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The prognosis of patients with advanced high-grade (G3) digestive neuroendocrine neoplasms (NENs) is rather poor. The addition of immune checkpoint inhibition to platinum-based chemotherapy may improve survival. NICE-NEC (NCT03980925) is a single-arm, phase II trial that recruited chemotherapy-naive, unresectable advanced or metastatic G3 NENs of gastroenteropancreatic (GEP) or unknown origin. Patients received nivolumab 360 mg intravenously (iv) on day 1, carboplatin AUC 5 iv on day 1, and etoposide 100 mg/m2/d iv on days 1–3, every 3 weeks for up to six cycles, followed by nivolumab 480 mg every 4 weeks for up to 24 months, disease progression, death or unacceptable toxicity. The primary endpoint was the 12-month overall survival (OS) rate (H0 50%, H1 72%, β 80%, α 5%). Secondary endpoints were objective response rate (ORR), duration of response (DoR), progression-free survival (PFS), and safety. From 2019 to 2021, 37 patients were enrolled. The most common primary sites were the pancreas (37.8%), stomach (16.2%) and colon (10.8%). Twenty-five patients (67.6%) were poorly differentiated carcinomas (NECs) and/or had a Ki67 index >55%. The ORR was 56.8%. Median PFS was 5.7 months (95%CI: 5.1-9) and median OS 13.9 months (95%CI: 8.3-Not reached), with a 12-month OS rate of 54.1% (95%CI: 40.2-72.8) that did not meet the primary endpoint. However, 37.6% of patients were long-term survivors (>2 years). The safety profile was consistent with previous reports. There was one treatment-related death. Nivolumab plus platinum-based chemotherapy was associated with prolonged survival in over one-third of chemonaïve patients with G3 GEP-NENs, with a manageable safety profile. Immune checkpoint inhibitors have been incorporated as the standard of care for some high-grade neuroendocrine neoplasms (NEN), but their efficacy in digestive NEN is still unclear. Here the authors report the results of a phase II trial of nivolumab (anti-PD1) in combination with platinum-doublet chemotherapy (carboplatin-etoposide) as first-line treatment in patients with unresectable or metastatic advanced grade 3 NENs of gastro-enteropancreatic or unknown origin. [ABSTRACT FROM AUTHOR]

Pancreatic cancer and biliary tract cancer have a poor prognosis. In recent years, the development of new diagnostic techniques has enabled the identification of the main genetic alterations involved in the development of these tumours. Multiple studies have assessed the ability of certain biomarkers, such as BRCA in pancreatic cancer, IDH1 or FGFR2 in biliary tract cancer and microsatellite instability or NTRK fusions in an agnostic tumour fashion, to predict response to treatment. In this consensus, a group of experts selected by the Spanish Society of Medical Oncology (SEOM) and the Spanish Society of Pathology (SEAP) reviewed the role played by these mutations in the process of carcinogenesis and their clinical implications. As a result, this article proposes a series of recommendations to optimize the determination of these biomarkers to help standardize the diagnosis and treatment of these tumours. [ABSTRACT FROM AUTHOR]

We present a Python package geared toward the intuitive analysis and visualization of paleoclimate timeseries, Pyleoclim. The code is open‐source, object‐oriented, and built upon the standard scientific Python stack, allowing users to take advantage of a large collection of existing and emerging techniques. We describe the code's philosophy, structure, and base functionalities and apply it to three paleoclimate problems: (a) orbital‐scale climate variability in a deep‐sea core, illustrating spectral, wavelet, and coherency analysis in the presence of age uncertainties; (b) correlating a high‐resolution speleothem to a climate field, illustrating correlation analysis in the presence of various statistical pitfalls (including age uncertainties); (c) model‐data confrontations in the frequency domain, illustrating the characterization of scaling behavior. We show how the package may be used for transparent and reproducible analysis of paleoclimate and paleoceanographic datasets, supporting Findable, Accessible, Interoperable, and Reusable software and an open science ethos. The package is supported by an extensive documentation and a growing library of tutorials shared publicly as videos and cloud‐executable Jupyter notebooks, to encourage adoption by new users. Plain Language Summary: This article describes a software application called Pyleoclim meant to help scientists analyze datasets of ordered observations, particularly applicable to the study of past climates, environments, and ecology. Pyleoclim is meant to be used by domain scientists as well as students interested in learning more about Earth's climate through examples provided in the documentation and online tutorials. Pyleoclim is intended to help scientists save time with their analyses, documenting the steps for better transparency, and as such, allows other scientists to reproduce results from previous studies. Key Points: Pyleoclim makes timeseries analysis tools accessible to practicing scientists, via a user‐friendly Python packageThree Jupyter Notebooks illustrate how Pyleoclim facilitates common and advanced tasksPyleoclim can enhance reproducibility and rigor of paleogeoscientific workflows involving timeseries [ABSTRACT FROM AUTHOR]

In this presidential address, I would like to start with a personal reflection on the field and then share with you the research directions I am pursuing and my excitement about the future of AI. In my personal research to advance AI while advancing scientific discoveries, one question that I have been pondering for some years now is whether AI will write scientific papers in the future. I want to reflect on this question, and look back at the many accomplishments in our field that can make us very hopeful that the answer will be yes, and that it may happen sooner than we might expect. [ABSTRACT FROM AUTHOR]

The article presents an interview with the Mariano Peset, a Professor of History of Law at the University of Valencia talk about some aspects of his formation and his connections with Germany and then with Mexico. It mentions that history of Spain during the war, along with discusses the understanding of barbarism through the publication of the process by Marc Baldó, María Fernanda Mancebo and Salvador Albiñana.

