Impacto de las estrategias didácticas implementadas en lengua castellana a estudiantes de grado primero en tiempos de COVID-19

Ante el cierre preventivo de instituciones escolares producto de la emergencia por COVID-19, cientos de países definieron un plan para que la educación no se detenga. Sin embargo, asegurar la continuidad en el proceso educativo no es simple y lleva implícito grandes desafíos para docentes, padres de familia, cuidadores y estudiantes; aunque existen recomendaciones el tema se reconoce como “abierto” y lejos aún de evidencias concluyentes que puedan orientar las acciones pedagógicas, (Pimentel, 2020) el panorama de las políticas educativas se describe como emergente y fluido, la evidencia y documentación es poca generalmente carece de detalles, lo que hace difícil determinar que funciona y que no en esta etapa (Jyones Gibbs, Sims, Rodnet y 2020). En este contexto la investigación recogió información sobre el impacto de las estrategias didácticas implementadas por los docentes de la Institución Educativa Cedid Ciudad Bolívar Sede C Jornada Tarde a los estudiantes de grado 102 durante el confinamiento por COVID-19 en el II y III periodo académico 2020. De los resultados surgió una descripción de las herramientas utilizadas para la enseñanza y el aprendizaje orientadas a dar continuidad a la educación para ello los docentes combinaron estrategias tradicionales y digitales de segunda y tercera generación. De otro lado se encontró que las principales problemáticas a las que se enfrentaron son logísticas, tecnológicas y socioafectivas. En cuanto al uso de la tecnología para la comunicación utilizaron WhatsApp, para su trabajo académico Google Classroom, Wixsite y la plataforma institucional, para trabajo sincrónico las plataformas Zoom, Teams y Meet. La mayoría de los docentes refieren requerir apoyo tecnológico y asesoría didáctica para continuar los procesos académicos. (apartes del texto)Facing the preventive closure of school institutions as a result of the COVID-19 emergency, hundreds of countries defined a plan so that education does not stop. However, ensuring continuity in the educational process is not that simple and it implies great challenges for teachers, parents, caregivers and students. Although there are some recommendations, the subject is recognized as "open" and still far from conclusive evidence that can guide pedagogical actions, the panorama of educational policies is described as emerging and fluid, the evidence and documentation is scarce, generally lacks details, which makes hard to determine what works and what doesn't at this point. Having this in mind, this research collected information on the impact of the didactic strategies implemented by the teachers of the “Institución Educativa Cedid Ciudad Bolívar Sede C Jornada Tarde” to the students of grade 102 during the confinement by COVID-19 in the II and III academic period of2020. As a result, a description of the tools used for teaching and learning surged and this aimed at providing continuity to education, this is why the teachers combined traditional and digital second and third generation strategies. On the other hand, it was found that the main problems the teachers faced are logistical, technological and socio-affective. Regarding the use of technology for communication, they used WhatsApp, for their academic work Google Classroom, Wixsite and the institutional platform, for synchronous work the Zoom, Teams and Meet platforms. Most of the teachers report requiring technological support and didactic advice to continue the academic processes.Fundación Universitaria Los Libertadore

