10 research outputs found
AI is a viable alternative to high throughput screening: a 318-target study
: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNetÂź convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNetÂź model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery
Red Nacional de reconocedores de suelos.
Los relevamientos sistemĂĄticos de suelos en Argentina comenzaron en la dĂ©cada de 1960, en el marco del Plan Mapa de Suelos. Dicho plan, desarrollado y liderado por el INTA, dio impulso a la formaciĂłn de especialistas y a la producciĂłn de cartografĂa de suelos a diferentes escalas. Sin embargo, a partir del año 2000 las actividades se redujeron notablemente y gran parte de los equipos provinciales formados hasta ese momento se desarticularon. Desde entonces los relevamientos continuaron de manera aislada sĂłlo en aquellas provincias donde se mantuvieron los grupos de trabajo. Este hecho condujo a que actualmente diferentes regiones del paĂs no cuenten con informaciĂłn acerca de las propiedades y distribuciĂłn de suelos a una escala adecuada para la toma de decisiones. En este contexto, en el 2018 se crea la Red Nacional de Reconocedores de Suelos (RNRS) que organiza las capacidades tĂ©cnicas y operativas a nivel nacional para dar pronta respuesta a la creciente demanda de cartografĂa. Se trata de un equipo interinstitucional e interdisciplinario de especialistas distribuidos por todo el paĂs, que realiza tareas de relevamiento, produce y difunde cartografĂa bĂĄsica y utilitaria de suelos, ofrece capacitaciĂłn y genera espacios de discusiĂłn y actualizaciĂłn metodolĂłgica. A la fecha, la RNRS ha relevado aproximadamente 760.000 ha en el sur de CĂłrdoba, estimando completar durante el presente año el relevamiento del departamento RĂo Cuarto. Esta estrategia organizacional permitirĂĄ avanzar en el mapeo semidetallado de suelos en nuestro paĂs, estableciendo vinculaciones sinĂ©rgicas entre profesionales de diferentes instituciones a fin de fortalecer y potenciar los equipos de trabajo en cada regiĂłn. El motivo de esta contribuciĂłn es presentar la RNRS, sus objetivos, avances a la fecha y desafĂos a futuro, haciendo una breve revisiĂłn del estado actual de los relevamientos a escala semidetallada en nuestro paĂs.Fil: Moretti, Lucas M. Instituto Nacional de TecnologĂa Agropecuaria (INTA). EstaciĂłn Experimental Agropecuaria Cerro Azul; ArgentinaFil: Rodriguez, DarĂo M. Instituto Nacional de TecnologĂa Agropecuaria (INTA). Instituto de Suelos; ArgentinaFil: Schulz, Guillermo A. Instituto Nacional de TecnologĂa Agropecuaria (INTA). Instituto de Suelos; ArgentinaFil: Kurtz, Ditmar Bernardo. Instituto Nacional de TecnologĂa Agropecuaria (INTA). EstaciĂłn Experimental Agropecuaria Corrientes; ArgentinaFil: Altamirano D. Instituto Nacional de TecnologĂa Agropecuaria (INTA). EstaciĂłn Experimental Agropecuaria Manfredi; ArgentinaFil: Amin, S. Universidad Nacional de RĂo Cuarto; ArgentinaFil: Angelini, Marcos Esteban. Instituto Nacional de TecnologĂa Agropecuaria (INTA). Instituto de Suelos; Argentina. Wageningen University. Soil Geography and Landscape group; Holanda. International Soil Reference and Information Centre. World Soil Information; HolandaFil: Babelis, German Claudio. Instituto Nacional de TecnologĂa Agropecuaria (INTA). EstaciĂłn Experimental Agropecuaria San Juan; ArgentinaFil: Becerra, Alejandra Gabriela. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas. Centro CientĂfico TecnolĂłgico Conicet - CĂłrdoba. Instituto Multidisciplinario de BiologĂa Vegetal. Universidad Nacional de CĂłrdoba. Facultad de Ciencias Exactas FĂsicas y Naturales. Instituto Multidisciplinario de BiologĂa Vegetal; ArgentinaFil: Bedendo, Dante Julian. Instituto Nacional de TecnologĂa Agropecuaria (INTA). EstaciĂłn Experimental Agropecuaria ParanĂĄ; ArgentinaFil: Boldrini, C. Instituto Nacional de TecnologĂa Agropecuaria (INTA). EstaciĂłn Experimental Agropecuaria Marcos JuĂĄrez. Agencia de ExtensiĂłn Rural RĂo Cuarto; AgentinaFil: Bongiovanni, C. Universidad Nacional de RĂo Cuarto; ArgentinaFil: Bozzer, S. Universidad Nacional de RĂo Cuarto; ArgentinaFil: Cabrera, A. Universidad Nacional de RĂo Cuarto; ArgentinaFil: Canale, A. Instituto Nacional de TecnologĂa Agropecuaria (INTA). EstaciĂłn Experimental Agropecuaria Marcos JuĂĄrez. Agencia de ExtensiĂłn Rural RĂo Cuarto; AgentinaFil: Chilano, Y. Universidad Nacional de RĂo Cuarto; ArgentinaFil: