International Comparison Exercise for Biological Dosimetry after Exposures with Neutrons Performed at Two Irradiation Facilities as Part of the BALANCE Project.

In the case of a radiological or nuclear event, biological dosimetry can be an important tool to support clinical decision-making. During a nuclear event, individuals might be exposed to a mixed field of neutrons and photons. The composition of the field and the neutron energy spectrum influence the degree of damage to the chromosomes. During the transatlantic BALANCE project, an exposure similar to a Hiroshima-like device at a distance of 1.5 km from the epicenter was simulated, and biological dosimetry based on dicentric chromosomes was performed to evaluate the participants ability to discover unknown doses and to test the influence of differences in neutron spectra. In a first step, calibration curves were established by irradiating blood samples with 5 doses in the range of 0-4 Gy at two different facilities in Germany (Physikalisch-Technische Bundesanstalt [PTB]) and the USA (the Columbia IND Neutron Facility [CINF]). The samples were sent to eight participating laboratories from the RENEB network and dicentric chromosomes were scored by each participant. Next, blood samples were irradiated with 4 blind doses in each of the two facilities and sent to the participants to provide dose estimates based on the established calibration curves. Manual and semiautomatic scoring of dicentric chromosomes were evaluated for their applicability to neutron exposures. Moreover, the biological effectiveness of the neutrons from the two irradiation facilities was compared. The calibration curves from samples irradiated at CINF showed a 1.4 times higher biological effectiveness compared to samples irradiated at PTB. For manual scoring of dicentric chromosomes, the doses of the test samples were mostly successfully resolved based on the calibration curves established during the project. For semiautomatic scoring, the dose estimation for the test samples was less successful. Doses >2 Gy in the calibration curves revealed nonlinear associations between dose and dispersion index of the dicentric counts, especially for manual scoring. The differences in the biological effectiveness between the irradiation facilities suggested that the neutron energy spectrum can have a strong impact on the dicentric counts.

Efficacy of Magnetic Therapy in Pain Reduction in Patients with Chronic Pelvic Pain: A Systematic Review.

Chronic pelvic pain (CPP), also known as chronic pelvic pain syndrome (CPPS), is a common and painful condition. However, its treatment is still a challenge. The findings about the beneficial effects of electromagnetic therapy provide a new, potentially valid, therapeutic alternative for the management of patients with CPP. Objectives: to analyze the efficacy of magnetic field therapy in pain reduction in patients with CPP and for other variables, such as urinary symptoms and quality of life, as well as to review the evidence, in order to establish an action protocol. A qualitative systematic review was carried out, based on the PRISMA protocol and registered in PROSPERO (CRD42022285428). A search was performed in the PubMed, Medline, Scopus, Cochrane, PEDro, BVS, and WOS databases, including those articles in which the patients suffered from CPP; the study variable was pain, and the intervention was based on the application of magnetic fields. Results: Among the 81 articles found, five clinical trials were considered (with an average score of 7.2 in the PEDro scale), with a total of 278 participants, most of whom presented improvements in perceived pain (p ≤ 0.05), as well as in quality of life (p < 0.05) and urinary symptoms (p = 0.05), evaluated through the NIH-CPSI and VAS scales. The therapy was conducted as a monotherapy or in combination with a pharmacological treatment. There was no common protocol among the different articles. Conclusions: Intervention programs through electromagnetic therapy, on their own or with other therapies, can be effective in patients with CPP.

RENEB/EURADOS field exercise 2019: robust dose estimation under outdoor conditions based on the dicentric chromosome assay.

PURPOSE: Biological and/or physical assays for retrospective dosimetry are valuable tools to recover the exposure situation and to aid medical decision making. To further validate and improve such biological and physical assays, in 2019, EURADOS Working Group 10 and RENEB performed a field exercise in Lund, Sweden, to simulate various real-life exposure scenarios. MATERIALS AND METHODS: For the dicentric chromosome assay (DCA), blood tubes were located at anthropomorphic phantoms positioned in different geometries and were irradiated with a 1.36 TBq 192Ir-source. For each exposure condition, dose estimates were provided by at least one laboratory and for four conditions by 17 participating RENEB laboratories. Three radio-photoluminescence glass dosimeters were placed at each tube to assess reference doses. RESULTS: The DCA results were homogeneous between participants and matched well with the reference doses (≥95% of estimates within ±0.5 Gy of the reference). For samples close to the source systematic underestimation could be corrected by accounting for exposure time. Heterogeneity within and between tubes was detected for reference doses as well as for DCA doses estimates. CONCLUSIONS: The participants were able to successfully estimate the doses and to provide important information on the exposure scenarios under conditions closely resembling a real-life situation.

