Twenty Years of Rad-Hard K14 SPAD in Space Projects

During last two decades, several photon counting detectors have been developed in our laboratory. One of the most promising detector coming from our group silicon K14 Single Photon Avalanche Diode (SPAD) is presented with its valuable features and space applications. Based on the control electronics, it can be operated in both gated and non-gated mode. Although it was designed for photon counting detection, it can be employed for multiphoton detection as well. With respect to control electronics employed, the timing jitter can be as low as 20 ps RMS. Detection efficiency is about 40%in range of 500 nm to 800 nm. The detector including gating and quenching circuitry has outstanding timing stability. Due to its radiation resistivity, the diode withstands 100 krad gamma ray dose without parameters degradation. Single photon detectors based on K14 SPAD were used for planetary altimeter and atmospheric lidar in MARS92/96 and Mars Surveyor ’98 space projects, respectively. Recent space applications of K14 SPAD comprises LIDAR and mainly time transfer between ground stations and artificial satellites. These include Laser Time Transfer, Time Transfer by Laser Link, and European Laser Timing projects

Photon-number distributions of twin beams generated in spontaneous parametric down-conversion and measured by an intensified CCD camera

The measurement of photon-number statistics of fields composed of photon pairs, generated in spontaneous parametric down-conversion and detected by an intensified CCD camera is described. Final quantum detection efficiencies, electronic noises, finite numbers of detector pixels, transverse intensity spatial profiles of the detected beams as well as losses of single photons from a pair are taken into account in a developed general theory of photon-number detection. The measured data provided by an iCCD camera with single-photon detection sensitivity are analyzed along the developed theory. Joint signal-idler photon-number distributions are recovered using the reconstruction method based on the principle of maximum likelihood. The range of applicability of the method is discussed. The reconstructed joint signal-idler photon-number distribution is compared with that obtained by a method that uses superposition of signal and noise and minimizes photoelectron entropy. Statistics of the reconstructed fields are identified to be multi-mode Gaussian. Elements of the measured as well as the reconstructed joint signal-idler photon-number distributions violate classical inequalities. Sub-shot-noise correlations in the difference of the signal and idler photon numbers as well as partial suppression of odd elements in the distribution of the sum of signal and idler photon numbers are observed.Comment: 14 pages, 14 figure

T Lymphocyte Therapy of Cancer

Summary The rationale for the use of T lymphocytes to fight cancer is the immunogenicity of tumor cells. T cells are capable to recognize and finally to kill tumor cells. Adoptive cell transfer therapies provide the opportunity to overcome tolerogenic mechanisms by enabling the selection and activation of highly reactive T cell subpopulations and by manipulation of the host environment into which the T cells are introduced. The aim of this article is to review the possibilities, limitations and recent clinical experience with this novel anticancer treatment, namely with adoptive immunotherapy using antigen-specific T cells

High incidence of Epstein-Barr virus, cytomegalovirus and human herpesvirus 6 infections in children with cancer

BACKGROUND: A prospective single-center study was performed to study infection with lymphotropic herpesviruses (LH) Epstein-Barr virus (EBV), cytomegalovirus (CMV) and human herpesvirus 6 (HHV-6) in children with cancer. METHODS: The group of 186 children was examined for the presence of LH before, during and 2 months after the end of anticancer treatment. Serology of EBV and CMV was monitored in all children, serology of HHV-6 and DNA analysis of all three LH was monitored in 70 children. RESULTS: At the time of cancer diagnosis (pre-treatment), there was no difference between cancer patients and age-matched healthy controls in overall IgG seropositivity for EBV (68.8% vs. 72.0%; p = 0.47) and CMV (37.6% vs. 41.7%; p = 0.36). During anticancer therapy, primary or reactivated EBV and CMV infection was present in 65 (34.9%) and 66 (35.4%) of 186 patients, respectively, leading to increased overall post-treatment IgG seropositivity that was significantly different from controls for EBV (86.6% vs. 72.0%; p = 0.0004) and CMV (67.7% vs. 41.7%; p < 0.0001). Overall pre-treatment IgG seropositivity for HHV-6 was significantly lower in patients than in controls (80.6% vs. 91.3%; p = 0.0231) which may be in agreement with Greaves hypothesis of protective effect of common infections in infancy to cancer development. Primary or reactivated HHV-6 infection was present in 23 (32.9%) of 70 patients during anticancer therapy leading to post-treatment IgG seropositivity that was not significantly different from controls (94.3% vs. 91.3%; p = 0.58). The LH infection occurred independently from leukodepleted blood transfusions given. Combination of serology and DNA analysis in detection of symptomatic EBV or CMV infection was superior to serology alone. CONCLUSION: EBV, CMV and HHV-6 infections are frequently present during therapy of pediatric malignancy

The World Spider Trait database : a centralised global open repository for curated data on spider traits

