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  1. Book ; Online ; E-Book: Psychologie der Schwangerschaft

    Alvarez, Luis / Cayol, Véronique / Peter, Antje

    Veränderungen bewusst erleben und sich selbst verstehen

    2016  

    Title translation Psychologie et psychiatrie de la grossesse
    Author's details Luis Alvarez, Véronique Cayol ; aus dem Französischen von Antje Peter
    Keywords Pregnancy ; Psychological aspects ; Electronic books ; Schwangerschaft ; Psychische Verarbeitung ; Persönlichkeitsentwicklung ; Lebensereignis ; Elternschaft ; Mutter ; Kind
    Subject Mütter ; Life event ; Kindheit ; Kindesalter ; Kindschaft ; Kinder ; Persönlichkeit ; Persönlichkeitsbildung ; Persönlichkeitsentfaltung ; Verarbeitung ; Seelische Verarbeitung ; Gestation ; Gravidität
    Language German
    Size 1 Online-Ressource (167 Seiten)
    Publisher Herder
    Publishing place Freiburg ; Basel ; Wien
    Publishing country Germany ; Switzerland ; Austria
    Document type Book ; Online ; E-Book
    Remark Zugriff für angemeldete ZB MED-Nutzerinnen und -Nutzer
    HBZ-ID HT020457858
    ISBN 978-3-451-80994-1 ; 9783451613876 ; 3-451-80994-X ; 3451613875
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  2. Article: A model to forecast the evolution of the number of COVID-19 symptomatic patiens after drastic isolation measures

    Alvarez, Luis

    Abstract: In this work we propose a model to forecast the evolution of the number of COVID-19 symptomatic patients after drastic isolation measures using a combination of exponential grow models and the probability distribution of the incubation period. ...

    Abstract In this work we propose a model to forecast the evolution of the number of COVID-19 symptomatic patients after drastic isolation measures using a combination of exponential grow models and the probability distribution of the incubation period.
    Keywords covid19
    Publisher ArXiv
    Document type Article
    Database COVID19

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  3. Book ; Online: An empirical algorithm to forecast the evolution of the number of COVID-19 symptomatic patients after social distancing interventions

    Alvarez, Luis

    2020  

    Abstract: We present an empirical algorithm to forecast the evolution of the number of COVID-19 symptomatic patients in the early stages of the pandemic spread and after strict social distancing interventions. The algorithm is based on a low dimensional model for ... ...

    Abstract We present an empirical algorithm to forecast the evolution of the number of COVID-19 symptomatic patients in the early stages of the pandemic spread and after strict social distancing interventions. The algorithm is based on a low dimensional model for the variation of the exponential growth rate that decreases after the implementation of strict social distancing measures. From the observable data given by the number of tested positive, our model estimates the number of infected hindcast introducing in the model formulation the incubation time. We also use the model to follow the number of infected patients who later die using the registered number of deaths and the distribution time from infection to death. The relationship of the proposed model with the SIR models is studied. Model parameters fitting is done by minimizing a quadratic error between the data and the model forecast. An extended model is also proposed that allows a longer term forecast. An online implementation of the model is avalaible at www.ctim.es/covid19
    Keywords Quantitative Biology - Populations and Evolution
    Subject code 330
    Publishing date 2020-03-22
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article: An empirical algorithm to forecast the evolution of the number of COVID-19 symptomatic patients after social distancing interventions

    Alvarez, Luis

    Abstract: We present an empirical algorithm to forecast the evolution of the number of COVID-19 symptomatic patients in the early stages of the pandemic spread and after strict social distancing interventions. The algorithm is based on a low dimensional model for ... ...

