102 research outputs found

    COVID-19 Pandemic and Remote Consultations in Children: A Bibliometric Analysis.

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    Telemedicine is becoming a standard method of consultation, and the COVID-19 pandemic has increased its need. Telemedicine is suitable for non-communicable diseases (NCDs) in the pediatric population, as these are chronic conditions that affect many children worldwide. The aim of this study was to analyze the bibliometric parameters of publications on the use of telemedicine for the most common NCDs in children before and after the COVID-19 pandemic. Following the electronic search, 585 records were selected. "Metabolic diseases" was the most frequent topic before and after the pandemic, accounting for 34.76% in 2017-2019 and 33.97% in 2020-2022. The average IF of the journals from which records were retrieved was 5.46 ± 4.62 before and 4.58 ± 2.82 after the pandemic, with no significant variation. The number of citations per reference averaged 14.71 ± 17.16 in 2017-2019 (95% CI: 12.07; 17.36) and 5.54 ± 13.71 in 2020-2022 (95% CI: 4.23; 6.86). Asthma, metabolic diseases, and neurodevelopmental disorders were the most explored topics. A relevant finding concerns the increasing number of observational studies after the pandemic, with a reduction of the interventional studies. The latter type of study should be recommended as it can increase the evaluation of new strategies for the management of NCDs

    A minimal model of peptide binding predicts ensemble properties of serum antibodies

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    <p/> <p>Background</p> <p>The importance of peptide microarrays as a tool for serological diagnostics has strongly increased over the last decade. However, interpretation of the binding signals is still hampered by our limited understanding of the technology. This is in particular true for arrays probed with antibody mixtures of unknown complexity, such as sera. To gain insight into how signals depend on peptide amino acid sequences, we probed random-sequence peptide microarrays with sera of healthy and infected mice. We analyzed the resulting antibody binding profiles with regression methods and formulated a minimal model to explain our findings.</p> <p>Results</p> <p>Multivariate regression analysis relating peptide sequence to measured signals led to the definition of amino acid-associated weights. Although these weights do not contain information on amino acid position, they predict up to 40-50% of the binding profiles' variation. Mathematical modeling shows that this position-independent ansatz is only adequate for highly diverse random antibody mixtures which are not dominated by a few antibodies. Experimental results suggest that sera from healthy individuals correspond to that case, in contrast to sera of infected ones.</p> <p>Conclusions</p> <p>Our results indicate that position-independent amino acid-associated weights predict linear epitope binding of antibody mixtures only if the mixture is random, highly diverse, and contains no dominant antibodies. The discovered ensemble property is an important step towards an understanding of peptide-array serum-antibody binding profiles. It has implications for both serological diagnostics and B cell epitope mapping.</p

    A proposed new generation of evidence-based microsimulation models to inform global control of cervical cancer

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    Health decision models are the only available tools designed to consider the lifetime natural history of human papillomavirus (HPV) infection and pathogenesis of cervical cancer, and the estimated long-term impact of preventive interventions. Yet health decision modeling results are often considered a lesser form of scientific evidence due to the inherent needs to rely on imperfect data and make numerous assumptions and extrapolations regarding complex processes. We propose a new health decision modeling framework that de-emphasizes cytologic-colposcopic-histologic diagnoses due to their subjectivity and lack of reproducibility, relying instead on HPV type and duration of infection as the major determinants of subsequent transition probabilities. We posit that the new model health states (normal, carcinogenic HPV infection, precancer, cancer) and corollary transitions are universal, but that the probabilities of transitioning between states may vary by population. Evidence for this variability in host response to HPV infections can be inferred from HPV prevalence patterns in different regions across the lifespan, and might be linked to different average population levels of immunologic control of HPV infections. By prioritizing direct estimation of model transition probabilities from longitudinal data (and limiting reliance on model-fitting techniques that may propagate error when applied to multiple transitions), we aim to reduce the number of assumptions for greater transparency and reliability. We propose this new microsimulation model for critique and discussion, hoping to contribute to models that maximally inform efficient strategies towards global cervical cancer elimination

