Performance assessment of demand controlled ventilation controls concerning indoor VOC exposure based on a dynamic VOC emission model

The performance assessment of ventilation systems often focusses only on CO2 and humidity levels. The indoor Volatile Organic Compounds (VOC) emissions of building materials or other products is thereby overlooked. The new generation of ventilation systems, Demand Controlled Ventilation (DCV), are systems that do not supply the nominal airflow continuously but are controlled by CO2 or humidity sensors in order to save energy. This poses potential problems for exposure to VOCs. In this study, a dynamic VOC model, which takes into account changing temperature and humidity that was derived from literature, is implemented in a CONTAM model of the Belgian reference apartment. The impact of a DCV system on the indoor VOC levels is investigated. Results show that the use of a dynamic model is necessary compared to the previously used approximation of a constant emission. Furthermore, on a system level, the influence of the ventilation system control on the indoor VOC levels shows. The overall VOC concentration in the different rooms will be higher because of lowered ventilation rates. Especially in rooms that are often unoccupied during the day, the accumulation of VOCs shows. In the development of DCV system controls, the aspect of VOC exposure should not be overlooked to be able to benefit from both the energy savings and improved Indoor Air Quality (IAQ)

VOC exposure in Belgian dwellings : evaluation with a temperature and humidity based emission model

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Symptom and Course Heterogeneity of Depressive Symptoms and Prognosis Following Myocardial Infarction

Objective: Previously published findings from the DepreMI cohort suggested that both the course and the type of depressive symptoms following myocardial infarction (MI) are related to prognosis but did not examine both factors simultaneously. The aim of this reanalysis study was to assess whether MI patients can be empirically classified based on trajectories of cognitive/affective (CA) and somatic/affective (SA) symptoms, and whether these classes differentially predict adverse outcomes. Method: Patients with acute MI (n = 457) were recruited between 1997 and 2000 and provided (BDI-I) data at baseline, 3, 6 and 12 months. Parallel Processes latent class growth analysis was used to identify latent classes. Patients were followed up until 2007 for all-cause mortality and cardiovascular readmissions. Results: Three classes were identified: low severity = consistently low CA and SA (n = 316); somatic persistence = consistently low CA and high SA (n = 110); and overall persistence = high and increasing CA and SA (n = 31). After adjustment for gender and the Global Registry of Acute Coronary Events risk score, somatic persistence (hazard ratio [HR]: 1.86; 95% CI: 1.18 -2.94; p = .008) but not overall persistence (HR: 1.09.; 95% CI: 0.39-3.03; p = .87), predicted mortality compared with low severity. Classes were not predictive of nonfatal cardiovascular events. Conclusions: MI patient classes differed in severity and course of CA and SA depressive symptoms in the post-MI year. Only a class with persistent SA depressive symptoms was associated with increased mortality compared with patients with low severity. This is suggestive of different origins of SA depressive symptoms in MI patients that may explain the differential associations with mortality

Using bundle embeddings to predict daily cortisol levels in human subjects

BACKGROUND: Many biological variables sampled from human subjects show a diurnal pattern, which poses special demands on the techniques used to analyze such data. Furthermore, most biological variables belong to nonlinear dynamical systems, which may make linear statistical techniques less suitable to analyze their dynamics. The current study investigates the usefulness of two analysis techniques based on nonlinear lagged vector embeddings: sequentially weighted global linear maps (SMAP), and bundle embeddings. METHODS: Time series of urinary cortisol were collected in 10 participants, in the morning ('night' measurement) and the evening ('day' measurement), resulting in 126 consecutive measurements. These time series were used to create lagged vector embeddings, which were split into 'night' and 'day' bundle embeddings. In addition, embeddings were created based on time series that were corrected for the average time-of-day (TOD) values. SMAP was used to predict future values of cortisol in these embeddings. Global (linear) and local (non-linear) predictions were compared for each embedding. Bootstrapping was used to obtain confidence intervals for the model parameters and the prediction error. RESULTS: The best cortisol predictions were found for the night bundle embeddings, followed by the full embeddings and the time-of-day corrected embeddings. The poorest predictions were found for the day bundle embeddings. The night bundle embeddings, the full embeddings and the TOD-corrected embeddings all showed low dimensions, indicating the absence of dynamical processes spanning more than one day. The dimensions of the day bundles were higher, indicating the presence of processes spanning more than one day, or a higher amount of noise. In the full embeddings, local models gave the best predictions, whereas in the bundles the best predictions were obtained from global models, indicating potential nonlinearity in the former but not the latter. CONCLUSIONS: Using a bundling approach on time series of cortisol may reveal differences between the predictions of night and day cortisol that are difficult to find with conventional time-series methods. Combination of this approach with SMAP may especially be useful when analyzing time-series data with periodic components