    Abstract We present an empirical algorithm to forecast the evolution of the number of COVID-19 symptomatic patients in the early stages of the pandemic spread and after strict social distancing interventions. The algorithm is based on a low dimensional model for the variation of the exponential growth rate that decreases after the implementation of strict social distancing measures. From the observable data given by the number of tested positive, our model estimates the number of infected hindcast introducing in the model formulation the incubation time. We also use the model to follow the number of infected patients who later die using the registered number of deaths and the distribution time from infection to death. The relationship of the proposed model with the SIR models is studied. Model parameters fitting is done by minimizing a quadratic error between the data and the model forecast. An extended model is also proposed that allows a longer term forecast. An online implementation of the model is avalaible at www.ctim.es/covid19
    Keywords covid19
    Publisher ArXiv
    Document type Article
    Database COVID19

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  5. Article ; Online: Comparative analysis of the first wave of the COVID-19 pandemic in South Korea, Italy, Spain, France, Germany, the United Kingdom, the USA and the New-York state

    Alvarez, Luis

    medRxiv

    Abstract: We use an exponential growth model to analyze the first wave of the COVID-19 pandemic in South Korea, Italy, Spain, France, Germany, the United Kingdom, the USA and the New-York state. This model uses the number of officially reported patients tested ... ...

    Abstract We use an exponential growth model to analyze the first wave of the COVID-19 pandemic in South Korea, Italy, Spain, France, Germany, the United Kingdom, the USA and the New-York state. This model uses the number of officially reported patients tested positive and deaths to estimate an infected hindcast of the cumulative number of patients who later tested positive or who later die. For each region, an epidemic timeline is established, obtaining a precise knowledge of the chronology of the main epidemiological events during the full course of the first wave. It includes, in particular, the time that the virus has been in free circulation before the impact of the social distancing measures were observable. The results of the study suggest that among the analyzed regions, only South Korea and Germany possessed, at the beginning of the epidemic, a testing capacity that allowed to correctly follow the evolution of the epidemic. Anticipation in taking measures in these two countries caused the virus to spend less time in free circulation than in the rest of the regions. The analysis of the growth rates in the different regions suggests that the exponential growth rate of the cumulative number of infected, when the virus is in free circulation, is around 0.250737. In addition, we also study the ability of the model to properly forecast the epidemic spread at the beginning of the epidemic outbreak when very little data and information about the coronavirus were available. In the case of France, we obtain a reasonable estimate of the peak of the new cases of patients tested positive 9 days in advance and only 7 days after the implementation of a strict lockdown.
    Keywords covid19
    Language English
    Publishing date 2020-11-23
    Publisher Cold Spring Harbor Laboratory Press
    Document type Article ; Online
    DOI 10.1101/2020.11.20.20235689
    Database COVID19

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  6. Article ; Online: Time warping between main epidemic time series in epidemiological surveillance.

    Morel, Jean-David / Morel, Jean-Michel / Alvarez, Luis

    PLoS computational biology

    2023  Volume 19, Issue 12, Page(s) e1011757

    Abstract: The most common reported epidemic time series in epidemiological surveillance are the daily or weekly incidence of new cases, the hospital admission count, the ICU admission count, and the death toll, which played such a prominent role in the struggle to ...

    Abstract The most common reported epidemic time series in epidemiological surveillance are the daily or weekly incidence of new cases, the hospital admission count, the ICU admission count, and the death toll, which played such a prominent role in the struggle to monitor the Covid-19 pandemic. We show that pairs of such curves are related to each other by a generalized renewal equation depending on a smooth time varying delay and a smooth ratio generalizing the reproduction number. Such a functional relation is also explored for pairs of simultaneous curves measuring the same indicator in two neighboring countries. Given two such simultaneous time series, we develop, based on a signal processing approach, an efficient numerical method for computing their time varying delay and ratio curves, and we verify that its results are consistent. Indeed, they experimentally verify symmetry and transitivity requirements and we also show, using realistic simulated data, that the method faithfully recovers time delays and ratios. We discuss several real examples where the method seems to display interpretable time delays and ratios. The proposed method generalizes and unifies many recent related attempts to take advantage of the plurality of these health data across regions or countries and time, providing a better understanding of the relationship between them. An implementation of the method is publicly available at the EpiInvert CRAN package.
    MeSH term(s) Humans ; Time Factors ; Pandemics ; COVID-19/epidemiology ; Hospitalization ; Incidence
    Language English
    Publishing date 2023-12-27
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2193340-6
    ISSN 1553-7358 ; 1553-734X
    ISSN (online) 1553-7358
    ISSN 1553-734X
    DOI 10.1371/journal.pcbi.1011757
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: The paediatrician and the prevention of non-communicables diseases (NCD).