    Two transiting hot Jupiters from the WASP survey : WASP-150b and WASP-176b

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    Funding: The research leading to these results has received funding from the European Research Council under the FP/2007-2013 ERC grant Agreement No. 336480 and from the ARC grant for Concerted Research Actions financed by the Wallonia-Brussels Federation. A.C.C. acknowledges support from the UK Science and Technology Facilities Council (STFC)consolidated grant No. ST/R000824/1.We report the discovery of two transiting exoplanets from the WASP survey, WASP-150b and WASP-176b. WASP-150b is an eccentric (e = 0.38) hot Jupiter on a 5.6 day orbit around a V = 12.03, F8 main-sequence host. The host star has a mass and radius of 1.4 M⊙ and 1.7 R⊙ respectively. WASP-150b has a mass and radius of 8.5 MJ and 1.1 RJ, leading to a large planetary bulk density of 6.4 ρJ. WASP-150b is found to be ~3 Gyr old, well below its circularization timescale, supporting the eccentric nature of the planet. WASP-176b is a hot Jupiter planet on a 3.9 day orbit around a V = 12.01, F9 sub-giant host. The host star has a mass and radius of 1.3 M⊙ and 1.9 R⊙. WASP-176b has a mass and radius of 0.86 MJ and 1.5 RJ, respectively, leading to a planetary bulk density of 0.23 ρJ.Publisher PDFPeer reviewe

    Understanding Factors Associated With Psychomotor Subtypes of Delirium in Older Inpatients With Dementia

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    Integrative genome-wide expression profiling identifies three distinct molecular subgroups of renal cell carcinoma with different patient outcome

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    ABSTRACT: BACKGROUND: Renal cell carcinoma (RCC) is characterized by a number of diverse molecular aberrations that differ among individuals. Recent approaches to molecularly classify RCC were based on clinical, pathological as well as on single molecular parameters. As a consequence, gene expression patterns reflecting the sum of genetic aberrations in individual tumors may not have been recognized. In an attempt to uncover such molecular features in RCC, we used a novel, unbiased and integrative approach. METHODS: We integrated gene expression data from 97 primary RCCs of different pathologic parameters, 15 RCC metastases as well as 34 cancer cell lines for two-way nonsupervised hierarchical clustering using gene groups suggested by the PANTHER Classification System. We depicted the genomic landscape of the resulted tumor groups by means of Single Nuclear Polymorphism (SNP) technology. Finally, the achieved results were immunohistochemically analyzed using a tissue microarray (TMA) composed of 254 RCC. Results: We found robust, genome wide expression signatures, which split RCC into three distinct molecular subgroups. These groups remained stable even if randomly selected gene sets were clustered. Notably, the pattern obtained from RCC cell lines was clearly distinguishable from that of primary tumors. SNP array analysis demonstrated differing frequencies of chromosomal copy number alterations among RCC subgroups. TMA analysis with group-specific markers showed a prognostic significance of the different groups. Conclusion: We propose the existence of characteristic and histologically independent genome-wide expression outputs in RCC with potential biological and clinical relevance

    Informationsgewinnung mittels Bindungsanalysen von Serumantikörpern an Peptidbibliotheken

