Celldeath: A tool for detection of cell death in transmitted light microscopy images by deep learning-based visual recognition

Cell death experiments are routinely done in many labs around the world, these experiments are the backbone of many assays for drug development. Cell death detection is usually performed in many ways, and requires time and reagents. However, cell death is preceded by slight morphological changes in cell shape and texture. In this paper, we trained a neural network to classify cells undergoing cell death. We found that the network was able to highly predict cell death after one hour of exposure to camptothecin. Moreover, this prediction largely outperforms human ability. Finally, we provide a simple python tool that can broadly be used to detect cell death.Fil: la Greca, Alejandro Damián. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Pérez, Nelba. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; ArgentinaFil: Castañeda, Sheila Lucia. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Milone, Paula Melania. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Scarafia, Maria Agustina. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Möbbs, Alan Miqueas. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Waisman, Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; ArgentinaFil: Moro, Lucía Natalia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; ArgentinaFil: Sevlever, Gustavo Emilio. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; ArgentinaFil: Luzzani, Carlos Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; ArgentinaFil: Miriuka, Santiago Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Fundación para la Lucha contra las Enfermedades Neurológicas de la Infancia; Argentin

Predicción de propiedades de celdas solares y módulos fotovoltaicos por métodos de inteligencia artificial

La optimización de los sistemas fotovoltaicos para la generación de energía eléctrica implica la necesidad de disponer datos reales de las diferentes variables involucradas, como así también la determinación de sus correlaciones. En el ámbito de la energía solar fotovoltaica resulta de interés poder predecir la energía eléctrica generada por los módulos en función de la radiación solar y de los parámetros climáticos. En este trabajo, se propone un método de correlación basado en técnicas de inteligencia artificial, que permite obtener la energía generada para distintas condiciones climáticas durante un año. Además, se propone un modelo que relaciona la corriente de cortocircuito de una celda solar con la radiación global, pero a diferencia de lo usual, se considera el verdadero comportamiento no lineal de la relación entre las variables. Los resultados del método propuesto empleando datos reales muestran su validez y utilidad en la predicción de energía generada por módulos fotovoltaicos y en avances tendientes a encontrar métodos de medición de radiación solar alternativos con bajo error.In the optimisation of photovoltaic systems for electricity generation real data of the different variables involved are needed as well as determination of their relationships. In the field of photovoltaic solar energy there is interest to predict the energy generation in terms of solar radiation and climatic parameters. In this paper, we propose a method based on artificial intelligence techniques for obtaining the generated energy under climatic conditions during a year. In addition, we propose a model that relates short-circuit current with radiation, but unlike usual, is considered the true nonlinear behavior of the relationship between variables. The results of the proposed method using real data show its validity and usefulness in predicting the generated energy by photovoltaic modules and the search for alternative methods of measuring global radiation at low cost and reasonable error.Asociación Argentina de Energías Renovables y Medio Ambiente (ASADES

Sustained Progression-Free Survival Benefit of Rituximab Maintenance in Patients With Follicular Lymphoma : Long-Term Results of the PRIMA Study

PURPOSE The PRIMA study (ClinicalTrials.gov identifier: NCT00140582) established that 2 years of rituximab maintenance after first-line immunochemotherapy significantly improved progression-free survival (PFS) in patients with follicular lymphoma compared with observation. Here, we report the final PFS and overall survival (OS) results from the PRIMA study after 9 years of follow-up and provide a final overview of safety. METHODS Patients (> 18 years of age) with previously untreated high-tumor-burden follicular lymphoma were nonrandomly assigned to receive one of three immunochemotherapy induction regimens. Responding patients were randomly assigned (stratified by induction regimen, response to induction treatment, treatment center, and geographic region) 1:1 to receive 2 years of rituximab maintenance (375 mg/m(2), once every 8 weeks), starting 8 weeks after the last induction treatment, or observation (no additional treatment). All patients in the extended follow-up provided their written informed consent (data cutoff: December 31, 2016). RESULTS In total, 1,018 patients completed induction treatment and were randomly assigned to rituximab maintenance (n = 505) or observation (n = 513). Consent for the extended follow-up was provided by 607 patients (59.6%) of 1,018 (rituximab maintenance, n = 309; observation, n = 298). After data cutoff, median PFS was 10.5 years in the rituximab maintenance arm compared with 4.1 years in the observation arm (hazard ratio, 0.61; 95% CI, 0.52 to 0.73; P <.001). No OS difference was seen in patients randomly assigned to rituximab maintenance or observation (hazard ratio, 1.04; 95% CI, 0.77 to 1.40; P = .7948); 10-year OS estimates were approximately 80% in both study arms. No new safety signals were observed. CONCLUSION Rituximab maintenance after induction immunochemotherapy provides a significant long-term PFS, but not OS, benefit over observation.Peer reviewe

Differentiation syndrome in patients with acute promyelocytic leukemia treated with all- trans retinoic acid and anthracycline chemotherapy: Characteristics, outcome, and prognostic factors

