Benzotrithiophenes vs. Benzo/Naptha-dithiophenes: The Effect of Star-Shaped versus Linear Conjugation on Their Electronic Structures

Star-shaped complexes of π-conjugated chromophores are currently of great interest for use in optoelectronic devices.1 Recently, different planar central cores involving three thiophene rings fused to a benzenic ring (BTTs) have been described. In these systems, the coplanarity and extended π-conjugation of the BTT skeleton should promote intermolecular π-stacking, which would induce strong aggregation and enhanced packing in the solid state of BTT-containing molecules. We propose here the study of a BTT conjugated system with DPPT fragments, in which three DPP2T units are linked to a central rigid trithienobenzene core. Comparison with homologous linear systems, based on the benzodithiophene (BDT) unit and the naphtodithiophene (NDT) unit,2 will be carried out in order to elucidate the effect of star-shaped configuration versus linear conformation on the optical and electrical properties.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Atmospheric CO2 emissions and ocean acidification from bottom-trawling

Trawling the seafloor can disturb carbon that took millennia to accumulate, but the fate of that carbon and its impact on climate and ecosystems remains unknown. Using satellite-inferred fishing events and carbon cycle models, we find that 55-60% of trawling-induced aqueous CO2 is released to the atmosphere over 7-9 years. Using recent estimates of bottom trawling’s impact on sedimentary carbon, we found that between 1996-2020 trawling could have released, at the global scale, up to 0.34-0.37 Pg CO2 yr-1 to the atmosphere, and locally altered water pH in some semi-enclosed and heavy trawled seas. Our results suggest that the management of bottom-trawling efforts could be an important climate solution

Culture-free genome-wide locus sequence typing (GLST) provides new perspectives on Trypanosoma cruzi dispersal and infection complexity.

Analysis of genetic polymorphism is a powerful tool for epidemiological surveillance and research. Powerful inference from pathogen genetic variation, however, is often restrained by limited access to representative target DNA, especially in the study of obligate parasitic species for which ex vivo culture is resource-intensive or bias-prone. Modern sequence capture methods enable pathogen genetic variation to be analyzed directly from host/vector material but are often too complex and expensive for resource-poor settings where infectious diseases prevail. This study proposes a simple, cost-effective 'genome-wide locus sequence typing' (GLST) tool based on massive parallel amplification of information hotspots throughout the target pathogen genome. The multiplexed polymerase chain reaction amplifies hundreds of different, user-defined genetic targets in a single reaction tube, and subsequent agarose gel-based clean-up and barcoding completes library preparation at under 4 USD per sample. Our study generates a flexible GLST primer panel design workflow for Trypanosoma cruzi, the parasitic agent of Chagas disease. We successfully apply our 203-target GLST panel to direct, culture-free metagenomic extracts from triatomine vectors containing a minimum of 3.69 pg/μl T. cruzi DNA and further elaborate on method performance by sequencing GLST libraries from T. cruzi reference clones representing discrete typing units (DTUs) TcI, TcIII, TcIV, TcV and TcVI. The 780 SNP sites we identify in the sample set repeatably distinguish parasites infecting sympatric vectors and detect correlations between genetic and geographic distances at regional (< 150 km) as well as continental scales. The markers also clearly separate TcI, TcIII, TcIV and TcV + TcVI and appear to distinguish multiclonal infections within TcI. We discuss the advantages, limitations and prospects of our method across a spectrum of epidemiological research

Repeat-Driven Generation of Antigenic Diversity in a Major Human Pathogen, Trypanosoma cruzi.

Trypanosoma cruzi, a zoonotic kinetoplastid protozoan parasite, is the causative agent of American trypanosomiasis (Chagas disease). Having a very plastic, repetitive and complex genome, the parasite displays a highly diverse repertoire of surface molecules, with pivotal roles in cell invasion, immune evasion and pathogenesis. Before 2016, the complexity of the genomic regions containing these genes impaired the assembly of a genome at chromosomal level, making it impossible to study the structure and function of the several thousand repetitive genes encoding the surface molecules of the parasite. We here describe the genome assembly of the Sylvio X10/1 genome sequence, which since 2016 has been used as a reference genome sequence for T. cruzi clade I (TcI), produced using high coverage PacBio single-molecule sequencing. It was used to analyze deep Illumina sequence data from 34 T. cruzi TcI isolates and clones from different geographic locations, sample sources and clinical outcomes. Resolution of the surface molecule gene distribution showed the unusual duality in the organization of the parasite genome, a synteny of the core genomic region with related protozoa flanked by unique and highly plastic multigene family clusters encoding surface antigens. The presence of abundant interspersed retrotransposons in these multigene family clusters suggests that these elements are involved in a recombination mechanism for the generation of antigenic variation and evasion of the host immune response on these TcI strains. The comparative genomic analysis of the cohort of TcI strains revealed multiple cases of such recombination events involving surface molecule genes and has provided new insights into T. cruzi population structure

The impact of surgical delay on resectability of colorectal cancer: An international prospective cohort study