Semantic Deep Learning: Prior Knowledge and a Type of Four-Term Embedding Analogy to Acquire Treatments for Well-Known Diseases.

BACKGROUND: How to treat a disease remains to be the most common type of clinical question. Obtaining evidence-based answers from biomedical literature is difficult. Analogical reasoning with embeddings from deep learning (embedding analogies) may extract such biomedical facts, although the state-of-the-art focuses on pair-based proportional (pairwise) analogies such as man:woman::king:queen ("queen = -man +king +woman"). OBJECTIVE: This study aimed to systematically extract disease treatment statements with a Semantic Deep Learning (SemDeep) approach underpinned by prior knowledge and another type of 4-term analogy (other than pairwise). METHODS: As preliminaries, we investigated Continuous Bag-of-Words (CBOW) embedding analogies in a common-English corpus with five lines of text and observed a type of 4-term analogy (not pairwise) applying the 3CosAdd formula and relating the semantic fields person and death: "dagger = -Romeo +die +died" (search query: -Romeo +die +died). Our SemDeep approach worked with pre-existing items of knowledge (what is known) to make inferences sanctioned by a 4-term analogy (search query -x +z1 +z2) from CBOW and Skip-gram embeddings created with a PubMed systematic reviews subset (PMSB dataset). Stage1: Knowledge acquisition. Obtaining a set of terms, candidate y, from embeddings using vector arithmetic. Some n-gram pairs from the cosine and validated with evidence (prior knowledge) are the input for the 3cosAdd, seeking a type of 4-term analogy relating the semantic fields disease and treatment. Stage 2: Knowledge organization. Identification of candidates sanctioned by the analogy belonging to the semantic field treatment and mapping these candidates to unified medical language system Metathesaurus concepts with MetaMap. A concept pair is a brief disease treatment statement (biomedical fact). Stage 3: Knowledge validation. An evidence-based evaluation followed by human validation of biomedical facts potentially useful for clinicians. RESULTS: We obtained 5352 n-gram pairs from 446 search queries by applying the 3CosAdd. The microaveraging performance of MetaMap for candidate y belonging to the semantic field treatment was F-measure=80.00% (precision=77.00%, recall=83.25%). We developed an empirical heuristic with some predictive power for clinical winners, that is, search queries bringing candidate y with evidence of a therapeutic intent for target disease x. The search queries -asthma +inhaled_corticosteroids +inhaled_corticosteroid and -epilepsy +valproate +antiepileptic_drug were clinical winners, finding eight evidence-based beneficial treatments. CONCLUSIONS: Extracting treatments with therapeutic intent by analogical reasoning from embeddings (423K n-grams from the PMSB dataset) is an ambitious goal. Our SemDeep approach is knowledge-based, underpinned by embedding analogies that exploit prior knowledge. Biomedical facts from embedding analogies (4-term type, not pairwise) are potentially useful for clinicians. The heuristic offers a practical way to discover beneficial treatments for well-known diseases. Learning from deep learning models does not require a massive amount of data. Embedding analogies are not limited to pairwise analogies; hence, analogical reasoning with embeddings is underexploited.

Executive Summary of the Consensus Statement of the Spanish Society of Infectious Diseases and Clinical Microbiology (SEIMC), the Spanish Society of Tropical Medicine and International Health (SEMTSI), the Spanish Association of Surgeons (AEC), the Spanish Society of Pneumology and Thoracic Surgery (SEPAR), the Spanish Society of Thoracic Surgery (SECT), the Spanish Society of Vascular and Interventional Radiology (SERVEI), and the Spanish Society of Paediatric Infectious Diseases (SEIP), on the Management of Cystic Echinococcosis / Resumen ejecutivo de la Declaración de consenso de la Sociedad Española de Enfermedades Infecciosas y Microbiología Clínica (SEIMC), la Sociedad Española de Medicina Tropical y Salud Internacional (SEMTSI), la Asociación Española de Cirujanos (AEC), la Sociedad Española de Neumología y Cirugía Torácica (SEPAR), la Sociedad Española de Cirugía Torácica (SECT), la Sociedad Española de Radiología Vascular e Intervencionista (SERVEI) y la Sociedad Española de Infectología Pediátrica (SEIP) sobre el tratamiento de la equinococosis quística

