Resistance to autosomal dominant Alzheimer's disease in an APOE3 Christchurch homozygote: a case report.

We identified a PSEN1 (presenilin 1) mutation carrier from the world's largest autosomal dominant Alzheimer's disease kindred, who did not develop mild cognitive impairment until her seventies, three decades after the expected age of clinical onset. The individual had two copies of the APOE3 Christchurch (R136S) mutation, unusually high brain amyloid levels and limited tau and neurodegenerative measurements. Our findings have implications for the role of APOE in the pathogenesis, treatment and prevention of Alzheimer's disease

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

Background Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide.Methods A multimethods analysis was performed as part of the GlobalSurg 3 study-a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital.Findings Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3.85 [95% CI 2.58-5.75]; p<0.0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63.0% vs 82.7%; OR 0.35 [0.23-0.53]; p<0.0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer.Interpretation Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised

Soil organic carbon stocks in native forest of Argentina: a useful surrogate for mitigation and conservation planning under climate variability

Background The nationally determined contribution (NDC) presented by Argentina within the framework of the Paris Agreement is aligned with the decisions made in the context of the United Nations Framework Convention on Climate Change (UNFCCC) on the reduction of emissions derived from deforestation and forest degradation, as well as forest carbon conservation (REDD+). In addition, climate change constitutes one of the greatest threats to forest biodiversity and ecosystem services. However, the soil organic carbon (SOC) stocks of native forests have not been incorporated into the Forest Reference Emission Levels calculations and for conservation planning under climate variability due to a lack of information. The objectives of this study were: (i) to model SOC stocks to 30 cm of native forests at a national scale using climatic, topographic and vegetation as predictor variables, and (ii) to relate SOC stocks with spatial–temporal remotely sensed indices to determine biodiversity conservation concerns due to threats from high inter‑annual climate variability. Methods We used 1040 forest soil samples (0–30 cm) to generate spatially explicit estimates of SOC native forests in Argentina at a spatial resolution of approximately 200 m. We selected 52 potential predictive environmental covariates, which represent key factors for the spatial distribution of SOC. All covariate maps were uploaded to the Google Earth Engine cloud‑based computing platform for subsequent modelling. To determine the biodiversity threats from high inter‑annual climate variability, we employed the spatial–temporal satellite‑derived indices based on Enhanced Vegetation Index (EVI) and land surface temperature (LST) images from Landsat imagery. Results SOC model (0–30 cm depth) prediction accounted for 69% of the variation of this soil property across the whole native forest coverage in Argentina. Total mean SOC stock reached 2.81 Pg C (2.71–2.84 Pg C with a probability of 90%) for a total area of 460,790 km2, where Chaco forests represented 58.4% of total SOC stored, followed by Andean Patagonian forests (16.7%) and Espinal forests (10.0%). SOC stock model was fitted as a function of regional climate, which greatly influenced forest ecosystems, including precipitation (annual mean precipitation and precipitation of warmest quarter) and temperature (day land surface temperature, seasonality, maximum temperature of warmest month, month of maximum temperature, night land surface temperature, and monthly minimum temperature). Biodiversity was influenced by the SOC levels and the forest regions. Conclusions In the framework of the Kyoto Protocol and REDD+, information derived in the present work from the estimate of SOC in native forests can be incorporated into the annual National Inventory Report of Argentina to assist forest management proposals. It also gives insight into how native forests can be more resilient to reduce the impact of biodiversity loss.EEA Santa CruzFil: Peri, Pablo Luis. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina.Fil: Peri, Pablo Luis. Universidad Nacional de la Patagonia Austral; Argentina.Fil: Peri, Pablo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Gaitan, Juan José. Universidad Nacional de Luján. Buenos Aires; Argentina.Fil: Gaitan, Juan José. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Mastrangelo, Matias Enrique. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias. Grupo de Estudio de Agroecosistemas y Paisajes Rurales; Argentina.Fil: Mastrangelo, Matias Enrique. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Nosetto, Marcelo Daniel. Universidad Nacional de San Luis. Instituto de Matemática Aplicada San Luis. Grupo de Estudios Ambientales; Argentina.Fil: Nosetto, Marcelo Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Villagra, Pablo Eugenio. