Plasma and CSF biomarkers in a memory clinic: Head-to-head comparison of phosphorylated tau immunoassays

INTRODUCTION: Direct comparisons of the main blood phosphorylated tau immunoassays in memory clinic populations are needed to understand possible differences. METHODS: In the BIODEGMAR study, 197 participants presenting with cognitive complaints were classified into an Alzheimer's disease (AD) or a non-AD cerebrospinal fluid (CSF) profile group, according to their amyloid beta 42/ phosphorylated tau (Aβ42/p-tau) ratio. We performed a head-to-head comparison of nine plasma and nine CSF tau immunoassays and determined their accuracy to discriminate abnormal CSF Aβ42/p-tau ratio. RESULTS: All studied plasma tau biomarkers were significantly higher in the AD CSF profile group compared to the non-AD CSF profile group and significantly discriminated abnormal CSF Aβ42/p-tau ratio. For plasma p-tau biomarkers, the higher discrimination accuracy was shown by Janssen p-tau217 (r = 0.76; area under the curve [AUC] = 0.96), ADx p-tau181 (r = 0.73; AUC = 0.94), and Lilly p-tau217 (r = 0.73; AUC = 0.94). DISCUSSION: Several plasma p-tau biomarkers can be used in a specialized memory clinic as a stand-alone biomarker to detect biologically-defined AD. HIGHLIGHTS: Patients with an Alzheimer's disease cerebrospinal fluid (AD CSF) profile have higher plasma phosphorylated tau (p-tau) levels than the non-AD CSF profile group. All plasma p-tau biomarkers significantly discriminate patients with an AD CSF profile from the non-AD CSF profile group. Janssen p-tau217, ADx p-tau181, and Lilly p-tau217 in plasma show the highest accuracy to detect biologically defined AD. Janssen p-tau217, ADx p-tau181, Lilly p-tau217, Lilly p-tau181, and UGot p-tau231 in plasma show performances that are comparable to their CSF counterparts

Broad targeting of resistance to apoptosis in cancer

Apoptosis or programmed cell death is natural way of removing aged cells from the body. Most of the anti-cancer therapies trigger apoptosis induction and related cell death networks to eliminate malignant cells. However, in cancer, de-regulated apoptotic signaling, particularly the activation of an anti-apoptotic systems, allows cancer cells to escape this program leading to uncontrolled proliferation resulting in tumor survival, therapeutic resistance and recurrence of cancer. This resistance is a complicated phenomenon that emanates from the interactions of various molecules and signaling pathways. In this comprehensive review we discuss the various factors contributing to apoptosis resistance in cancers. The key resistance targets that are discussed include (1) Bcl-2 and Mcl-1 proteins; (2) autophagy processes; (3) necrosis and necroptosis; (4) heat shock protein signaling; (5) the proteasome pathway; (6) epigenetic mechanisms; and (7) aberrant nuclear export signaling. The shortcomings of current therapeutic modalities are highlighted and a broad spectrum strategy using approaches including (a) gossypol; (b) epigallocatechin-3-gallate; (c) UMI-77 (d) triptolide and (e) selinexor that can be used to overcome cell death resistance is presented. This review provides a roadmap for the design of successful anti-cancer strategies that overcome resistance to apoptosis for better therapeutic outcome in patients with cancer