Differentiation syndrome (DS) can be a life-threatening complication in patients with acute promyelocytic leukemia (APL) undergoing induction therapy with all- trans retinoic acid (ATRA). Detailed knowl- edge about DS has remained limited. We present an analysis of the incidence, char- acteristics, prognostic factors, and out- come of 739 APL patients treated with ATRA plus idarubicin in 2 consecutive trials (Programa Espanol de Tratamientos en Hematologíc [PETHEMA] LPA96 and LPA99). Overall, 183 patients (24.8%) ex- perienced DS, 93 with a severe form (12.6%) and 90 with a moderate form (12.2%). Severe but not moderate DS was associated with an increase in mortality. A bimodal incidence of DS was observed, with peaks occurring in the first and third weeks after the start of ATRA therapy. A multivariate analysis indicated that a WBC count greater than 5 x 109/L and an abnor- mal serum creatinine level correlated with an increased risk of developing severe DS. Patients receiving systematic pred- nisone prophylaxis (LPA99 trial) in con- trast to those receiving selective prophy- laxis with dexamethasone (LPA96 trial) had a lower incidence of severe DS. Pa- tients developing severe DS showed a reduced 7-year relapse-free survival in the LPA96 trial (60% vs 85%, P = .003), but this difference was not apparent in the LPA99 trial

Evolving trends in the management of acute appendicitis during COVID-19 waves. The ACIE appy II study

Background: In 2020, ACIE Appy study showed that COVID-19 pandemic heavily affected the management of patients with acute appendicitis (AA) worldwide, with an increased rate of non-operative management (NOM) strategies and a trend toward open surgery due to concern of virus transmission by laparoscopy and controversial recommendations on this issue. The aim of this study was to survey again the same group of surgeons to assess if any difference in management attitudes of AA had occurred in the later stages of the outbreak. Methods: From August 15 to September 30, 2021, an online questionnaire was sent to all 709 participants of the ACIE Appy study. The questionnaire included questions on personal protective equipment (PPE), local policies and screening for SARS-CoV-2 infection, NOM, surgical approach and disease presentations in 2021. The results were compared with the results from the previous study. Results: A total of 476 answers were collected (response rate 67.1%). Screening policies were significatively improved with most patients screened regardless of symptoms (89.5% vs. 37.4%) with PCR and antigenic test as the preferred test (74.1% vs. 26.3%). More patients tested positive before surgery and commercial systems were the preferred ones to filter smoke plumes during laparoscopy. Laparoscopic appendicectomy was the first option in the treatment of AA, with a declined use of NOM. Conclusion: Management of AA has improved in the last waves of pandemic. Increased evidence regarding SARS-COV-2 infection along with a timely healthcare systems response has been translated into tailored attitudes and a better care for patients with AA worldwide

HSP90 identified by a proteomic approach as druggable target to reverse platinum resistance in ovarian cancer

Acquired resistance to platinum (Pt)-based therapies is an urgent unmet need in the management of epithelial ovarian cancer (EOC) patients. Here, we characterized by an unbiased proteomics method three isogenic EOC models of acquired Pt resistance (TOV-112D, OVSAHO, and MDAH-2774). Using this approach, we identified several differentially expressed proteins in Pt-resistant (Pt-res) compared to parental cells and the chaperone HSP90 as a central hub of these protein networks. Accordingly, up-regulation of HSP90 was observed in all Pt-res cells and heat-shock protein 90 alpha isoform knockout resensitizes Pt-res cells to cisplatin (CDDP) treatment. Moreover, pharmacological HSP90 inhibition using two different inhibitors [17-(allylamino)-17-demethoxygeldanamycin (17AAG) and ganetespib] synergizes with CDDP in killing Pt-res cells in all tested models. Mechanistically, genetic or pharmacological HSP90 inhibition plus CDDP -induced apoptosis and increased DNA damage, particularly in Pt-res cells. Importantly, the antitumor activities of HSP90 inhibitors (HSP90i) were confirmed both ex vivo in primary cultures derived from Pt-res EOC patients ascites and in vivo in a xenograft model. Collectively, our data suggest an innovative antitumor strategy, based on Pt compounds plus HSP90i, to rechallenge Pt-res EOC patients that might warrant further clinical evaluation

Energía efectiva generada por módulos fotovoltaicos bajo condiciones naturales

La eficiencia efectiva de los módulos fotovoltaicos montados a la intemperie difiere significativamente del dato de eficiencia que puede disponerse a priori de sus hojas técnicas, incluso tampoco es constante. Se midió durante un periodo la energía generada por tres módulos fotovoltaicos de silicio monocristalino, amorfo y policristalino montados a 30 º respecto al plano horizontal, conjuntamente con la radiación y variables climáticas. Se modeló la función energía generada mediante técnicas de inteligencia computacional para los distintos materiales. Las funciones solución encontradas independientemente muestran una forma común en los materiales estudiados pero difieren en las constantes del modelo. Estos resultados permiten obtener la energía generada en función de datos usualmente disponibles para distintos tipos de módulos en condiciones reales de operación.Fil: Sánchez Reinoso, Carlos Roberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico Para la Industria Química; ArgentinaFil: Cutrera, Miriam Edith. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico Para la Industria Química; ArgentinaFil: Battioni, Mario Ruben. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico Para la Industria Química; ArgentinaFil: Risso, Gustavo Armando. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico Para la Industria Química; ArgentinaFil: Milone, Diego Humberto. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Departamento de Informática. Laboratorio de Investigaciones En Señales E Inteligencia Computacional; ArgentinaFil: Buitrago, Roman Horacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico Para la Industria Química; Argentin