Jóvenes, pandemia y amor

Treball Final de Grau en Periodisme. Codi: PE0932. Curs acadèmic: 2020/2021Our report "Youth, pandemic and love" talks about love in times of pandemic. Throughout all this time, we have seen how data on deaths, the economic impact or the management of public health in this health crisis, have been the negative collateral damage that has monopolized all the news. However, many other negative consequences that this pandemic has caused have not been as important as they deserve. One of them is, in the most social aspect, love. On our topic, love in times of pandemic, we have seen a lack of information about it. For this reason, we wanted to investigate the subject, emphasizing what has happened to love as a couple and how we relate to each other now. As young people we feel harmed by the lack of information about what has happened to love during confinement, how all those people who have not had a partner in that period of time have experienced it, or in what way it has harmed or not couples who have spent confinement both in the same house and separately. But, above all, we find a lack of information on what is going to happen with love from now on, how we relate to so many restrictions and how we are going to meet new people without risk of contagion. It should be noted that we focus on a young target audience, of people between 15 and 30 years old. The main reason that leads us to narrow our target audience at this age is that, as young people, we feel harmed by this problem, and we believe it is necessary to carry out a report showing all the consequences that the pandemic has caused in love. Thus, with this report focused on young people, we intend to provide a new vision from the point of view of young people, in a closer and more direct way. In addition, this age group is when love is most experienced. Meeting people in discos, touching each other, seeing each other freely, have been many of the things that have been prohibited during the year and a half of the pandemic. And we do not know if we will be able to carry them out again or in how long. Therefore, it is a time lost in the experimentation of love and that has had its repercussion especially in young people. Regarding the news of this report, it should be noted that it is a contemporary issue that, to this day, we still continue to suffer. The importance of this report is undoubted since we are going through an unknown situation for our society. As future professionals in the field of information and communication, we believe that it is Autoras: Raquel Jerez y Alba María Lluesma Tutor: Abel Campos 44 Jóvenes, pandemia y amor essential to speak about all possible issues that concern the population and give voice to problems that affect society. As young people, we consider that it is also convenient not to forget our generation, which, although it is one of the most prepared and informed, is one of those that also raises the most doubts and who most demands answers and solutions. If we talk about love we always think about banal things, but nothing is further from reality, love is a fundamental piece in our lives. We are increasingly discovering what love is, that there are many different and valid types of love, as well as the importance of love in our personal lives and as a society. So, with our report we wanted to focus on love, focusing on love as a couple in youth. Within the theme of love in times of pandemic, first of all, we wanted to limit our work on how love is lived in a target audience of young people between 15 and 30 years old. Secondly, we have focused our work on love as a couple, involving young people who have gone through confinement with their partner, separated from her, as well as people who have gone through confinement without a partner. The assembly phase has been carried out entirely with the Adobe Premiere Pro, version 14 editing program. The first technique we have used is to set the video sequence to a Sony XDCAM HD422 1080 PAL editing mode. In order to give it more movement and variety, we have used techniques such as time lapse, stop motion and multiscreen. With this we use three different ways of editing and that differ from the rest of the effects and elements of the montage that we have used during the edition. The objective of using these effects is to give more speed and dynamism to the video, as well as a greater agility to the shots. In general, we have used a direct cut as a step between sequences and scenes, since it does not seem necessary to reload our report with transitions. The use of the "multiscreen" we have used as a resource plan before presenting the protagonists of the report, both couples and single people, and also the random people we have asked on the street. To correct the blurring of an image we have decided to use the "unsharp mask" video effect with quantity values of 50% and radius values of 50%. Autoras: Raquel Jerez y Alba María Lluesma Tutor: Abel Campos 45 Jóvenes, pandemia y amor Thus, to solve the cuts in the interviews we have applied the video transition «dissolve» → «transformation cut». With regard to color, it must be said that in the recording phase we always took into account the same values in the camera so as not to have too many mismatches later. Of course, each scenario was different so many times the values had to be adapted and we did so. Even so, in this post-production phase we have had to perform some color correction task, to correct any imperfection. To do this, we have used automatic basic color correction in the lumetri color adjustments. From there, we have also made manual adjustments, to give more warmth to the images and to retouch the light left by the spotlights, as well as some burnt backgrounds. As for the sound, we have made use of a sound overlap. That is to say, when the word was heard, the base of the song used progressively lowered and when there was no word the song was raised gradually as well. We have also made use of the "repair" effect from the window option, in the essential sound section. From there we have removed all the ambient sound that could sneak in, such as the air, the birds, the murmur of the people, etc. Our target audience is young people, specifically those in the 15 to 30 age range. According to the Youth Report carried out in 2020 by the Ministry of Social Law and the 2030 Agenda, today's young people are digital natives, “which implies that they have developed great familiarity with online environments, which they use to inform themselves, study, interact, buy and entertain themselves ”, so our report would be broadcast on digital platforms. The two options for digital platforms belong to RTVE. We want to bet on this public channel, since we think that they are not subject to political ideals. We also want to make use of this public tool, since it also belongs to us. The first option would be Playz, RTVE's online content platform. It is aimed especially at a young audience and hence the reason for its name 'Playz', since it refers to generation Z, those people born between 1995 and 2015 approximately. A second option would be Lab RTVE, the audiovisual innovation laboratory of Radio Televisión Española. We believe that our report could fit into this format, as similar products are disseminated Autoras: Raquel Jerez y Alba María Lluesma Tutor: Abel Campos 46 Jóvenes, pandemia y amor and the possibilities offered by the Internet are explored. We also opted for the broadcast of the report on our Valencian public television, À Punt Mèdia. Regarding the strengths of our report, it should be noted that, without any doubt, it is a current and innovative topic. To this day we are still immersed in the last throes of a pandemic that has made us rethink many things, including love. Our report also stands out for its closeness to young and spontaneous sources who shamelessly expose what worries them and ask themselves the same questions as so many other young people. Regarding the weak points of our report, mainly, we can say that since it is a topic that has not been covered in depth, we had little such concrete expert information. We also find it difficult to focus on the subject since, being such a broad subject with so many aspects and that it could be approached from different and different perspectives, many times the subject could go to another problem. That is, love is very diverse, there is love as a couple, love for your family, friends, self-love, etc. For love as a couple we have the expert sources explained above but we could have also spoken with philosophers, writers, sex educators, to give you another point of view. Within love as a couple, other interesting topics arose to deal with, such as separations in confinement, violence in the couple, etc. Therefore, many times the information that we obtained and found could make us change the focus of our report almost without realizing it