This research forms part of the project titled: 'Aesthetic quality research of three Valencian schools', that analyses the effects in detail that images displayed in schools have, as a variable in evaluating educational quality. Through applying Arts Based Educational Research, images displayed on 29 classroom walls in three schools were photographed and analysed based upon their function; they were subsequently classified as educational images, academic images, and comfort-generating images. The results of this research show quantitative, qualitative, and aesthetic values of this visual heritage by using photographic series that are laid out in a chart-like manner, creating a visual message for each classroom. Upon observing these typologies, one perceives: the predominate utilisation of the image and its aesthetics; the differences in visible occurrences between subject matters displayed on the walls; the teacher's intentions when displaying the images. In the conclusions, alternatives are proposed for improving the schools' aesthetical qualities. [ABSTRACT FROM AUTHOR]

Background: NF-κB1 is a master regulator of both acquired and innate responses. NFKB1 loss-of-function mutations elicit a wide clinical phenotype with asymptomatic individuals at one end of the spectrum and patients with common variable immunodeficiency, combined immunodeficiency or autoinflammation at the other. Impairment of acquired and innate immunity and disseminated Mycobacterium genavense infection expands the clinical and immunological phenotype of NF-κB1 deficiency. Objective: Functional and molecular characterization of a patient with a novel phenotype of NF-κB1 deficiency. Methods: Circulating T, B, dendritic cell subsets and innate or unconventional T-cells were quantified. The cytokine production in stimulated whole blood samples was assessed and molecular characterization by next generation sequencing and gene expression assays were also performed. Results: We report a patient presenting with features of combined immunodeficiency (CID) and disseminated Mycobacterium genavense infection. Sequencing of genomic DNA identified a novel synonymous mutation (c.705G > A) in NFKB1 gene which resulted in exon 8 skipping and haploinsufficiency of the NF-κB1 subunit p50. The susceptibility to atypical mycobacterial infection has not been previously reported and may be the result of a dendritic cell deficiency. A selective deficiency of circulating follicular helper T (cTFH) cells responsible for mediating the differentiation of naive B cells into memory and plasma cells was also present in the patient. It could affect the maturation of innate or unconventional T cells where NF-κB1 could also be involved. Conclusion: These findings showed that the role of NF-κB1 in humans could be critical for the development of acquired and innate immunity and further highlights the role of human T cells in anti-mycobacterial immunity. [ABSTRACT FROM AUTHOR]

This article contains the observations of Yolanda Gil, director of knowledge technologies and research professor at the Information Sciences Institute of the University of Southern California, USA, and president of Association for Advancement of Artificial Intelligence who was recently interviewed about the factors that could influence successful AI research. The editorial team interviewers included members of the special track editorial team from IBM Research (Biplav Srivastava, Ching-Hua Chen) and Rensselaer Polytechnic Institute (Oshani Seneviratne). [ABSTRACT FROM AUTHOR]

Artificial intelligence, like any science, must rely on reproducible experiments to validate results. Our objective is to give practical and pragmatic recommendations for how to document AI research so that results are reproducible. Our analysis of the literature shows that AI publications currently fall short of providing enough documentation to facilitate reproducibility. Our suggested best practices are based on a framework for reproducibility and recommendations for best practices given by scientific organizations, scholars, and publishers. We have made a reproducibility checklist based on our investigation and described how every item in the checklist can be documented by authors and examined by reviewers. We encourage authors and reviewers to use the suggested best practices and author checklist when considering submissions for AAAI publications and conferences. [ABSTRACT FROM AUTHOR]

Purpose: The objective of this work was to determine which embryonic morphokinetic parameters up to D3 of in vitro development have predictive value for implantation for the selection of embryos for transfer in clinical practice based upon information generated from embryo transfers with known implantation data (KID). Methods: A total of 800 KID embryos (100% implantation rate (IR) per transfer and 0% IR per transfer) cultured in an incubator with Time-Lapse system were retrospectively analysed. Of them, 140 embryos implanted, whereas 660 did not. Results: The analysis of morphokinetic parameters, together with the embryo morphology assessment on D3, enabled us to develop a hierarchical model that places the classical morphological score, the t4 and t8 morphokinetic values, as the variables with the best prognosis of implantation. Conclusion: In our decision tree, the classical morphological score is the most predictive parameter. Among embryos with better morphological scores, morphokinetics permits deselection of embryos with the lowest implantation potential. [ABSTRACT FROM AUTHOR]

