Ventilation of double facades

This paper deals with the development and thetesting of a simulation algorithm for the temperaturebehaviour and the flow characteristics of doublefaçades. It has been developed in order to obtain atool which enables the energy consultant to makequick design decisions without being required to usefairly complicated CFD tools.In order to determine the degree of accuracy of thealgorithm, a double façade has been monitored undercontrolled conditions and the results have beencompared against the predicted values for severaldesign situations. The resulting inaccuracy in somecases can be traced back to how the flow resistanceof various geometries are modelled. This paper deals with the development and thetesting of a simulation algorithm for the temperaturebehaviour and the flow characteristics of doublefaçades. It has been developed in order to obtain atool which enables the energy consultant to makequick design decisions without being required to usefairly complicated CFD tools.In order to determine the degree of accuracy of thealgorithm, a double façade has been monitored undercontrolled conditions and the results have beencompared against the predicted values for severaldesign situations. The resulting inaccuracy in somecases can be traced back to how the flow resistanceof various geometries are modelled

Ermittlung der Zuverlässigkeit von Stahlbetonbauteilen mit mehrdimensionalen physikalisch nichtlinearen FE-Modellen

In dem vorliegenden Beitrag sind die Einsatzmöglichkeiten nichtlinearer Berechnungsverfahren aufgezeigt. Hierbei zeichnen sich mehrdimensionale Modelle auf Grundlage der Methode der Finiten Elemente durch die erzielbare Realitätsnähe aus. Für den Nachweis ausreichender Sicherheit in den Grenzzuständen der Trag- und Gebrauchstauglichkeit ist die Verbindung mit zuverlässigkeitstheoretischen Algorithmen dargestellt Hierbei wird die Grenzzustandsgleichung durch Ansatz eines als offene Schnittstelle konzipierten Algorithmus approximiert. Bei der Verknüpfung von nichtlinearen mechanischen Modellen und Zuverlässigkeitsanalysen wird das rechnerische Sicherheitsniveau wesentlich durch die statistischen Parameter der betrachteten Basisvariablen geprägt. Der Beitrag enthält Angaben für Verteilungsarten und -parameter für Nachweise im Stahlbetonba

Experimental investigation of ventilation efficiency in a dentistry surgical room

As a response to the need to provide an acceptable thermal comfort and air quality in indoor environments, various ventilation performance indicators were developed over the years. These metrics are mainly geared towards air distribution, heat and pollutant removals. Evidence exists of influencing factors on these indicators as centered on ventilation design and operations. Unlike other indoor environments, health care environment requires better performance of ventilation system to prevent an incidence of nosocomial and other hospital acquired illnesses. This study investigates, using in-situ experiments, the ventilation efficiency in a dentistry surgical room. Thermal and hygric parameters were monitored on the air terminal devices and occupied zone over a period of one week covering both occupied and unoccupied hours. The resulting time-series parameters were used to evaluate the room's ventilation effectiveness. Also, the obtained parameters were benchmarked against ASHRAE 170 (2013) and MS1525 (2014) requirements for ventilation in health care environment and building energy efficiency respectively. The results show that the mean daily operative conditions failed to satisfy the provisions of both standards. Regarding effectiveness, the findings reveal that the surgical room ventilation is ineffective with ventilation efficiency values ranging between 0 and 0.5 indicating air distribution short-circuiting. These results suggest further investigations, through numerical simulation, on the effect of this short-circuiting on thermal comfort, infection risk assessments and possible design improvements, an endeavour that forms our next line of research inquiries