Explainable clinical coding with in-domain adapted transformers

Background and Objective: Automatic clinical coding is a crucial task in the process of extracting relevant in-formation from unstructured medical documents contained in Electronic Health Records (EHR). However, most of the existing computer-based methods for clinical coding act as “black boxes”, without giving a detailed description of the reasons for the clinical-coding assignments, which greatly limits their applicability to real-world medical scenarios. The objective of this study is to use transformer-based models to effectively tackle explainable clinical-coding. In this way, we require the models to perform the assignments of clinical codes to medical cases, but also to provide the reference in the text that justifies each coding assignment. Methods: We examine the performance of 3 transformer-based architectures on 3 different explainable clinical-coding tasks. For each transformer, we compare the performance of the original general-domain version with an in-domain version of the model adapted to the specificities of the medical domain. We address the explainable clinical-coding problem as a dual medical named entity recognition (MER) and medical named entity normal-ization (MEN) task. For this purpose, we have developed two different approaches, namely a multi-task and a hierarchical-task strategy. Results: For each analyzed transformer, the clinical-domain version significantly outperforms the corresponding general domain model across the 3 explainable clinical-coding tasks analyzed in this study. Furthermore, the hierarchical-task approach yields a significantly superior performance than the multi-task strategy. Specifically, the combination of the hierarchical-task strategy with an ensemble approach leveraging the predictive capa-bilities of the 3 distinct clinical-domain transformersFunding for open access charge: Universidad de Málaga / CBUA. The authors thankfully acknowledge the computer resources, technical expertise and assistance provided by the SCBI (Supercomputing and Bioinformatics) center of the University of Málaga