The comparative evidence basis for the efficacy of second-generation antidepressants in the treatment of depression in the US: A Bayesian meta-analysis of Food and Drug Administration reviews

Background Studies have shown similar efficacy of different antidepressants in the treatment of depression. Method Data of phase-2 and -3 clinical-trials for 16 antidepressants (levomilnacipran, desvenlafaxine, duloxetine, venlafaxine, paroxetine, escitalopram, vortioxetine, mirtazapine, venlafaxine XR, sertraline, fluoxetine, citalopram, paroxetine CR, nefazodone, bupropion, vilazodone), approved by the FDA for the treatment of depression between 1987 and 2016, were extracted from the FDA reviews that were used to evaluate efficacy prior to marketing approval, which are less liable to reporting biases. Meta-analytic Bayes factors, which quantify the strength of evidence for efficacy, were calculated. In addition, posterior pooled effect-sizes were calculated and compared with classical estimations. Results The resulted Bayes factors showed that the evidence load for efficacy varied strongly across antidepressants. However, all tested drugs except for bupropion and vilazodone showed strong evidence for their efficacy. The posterior effect-size distributions showed variation across antidepressants, with the highest pooled estimated effect size for venlafaxine followed by paroxetine, and the lowest for bupropion and vilazodone. Limitations Not all published trials were included in the study. Conclusions The results illustrate the importance of considering both the effect size and the evidence-load when judging the efficacy of a treatment. In doing so, the currently employed Bayesian approach provided clear insights on top of those gained with traditional approaches

Compliance to Screening Protocols for Multidrug-Resistant Microorganisms at the Emergency Departments of Two Academic Hospitals in the Dutch-German Cross-Border Region

Infections caused by multidrug-resistant organisms (MDROs) are associated with prolonged hospitalization and higher risk of mortality. Patients arriving in the hospital via the emergency department (ED) are screened for the presence of MDROs in compliance with the screening protocols in order to apply the correct isolation measures. In the Dutch-German border region, local hospitals apply their own screening protocols which are based upon national screening protocols. The contents of the national and local MDRO screening protocols were compared on vancomycin-resistant enterococci (VRE), methicillin-resistant Staphylococcus aureus (MRSA), and carbapenemase-producing and carbapenem-resistant Enterobacteriaceae (CPE/CRE). The practicality of the screening protocols was evaluated by performing an audit. As a result, the content of the MDRO screening protocols differed regarding risk factors for MDRO carriage, swab site, personal protective equipment, and isolation measures. The observations and questionnaires showed that the practicality was sufficient; however, the responsibility was not designated clearly and education regarding the screening protocols was deemed inappropriate. The differences between the MDRO screening protocols complicate patient care in the Dutch-German border region. Arrangements have to be made about the responsibility of the MDRO screening, and improvements are necessary concerning education regarding the MDRO screening protocols

