and FAIR principles are major topics in the field of modern microscopy for biology. This is due to both new data acquisition technologies like super-resolution and light sheet microscopy that generate large datasets but also to the new data analysis methodologies such as deep learning that automated data mining with high accuracy. Nevertheless data are still rarely shared and annotated because this implies a lot of manual and tedious work and software packaging. We present BioImageIT an open source framework that integrates automation of image datamanagement with data processing. Scientists then only need to import their data once in BioImageIT, which automatically generates and manages the metadata every time an operation is performed on the data. This accelerates the data mining process with no need anymore to deal with IT integration and manual analysis and annotations. BioImageIT then automatically implements FAIR principles. The interest of bioImageIT is thus twice. Wewill illustrate this through diverse application workflows, including preprocessing of raw data, complex images reconstructions (i.e Lattice Light Sheet or Multi-Angle TIRF micrscopy), deconvolution/denoising (including DL approaches) and analysis (tracking)

Evaluating Complex Interventions Using Qualitative Longitudinal Research: A Case Study of Understanding Pathways to Violence Prevention.

Evaluating social change programs requires methods that account for changes in context, implementation, and participant experience. We present a case study of a school-based partner violence prevention program with young people, where we conducted 33 repeat interviews with nine participants during and after an intervention and analyzed participant trajectories. We show how repeat interviews conducted during and after a social change program were useful in helping us understand how the intervention worked by providing rich contextual information, elucidating gradual shifts among participants, and identifying aspects of the intervention that appear to influence change. Long-term effects of social change interventions are very hard to quantify or measure directly. We argue that a qualitative longitudinal approach provides a way to measure subtle changes that can serve as proxies for longer term impacts

SPITFIR(e): A supermaneuverable algorithm for fast denoising and deconvolution of 3D fluorescence microscopy images and videos

International audienceModern fluorescent microscopy imaging is still limited by the optical aberrations and the photon budget available in the specimen. A direct consequence is the necessity to develop flexible and "off-road" algorithms in order to recover structural details and improve spatial resolution, which is critical when restraining the illumination to low levels in order to limit photo-damages. Here, we report SPITFIR(e) a flexible method designed to accurately and quickly restore 2D-3D fluorescence microscopy images and videos (4D images). We designed a generic sparse-promoting regularizer to subtract undesirable out-of-focus background and we developed a primal-dual algorithm for fast optimization. SPITFIR(e) is a "swiss-knife" method for practitioners as it adapts to any microscopy techniques, to various sources of signal degradation (noise, blur), to variable image contents, aswell as to low signal-to-noise ratios. Our method outperforms existing state-of-the-art algorithms, and is more flexible than supervised deep-learning methods requiring ground truth datasets. The performance, the flexibility, and the ability to push the spatiotemporal resolution limit of sub-diffracted fluorescence microscopy techniques are demonstrated on experimental datasets acquired with various microscopy techniques from 3D spinning-disk confocal up to lattice light sheet microscopy

EHD2 is a mechanotransducer connecting caveolae dynamics with gene transcription

Caveolae are small invaginated pits that function as dynamic mechanosensors to buffer tension variations at the plasma membrane. Here we show that under mechanical stress, the EHD2 ATPase is rapidly released from caveolae, SUMOylated, and translocated to the nucleus, where it regulates the transcription of several genes including those coding for caveolae constituents. We also found that EHD2 is required to maintain the caveolae reservoir at the plasma membrane during the variations of membrane tension induced by mechanical stress. Metal-replica electron microscopy of breast cancer cells lacking EHD2 revealed a complete absence of caveolae and a lack of gene regulation under mechanical stress. Expressing EHD2 was sufficient to restore both functions in these cells. Our findings therefore define EHD2 as a central player in mechanotransduction connecting the disassembly of the caveolae reservoir with the regulation of gene transcription under mechanical stress

The role of APC-mediated actin assembly in microtubule capture and focal adhesion turnover

International audienceFocal adhesion (FA) turnover depends on microtubules and actin. Microtubule ends are captured at FAs, where they induce rapid FA disassembly. However, actin’s roles are less clear. Here, we use polarization-resolved microscopy, FRAP, live cell imaging, and a mutant of Adenomatous polyposis coli (APC-m4) defective in actin nucleation to investigate the role of actin assembly in FA turnover. We show that APC-mediated actin assembly is critical for maintaining normal F-actin levels, organization, and dynamics at FAs, along with organization of FA components. In wild type cells, microtubules are captured repeatedly at FAs as they mature, but once a FA reaches peak maturity, the next microtubule capture event leads to delivery of an autophagosome, triggering FA disassembly. In APC-m4 cells, microtubule capture frequency and duration are altered, and there are long delays between autophagosome delivery and FA disassembly. Thus, APC-mediated actin assembly is required for normal feedback between microtubules and FAs, and maintaining FAs in a state ‘primed’ for microtubule-induced turnover

The final twist in endocytic membrane scission

International audienceMany endocytic uptake events depend on the 'pinchase' activity of dynamin. By measuring the orientation of single gold nanorods, a new study reveals that invaginated clathrin-coated endocytic pits undergo a strong rotational twist prior to or concomitant with their detachment