Clinical text classification in Cancer Real-World Data in Spanish

Healthcare systems currently store a large amount of clinical data, mostly unstructured textual information, such as electronic health records (EHRs). Manually extracting valuable information from these documents is costly for healthcare professionals. For example, when a patient first arrives at an oncology clinical analysis unit, clinical staff must extract information about the type of neoplasm in order to assign the appropriate clinical specialist. Automating this task is equivalent to text classification in natural language processing (NLP). In this study, we have attempted to extract the neoplasm type by processing Spanish clinical documents. A private corpus of 23, 704 real clinical cases has been processed to extract the three most common types of neoplasms in the Spanish territory: breast, lung and colorectal neoplasms. We have developed methodologies based on state-of-the-art text classification task, strategies based on machine learning and bag-of-words, based on embedding models in a supervised task, and based on bidirectional recurrent neural networks with convolutional layers (C-BiRNN). The results obtained show that the application of NLP methods is extremely helpful in performing the task of neoplasm type extraction. In particular, the 2-BiGRU model with convolutional layer and pre-trained fastText embedding obtained the best performance, with a macro-average, more representative than the micro-average due to the unbalanced data, of 0.981 for precision, 0.984 for recall and 0.982 for F1-score.The authors acknowledge the support from the Ministerio de Ciencia e Innovación (MICINN) under project PID2020-116898RB-I00, from Universidad de Málaga and Junta de Andalucía through grants UMA20-FEDERJA-045 and PYC20-046-UMA (all including FEDER funds), and from the Malaga-Pfizer consortium for AI research in Cancer - MAPIC. Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Detection of tumor morphology mentions in clinical reports in spanish using transformers

The aim of this study is to systematically examine the performance of transformer-based models for the detection of tumor morphology mentions in clinical documents in Spanish. For this purpose, we analyzed 3 transformer models supporting the Spanish language, namely multilingual BERT, BETO and XLM-RoBERTa. By means of a transfer- learning-based approach, the models were first pretrained on a collection of real-world oncology clinical cases with the goal of adapting trans- formers to the distinctive features of the Spanish oncology domain. The resulting models were further fine-tuned on the Cantemist-NER task, addressing the detection of tumor morphology mentions as a multi-class sequence-labeling problem. To evaluate the effectiveness of the proposed approach, we compared the obtained results by the domain-specific ver- sion of the examined transformers with the performance achieved by the general-domain version of the models. The results obtained in this pa- per empirically demonstrated that, for every analyzed transformer, the clinical version outperformed the corresponding general-domain model on the detection of tumor morphology mentions in clinical case reports in Spanish. Additionally, the combination of the transfer-learning-based approach with an ensemble strategy exploiting the predictive capabilities of the distinct transformer architectures yielded the best obtained results, achieving a precision value of 0.893, a recall of 0.887 and an F1-score of 0.89, which remarkably surpassed the prior state-of-the-art performance for the Cantemist-NER task

Serum protein levels following surgery in breast cancer patients: A protein microarray approach

Este artículo ha sido publicado en INTERNATIONAL JOURNAL OF ONCOLOGY No hemos podido encontrar infomración sobre si permite depositar conlicencia creative Commons El archivo solicitado a la editorial como postprint que nos ha remitido es el que depositamosSurgery is the primary treatment for non-metastatic breast cancer. However, the risk of early recurrence remains after surgical removal of the primary tumor. Recurrence is suggested to result from hidden micrometastatic foci, which are triggered to escape from dormancy by surgical resection of the primary tumor. In this study, we focused on the differential impact of breast surgery on the serum profiles of early breast cancer patients and healthy women. Serum samples from invasive breast cancer patients, in situ carcinoma breast cancer patients and healthy women were analyzed using reverse phase protein array technology. Samples were collected prior to breast surgery and 24 h following breast surgery. Both the expression level and the velocity of 42 serum proteins were quantified and compared among groups. We found that surgery increased the concentration of several proteins (CSF1, THSB2, IL6, IL7, IL16, FasL and VEGF-B) in the overall population. Compared with healthy women and patients with non-invasive tumors, invasive tumor patients exhibited higher preoperative levels of several serum proteins, such as αFP, IFNβ1, VEGF-A, IL18, E-cadherin or CD31, and lower postoperative levels of TNFα and IL5. Similarly, we detected significant surgery-induced changes in the velocity of VEGF-A and IL16 accumulation in samples derived from invasive breast cancer patients. In conclusion, breast surgery induced distinct changes in the concentrations and dynamics of serum proteins in invasive breast cancer patients compared with healthy women and noninvasive tumor patients.The authors acknowledge support through grants from the Junta de Andalucia (0199/2006 and TIC-4026), the Fundacion Mutua Madrileña and the Spanish MINECO (TIN2010-16556)