Publisher Copyright: © The Author(s) 2021. Published by Oxford University Press.Spiders are a highly diversified group of arthropods and play an important role in terrestrial ecosystems as ubiquitous predators, which makes them a suitable group to test a variety of eco-evolutionary hypotheses. For this purpose, knowledge of a diverse range of species traits is required. Until now, data on spider traits have been scattered across thousands of publications produced for over two centuries and written in diverse languages. To facilitate access to such data, we developed an online database for archiving and accessing spider traits at a global scale. The database has been designed to accommodate a great variety of traits (e.g. ecological, behavioural and morphological) measured at individual, species or higher taxonomic levels. Records are accompanied by extensive metadata (e.g. location and method). The database is curated by an expert team, regularly updated and open to any user. A future goal of the growing database is to include all published and unpublished data on spider traits provided by experts worldwide and to facilitate broad cross-taxon assays in functional ecology and comparative biology. Database URL:https://spidertraits.sci.muni.cz/.Peer reviewe

The World Spider Trait database: a centralized global open repository for curated data on spider traits

Spiders are a highly diversified group of arthropods and play an important role in terrestrial ecosystems as ubiquitous predators, which makes them a suitable group to test a variety of eco-evolutionary hypotheses. For this purpose, knowledge of a diverse range of species traits is required. Until now, data on spider traits have been scattered across thousands of publications produced for over two centuries and written in diverse languages. To facilitate access to such data, we developed an online database for archiving and accessing spider traits at a global scale. The database has been designed to accommodate a great variety of traits (e.g. ecological, behavioural and morphological) measured at individual, species or higher taxonomic levels. Records are accompanied by extensive metadata (e.g. location and method). The database is curated by an expert team, regularly updated and open to any user. A future goal of the growing database is to include all published and unpublished data on spider traits provided by experts worldwide and to facilitate broad cross-taxon assays in functional ecology and comparative biology.Fil: Pekár, Stano. Masaryk University; República ChecaFil: Wolff, Jonas O. University of Greifswald; AlemaniaFil: Cernecká, L'udmila. Slovak Academy of Sciences; ArgentinaFil: Birkhofer, Klaus. Brandenburgische Technische Universität Cottbus; AlemaniaFil: Mammola, Stefano. University of Helsinki; FinlandiaFil: Lowe, Elizabeth C.. Macquarie University; AustraliaFil: Fukushima, Caroline S.. University of Helsinki; FinlandiaFil: Herberstein, Marie E.. Macquarie University; AustraliaFil: Kucera, Adam. Masaryk University; República ChecaFil: Buzatto, Bruno A.. University of Western Australia; AustraliaFil: Djoudi, El Aziz. Brandenburgische Technische Universität Cottbus; AlemaniaFil: Domenech, Marc. Universidad de Barcelona; EspañaFil: Enciso, Alison Vanesa. Fundación Protectora Ambiental Planadas Tolima; ColombiaFil: Piñanez Espejo, Yolanda María Guadalupe. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Posadas | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Posadas; ArgentinaFil: Febles, Sara. No especifíca;Fil: García, Luis F. Universidad de la República; UruguayFil: Gonçalves Souza, Thiago. Universidad Federal Rural Pernambuco; BrasilFil: Isaia, Marco. Università di Torino; ItaliaFil: Lafage, Denis. Universite de Rennes I; FranciaFil: Líznarová, Eva. Masaryk University; República ChecaFil: Macías Hernández, Nuria. Universidad de La Laguna; EspañaFil: Fiorini de Magalhaes, Ivan Luiz. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Museo Argentino de Ciencias Naturales "Bernardino Rivadavia"; ArgentinaFil: Malumbres Olarte, Jagoba. Universidade Dos Açores; PortugalFil: Michálek, Ondrej. Masaryk University; República ChecaFil: Michalik, Peter. ERNST MORITZ ARNDT UNIVERSITÄT GREIFSWALD (UG);Fil: Michalko, Radek. No especifíca;Fil: Milano, Filippo. Università di Torino; ItaliaFil: Munévar, Ana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; ArgentinaFil: Nentwig, Wolfgang. University of Bern; SuizaFil: Nicolosi, Giuseppe. Università di Torino; ItaliaFil: Painting, Christina J. No especifíca;Fil: Pétillon, Julien. Universite de Rennes I; FranciaFil: Piano, Elena. Università di Torino; ItaliaFil: Privet, Kaïna. Universite de Rennes I; FranciaFil: Ramirez, Martin Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Museo Argentino de Ciencias Naturales "Bernardino Rivadavia"; ArgentinaFil: Ramos, Cândida. No especifíca;Fil: Rezác, Milan. No especifíca;Fil: Ridel, Aurélien. Universite de Rennes I; FranciaFil: Ruzicka, Vlastimil. No especifíca;Fil: Santos, Irene. No especifíca;Fil: Sentenská, Lenka. Masaryk University; República ChecaFil: Walker, Leilani. No especifíca;Fil: Wierucka, Kaja. Universitat Zurich; SuizaFil: Zurita, Gustavo Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Posadas | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Posadas; ArgentinaFil: Cardoso, Pedro. No especifíca

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

Author Correction: Federated learning enables big data for rare cancer boundary detection.

10.1038/s41467-023-36188-7NATURE COMMUNICATIONS14