Modelling human choices: MADeM and decision‑making

Research supported by FAPESP 2015/50122-0 and DFG-GRTK 1740/2. RP and AR are also part of the Research, Innovation and Dissemination Center for Neuromathematics FAPESP grant (2013/07699-0). RP is supported by a FAPESP scholarship (2013/25667-8). ACR is partially supported by a CNPq fellowship (grant 306251/2014-0)

Einflüsse der Coronapandemie auf gesundheitsbezogene Verhaltensweisen und Belastungen von Studierenden

Hintergrund: Studierende bilden die größte Gruppe an Hochschulen, somit ist ein studentisches Gesundheitsmanagement unerlässlich. Diese Gruppe zählt zwar aufgrund ihres Alters zu einer eher gesunden Bevölkerungsgruppe, dennoch sind auch Studierende gesundheitlichen Belastungen ausgesetzt. Daher sind die Auswirkungen der Coronapandemie auf die Studierenden von allgemeinem Interesse. Fragestellung: Der Artikel befasst sich mit der Frage, wie die Rahmenbedingungen der Coronapandemie gesundheitsbezogene Verhaltensweisen und Belastungen der Studierenden an der Ostfalia Hochschule für angewandte Wissenschaften beeinflussen. Material und Methoden: Auf Grundlage einer Literaturrecherche wurde ein Fragebogen zu den Themenbereichen Bewegung, Ernährung, wahrgenommenes Stresserleben und Suchtmittelkonsum erstellt. Die Stichprobe der Onlinebefragung umfasst 1281 Studierende. Die Ergebnisse wurden über Microsoft Excel ausgewertet. Ergebnisse: Infolge der Coronapandemie bewegen sich Studierende in ihrem Alltag weniger, müssen aufgrund der gesetzlichen Regelungen ihre Mahlzeitenplanung neu organisieren und sind, z. B. durch veränderte Prüfungsleistungen oder den Verlust des Nebenjobs, einem höheren Stresslevel ausgesetzt. Der Suchtmittelkonsum bleibt dabei nahezu unverändert. Schlussfolgerung: Die Coronapandemie bewirkt sowohl positive als auch negative Veränderungen der gesundheitlichen Verhaltensweisen und Belastungen bei Studierenden. Dennoch sind weitere Untersuchungen erforderlich, um die Auswirkungen der Pandemie auf die Studierenden umfassender in den Blick zu nehmen

Identification of a Disulfide Bridge Essential for Transport Function of the Human Proton-coupled Amino Acid Transporter hPAT1*

The proton-coupled amino acid transporter 1 (PAT1, SLC36A1) mediates the uptake of small neutral amino acids at the apical membrane of intestinal epithelial cells after protein digestion. The transporter is currently under intense investigation, because it is a possible vehicle for oral drug delivery. Structural features of the protein such as the number of transmembrane domains, the substrate binding site, or essential amino acids are still unknown. In the present study we use mutagenesis experiments and biochemical approaches to determine the role of the three putative extracellular cysteine residues on transport function and their possible involvement in the formation of a disulfide bridge. As treatment with the reducing reagent dithiothreitol impaired transport function of hPAT1 wild type protein, substitution of putative extracellular cysteine residues Cys-180, Cys-329, and Cys-473 by alanine or serine was performed. Replacement of the two highly conserved cysteine residues Cys-180 and Cys-329 abolished the transport function of hPAT1 in Xenopus laevis oocytes. Studies of wild type and mutant transporters expressed in human retinal pigment epithelial (HRPE) cells suggested that the binding of the substrate was inhibited in these mutants. Substitution of the third putative extracellular nonconserved cysteine residue Cys-473 did not affect transport function. All mutants were expressed at the plasma membrane. Biotinylation of free sulfhydryl groups using maleimide-PEG11-biotin and SDS-PAGE analysis under reducing and nonreducing conditions provided direct evidence for the existence of an essential disulfide bond between Cys-180 and Cys-329. This disulfide bridge is very likely involved in forming or stabilizing the substrate binding site

Decreased Mortality Over Time During the First Wave in Patients With COVID-19 in Geriatric Care : Data From the Stockholm GeroCovid Study.

OBJECTIVE: To describe temporal changes in treatment, care, and short-term mortality outcomes of geriatric patients during the first wave of the COVID-19 pandemic. DESIGN: Observational study. SETTING AND PARTICIPANTS: Altogether 1785 patients diagnosed with COVID-19 and 6744 hospitalized for non-COVID-19 causes at 7 geriatric clinics in Stockholm from March 6 to July 31, 2020, were included. METHODS: Across admission month, patient vital signs and pharmacological treatment in relationship to risk for in-hospital death were analyzed using the Poisson regression model. Incidence rates (IRs) and incidence rate ratios (IRRs) of death are presented. RESULTS: In patients with COVID-19, the IR of mortality were 27%, 17%, 10%, 8%, and 2% from March to July, respectively, after standardization for demographics and vital signs. Compared with patients admitted in March, the risk of in-hospital death decreased by 29% [IRR 0.71, 95% confidence interval (CI) 0.51-0.99] in April, 61% (0.39, 0.26-0.58) in May, 68% (0.32, 0.19-0.55) in June, and 86% (0.14, 0.03-0.58) in July. The proportion of patients admitted for geriatric care with oxygen saturation <90% decreased from 13% to 1%, which partly explains the improvement of COVID-19 patient survival. In non-COVID-19 patients during the pandemic, mortality rates remained relatively stable (IR 1.3%-2.3%). Compared with non-COVID-19 geriatric patients, the IRR of death declined from 11 times higher (IRR 11.7, 95% CI 6.11-22.3) to 1.6 times (2.61, 0.50-13.7) between March and July in patients with COVID-19. CONCLUSIONS AND IMPLICATIONS: Mortality risk in geriatric patients from the Stockholm region declined over time throughout the first pandemic wave of COVID-19. The improved survival rate over time was only partly related to improvement in saturation status at the admission of the patients hospitalized later throughout the pandemic. Lower incidence during the later months could have led to less severe hospitalized cases driving down mortality