Campo Experimental Potrok Aike : resultado de 15 años de labor técnica

Libro de edición impresa publicado en 2005 y con edición electrónica en el año 2016.Al crearse, en el año 1985, la Estación Experimental Santa Cruz en el marco del convenio entre el INTA y la provincia de Santa Cruz surgió la necesidad de contar con un campo donde se pudieran desarrollar trabajos de investigación en ganadería, fundamentalmente ovina, y en pastizales naturales con el necesario control de diferentes variables productivas y ambientales. El gobierno provincial cedió un predio ubicado al sur de la provincia de Santa Cruz, en una zona representativa de la Estepa magallánica seca, en el extremo austral de la Patagonia. Esta publicación recopiló y organizó los datos e información dispersa resultante de más de 15 años de trabajo, y transformó esa materia prima en información accesible para técnicos y productores. Conformada por el aporte de distintos autores ofrece la información de base para describir el ambiente del Campo Experimental Potrok Aike, más las conclusiones de ensayos y experiencias llevadas a cabo en el lugar, que son perfectamente extrapolables a todo el sur provincial.EEA Santa CruzFil: Alegre, María Beatriz. Universidad Nacional de la Patagonia Austral. Unidad Académica Río Gallegos; Argentina.Fil: Alegre, María Beatriz. Consejo Agrario Provincial- Provincia de Santa Cruz; Argentina.Fil: Alegre, María Beatriz. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; ArgentinaFil: Anglesio, Francisco. Secretaría de Medio Ambiente. Provincia de Santa Cruz. Santa Cruz; Argentina.Fil: Baetti, Carlos. Consejo Agrario Provincial- Provincia de Santa Cruz; Argentina.Fil: Baetti, Carlos. Universidad Nacional de la Patagonia Austral. Unidad Académica Río Gallegos; Argentina.Fil: Bahamonde, Héctor Alejandro. Universidad Nacional de la Patagonia Austral. Unidad Académica Río Gallegos; Argentina.Fil: Bahamonde, Héctor Alejandro. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; ArgentinaFil: Barría, Julio. Consejo Agrario Provincial- Provincia de Santa Cruz; Argentina.Fil: Battini, Alberto. Consejo Agrario Provincial- Provincia de Santa Cruz; Argentina.Fil: Baumann, Osvaldo. Universidad Nacional de la Patagonia Austral. Unidad Académica Río Gallegos; Argentina.Fil: Borrelli, Pablo. Consultor privado. Buenos Aires; Argentina.Fil: Camejo, Ana María. Consultor privado. Trelew; Argentina.Fil: Castillo, Miguel. Universidad Nacional de la Patagonia Austral. Unidad Académica Río Gallegos; Argentina.Fil: Cibils, Andrés. New México State University. Department of Animal and Range Sciences; Estados UnidosFil: Ciurca, Lorena. Universidad Nacional de la Patagonia Austral. Unidad Académica Río Gallegos; Argentina.Fil: Clifton, Guillermo Raimundo. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina.Fil: Clifton, Guillermo Raimundo. Universidad Nacional de la Patagonia Austral. Unidad Académica Río Gallegos; Argentina.Fil: Culun, Victor Pascual. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; ArgentinaFil: Escalada, Julián. Universidad Nacional de la Patagonia Austral. Unidad Académica Río Gallegos; Argentina.Fil: Ferrante, Daniela. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; ArgentinaFil: Ferrante, Daniela. Universidad Nacional de la Patagonia Austral. Unidad Académica Río Gallegos; Argentina.Fil: Gismondi, Daniel. Universidad Nacional de la Patagonia Austral. Unidad Académica Río Gallegos; Argentina.Fil: González, Liliana. Consejo Agrario Provincial- Provincia de Santa Cruz; Argentina.Fil: Grima, Daniel. Universidad Nacional de la Patagonia Austral. Unidad Académica Río Gallegos; Argentina.Fil: Humano, Gervasio. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; ArgentinaFil: Iacomini, Mónica. Secretaría de la Producción. Provincia de Santa Cruz. Santa Cruz; Argentina.Fil: Iglesias, Roberto. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Chubut; Argentina.Fil: Kofalt, Bustamante Rosa. Consejo Agrario Provincial- Provincia de Santa Cruz; Argentina.Fil: Kofalt, Bustamante Rosa. Universidad Nacional de la Patagonia Austral. Unidad Académica Río Gallegos; Argentina.Fil: Kofalt, Bustamante Rosa. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina.Fil: Lamoureux, Mabel Noemi. Consejo Agrario Provincial- Provincia de Santa Cruz; Argentina.Fil: Lamoureux, Mabel Noemi. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; ArgentinaFil: Larrosa, José. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; ArgentinaFil: Manero, Amanda. Universidad Nacional de la Patagonia Austral. Unidad Académica Río Gallegos; Argentina.Fil: Manero, Amanda. Consejo Agrario Provincial- Provincia de Santa Cruz; Argentina.Fil: Marcolín, Arrigo. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche; Argentina.Fil: Mascó, Mercedes. Consejo Agrario Provincial- Provincia de Santa Cruz; Argentina.Fil: Mascó, Mercedes. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina.Fil: Mascó, Mercedes. Universidad Nacional de la Patagonia Austral. Unidad Académica Río Gallegos; Argentina.Fil: Migliora, Horacio. Consejo Agrario Provincial- Provincia de Santa Cruz; Argentina.Fil: Milicevic, Francisco. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; ArgentinaFil: Montes, Leopoldo. Instituto Nacional de Tecnología Agropecuaria (INTA). Centro Regional Patagonia Sur; Argentina.Fil: Oliva, Gabriel Esteban. Universidad Nacional de la Patagonia Austral. Unidad Académica Río Gallegos; Argentina.Fil: Oliva, Gabriel Esteban. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina.Fil: Osses, Julio Angel. Consejo Agrario Provincial- Provincia de Santa Cruz; Argentina.Fil: Paredes, Paula. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina.Fil: Peinetti, Raúl. Universidad Nacional de La Pampa. Facultad de Agronomía; Argentina.Fil: Rial, Pablo Eduardo. Ministerio de Economía y Obras Públicas. Provincia de Santa Cruz; Argentina.Fil: Rial, Pablo Eduardo. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina.Fil: Romero, Rubén. Universidad Nacional de la Patagonia Austral. Unidad Académica Río Gallegos; Argentina.Fil: Rosales, Valeria. Universidad Nacional de la Patagonia Austral. Unidad Académica Río Gallegos; Argentina.Fil: Salazar, Daniel. LU85 TV Canal 9. Auxiliar en Control de Erosión de Suelos. Provincia de Santa Cruz; Argentina.Fil: Tapia, Hector Horacio. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Chubut; Argentina.Fil: Torra, Francisco. Universidad Nacional de la Patagonia Austral. Unidad Académica Río Gallegos; Argentina.Fil: Zerpa, Débora. Universidad Nacional de la Patagonia Austral. Unidad Académica Río Gallegos; Argentina