Cholaky, Carmen. Universidad Nacional de RĂo Cuarto. Facultad de AgronomĂa y Veterinaria; ArgentinaFil: Cisneros; JosĂ© Manuel. Universidad Nacional de RĂo Cuarto. CĂĄtedra de Uso y Manejo de Suelos; ArgentinaFil: Colazo, Juan Cruz. Instituto Nacional de TecnologĂa Agropecuaria (INTA). EstaciĂłn Experimental Agropecuaria San Luis; ArgentinaFil: Corigliano, J. Universidad Nacional de RĂo Cuarto; ArgentinaFil: Degioanni, AmĂ©rico JosĂ©. Universidad Nacional RĂo Cuarto. Facultad de AgronomĂa y Veterinaria. Departamento de EcologĂa Agraria; ArgentinaFil: de la Fuente, Juan Carlos Instituto Nacional de TecnologĂa Agropecuaria (INTA). Instituto de Suelos; ArgentinaFil: Escobar, Dardo. Ministerio de Agricultura, GanaderĂa y Pesca; ArgentinaFil: Faule, L. Instituto Nacional de TecnologĂa Agropecuaria (INTA). EstaciĂłn Experimental Agropecuaria Manfredi. CĂłrdoba. ArgentinaFil: Galarza, Carlos Martin. Instituto Nacional de TecnologĂa Agropecuaria (INTA). EstaciĂłn Experimental Agropecuaria Marcos JuĂĄrez; ArgentinaFil: GonzĂĄlez, J. Universidad Nacional de RĂo Cuarto; ArgentinaFil: Holzmann, R. Instituto Nacional de TecnologĂa Agropecuaria (INTA). EstaciĂłn Experimental Agropecuaria Alto Valle; ArgentinaFil: Irigoin, Julieta. Instituto Nacional de TecnologĂa Agropecuaria (INTA). Instituto de Suelos; Argentina. Universidad Nacional de LujĂĄn. Departamento TecnologĂa; ArgentinaFil: Lanfranco, M. Instituto Nacional de TecnologĂa Agropecuaria (INTA). EstaciĂłn Experimental Agropecuaria Manfredi; ArgentinaFil: LeĂłn Giacosa, C. Instituto Nacional de TecnologĂa Agropecuaria (INTA). EstaciĂłn Experimental Agropecuaria Rafaela; ArgentinaFil: Matteio, J.P. Instituto Nacional de TecnologĂa Agropecuaria (INTA). Instituto de Suelos; ArgentinaFil: MĂĄrquez, C. Gobierno de CĂłrdoba. Ministerio de Agricultura y GanaderĂa; ArgentinaFil: Marzari, R. Universidad Nacional de RĂo Cuarto; ArgentinaFil: Mattalia, M.L. Universidad Nacional de RĂo Cuarto; ArgentinaFil: Morales Poclava, P.C. Instituto Nacional de TecnologĂa Agropecuaria (INTA). EstaciĂłn Experimental Agropecuaria Salta; ArgentinaFil: Muñoz, S. Instituto Nacional de TecnologĂa Agropecuaria (INTA). EstaciĂłn Experimental Agropecuaria Marcos JuĂĄrez; ArgentinaFil: Paladino, Ileana Ruth. Instituto Nacional de TecnologĂa Agropecuaria (INTA). Instituto de Suelos; Argentina. Universidad Nacional de Lomas de Zamora. Facultad de Ciencias Agrarias; ArgentinaFil: Parra, B. Universidad Nacional de RĂo Cuarto; ArgentinaFil: PĂ©rez, M. Gobierno de CĂłrdoba. Ministerio de Agricultura y GanaderĂa; ArgentinaFil: Pezzola, A. Instituto Nacional de TecnologĂa Agropecuaria (INTA). EstaciĂłn Experimental Agropecuaria Hilario Ascasubi; ArgentinaFil: Perucca, S. Instituto Nacional de TecnologĂa Agropecuaria (INTA). EstaciĂłn Experimental Agropecuaria Marcos JuĂĄrez. Agencia de ExtensiĂłn Rural RĂo Cuarto; ArgentinaFil: Porcel de Peralta, R. Gobierno de CĂłrdoba. Ministerio de Agricultura y GanaderĂa; ArgentinaFil: Renaudeau, S. Instituto Nacional de TecnologĂa Agropecuaria (INTA). EstaciĂłn Experimental Agropecuaria Corrientes; ArgentinaFil: Salustio, M. Instituto Nacional de TecnologĂa Agropecuaria (INTA). EstaciĂłn Experimental Agropecuaria Marcos JuĂĄrez. Agencia de ExtensiĂłn Rural RĂo Cuarto; ArgentinaFil: Sapino, V. Instituto Nacional de TecnologĂa Agropecuaria (INTA). EstaciĂłn Experimental Agropecuaria Rafaela; ArgentinaFil: Tenti Vuegen, L.M. Instituto Nacional de TecnologĂa Agropecuaria (INTA). Instituto de Suelos. ArgentinaFil: Tosolini, R. Instituto Nacional de TecnologĂa Agropecuaria (INTA). EstaciĂłn Experimental Agropecuaria Rafaela; ArgentinaFil: Vicondo, M.E. Instituto Nacional de TecnologĂa Agropecuaria (INTA). EstaciĂłn Experimental Agropecuaria Manfredi; Argentina. Universidad Nacional de CĂłrdoba. ArgentinaFil: Vizgarra, L.A. Instituto Nacional de TecnologĂa Agropecuaria (INTA). EstaciĂłn Experimental Agropecuaria Quimili; ArgentinaFil: Ybarra, D.D. Instituto Nacional de TecnologĂa Agropecuaria (INTA). EstaciĂłn Experimental Agropecuaria Corrientes; ArgentinaFil: Winschel, C. Instituto Nacional de TecnologĂa Agropecuaria (INTA). EstaciĂłn Experimental Agropecuaria Hilario Ascasubi; ArgentinaFil: Zamora, E. Instituto Nacional de TecnologĂa Agropecuaria (INTA). EstaciĂłn Experimental Agropecuaria Corrientes; Argentin
31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two
Background
The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd.