The Spanish Society of Infectious Diseases and Clinical Microbiology (SEIMC), the Spanish Society of Tropical Medicine and International Health (SEMTSI), the Spanish Association of Surgeons (AEC), the Spanish Society of Pneumology and Thoracic Surgery (SEPAR), the Spanish Society of Thoracic Surgery (SECT), the Spanish Society of Vascular and Interventional Radiology (SERVEI), and the Spanish Society of Paediatric Infectious Diseases (SEIP) considered it pertinent to issue a consensus statement on the management of cystic echinococcosis (CE) to guide healthcare professionals in the care of patients with CE. Specialists from several fields (clinicians, surgeons, radiologists, microbiologists, and parasitologists) identified the most clinically relevant questions and developed this Consensus Statement, evaluating the available evidence-based data to propose a series of recommendations on the management of this disease. This Consensus Statement is accompanied by the corresponding references on which these recommendations are based. Prior to publication, the manuscript was open for comments and suggestions from the members of the SEIMC and the scientific committees and boards of the various societies involved

La Sociedad Española de Enfermedades Infecciosas y Microbiología Clínica (SEIMC), la Sociedad Española de Medicina Tropical y Salud Internacional (SEMTSI), la Asociación Española de Cirujanos (AEC), la Sociedad Española de Neumología y Cirugía Torácica (SEPAR), la Sociedad Española de Cirugía Torácica (SECT), la Sociedad Española de Radiología Vascular e Intervencionista (SERVEI) y la Sociedad Española de Infectología Pediátrica (SEIP) han considerado pertinente la elaboración de una declaración de consenso sobre el tratamiento de la equinococosis quística (EQ) que sirva de ayuda al personal sanitario en la atención de pacientes con EQ. Varios tipos de profesionales (médicos, cirujanos, radiólogos, microbiólogos y parasitólogos) han seleccionado las preguntas más clínicamente relevantes y han desarrollado esta Declaración de consenso, en la que evalúan los datos basados en la evidencia disponibles para proponer una serie de recomendaciones sobre el tratamiento de esta enfermedad. Esta Declaración de consenso se acompaña de la bibliografía correspondiente que fundamenta estas recomendaciones. Antes de su publicación, el manuscrito estuvo abierto a comentarios y sugerencias de los miembros de la SEIMC y de los comités científicos y juntas directivas de las diferentes sociedades implicadas

Executive Summary of the Consensus Statement of the Spanish Society of Infectious Diseases and Clinical Microbiology (SEIMC), the Spanish Society of Tropical Medicine and International Health (SEMTSI), the Spanish Association of Surgeons (AEC), the Spanish Society of Pneumology and Thoracic Surgery (SEPAR), the Spanish Society of Thoracic Surgery (SECT), the Spanish Society of Vascular and Interventional Radiology (SERVEI), and the Spanish Society of Paediatric Infectious Diseases (SEIP), on the Management of Cystic Echinococcosis.

The Spanish Society of Infectious Diseases and Clinical Microbiology (SEIMC), the Spanish Society of Tropical Medicine and International Health (SEMTSI), the Spanish Association of Surgeons (AEC), the Spanish Society of Pneumology and Thoracic Surgery (SEPAR), the Spanish Society of Thoracic Surgery (SECT), the Spanish Society of Vascular and Interventional Radiology (SERVEI), and the Spanish Society of Paediatric Infectious Diseases (SEIP) considered it pertinent to issue a consensus statement on the management of cystic echinococcosis (CE) to guide healthcare professionals in the care of patients with CE. Specialists from several fields (clinicians, surgeons, radiologists, microbiologists, and parasitologists) identified the most clinically relevant questions and developed this Consensus Statement, evaluating the available evidence-based data to propose a series of recommendations on the management of this disease. This Consensus Statement is accompanied by the corresponding references on which these recommendations are based. Prior to publication, the manuscript was open for comments and suggestions from the members of the SEIMC and the scientific committees and boards of the various societies involved.

Exploring semantic deep learning for building reliable and reusable one health knowledge from PubMed systematic reviews and veterinary clinical notes.