    Cabana, Jorge / Gil, Stella / Alvarez, Luis García-Marcos

    Anales de pediatria

    2023  Volume 99, Issue 5, Page(s) 371–372

    MeSH term(s) Humans ; Noncommunicable Diseases/prevention & control ; Risk Factors ; Health Promotion ; Pediatricians
    Language English
    Publishing date 2023-11-01
    Publishing country Spain
    Document type Letter
    ZDB-ID 2830901-7
    ISSN 2341-2879 ; 2341-2879
    ISSN (online) 2341-2879
    ISSN 2341-2879
    DOI 10.1016/j.anpede.2023.08.016
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Learning from the past: A short term forecast method for the COVID-19 incidence curve.

    Morel, Jean-David / Morel, Jean-Michel / Alvarez, Luis

    PLoS computational biology

    2023  Volume 19, Issue 6, Page(s) e1010790

    Abstract: The COVID-19 pandemy has created a radically new situation where most countries provide raw measurements of their daily incidence and disclose them in real time. This enables new machine learning forecast strategies where the prediction might no longer ... ...

    Abstract The COVID-19 pandemy has created a radically new situation where most countries provide raw measurements of their daily incidence and disclose them in real time. This enables new machine learning forecast strategies where the prediction might no longer be based just on the past values of the current incidence curve, but could take advantage of observations in many countries. We present such a simple global machine learning procedure using all past daily incidence trend curves. Each of the 27,418 COVID-19 incidence trend curves in our database contains the values of 56 consecutive days extracted from observed incidence curves across 61 world regions and countries. Given a current incidence trend curve observed over the past four weeks, its forecast in the next four weeks is computed by matching it with the first four weeks of all samples, and ranking them by their similarity to the query curve. Then the 28 days forecast is obtained by a statistical estimation combining the values of the 28 last observed days in those similar samples. Using comparison performed by the European Covid-19 Forecast Hub with the current state of the art forecast methods, we verify that the proposed global learning method, EpiLearn, compares favorably to methods forecasting from a single past curve.
    MeSH term(s) Humans ; COVID-19/epidemiology ; Incidence ; Forecasting
    Language English
    Publishing date 2023-06-21
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2193340-6
    ISSN 1553-7358 ; 1553-734X
    ISSN (online) 1553-7358
    ISSN 1553-734X
    DOI 10.1371/journal.pcbi.1010790
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: The tailored sperm cell.

    Alvarez, Luis

    Journal of plant research

    2017  Volume 130, Issue 3, Page(s) 455–464

    Abstract: Sperm are ubiquitous and yet unique. Genes involved in sexual reproduction are more divergent than most genes expressed in non-reproductive tissues. It has been argued that sperm have been altered during evolution more than any somatic cell. Profound ... ...