AIM: The SARS-CoV-2 pandemic has provided a unique opportunity to explore the impact of surgical delays on cancer resectability. This study aimed to compare resectability for colorectal cancer patients undergoing delayed versus non-delayed surgery. METHODS: This was an international prospective cohort study of consecutive colorectal cancer patients with a decision for curative surgery (January-April 2020). Surgical delay was defined as an operation taking place more than 4 weeks after treatment decision, in a patient who did not receive neoadjuvant therapy. A subgroup analysis explored the effects of delay in elective patients only. The impact of longer delays was explored in a sensitivity analysis. The primary outcome was complete resection, defined as curative resection with an R0 margin. RESULTS: Overall, 5453 patients from 304 hospitals in 47 countries were included, of whom 6.6% (358/5453) did not receive their planned operation. Of the 4304 operated patients without neoadjuvant therapy, 40.5% (1744/4304) were delayed beyond 4 weeks. Delayed patients were more likely to be older, men, more comorbid, have higher body mass index and have rectal cancer and early stage disease. Delayed patients had higher unadjusted rates of complete resection (93.7% vs. 91.9%, P = 0.032) and lower rates of emergency surgery (4.5% vs. 22.5%, P < 0.001). After adjustment, delay was not associated with a lower rate of complete resection (OR 1.18, 95% CI 0.90-1.55, P = 0.224), which was consistent in elective patients only (OR 0.94, 95% CI 0.69-1.27, P = 0.672). Longer delays were not associated with poorer outcomes. CONCLUSION: One in 15 colorectal cancer patients did not receive their planned operation during the first wave of COVID-19. Surgical delay did not appear to compromise resectability, raising the hypothesis that any reduction in long-term survival attributable to delays is likely to be due to micro-metastatic disease

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

(farsi - فارسی‎) 2023 تقویم علمی مکتب

El proyecto “Calendario Científico Escolar 2023” ha consistido en la elaboración de un calendario dirigido al alumnado de educación primaria y secundaria obligatoria. Cada día se ha recogido un aniversario científico o tecnológico como, por ejemplo, nacimientos de personas de estos ámbitos o conmemoraciones de hallazgos destacables. Además, el calendario se acompaña de una guía didáctica con orientaciones para el aprovechamiento educativo transversal del calendario en las clases, incluyendo actividades adaptadas a cada rango de edad y al alumnado con necesidades especiales. Se trata de la cuarta edición de este proyecto de divulgación científica.Proyecto FCT-21-17253 de la Fundación Española para la Ciencia y la Tecnología (FECYT); Agencia Estatal de Investigación (España); Ministerio de Ciencia e Innovación; Consejo Superior de Investigaciones Científicas; Universidad de León; Delegación del CSIC en Castilla y León; Instituto de Ganadería de Montaña (IGM, CSIC-ULE); Casa de la Ciència de Valencia (CSIC); Cátedra de Cultura Científica de la Universidad del País Vasco/ Euskal Herriko Unibertsitatea (UPV/EHU); People Help; University of California-Davis; Academia de la Llingua Asturiana; Federación Española de Esperanto; Teagasc; PuraVida Software; Universidad de Zaragoza; Casa Árabe; CSIC Delegació a Catalunya; CCULT.org; Museo Didáctico e Interactivo de Ciencias de la Vega Baja del Segura (MUDIC VBS-CV); Universidad Miguel Hernández; Unidade de Divulgación Científica e Cultural - Universidade da Coruña; Asociación Cultural Nogará Religada .Mujeres con Ciencia; Asociaţia Secular-Umanistă din România; Instituto Geológico y Minero de España (IGME); Centro de Biología Molecular Severo Ochoa (CSIC-UAM); Asociación Española para el Avance de la Ciencia (AEAC); Centro de Investigación del Cáncer (CIC, CSIC-USAL); Discapacitodos; Universitat de les Illes Balears (UIB); Comisión Mujeres y Ciencia de la Sociedad Geológica de España; Institut d’Investigació en Intel.ligéncia Artificial (IIIA-CSIC); Centre for Research in Agricultural Genomics (GRAG, CSIC-UAB-ICREA); Escuela de Estudios Hispano-americanos (CSIC); Institut Botànic de Barcelona (IIB, CSIC-Ajuntament Barcelona); Institut de Ciència de Materials de Barcelona (ICMAB, CSIC); Institut de Ciències del Mar (ICM, CSIC); PRISMA – Asociación para la diversidad afectivo-sexual y de género en ciencia, tecnología e innovación; Instituto de Recursos Naturales y Agrobiología de Salamanca (IRNASA, CSIC); Círculo Escéptico; Civiencia; Universidad Autónoma de Madrid; Escuela de Estudios Árabes (CSIC); Evento Ciencia; Europa Laica; Universidad de Oviedo; Institut de Microelectrònica de Barcelona - Centre Nacional de Microelectrònica (IMB-CNM, CSIC); Centre d'Estudis Avançats de Blanes (CEAB, CSIC). ePeer reviewe