BACKGROUND: Deep Learning opens up opportunities for routinely scanning large bodies of biomedical literature and clinical narratives to represent the meaning of biomedical and clinical terms. However, the validation and integration of this knowledge on a scale requires cross checking with ground truths (i.e. evidence-based resources) that are unavailable in an actionable or computable form. In this paper we explore how to turn information about diagnoses, prognoses, therapies and other clinical concepts into computable knowledge using free-text data about human and animal health. We used a Semantic Deep Learning approach that combines the Semantic Web technologies and Deep Learning to acquire and validate knowledge about 11 well-known medical conditions mined from two sets of unstructured free-text data: 300 K PubMed Systematic Review articles (the PMSB dataset) and 2.5 M veterinary clinical notes (the VetCN dataset). For each target condition we obtained 20 related clinical concepts using two deep learning methods applied separately on the two datasets, resulting in 880 term pairs (target term, candidate term). Each concept, represented by an n-gram, is mapped to UMLS using MetaMap; we also developed a bespoke method for mapping short forms (e.g. abbreviations and acronyms). Existing ontologies were used to formally represent associations. We also create ontological modules and illustrate how the extracted knowledge can be queried. The evaluation was performed using the content within BMJ Best Practice. RESULTS: MetaMap achieves an F measure of 88% (precision 85%, recall 91%) when applied directly to the total of 613 unique candidate terms for the 880 term pairs. When the processing of short forms is included, MetaMap achieves an F measure of 94% (precision 92%, recall 96%). Validation of the term pairs with BMJ Best Practice yields precision between 98 and 99%. CONCLUSIONS: The Semantic Deep Learning approach can transform neural embeddings built from unstructured free-text data into reliable and reusable One Health knowledge using ontologies and content from BMJ Best Practice.

Deep learning meets ontologies: experiments to anchor the cardiovascular disease ontology in the biomedical literature.

BACKGROUND: Automatic identification of term variants or acceptable alternative free-text terms for gene and protein names from the millions of biomedical publications is a challenging task. Ontologies, such as the Cardiovascular Disease Ontology (CVDO), capture domain knowledge in a computational form and can provide context for gene/protein names as written in the literature. This study investigates: 1) if word embeddings from Deep Learning algorithms can provide a list of term variants for a given gene/protein of interest; and 2) if biological knowledge from the CVDO can improve such a list without modifying the word embeddings created. METHODS: We have manually annotated 105 gene/protein names from 25 PubMed titles/abstracts and mapped them to 79 unique UniProtKB entries corresponding to gene and protein classes from the CVDO. Using more than 14 M PubMed articles (titles and available abstracts), word embeddings were generated with CBOW and Skip-gram. We setup two experiments for a synonym detection task, each with four raters, and 3672 pairs of terms (target term and candidate term) from the word embeddings created. For Experiment I, the target terms for 64 UniProtKB entries were those that appear in the titles/abstracts; Experiment II involves 63 UniProtKB entries and the target terms are a combination of terms from PubMed titles/abstracts with terms (i.e. increased context) from the CVDO protein class expressions and labels. RESULTS: In Experiment I, Skip-gram finds term variants (full and/or partial) for 89% of the 64 UniProtKB entries, while CBOW finds term variants for 67%. In Experiment II (with the aid of the CVDO), Skip-gram finds term variants for 95% of the 63 UniProtKB entries, while CBOW finds term variants for 78%. Combining the results of both experiments, Skip-gram finds term variants for 97% of the 79 UniProtKB entries, while CBOW finds term variants for 81%. CONCLUSIONS: This study shows performance improvements for both CBOW and Skip-gram on a gene/protein synonym detection task by adding knowledge formalised in the CVDO and without modifying the word embeddings created. Hence, the CVDO supplies context that is effective in inducing term variability for both CBOW and Skip-gram while reducing ambiguity. Skip-gram outperforms CBOW and finds more pertinent term variants for gene/protein names annotated from the scientific literature.

Helmintosis y eosinofilia en España (1990-2015) / Helminthosis and eosinophilia in Spain (1990-2015)

La detección de eosinofilia periférica es un motivo relativamente frecuente para la remisión de un paciente a una Unidad/Servicio de Enfermedades Infecciosas. En general, se pretende descartar una enfermedad parasitaria, tanto en personas autóctonas como en viajeros o inmigrantes. Excepcionalmente la eosinofilia relacionada con parásitos corresponde a una protozoosis, siendo los helmintos los principales agentes causales de este hallazgo hematológico. La eosinofilia puede ser el único hallazgo anormal o formar parte del cuadro clínico-biológico del paciente. Por otro lado, no todas las helmintosis se asocian de forma sistemática a eosinofilia, y el grado de la misma difiere entre las fases de la infección y el tipo de helminto. El propósito de esta revisión es un estudio sistemático de la relación entre helmintosis y eosinofilia en la literatura española, distinguiendo los casos autóctonos e importados, así como la relación con situaciones de inmunodepresión (AU)

The finding of blood eosinophilia in a patient is a relatively frequent reason to refer him/her to a Clinical Department of Infectious Diseases. The doctor usually intends to rule out a parasitic disease in the autochthonous population, travelers or immigrants. It is uncommon for an eosinophilia to be produced by protozoa infection, whereas helminth parasites are more frequently associated with an increase of eosinophil counts in the infected patient. Eosinophilia can be the only abnormal finding, or it could be part of more complex clinical manifestations suffered by the patient. Furthermore, many, but not all, helminth infections are associated with eosinophilia, and the eosinophil level (low, high) differs according to parasite stages, helminth species, and worm co-infections. The purpose of the present article is to carry out a systematic review of cases and case series on helminth infections and eosinophilia reported in Spain from 1990 to 2015, making a distinction between autochthonous and imported (immigrants and travelers) cases, and studying their relationship with immunodepression situations (AU)

Helminthosis and eosinophilia in Spain (1990-2015). / Helmintosis y eosinofilia en España (1990-2015).