Molecular Alterations and Association with Clinical Parameters

Lynch syndrome is caused by germline mutations of DNA mismatch repair (MMR) genes, most frequently MLH1 and MSH2. Recently, MMR-deficient crypt foci (MMR- DCF) have been identified as a novel lesion which occurs at high frequency in the intestinal mucosa from Lynch syndrome mutation carriers, but very rarely progress to cancer. To shed light on molecular alterations and clinical associations of MMR-DCF, we systematically searched the intestinal mucosa from Lynch syndrome patients for MMR-DCF by immunohistochemistry. The identified lesions were characterised for alterations in microsatellite-bearing genes with proven or suspected role in malignant transformation. We demonstrate that the prevalence of MMR-DCF (mean 0.84 MMR-DCF per 1 cm2 mucosa in the colorectum of Lynch syndrome patients) was significantly associated with patients’ age, but not with patients’ gender. No MMR-DCF were detectable in the mucosa of patients with sporadic MSI-H colorectal cancer (n = 12). Microsatellite instability of at least one tested marker was detected in 89% of the MMR-DCF examined, indicating an immediate onset of microsatellite instability after MMR gene inactivation. Coding microsatellite mutations were most frequent in the genes HT001 (ASTE1) with 33%, followed by AIM2 (17%) and BAX (10%). Though MMR deficiency alone appears to be insufficient for malignant transformation, it leads to measurable microsatellite instability even in single MMR-deficient crypts. Our data indicate for the first time that the frequency of MMR-DCF increases with patients’ age. Similar patterns of coding microsatellite instability in MMR-DCF and MMR-deficient cancers suggest that certain combinations of coding microsatellite mutations, including mutations of the HT001, AIM2 and BAX gene, may contribute to the progression of MMR-deficient lesions into MMR-deficient cancers

Organotypic Co-Cultures as a Novel 3D Model for Head and Neck Squamous Cell Carcinoma

Background: Head and neck squamous cell carcinomas (HNSCC) are phenotypically and molecularly heterogeneous and frequently develop therapy resistance. Reliable patient-derived 3D tumor models are urgently needed to further study the complex pathogenesis of these tumors and to overcome treatment failure. Methods: We developed a three-dimensional organotypic co-culture (3D-OTC) model for HNSCC that maintains the architecture and cell composition of the individual tumor. A dermal equivalent (DE), composed of healthy human-derived fibroblasts and viscose fibers, served as a scaffold for the patient sample. DEs were co-cultivated with 13 vital HNSCC explants (non-human papillomavirus (HPV) driven, n = 7; HPV-driven, n = 6). Fractionated irradiation was applied to 5 samples (non-HPV-driven, n = 2; HPV-driven n = 3). To evaluate expression of ki-67, cleaved caspase-3, pan-cytokeratin, p16INK4a, CD45, ∝smooth muscle actin and vimentin over time, immunohistochemistry and immunofluorescence staining were performed Patient checkup data were collected for up to 32 months after first diagnosis. Results: All non-HPV-driven 3D-OTCs encompassed proliferative cancer cells during cultivation for up to 21 days. Proliferation indices of primaries and 3D-OTCs were comparable and consistent over time. Overall, tumor explants displayed heterogeneous growth patterns (i.e., invasive, expansive, silent). Cancer-associated fibroblasts and leukocytes could be detected for up to 21 days. HPV DNA was detectable in both primary and 3D-OTCs (day 14) of HPV-driven tumors. However, p16INK4a expression levels were varying. Morphological alterations and radioresistant tumor cells were detected in 3D-OTC after fractionated irradiation in HPV-driven and non-driven samples. Conclusions: Our 3D-OTC model for HNSCC supports cancer cell survival and proliferation in their original microenvironment. The model enables investigation of invasive cancer growth and might, in the future, serve as a platform to perform sensitivity testing upon treatment to predict therapy response

Immunoadsorption for Treatment of Patients with Suspected Alzheimer Dementia and Agonistic Autoantibodies against Alpha1a-Adrenoceptor—Rationale and Design of the IMAD Pilot Study