Male breast cancer: correlation between immunohistochemical subtyping and PAM50 intrinsic subtypes, and the subsequent clinical outcomes

Política de acceso abierto tomada de: https://beta.sherpa.ac.uk/id/publication/4003Male breast cancer is a rare disease that is still poorly understood. It is mainly classified by immunohistochemistry as a luminal disease. In this study, we assess for the first time the correlation between molecular subtypes based on a validated six-marker immunohistochemical panel and PAM50 signature in male breast cancer, and the subsequent clinical outcome of these different subtypes. We collected 67 surgical specimens of invasive male breast cancer from four different Spanish pathology laboratories. Immunohistochemical staining for the six-marker panel was performed on tissue microarrays. PAM50 subtypes were determined in a research-use-only nCounter Analysis System. We explored the association of immunohistochemical and PAM50 subtypes. Overall survival and disease-free survival were analyzed in the different subtypes of each classification. The distribution of tumor molecular subtypes according PAM50 was: 60% luminal B, 30% luminal A and 10% human epidermal growth factor receptor 2 (Her2) enriched. Only one Her2-enriched tumor was also positive by immunohistochemistry and was treated with trastuzumab. None of the tumors were basal-like. Using immunohistochemical surrogates, 51% of the tumors were luminal B, 44% luminal A, 4% triple-negative and 1% Her2-positive. The clinicopathological characteristics did not differ significantly between immunohistochemical and PAM50 subtypes. We found a significant worse overall survival in Her2-enriched compared with luminal tumors. Male breast cancer seems to be mainly a genomic luminal disease with a predominance of the luminal B subtype. In addition, we found a proportion of patients with Her2-negative by immunohistochemistry but Her2-enriched profile by PAM50 tumors with a worse outcome compared with luminal subtypes that may benefit from anti-Her2 therapies

Machine learning and natural language processing (NLP) approach to predict early progression to first-line treatment in real-world hormone receptor-positive (HRþ)/HER2-negative advanced breast cancer patients.

Este artículo ha sido publicado en la revista European Journal of Cancer. Esta versión tiene Licencia Creative Commons CC-BY-NC-NDBackground: CDK4/6 inhibitors plus endocrine therapies are the current standard of care in the first-line treatment of HRþ/HER2-negative metastatic breast cancer, but there are no well-established clinical or molecular predictive factors for patient response. In the era of personalised oncology, new approaches for developing predictive models of response are needed. Materials and methods: Data derived from the electronic health records (EHRs) of real-world patients with HRþ/HER2-negative advanced breast cancer were used to develop predictive models for early and late progression to first-line treatment. Two machine learning approaches were used: a classic approach using a data set of manually extracted features from reviewed (EHR) patients, and a second approach using natural language processing (NLP) of freetext clinical notes recorded during medical visits. Results: Of the 610 patients included, there were 473 (77.5%) progressions to first-line treatment, of which 126 (20.6%) occurred within the first 6 months. There were 152 patients (24.9%) who showed no disease progression before 28 months from the onset of first-line treatment. The best predictive model for early progression using the manually extracted dataset achieved an area under the curve (AUC) of 0.734 (95% CI 0.687e0.782). Using the NLP free-text processing approach, the best model obtained an AUC of 0.758 (95% CI 0.714 e0.800). The best model to predict long responders using manually extracted data obtained an AUC of 0.669 (95% CI 0.608e0.730). With NLP free-text processing, the best model attained an AUC of 0.752 (95% CI 0.705e0.799). Conclusions: Using machine learning methods, we developed predictive models for early and late progression to first-line treatment of HRþ/HER2-negative metastatic breast cancer, also finding that NLP-based machine learning models are slightly better than predictive models based on manually obtained data

Triple negative breast cancer subtypes and pathologic complete response rate to neoadjuvant chemotherapy.