Switching TNF antagonists in patients with chronic arthritis: An observational study of 488 patients over a four-year period

The objective of this work is to analyze the survival of infliximab, etanercept and adalimumab in patients who have switched among tumor necrosis factor (TNF) antagonists for the treatment of chronic arthritis. BIOBADASER is a national registry of patients with different forms of chronic arthritis who are treated with biologics. Using this registry, we have analyzed patient switching of TNF antagonists. The cumulative discontinuation rate was calculated using the actuarial method. The log-rank test was used to compare survival curves, and Cox regression models were used to assess independent factors associated with discontinuing medication. Between February 2000 and September 2004, 4,706 patients were registered in BIOBADASER, of whom 68% had rheumatoid arthritis, 11% ankylosing spondylitis, 10% psoriatic arthritis, and 11% other forms of chronic arthritis. One- and two-year drug survival rates of the TNF antagonist were 0.83 and 0.75, respectively. There were 488 patients treated with more than one TNF antagonist. In this situation, survival of the second TNF antagonist decreased to 0.68 and 0.60 at 1 and 2 years, respectively. Survival was better in patients replacing the first TNF antagonist because of adverse events (hazard ratio (HR) for discontinuation 0.55 (95% confidence interval (CI), 0.34-0.84)), and worse in patients older than 60 years (HR 1.10 (95% CI 0.97-2.49)) or who were treated with infliximab (HR 3.22 (95% CI 2.13-4.87)). In summary, in patients who require continuous therapy and have failed to respond to a TNF antagonist, replacement with a different TNF antagonist may be of use under certain situations. This issue will deserve continuous reassessment with the arrival of new medications. © 2006 Gomez-Reino and Loreto Carmona; licensee BioMed Central Ltd

Guidelines for the use and interpretation of assays for monitoring autophagy

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. A key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process vs. those that measure flux through the autophagy pathway (i.e., the complete process); thus, a block in macroautophagy that results in autophagosome accumulation needs to be differentiated from stimuli that result in increased autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field

Guidelines for the use and interpretation of assays for monitoring autophagy

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. A key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process vs. those that measure flux through the autophagy pathway (i.e., the complete process); thus, a block in macroautophagy that results in autophagosome accumulation needs to be differentiated from stimuli that result in increased autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field