The finding of blood eosinophilia in a patient is a relatively frequent reason to refer him/her to a Clinical Department of Infectious Diseases. The doctor usually intends to rule out a parasitic disease in the autochthonous population, travelers or immigrants. It is uncommon for an eosinophilia to be produced by protozoa infection, whereas helminth parasites are more frequently associated with an increase of eosinophil counts in the infected patient. Eosinophilia can be the only abnormal finding, or it could be part of more complex clinical manifestations suffered by the patient. Furthermore, many, but not all, helminth infections are associated with eosinophilia, and the eosinophil level (low, high) differs according to parasite stages, helminth species, and worm co-infections. The purpose of the present article is to carry out a systematic review of cases and case series on helminth infections and eosinophilia reported in Spain from 1990 to 2015, making a distinction between autochthonous and imported (immigrants and travelers) cases, and studying their relationship with immunodepression situations.

A Case Study on Sepsis Using PubMed and Deep Learning for Ontology Learning.

We investigate the application of distributional semantics models for facilitating unsupervised extraction of biomedical terms from unannotated corpora. Term extraction is used as the first step of an ontology learning process that aims to (semi-)automatic annotation of biomedical concepts and relations from more than 300K PubMed titles and abstracts. We experimented with both traditional distributional semantics methods such as Latent Semantic Analysis (LSA) and Latent Dirichlet Allocation (LDA) as well as the neural language models CBOW and Skip-gram from Deep Learning. The evaluation conducted concentrates on sepsis, a major life-threatening condition, and shows that Deep Learning models outperform LSA and LDA with much higher precision.

Web based scoring is useful for validation and harmonisation of scoring criteria within RENEB.

PURPOSE: To establish a training data set of digital images and to investigate the scoring criteria and dose assessment of the dicentric assay within the European network of biodosimetry (RENEB), a web based scoring inter-comparison was undertaken by 17 RENEB partners. MATERIALS AND METHODS: Two sets of 50 high resolution images were uploaded onto the RENEB website. One set included metaphases after a moderate exposure (1.3 Gy) and the other set consisted of metaphases after a high dose exposure (3.5 Gy). The laboratories used their own calibration curves for estimating doses based on observed aberration frequencies. RESULTS: The dose estimations and 95% confidence limits were compared to the actual doses and the corresponding z-values were satisfactory for the majority; only the dose estimations from two laboratories were too low or too high. The coefficients of variation were 17.6% for the moderate and 11.2% for the high dose. Metaphases with controversial results could be identified for training purposes. CONCLUSIONS: Overall, the web based scoring of the two galleries by the 17 laboratories produced very good results. Application of web based scoring for the dicentric assay may therefore be a relevant strategy for an operational biodosimetry assistance network.

RENEB - Running the European Network of biological dosimetry and physical retrospective dosimetry.

PURPOSE: A European network was initiated in 2012 by 23 partners from 16 European countries with the aim to significantly increase individualized dose reconstruction in case of large-scale radiological emergency scenarios. RESULTS: The network was built on three complementary pillars: (1) an operational basis with seven biological and physical dosimetric assays in ready-to-use mode, (2) a basis for education, training and quality assurance, and (3) a basis for further network development regarding new techniques and members. Techniques for individual dose estimation based on biological samples and/or inert personalized devices as mobile phones or smart phones were optimized to support rapid categorization of many potential victims according to the received dose to the blood or personal devices. Communication and cross-border collaboration were also standardized. To assure long-term sustainability of the network, cooperation with national and international emergency preparedness organizations was initiated and links to radiation protection and research platforms have been developed. A legal framework, based on a Memorandum of Understanding, was established and signed by 27 organizations by the end of 2015. CONCLUSIONS: RENEB is a European Network of biological and physical-retrospective dosimetry, with the capacity and capability to perform large-scale rapid individualized dose estimation. Specialized to handle large numbers of samples, RENEB is able to contribute to radiological emergency preparedness and wider large-scale research projects.