Glycan Binding Proteins in Therapeutic Mesenchymal Stem Cell Research

Mesenchymal stem/stromal cells (MSCs) are multipotent adult stem cells that hold enormous therapeutic potential. They are currently in a focus of intense clinical and scientific investigation. MSCs are a promising cell type for various applications in the field of tissue engineering due to their multi-lineage differentiation capacity. Furthermore, one of their most interesting characteristics is that they possess immunomodulatory properties making these cells an attractive candidate for therapy of several immune-mediated disorders. MSCs are of nonembryonic origin and thus provide a less controversial and technically more feasible alternative for ESCs in future therapeutic applications. Due to their location on the cell surface, glycans are ideal molecules for identification, purification, and characterization of cells for therapeutic purposes. Methods to reliably and proficiently determine both the change in the presence of a specific glycan structures and the changes in the glycome profile of a cell, are needed. Glycan binding proteins in general serve as diagnostic tools in medical and scientific laboratories. High affinity and exquisite specificity are important factors for their successful use. The aim of this study was to characterize the glycans on the surface of MSCs in order to find novel MSC specific glycan markers. Further goal was to develop antibodies specific for MSC surface glycans, including the novel MSC marker. As described in the original publications of this study, we first characterized the glycome of MSCs and discovered that certain specific glycan epitopes are present only in MSCs, and not in cells differentiated from them. These epitopes include i antigen, which was further characterized to be a marker for umbilical cord blood derived MSCs. An antibody against the i antigen was generated using recombinant technology. Antibodies recognizing MSC surface glycans were also generated by utilizing hybridoma technology, using whole MSCs in the immunization. Taken together, these studies provide information of the changes in the glycome profile during MSC differentiation and describe a novel MSC marker. In these studies, we used two different methods to generate anti-glycan antibodies and emphasize the importance of thorough characterization of the binding properties of GBPs. The information of the characteristic glycosylation features of MSCs, and specific markers especially, can be used to isolate and characterize desired, therapeutically advantageous cell populations for distinct applications. Development of better glycan binding proteins will advance the field of cellular therapy and also the glycobiological research in general.Mesenkymaaliset kantasolut (eli mesenkymaaliset stroomasolut) ovat monikykyisiä soluja, jotka pystyvät erilaistumaan useiksi erilaisiksi solutyypeiksi. Viime aikoina näiden solujen tutkimus ja kliininen käyttö on herättänyt paljon huomiota ja kiinnostusta. Mesenkymaalinen kantasolu on lupaava solutyyppi moniin terapeuttisiin sovelluksiin. Erityisesti kudosteknologiset sovellukset käyttävät hyväkseen mesenkymaalisten kantasolujen erilaistumiskykyä. Yksi mesenkymaalisten kantasolujen kiinnostavimmista piirteistä on kuitenkin niiden vaikutus immuunivasteeseen ja mahdollinen käyttö immuunivälitteisten sairauksien, kuten käänteishyljintäreaktion hoidossa. Sekä tutkimus- että terapiakäyttöön tarkoitetut solut täytyy voida tunnistaa, eristää ja karakterisoida hyvin. Solun pinnalla olevat sokerimolekyylit eli glykaanit tarjoavat tähän oivan mahdollisuuden. Sokerirakenteista voidaan tarkkailla yksittäisten glykaanien esiintymisen muutoksia sekä pinnan sokeriprofiilin kokonaismuutoksia. Tutkimusmenetelmät ovat viime vuosina kehittyneet huimasti, mutta vaativat vielä jatkuvaa kehitystä. Sokerirakenteita sitovat proteiinit (vasta-aineet ja lektiinit) ovat laboratorioissa yleisesti käytettyjä diagnostisia työkaluja, ja soveltuvat hyvin solun pinnan sokereiden tutkimiseen. Tarkasti määritetty sitoutumisspesifisyys ja riittävän hyvä sitoutumislujuus ovat merkittäviä tekijöitä glykaaneja sitovien proteiinien onnistuneelle käytölle sekä niiden avulla saatujen tulosten oikeellisuudelle. Tämän tutkimuksen tarkoituksena oli kartoittaa mesenkymaalisten kantasolujen pinnan sokerirakenteita tavoitteena löytää spesifinen markkeri sekä kehittää vasta-aineita näitä rakenteita tunnistamaan. Ensiksi havaitsimme solun pinnan sokeriprofiilin muuttuvan solun erilaistuessa. Keskityimme tarkastelemaan lineaarista poly-LacNAc rakennetta, eli i-antigeenia, jonka määrä solun pinnalla väheni huomattavasti solujen erilaistuessa. Tarkempi karakterisointi osoitti i-antigeenin olevan spesifinen markkeri mesenkymaalisille kantasoluille. Kehitimme i-antigeenin tunnistavan vasta-aineen rekombinanttitekniikalla sekä mesenkymaalisen solun pinnan sokereille spesifisiä vasta-aineita hybridoomatekniikalla. Jotta soluterapiaa voidaan turvallisesti kehittää lisääntyviin hoitotarpeisiin, tarvitaan tarkkoja karakterisointimenetelmiä ja hyviä työkaluja solujen tunnistamiseen ja eristämiseen. Tietoa pinnan sokerirakenteiden muutoksista voidaan käyttää eristettäessä haluttuja solupopulaatiota eri terapiasovelluksiin. Sokerirakenteita sitovien proteiinien kehittäminen edesauttaa sekä soluterapian että glykobiologisen tutkimuksen kehittymistä