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    Ein charakteristisches Merkmal des humoralen Immunsystems ist die Produktion vieler verschiedener Antikörper. Geläufige diagnostische Tests für den Nachweis von Krankheit-spezifischen Serumantikörpern nutzen Antigene zum Nachweis der Krankheit via Antikörperbindung. Derartige diagnostische Tests setzen jedoch die Kenntnis von Krankheit-spezifischen Antigenen voraus. Die vorliegende Arbeit berücksichtigt die unterschiedlichen Bindungsreaktivitäten ganzer Antikörperrepertoires verschiedener Gruppen von Individuen. Dazu werden die Serumantikörperbindungen gegenüber Zufallsbibliotheken gemessen. Die Moleküle dieser beliebigen Bibliotheken müssen keine Verwandtschaft zu den Antigenen der Krankheit haben. Mit modernen Herstellungsverfahren von Peptidarrays auf Glasträgern können mit einmal synthetisierten Peptiden hunderte von Träger-Replikas produziert werden. Die Suche nach hochaffinen Bindern zur Diagnose von Krankheiten mit unbekannten Antigenen oder mit Kreuzreaktivitäten zwischen gesunden und kranken Individuen könnte überflüssig werden. Gestützt auf die beschriebenen Voraussetzungen zeigt die vorliegende Arbeit, dass die Messung von Serumantikörper-Bindungen gegenüber Peptidbibliotheken mit zufälligen Sequenzen die Unterscheidung zwischen Gruppen von gesunden und kranken Individuen für unterschiedliche Krankheiten ermöglicht. Eine unerwartet kleine Anzahl von Peptiden ist ausreichend für eine zuverlässige Vorhersage der untersuchten Gruppen. Der unvoreingenommene Ansatz ermöglicht eine ebenso gute Unterscheidung von gesund und krank, wie sie auch mit voreingenommenen Bibliotheken gezeigt worden sind. Wir vermuten, dass der vorliegende Ansatz ein wichtiger Schritt in Richtung zuverlässiger Diagnose darstellt, insbesondere für Krankheiten mit noch unbekannten Antigenen. Ausserdem bietet die hohe Spezifizität der Detektone und deren kleinen Mitgliederzahl eine Grundlage für die gleichzeitige Diagnose von verschiedenen Krankheiten auf einem einzigen Peptid-Mikroarray.A characteristic trait of the humoral immune system is the production of lots of different antibodies. Commonly used diagnostic tests for the detection of disease-specific serum-antibodies successfully exploit these antibody reactivities against disease eliciting antigens. Such diagnostic tests do however need the knowledge of disease specific antigen as a prerequisite. The presented work looks at the binding reactivities of whole antibody repertoires of different groups of individuals. Therefore the binding of serum-antibodies are measured against arbitrary probe molecule libraries. The arbitrary molecules of such libraries do not need to be related to the antigens of the disease to be diagnosed. Modern synthesis and printing processes of peptides on glass chips arrays allow the production of hundreds or peptide-chip replicas with small amounts of uniquely synthesized peptides. The search for high-affinity binders for the diagnosis of diseases with no known antigens might become redundant. Based on the described premises the presented work demonstrates the differentiation of different diseases by means of antibody serum reactivity differences towards arbitrary peptide libraries between healthy and diseased individuals. The number of peptides necessary for reliable prediction of the investigated groups of individuals are unanticipated small. The unbiased approach of the library design works as well as it possibly could with intended libraries, like whole-proteome arrays, used in recent other works. We presume our approach to be an important step forward towards reliable diagnosis, in particular for diseases caused by yet unknown antigens. Furthermore, the high specificity of the detectons and their smallness in size might provide a basis for simultaneous diagnosis of various diseases on a single peptide microarray

    Repeated Cortisol Awakening Response as Predictor of Antidepressant Treatment Outcome with Duloxetine

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    Despite considerably extended knowledge about the mechanism of action of antidepressants, physicians would greatly benefit from reliable biological predictors identifying those patients who will respond poorly to a given treatment. The aim of the present study was to assess whether repeated testing of the cortisol awakening response (CAR) between baseline and after 10 days of duloxetine treatment is able to predict antidepressant treatment outcome after 6 weeks of treatment.; 12 patients with a major depressive episode were treated with duloxetine 90 mg/day for 6 weeks. At baseline and after 10 days of duloxetine treatment, the CAR was assessed, and changes between baseline and day 10 were categorized as improved or unimproved according to the change in cortisol area under the concentration-time curve total concentrations. Depression severity was assessed with the 21-item Hamilton Depression Rating Scale (HDRS-21).; Non-remission after 6 weeks of treatment with duloxetine was predicted by an unfavourable saliva cortisol change between baseline and 10 days of duloxetine treatment. Linear regression analysis revealed that patients with a higher decrease in saliva cortisol measures between baseline and 10 days of treatment show a higher decrease in HDRS-21 scores.; Repeated CAR during early treatment is a putative predictive marker of antidepressant treatment outcome with duloxetine. © 2015 S. Karger AG, Basel
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