    Abstract Sperm are ubiquitous and yet unique. Genes involved in sexual reproduction are more divergent than most genes expressed in non-reproductive tissues. It has been argued that sperm have been altered during evolution more than any somatic cell. Profound variations are found at the level of morphology, motility, search strategy for the egg, and the underlying signalling mechanisms. Sperm evolutionary adaptation may have arisen from sperm competition (sperm from rival males compete within the female's body to fertilize eggs), cryptic female choice (the female's ability to choose among different stored sperm), social cues tuning sperm quality or from the site of fertilization (internal vs. external fertilization), to name a few. Unquestionably, sperm represent an invaluable source for the exploration of biological diversity at the level of signalling, motility, and evolution. Despite the richness in sperm variations, only a few model systems for signalling and motility have been studied in detail. Using fast kinetic techniques, electrophysiological recordings, and optogenetics, the molecular players and the sequence of signalling events of sperm from a few marine invertebrates, mammals, and fish are being elucidated. Furthermore, recent technological advances allow studying sperm motility with unprecedented precision; these studies provide new insights into flagellar motility and navigation in three dimensions (3D). The scope of this review is to highlight variations in motile sperm across species, and discuss the great promise that 3D imaging techniques offer into unravelling sperm mysteries.
    MeSH term(s) Animals ; Bacterial Physiological Phenomena ; Biodiversity ; Biological Evolution ; Chemotaxis/physiology ; Fertilization/physiology ; Flagella/physiology ; Flagella/ultrastructure ; Gene Expression ; Imaging, Three-Dimensional ; Male ; Marine Biology ; Polymorphism, Genetic/physiology ; Reproduction/physiology ; Signal Transduction ; Sperm Motility/physiology ; Sperm Tail/physiology ; Sperm Tail/ultrastructure
    Language English
    Publishing date 2017-05
    Publishing country Japan
    Document type Journal Article ; Review
    ZDB-ID 2077362-6
    ISSN 1618-0860 ; 0918-9440
    ISSN (online) 1618-0860
    ISSN 0918-9440
    DOI 10.1007/s10265-017-0936-2
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: Renal improvement and remission in a patient with refractory ANCA-associated vasculitis treated with avacopan.

    Alvarez, Luis / Kambham, Neeraja / Su, Robert

    Journal of nephrology

    2023  Volume 36, Issue 8, Page(s) 2365–2370

    Abstract: Antineutrophil cytoplasmic autoantibody (ANCA)-associated vasculitis is associated with end-organ damage resulting in significant morbidity and mortality. Most recently, avacopan, an orally administered selective antagonist of the C5a receptor, was ... ...

    Abstract Antineutrophil cytoplasmic autoantibody (ANCA)-associated vasculitis is associated with end-organ damage resulting in significant morbidity and mortality. Most recently, avacopan, an orally administered selective antagonist of the C5a receptor, was approved by the US Food and Drug Administration as an adjunctive treatment of adult patients with severe, active ANCA-associated vasculitis (granulomatosis with polyangiitis and microscopic polyangiitis) in combination with standard therapy including glucocorticoids. This case study describes a 58-year-old Asian female with severe ANCA-associated vasculitis and acute renal failure who responded to adjunctive therapy with avacopan despite being refractory to rituximab and glucocorticoid therapy.
    MeSH term(s) Adult ; Humans ; Female ; Middle Aged ; Immunosuppressive Agents ; Anti-Neutrophil Cytoplasmic Antibody-Associated Vasculitis/complications ; Anti-Neutrophil Cytoplasmic Antibody-Associated Vasculitis/drug therapy ; Rituximab/therapeutic use ; Aniline Compounds/adverse effects ; Glucocorticoids/therapeutic use ; Glucocorticoids/adverse effects ; Antibodies, Antineutrophil Cytoplasmic ; Granulomatosis with Polyangiitis/drug therapy ; Remission Induction
    Chemical Substances Immunosuppressive Agents ; avacopan (O880NM097T) ; Rituximab (4F4X42SYQ6) ; Aniline Compounds ; Glucocorticoids ; Antibodies, Antineutrophil Cytoplasmic
    Language English
    Publishing date 2023-04-10
    Publishing country Italy
    Document type Journal Article
    ZDB-ID 1093991-x
    ISSN 1724-6059 ; 1120-3625 ; 1121-8428
    ISSN (online) 1724-6059
    ISSN 1120-3625 ; 1121-8428
    DOI 10.1007/s40620-023-01614-y
    Database MEDical Literature Analysis and Retrieval System OnLINE

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