This paper analyses the figure of Vincenzo Vincenzi on the basis of documents that place him in Valencia in 1635 as engineer and geometer to Cardinal Gaspar de Borja y Velasco. Vincenzi, who was born in the Urbino region, worked as a hydraulic engineer at the Villa d’Este in Tivoli. In Rome he made his name as the inventor of the wind gun and the mobile fountain, inventions that were disseminated through the works of Benedetto Castelli and, above all, those of Giovanni Faber who also served as an intermediary, recommending Vincenzi’s services to cardinals such as Emmanuele Pio di Savoia and taking it upon himself to find buyers for the wind gun. Vincenzi worked for the Bentivoglios on the bonifica del Gualtieri, and the Venetian Republic expressed its desire to purchase a number of his inventions, after which he travelled to Spain at the request of Borja in order to drain a salt marsh on the cardinal’s estates. [ABSTRACT FROM AUTHOR]

Copyright of Anales de Documentación is the property of Servicio de Publicaciones de la Universidad de Murcia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Cyberinfrastructure is enabling ever more integrative and transformative science. Technological advances in cyberinfrastructure have allowed deeper understanding of watershed hydrology by improved integration of data, information, and models. The synthesis of all sources of hydrologic variables (historical, real time, future scenarios, observed, and modeled) requires advanced data acquisition, data storage, data management, data integration, data mining, and data visualization. In this context, cyber-innovated hydrologic research was implemented to carry out watershed-based historical climate simulations at the Shale Hills Critical Zone Observatory. The simulations were based on the assimilation of data from a hydrologic monitoring network into a multiphysics hydrologic model (the Penn State Integrated Hydrology Model). We documented workflows for the model application and applied the model to short-time hyporheic exchange flow study and long-term climate scenario analysis. The effort reported herein demonstrates that advances in cyberscience allows innovative research that improves our ability to access and share data; to allow collective development of science hypotheses; and to support building models via team participation. We simplified communications between model developers and community scientists, software professionals, students, and decision makers, which in the long term will improve the utilization of hydrologic models for science and societal applications. [ABSTRACT FROM PUBLISHER]

Copyright of Avant is the property of Centre for Philosophical Research and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Recent highly publicized cases of premature patient assignment into clinical trials, resulting from non-reproducible omics analyses, have prompted many to call for a more thorough examination of translational omics and highlighted the critical need for transparency and reproducibility to ensure patient safety. The use of workflow platforms such as Galaxy and Taverna have greatly enhanced the use, transparency and reproducibility of omics analysis pipelines in the research domain and would be an invaluable tool in a clinical setting. However, the use of these workflow platforms requires deep domain expertise that, particularly within the multi-disciplinary fields of translational and clinical omics, may not always be present in a clinical setting. This lack of domain expertise may put patient safety at risk and make these workflow platforms difficult to operationalize in a clinical setting. In contrast, semantic workflows are a different class of workflow platform where resultant workflow runs are transparent, reproducible, and semantically validated. Through semantic enforcement of all datasets, analyses and user-defined rules/ constraints, users are guided through each workflow run, enhancing analytical validity and patient safety. Methods: To evaluate the effectiveness of semantic workflows within translational and clinical omics, we have implemented a clinical omics pipeline for annotating DNA sequence variants identified through next generation sequencing using the Workflow Instance Generation and Specialization (WINGS) semantic workflow platform. Results: We found that the implementation and execution of our clinical omics pipeline in a semantic workflow helped us to meet the requirements for enhanced transparency, reproducibility and analytical validity recommended for clinical omics. We further found that many features of the WINGS platform were particularly primed to help support the critical needs of clinical omics analyses. Conclusions: This is the first implementation and execution of a clinical omics pipeline using semantic workflows. Evaluation of this implementation provides guidance for their use in both translational and clinical settings. [ABSTRACT FROM AUTHOR]

The AAAI-14 Workshop program was held Sunday and Monday, July 27- 28, 2014, at the Québec City Convention Centre in Québec, Canada. The AAAI-14 workshop program included 15 workshops covering a wide range of topics in artificial intelligence. The titles of the workshops were Artificial Intelligence and Robotics; Artificial Intelligence Applied to Assistive Technologies and Smart Environments; Cognitive Computing for Augmented Human Intelligence; Computer Poker and Imperfect Information; Discovery Informatics; Incentives and Trust in Electronic Communities; Intelligent Cinematography and Editing; Machine Learning for Interactive Systems: Bridging the Gap Between Perception, Action, and Communication; Modern Artificial Intelligence for Health Analytics; Multiagent Interaction Without Prior Coordination; Multidisciplinary Workshop on Advances in Preference Handling; Semantic Cities -- Beyond Open Data to Models, Standards, and Reasoning; Sequential Decision Making with Big Data; Statistical Relational AI; and the World Wide Web and Public Health Intelligence. This article presents short summaries of those events. [ABSTRACT FROM AUTHOR]