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales (IANIGLA); Argentina.Fil: Villagra, Pablo Eugenio. Universidad Nacional de Cuyo. Facultad de Ciencias Agrarias; Argentina.Fil: Balducci, Ezequiel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Yuto; Argentina.Fil: Pinazo, Martín Alcides. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Montecarlo; Argentina.Fil: Eclesia, Roxana Paola. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Paraná; Argentina.Fil: Von Wallis, Alejandra. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Montecarlo; Argentina.Fil: Villarino, Sebastián. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias. Grupo de Estudio de Agroecosistemas y Paisajes Rurales; Argentina.Fil: Villarino, Sebastián. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Alaggia, Francisco Guillermo. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi. Campo Anexo Villa Dolores; Argentina.Fil: Alaggia, Francisco Guillermo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Gonzalez-Polo, Marina. Universidad Nacional del Comahue; Argentina.Fil: Gonzalez-Polo, Marina. Consejo Nacional de Investigaciones Científicas y Técnicas. INIBIOMA; Argentina.Fil: Manrique, Silvana M. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Energía No Convencional. CCT Salta‑Jujuy; Argentina.Fil: Meglioli, Pablo A. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales (IANIGLA); Argentina.Fil: Meglioli, Pablo A. Universidad Nacional de Cuyo. Facultad de Ciencias Agrarias; Argentina.Fil: Rodríguez‑Souilla, Julián. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas (CADIC); Argentina.Fil: Mónaco, Martín H. Ministerio de Ambiente y Desarrollo Sostenible. Dirección Nacional de Bosques; Argentina.Fil: Chaves, Jimena Elizabeth. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas (CADIC); Argentina.Fil: Medina, Ariel. Ministerio de Ambiente y Desarrollo Sostenible. Dirección Nacional de Bosques; Argentina.Fil: Gasparri, Ignacio. Universidad Nacional de Tucumán. Instituto de Ecología Regional; Argentina.Fil: Gasparri, Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Alvarez Arnesi, Eugenio. Universidad Nacional de Rosario. Instituto de Investigaciones en Ciencias Agrarias de Rosario; Argentina.Fil: Alvarez Arnesi, Eugenio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe; Argentina.Fil: Barral, María Paula. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias. Grupo de Estudio de Agroecosistemas y Paisajes Rurales; Argentina.Fil: Barral, María Paula. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Von Müller, Axel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Esquel Argentina.Fil: Pahr, Norberto Manuel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Montecarlo; Argentina.Fil: Uribe Echevarría, Josefina. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Quimilí; Argentina.Fil: Fernandez, Pedro Sebastian. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Famaillá; Argentina.Fil: Fernandez, Pedro Sebastian. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Ecología Regional; Argentina.Fil: Morsucci, Marina. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales (IANIGLA); Argentina.Fil: Morsucci, Marina. Universidad Nacional de Cuyo. Facultad de Ciencias Agrarias; Argentina.Fil: Lopez, Dardo Ruben. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi. Campo Anexo Villa Dolores; Argentina.Fil: Lopez, Dardo Ruben. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Cellini, Juan Manuel. Universidad Nacional de la Plata (UNLP). Facultad de Ciencias Naturales y Museo. Laboratorio de Investigaciones en Maderas; Argentina.Fil: Alvarez, Leandro M. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales (IANIGLA); Argentina.Fil: Alvarez, Leandro M. Universidad Nacional de Cuyo. Facultad de Ciencias Agrarias; Argentina.Fil: Barberis, Ignacio Martín. Universidad Nacional de Rosario. Instituto de Investigaciones en Ciencias Agrarias de Rosario; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe; Argentina.Fil: Barberis, Ignacio Martín. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe; Argentina.Fil: Colomb, Hernán Pablo. Ministerio de Ambiente y Desarrollo Sostenible. Dirección Nacional de Bosques; Argentina.Fil: Colomb, Hernán. Administración de Parques Nacionales (APN). Parque Nacional Los Alerces; Argentina.Fil: La Manna, Ludmila. Universidad Nacional de la Patagonia San Juan Bosco. Centro de Estudios Ambientales Integrados (CEAI); Argentina.Fil: La Manna, Ludmila. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Barbaro, Sebastian Ernesto. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Cerro Azul; Argentina.Fil: Blundo, Cecilia. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Ecología Regional; Argentina.Fil: Blundo, Cecilia. Universidad Nacional de Tucumán. Tucumán; Argentina.Fil: Sirimarco, Marina Ximena. Universidad Nacional de Mar del Plata. Grupo de Estudio de Agroecosistemas y Paisajes Rurales (GEAP); Argentina.Fil: Sirimarco, Marina Ximena. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Cavallero, Laura. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi. Campo Anexo Villa Dolores; Argentina.Fil: Zalazar, Gualberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales (IANIGLA); Argentina.Fil: Zalazar, Gualberto. Universidad Nacional de Cuyo. Facultad de Ciencias Agrarias; Argentina.Fil: Martínez Pastur, Guillermo José. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas (CADIC); Argentina