Background: agonistic autoantibodies (agAABs) against G protein-coupled receptors (GPCR) have been linked to cardiovascular disease. In dementia patients, GPCR-agAABs against the α1- and ß2-adrenoceptors (α1AR- and ß2AR) were found at a prevalence of 50%. Elimination of agAABs by immunoadsorption (IA) was successfully applied in cardiovascular disease. The IMAD trial (Efficacy of immunoadsorption for treatment of persons with Alzheimer dementia and agonistic autoantibodies against alpha1A-adrenoceptor) investigates whether the removal of α1AR-AABs by a 5-day IA procedure has a positive effect (improvement or non-deterioration) on changes of hemodynamic, cognitive, vascular and metabolic parameters in patients with suspected Alzheimer’s clinical syndrome within a one-year follow-up period. Methods: the IMAD trial is designed as an exploratory monocentric interventional trial corresponding to a proof-of-concept phase-IIa study. If cognition capacity of eligible patients scores 19–26 in the Mini Mental State Examination (MMSE), patients are tested for the presence of agAABs by an enzyme-linked immunosorbent assay (ELISA)-based method, followed by a bioassay-based confirmation test, further screening and treatment with IA and intravenous immunoglobulin G (IgG) replacement. We aim to include 15 patients with IA/IgG and to complete follow-up data from at least 12 patients. The primary outcome parameter of the study is uncorrected mean cerebral perfusion measured in mL/min/100 gr of brain tissue determined by magnetic resonance imaging with arterial spin labeling after 12 months. Conclusion: IMAD is an important pilot study that will analyze whether the removal of α1AR-agAABs by immunoadsorption in α1AR-agAAB-positive patients with suspected Alzheimer’s clinical syndrome may slow the progression of dementia and/or may improve vascular functional parameters

Skin Cancer Classification Using Convolutional Neural Networks: Systematic Review

Background: State-of-the-art classifiers based on convolutional neural networks (CNNs) were shown to classify images of skin cancer on par with dermatologists and could enable lifesaving and fast diagnoses, even outside the hospital via installation of apps on mobile devices. To our knowledge, at present there is no review of the current work in this research area. Objective: This study presents the first systematic review of the state-of-the-art research on classifying skin lesions with CNNs. We limit our review to skin lesion classifiers. In particular, methods that apply a CNN only for segmentation or for the classification of dermoscopic patterns are not considered here. Furthermore, this study discusses why the comparability of the presented procedures is very difficult and which challenges must be addressed in the future. Methods: We searched the Google Scholar, PubMed, Medline, ScienceDirect, and Web of Science databases for systematic reviews and original research articles published in English. Only papers that reported sufficient scientific proceedings are included in this review. Results: We found 13 papers that classified skin lesions using CNNs. In principle, classification methods can be differentiated according to three principles. Approaches that use a CNN already trained by means of another large dataset and then optimize its parameters to the classification of skin lesions are the most common ones used and they display the best performance with the currently available limited datasets. Conclusions: CNNs display a high performance as state-of-the-art skin lesion classifiers. Unfortunately, it is difficult to compare different classification methods because some approaches use nonpublic datasets for training and/or testing, thereby making reproducibility difficult. Future publications should use publicly available benchmarks and fully disclose methods used for training to allow comparability

Spatial transcriptome analysis reveals Notch pathway-associated prognostic markers in IDH1 wild-type glioblastoma involving the subventricular zone

Background: The spatial relationship of glioblastoma (GBM) to the subventricular zone (SVZ) is associated with inferior patient survival. However, the underlying molecular phenotype is largely unknown. We interrogated an SVZ-dependent transcriptome and potential location-specific prognostic markers. Methods: mRNA microarray data of a discovery set (n = 36 GBMs) were analyzed for SVZ-dependent gene expression and process networks using the MetaCore™ workflow. Differential gene expression was confirmed by qPCR in a validation set of 142 IDH1 wild-type GBMs that was also used for survival analysis. Results: Microarray analysis revealed a transcriptome distinctive of SVZ+ GBM that was enriched for genes associated with Notch signaling. No overlap was found to The Cancer Genome Atlas’s molecular subtypes. Independent validation of SVZ-dependent expression confirmed four genes with simultaneous prognostic impact: overexpression of HES4 (p = 0.034; HR 1.55) and DLL3 (p = 0.017; HR 1.61) predicted inferior, and overexpression of NTRK2 (p = 0.049; HR 0.66) and PIR (p = 0.025; HR 0.62) superior overall survival (OS). Additionally, overexpression of DLL3 was predictive of shorter progression-free survival (PFS) (p = 0.043; HR 1.64). Multivariate analysis revealed overexpression of HES4 to be independently associated with inferior OS (p = 0.033; HR 2.03), and overexpression of DLL3 with inferior PFS (p = 0.046; HR 1.65). Conclusions: We identified four genes with SVZ-dependent expression and prognostic significance, among those HES4 and DLL3 as part of Notch signaling, suggesting further evaluation of location-tailored targeted therapies