Este articulo ha sido publicado en la revista Oncotarget. Esta versión tiene Licencia Creative Commons CC-BYTriple negative breast cancer (TNBC) is a heterogeneous disease with distinct molecular subtypes that differentially respond to chemotherapy and targeted agents. The purpose of this study is to explore the clinical relevance of Lehmann TNBC subtypes by identifying any differences in response to neoadjuvant chemotherapy among them. We determined Lehmann subtypes by gene expression profiling in paraffined pre-treatment tumor biopsies from 125 TNBC patients treated with neoadjuvant anthracyclines and/or taxanes +/- carboplatin. We explored the clinicopathological characteristics of Lehmann subtypes and their association with the pathologic complete response (pCR) to different treatments. The global pCR rate was 37%, and it was unevenly distributed within Lehmann’s subtypes. Basal-like 1 (BL1) tumors exhibited the highest pCR to carboplatin containing regimens (80% vs 23%, p=0.027) and were the most proliferative (Ki-67>50% of 88.2% vs. 63.7%, p=0.02). Luminal-androgen receptor (LAR) patients achieved the lowest pCR to all treatments (14.3% vs 42.7%, p=0.045 when excluding mesenchymal stem-like (MSL) samples) and were the group with the lowest proliferation (Ki-67≤50% of 71% vs 27%, p=0.002). In our cohort, only tumors with LAR phenotype presented non-basal-like intrinsic subtypes (HER2- enriched and luminal A). TNBC patients present tumors with a high genetic diversity ranging from highly proliferative tumors, likely responsive to platinum-based therapies, to a subset of chemoresistant tumors with low proliferation and luminal characteristics.This work was supported by Centro de Investigación Biomédica en Red de Cáncer (CIBERONC) from Instituto de Salud Carlos III (ISCIII) (CB16/12/00241, CB16/12/00471, CB16/12/00481) and by research grants from ISCIII (PI13/00730), Mutua Madrileña 2013 and Sociedad Española de Oncología Médica (SEOM) 2013. The authors acknowledge support through grant TIN2017- 88728-C2-1-R from MICINN-SPAIN. Angela Santonja has a predoctoral grant PFIS-ISCIII (FI12/00489)

Classical BSE dismissed as the cause of CWD in Norwegian red deer despite strain similarities between both prion agents

The first case of CWD in a Norwegian red deer was detected by a routine ELISA test and confirmed by western blotting and immunohistochemistry in the brain stem of the animal. Two different western blotting tests were conducted independently in two different laboratories, showing that the red deer glycoprofile was different from the Norwegian CWD reindeer and CWD moose and from North American CWD. The isolate showed nevertheless features similar to the classical BSE (BSE-C) strain. Furthermore, BSE-C could not be excluded based on the PrPSc immunohistochemistry staining in the brainstem and the absence of detectable PrPSc in the lymphoid tissues. Because of the known ability of BSE-C to cross species barriers as well as its zoonotic potential, the CWD red deer isolate was submitted to the EURL Strain Typing Expert Group (STEG) as a BSE-C suspect for further investigation. In addition, different strain typing in vivo and in vitro strategies aiming at identifying the BSE-C strain in the red deer isolate were performed independently in three research groups and BSE-C was not found in it. These results suggest that the Norwegian CWD red deer case was infected with a previously unknown CWD type and further investigation is needed to determine the characteristics of this potential new CWD strain