Methods
We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background.
Results
First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001).
Conclusions
In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival
Bothrops insularis venomics: A proteomic analysis supported by transcriptomic-generated sequence data
A joint transcriptomic and proteomic approach employing two-dimensional electrophoresis, liquid chromatography and mass spectrometry was carried out to identify peptides and proteins expressed by the venom gland of the snake Bothrops insularis, an endemic species of Queimada Grande Island, Brazil. Four protein families were mainly represented in processed spots, namely metalloproteinase, serine proteinase, phospholipase A(2) and lectin. Other represented families were growth factors, the developmental protein G10, a disintegrin and putative novel bradykinin-potentiating peptides. The enzymes were present in several isoforms. Most of the experimental data agreed with predicted values for isoelectric point and M(r) of proteins found in the transcriptome of the venom gland. The results also support the existence of posttranslational modifications and of proteolytic processing of precursor molecules which could lead to diverse multifunctional proteins. This study provides a preliminary reference map for proteins and peptides present in Bothrops insularis whole venom establishing the basis for comparative studies of other venom proteomes which could help the search for new drugs and the improvement of venom therapeutics. Altogether, our data point to the influence of transcriptional and post-translational events on the final venom composition and stress the need for a multivariate approach to snake venomics studies. (c) 2009 Elsevier B.V. All rights reserved.Fundação de Amparo Ă Pesquisa do Estado do Rio de Janeiro (FAPERJ)FAPERJ/Rio de Janeiro Proteomics NetworkCAPESCoordenação de Aperfeiçoamento de Pessoal de NĂvel Superior (CAPES)Conselho Nacional de Desenvolvimento CientĂfico e TecnolĂłgico (CNPq)CNPqFundação de Amparo Ă Pesquisa do Estado de SĂŁo Paulo (FAPESP)FAPESPFundacao ButantanFundação Butanta
Radiation treatment inhibits monocyte entry into the optic nerve head and prevents neuronal damage in a mouse model of glaucoma
Glaucoma is a common ocular disorder that is a leading cause of blindness worldwide. It is characterized by the dysfunction and loss of retinal ganglion cells (RGCs). Although many studies have implicated various molecules in glaucoma, no mechanism has been shown to be responsible for the earliest detectable damage to RGCs and their axons in the optic nerve. Here, we show that the leukocyte transendothelial migration pathway is activated in the optic nerve head at the earliest stages of disease in an inherited mouse model of glaucoma. This resulted in proinflammatory monocytes entering the optic nerve prior to detectable neuronal damage. A 1-time x-ray treatment prevented monocyte entry and subsequent glaucomatous damage. A single x-ray treatment of an individual eye in young mice provided that eye with long-term protection from glaucoma but had no effect on the contralateral eye. Localized radiation treatment prevented detectable neuronal damage and dysfunction in treated eyes, despite the continued presence of other glaucomatous stresses and signaling pathways. Injection of endothelin-2, a damaging mediator produced by the monocytes, into irradiated eyes, combined with the other glaucomatous stresses, restored neural damage with a topography characteristic of glaucoma. Together, these data support a model of glaucomatous damage involving monocyte entry into the optic nerve
Association between convalescent plasma treatment and mortality in COVID-19: a collaborative systematic review and meta-analysis of randomized clinical trials