Improved darunavir genotypic mutation score predicting treatment response for patients infected with HIRaben-1 subtype B and non-subtype B receiving a salvage regimen

Objectives: The objective of this studywas to improve the prediction of the impact of HIV-1 protease mutations in different viral subtypes on virological response to darunavir. Methods: Darunavir-containing treatment change episodes (TCEs) in patients previously failing PIs were selected from large European databases. HIV-1 subtype B-infected patients were used as the derivation dataset and HIV- 1 non-B-infected patients were used as the validation dataset. The adjusted association of each mutation with week 8 HIV RNA change from baseline was analysed by linear regression. A prediction model was derived based on best subset least squares estimation with mutational weights corresponding to regression coefficients. Virological outcome prediction accuracy was compared with that from existing genotypic resistance interpretation systems (GISs) (ANRS 2013, Rega 9.1.0 and HIVdb 7.0). Results: TCEs were selected from 681 subtype B-infected and 199 non-B-infected adults. Accompanying drugs were NRTIs in 87%, NNRTIs in 27%and raltegravir ormaraviroc or enfuvirtide in 53%. The predictionmodel included weighted protease mutations, HIV RNA, CD4 and activity of accompanying drugs. The model's association with week 8 HIV RNA change in the subtype B (derivation) set was R2=0.47 [average squared error (ASE)=0.67, P>10-6]; in the non-B (validation) set, ASE was 0.91. Accuracy investigated by means of area under the receiver operating characteristic curves with a binary response (above the threshold value of HIV RNA reduction) showed that our finalmodel outperformed models with existing interpretation systems in both training and validation sets. Conclusions: A model with a new darunavir-weighted mutation score outperformed existing GISs in both B and non-B subtypes in predicting virological response to darunavir

Improved darunavir genotypic mutation score predicting treatment response for patients infected with HIRaben-1 subtype B and non-subtype B receiving a salvage regimen

Objectives: The objective of this studywas to improve the prediction of the impact of HIV-1 protease mutations in different viral subtypes on virological response to darunavir. Methods: Darunavir-containing treatment change episodes (TCEs) in patients previously failing PIs were selected from large European databases. HIV-1 subtype B-infected patients were used as the derivation dataset and HIV- 1 non-B-infected patients were used as the validation dataset. The adjusted association of each mutation with week 8 HIV RNA change from baseline was analysed by linear regression. A prediction model was derived based on best subset least squares estimation with mutational weights corresponding to regression coefficients. Virological outcome prediction accuracy was compared with that from existing genotypic resistance interpretation systems (GISs) (ANRS 2013, Rega 9.1.0 and HIVdb 7.0). Results: TCEs were selected from 681 subtype B-infected and 199 non-B-infected adults. Accompanying drugs were NRTIs in 87%, NNRTIs in 27%and raltegravir ormaraviroc or enfuvirtide in 53%. The predictionmodel included weighted protease mutations, HIV RNA, CD4 and activity of accompanying drugs. The model's association with week 8 HIV RNA change in the subtype B (derivation) set was R2=0.47 [average squared error (ASE)=0.67, P>10-6]; in the non-B (validation) set, ASE was 0.91. Accuracy investigated by means of area under the receiver operating characteristic curves with a binary response (above the threshold value of HIV RNA reduction) showed that our finalmodel outperformed models with existing interpretation systems in both training and validation sets. Conclusions: A model with a new darunavir-weighted mutation score outperformed existing GISs in both B and non-B subtypes in predicting virological response to darunavir

A highly virulent variant of HIV-1 circulating in the Netherlands

We discovered a highly virulent variant of subtype-B HIV-1 in the Netherlands. One hundred nine individuals with this variant had a 0.54 to 0.74 log10 increase (i.e., a ~3.5-fold to 5.5-fold increase) in viral load compared with, and exhibited CD4 cell decline twice as fast as, 6604 individuals with other subtype-B strains. Without treatment, advanced HIV-CD4 cell counts below 350 cells per cubic millimeter, with long-term clinical consequences-is expected to be reached, on average, 9 months after diagnosis for individuals in their thirties with this variant. Age, sex, suspected mode of transmission, and place of birth for the aforementioned 109 individuals were typical for HIV-positive people in the Netherlands, which suggests that the increased virulence is attributable to the viral strain. Genetic sequence analysis suggests that this variant arose in the 1990s from de novo mutation, not recombination, with increased transmissibility and an unfamiliar molecular mechanism of virulence