Dendritic cells in cancer immunology and immunotherapy

Dendritic cells (DCs) are a diverse group of specialized antigen-presenting cells with key roles in the initiation and regulation of innate and adaptive immune responses. As such, there is currently much interest in modulating DC function to improve cancer immunotherapy. Many strategies have been developed to target DCs in cancer, such as the administration of antigens with immunomodulators that mobilize and activate endogenous DCs, as well as the generation of DC-based vaccines. A better understanding of the diversity and functions of DC subsets and of how these are shaped by the tumour microenvironment could lead to improved therapies for cancer. Here we will outline how different DC subsets influence immunity and tolerance in cancer settings and discuss the implications for both established cancer treatments and novel immunotherapy strategies.S.K.W. is supported by a European Molecular Biology Organization Long- Term Fellowship (grant ALTF 438– 2016) and a CNIC–International Postdoctoral Program Fellowship (grant 17230–2016). F.J.C. is the recipient of a PhD ‘La Caixa’ fellowship. Work in the D.S. laboratory is funded by the CNIC, by the European Research Council (ERC Consolidator Grant 2016 725091), by the European Commission (635122-PROCROP H2020), by the Ministerio de Ciencia, Innovación e Universidades (MCNU), Agencia Estatal de Investigación and Fondo Europeo de Desarrollo Regional (FEDER) (SAF2016-79040-R), by the Comunidad de Madrid (B2017/BMD-3733 Immunothercan- CM), by FIS- Instituto de Salud Carlos III, MCNU and FEDER (RD16/0015/0018-REEM), by Acteria Foundation, by Atresmedia (Constantes y Vitales prize) and by Fundació La Marató de TV3 (201723). The CNIC is supported by the Instituto de Salud Carlos III, the MCNU and the Pro CNIC Foundation, and is a Severo Ochoa Centre of Excellence (SEV-2015-0505).S

Impact of chronic obstructive pulmonary disease on short-term outcome in patients with ST-elevation myocardial infarction during COVID-19 pandemic: insights from the international multicenter ISACS-STEMI registry

Background Chronic obstructive pulmonary disease (COPD) is projected to become the third cause of mortality worldwide. COPD shares several pathophysiological mechanisms with cardiovascular disease, especially atherosclerosis. However, no definite answers are available on the prognostic role of COPD in the setting of ST elevation myocardial infarction (STEMI), especially during COVID-19 pandemic, among patients undergoing primary angioplasty, that is therefore the aim of the current study. Methods In the ISACS-STEMI COVID-19 registry we included retrospectively patients with STEMI treated with primary percutaneous coronary intervention (PCI) between March and June of 2019 and 2020 from 109 high-volume primary PCI centers in 4 continents. Results A total of 15,686 patients were included in this analysis. Of them, 810 (5.2%) subjects had a COPD diagnosis. They were more often elderly and with a more pronounced cardiovascular risk profile. No preminent procedural dissimilarities were noticed except for a lower proportion of dual antiplatelet therapy at discharge among COPD patients (98.9% vs. 98.1%, P = 0.038). With regards to short-term fatal outcomes, both in-hospital and 30-days mortality occurred more frequently among COPD patients, similarly in pre-COVID-19 and COVID-19 era. However, after adjustment for main baseline differences, COPD did not result as independent predictor for in-hospital death (adjusted OR [95% CI] = 0.913[0.658-1.266], P = 0.585) nor for 30-days mortality (adjusted OR [95% CI] = 0.850 [0.620-1.164], P = 0.310). No significant differences were detected in terms of SARS-CoV-2 positivity between the two groups. Conclusion This is one of the largest studies investigating characteristics and outcome of COPD patients with STEMI undergoing primary angioplasty, especially during COVID pandemic. COPD was associated with significantly higher rates of in-hospital and 30-days mortality. However, this association disappeared after adjustment for baseline characteristics. Furthermore, COPD did not significantly affect SARS-CoV-2 positivity. Trial registration number: NCT 04412655 (2nd June 2020)

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 AtomNet® 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 AtomNet® 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

Advancements in dementia research, diagnostics and care in Latin America : highlights from the 2023 Alzheimer's association international conference satellite symposium in Mexico City

While Latin America (LatAm) is facing an increasing burden of dementia due to the rapid aging of the population, it remains underrepresented in dementia research, diagnostics and care. In 2023, the Alzheimer’s Association hosted its eighth Satellite Symposium in Mexico, highlighting emerging dementia research, priorities, and challenges within LatAm. A wide range of topics were covered, including epidemiology, social determinants, dementia national plans, risk reduction, genetics, biomarkers, biobanks, and advancements in treatments. Large initiatives in the region including intra-country support showcased their efforts in fostering national and international collaborations; genetic studies unveiled the unique genetic admixture in LatAm; emerging clinical trials discussed ongoing culturally specific interventions; and the urgent need to harmonize practices and studies, improve diagnosis and care and implement affordable biomarkers in the region was highlighted