Abstract Background Convalescent plasma has been widely used to treat COVID-19 and is under investigation in numerous randomized clinical trials, but results are publicly available only for a small number of trials. The objective of this study was to assess the benefits of convalescent plasma treatment compared to placebo or no treatment and all-cause mortality in patients with COVID-19, using data from all available randomized clinical trials, including unpublished and ongoing trials (Open Science Framework, https://doi.org/10.17605/OSF.IO/GEHFX ). Methods In this collaborative systematic review and meta-analysis, clinical trial registries (ClinicalTrials.gov, WHO International Clinical Trials Registry Platform), the Cochrane COVID-19 register, the LOVE database, and PubMed were searched until April 8, 2021. Investigators of trials registered by March 1, 2021, without published results were contacted via email. Eligible were ongoing, discontinued and completed randomized clinical trials that compared convalescent plasma with placebo or no treatment in COVID-19 patients, regardless of setting or treatment schedule. Aggregated mortality data were extracted from publications or provided by investigators of unpublished trials and combined using the HartungâKnappâSidikâJonkman random effects model. We investigated the contribution of unpublished trials to the overall evidence. Results A total of 16,477 patients were included in 33 trials (20 unpublished with 3190 patients, 13 published with 13,287 patients). 32 trials enrolled only hospitalized patients (including 3 with only intensive care unit patients). Risk of bias was low for 29/33 trials. Of 8495 patients who received convalescent plasma, 1997 died (23%), and of 7982 control patients, 1952 died (24%). The combined risk ratio for all-cause mortality was 0.97 (95% confidence interval: 0.92; 1.02) with between-study heterogeneity not beyond chance (I2 = 0%). The RECOVERY trial had 69.8% and the unpublished evidence 25.3% of the weight in the meta-analysis. Conclusions Convalescent plasma treatment of patients with COVID-19 did not reduce all-cause mortality. These results provide strong evidence that convalescent plasma treatment for patients with COVID-19 should not be used outside of randomized trials. Evidence synthesis from collaborations among trial investigators can inform both evidence generation and evidence application in patient care
Association between convalescent plasma treatment and mortality in COVID-19: a collaborative systematic review and meta-analysis of randomized clinical trials
Abstract Background Convalescent plasma has been widely used to treat COVID-19 and is under investigation in numerous randomized clinical trials, but results are publicly available only for a small number of trials. The objective of this study was to assess the benefits of convalescent plasma treatment compared to placebo or no treatment and all-cause mortality in patients with COVID-19, using data from all available randomized clinical trials, including unpublished and ongoing trials (Open Science Framework, https://doi.org/10.17605/OSF.IO/GEHFX ). Methods In this collaborative systematic review and meta-analysis, clinical trial registries (ClinicalTrials.gov, WHO International Clinical Trials Registry Platform), the Cochrane COVID-19 register, the LOVE database, and PubMed were searched until April 8, 2021. Investigators of trials registered by March 1, 2021, without published results were contacted via email. Eligible were ongoing, discontinued and completed randomized clinical trials that compared convalescent plasma with placebo or no treatment in COVID-19 patients, regardless of setting or treatment schedule. Aggregated mortality data were extracted from publications or provided by investigators of unpublished trials and combined using the HartungâKnappâSidikâJonkman random effects model. We investigated the contribution of unpublished trials to the overall evidence. Results A total of 16,477 patients were included in 33 trials (20 unpublished with 3190 patients, 13 published with 13,287 patients). 32 trials enrolled only hospitalized patients (including 3 with only intensive care unit patients). Risk of bias was low for 29/33 trials. Of 8495 patients who received convalescent plasma, 1997 died (23%), and of 7982 control patients, 1952 died (24%). The combined risk ratio for all-cause mortality was 0.97 (95% confidence interval: 0.92; 1.02) with between-study heterogeneity not beyond chance (I2 = 0%). The RECOVERY trial had 69.8% and the unpublished evidence 25.3% of the weight in the meta-analysis. Conclusions Convalescent plasma treatment of patients with COVID-19 did not reduce all-cause mortality. These results provide strong evidence that convalescent plasma treatment for patients with COVID-19 should not be used outside of randomized trials. Evidence synthesis from collaborations among trial investigators can inform both evidence generation and evidence application in patient care