Deep neural networks as surrogate models for time-efficient manufacturing process optimisation

Manufacturing process optimisation usually amounts to searching optima in high-dimensional parameter spaces. In industrial practice, this search is most often directed by human-subjective expert judgment and trial-and-error experiments. In contrast, high-fidelity simulation models in combination with general-purpose optimisation algorithms, e.g. finite element models and evolutionary algorithms, enable a methodological, virtual process exploration and optimisation. However, reliable process models generally entail significant computation times, which often renders classical, iterative optimisation impracticable. Thus, efficiency is a key factor in optimisation. One option to increase efficiency is surrogate-based optimisation (SBO): SBO seeks to reduce the overall computational load by constructing a numerically inexpensive, data-driven approximation („surrogate“) of the expensive simulation. Traditionally, classical regression techniques are applied for surrogate construction. However, they typically predict a predefined, scalar performance metric only, which limits the amount of usable information gained from simulations. The advent of machine learning (ML) techniques introduces additional options for surrogates: in this work, a deep neural network (DNN) is trained to predict the full strain field instead of a single scalar during textile forming („draping“). Results reveal an improved predictive accuracy as more process-relevant information from the supplied simulations can be extracted. Application of the DNN in an SBO-framework for blank holder optimisation shows improved convergence compared to classical evolutionary algorithms. Thus, DNNs are a promising option for future surrogates in SBO

Enhancement of Tumour-Specific Immune Responses In Vivo by ‘MHC Loading-Enhancer’ (MLE)

BACKGROUND:Class II MHC molecules (MHC II) are cell surface receptors displaying short protein fragments for the surveillance by CD4+ T cells. Antigens therefore have to be loaded onto this receptor in order to induce productive immune responses. On the cell surface, most MHC II molecules are either occupied by ligands or their binding cleft has been blocked by the acquisition of a non-receptive state. Direct loading with antigens, as required during peptide vaccinations, is therefore hindered. PRINCIPAL FINDINGS:Here we show, that the in vivo response of CD4+ T cells can be improved, when the antigens are administered together with 'MHC-loading enhancer' (MLE). MLE are small catalytic compounds able to open up the MHC binding site by triggering ligand-release and stabilizing the receptive state. Their enhancing effect on the immune response was demonstrated here with an antigen from the influenza virus and tumour associated antigens (TAA) derived from the NY-ESO-1 protein. The application of these antigens in combination with adamantane ethanol (AdEtOH), an MLE compound active on human HLA-DR molecules, significantly increased the frequency of antigen-specific CD4+ T cells in mice transgenic for the human MHC II molecule. Notably, the effect was evident only with the MLE-susceptible HLA-DR molecule and not with murine MHC II molecules non-susceptible for the catalytic effect of the MLE. CONCLUSION:MLE can specifically increase the potency of a vaccine by facilitating the efficient transfer of the antigen onto the MHC molecule. They may therefore open a new way to improve vaccination efficacy and tumour-immunotherapy

The Open Anchoring Quest Dataset: Anchored Estimates from 96 Studies on Anchoring Effects

People’s estimates are biased toward previously considered numbers (anchoring). We have aggregated all available data from anchoring studies that included at least two anchors into one large dataset. Data were standardized to comprise one estimate per row, coded according to a wide range of variables, and are available for download and analyses online (https://metaanalyses.shinyapps.io/OpAQ/). Because the dataset includes both original and meta-data it allows for fine-grained analyses (e.g., correlations of estimates for different tasks) but also for meta-analyses (e.g., effect sizes for anchoring effects)

MLE enhances the T cell response against NY-ESO-1 derived epitopes.

<p>(A) Cell surface loading of NY-ESO-1 epitopes. L929 fibroblasts transfected with HLA-DR1 (left panel) or HLA-DR4 (right panel) were incubated for 4 h with titrated amounts of NY-ESO-1 89–101 or NY-ESO-1 119–143, respectively. Loading was performed in the absence (closed circles) or presence (open circles) of 250 µM AdEtOH. Non-transfected L929 cells were used as a negative control (left side). Peptide loading was determined by analyzing the mean fluorescence of the streptavidin-signal gated on a distinct expression of HLA-DR. Background fluorescence was detected in the absence of biotinylated peptide (dashed line). (B) Detection of tumour-specific T cell response <i>in vivo</i>. Groups of HLA-DR1tg (left panel, n = 13) or HLA-DR4tg (right panel, n = 10) mice were s.c. primed with 5 µg of the respective NY-ESO-1 epitopes in IFA/CpG supplemented with or without AdEtOH. 12 days after vaccination, 1×10⁶ Lymph node cells were incubated with titrated amounts of NY-ESO-1 89–101 or NY-ESO-1 119–143, respectively. IFNγ-detection was carried out 48 hrs later using an Elispot assay and summarized data were analyzed using <i>student's t</i> test.</p

Adverse Effect of Early Epileptic Seizures in Patients Receiving Endovascular Therapy for Acute Stroke

The aim of this study was to analyze epileptic seizures and their impact on outcome in patients with stroke treated with endovascular therapy

Vaccination in presence of MLE increases the number of antigen-specific IFNγ-producing T cells.

<p>(A) Determination of IFNγ in an Elispot assay. 12 days after vaccination, 1×10⁶ lymph node cells from mice primed with 3 µg HA 306–318 in IFA/CpG supplemented without (left panel) or with AdEtOH (right panel) were incubated with titrated amounts of HA306–318 peptide on a plate coated with α-IFNγ antibody. Detection was carried out 48 hrs later by determining the spot number in each well. Spots represent single IFNγ+ cells. (B) Statistical analysis of the T cell response. Summarized Elispot data obtained from groups of BALB/c mice (left panel, n = 10) and HLA-DR1tg mice (right panel, n = 9) were analyzed using <i>student's t</i> test.</p

Influence of MLE on the class II MHC peptide-loading of dendritic cells.

<p>(A) Cell surface loading. HLA-DR4 expressing dendritic cells (DC) generated from the bone marrow of HLA-DR4 transgenic mice were incubated for 4 h with medium alone (left panel) or with 5 µg/ml biotinylated HA 306–318 peptide in the absence (middle panel) or presence of 250 µM AdEtOH, the model MLE compound used throughout this study (right panel). Contour plots are shown for DC after staining with anti-HLA-DR antibody (→ MHC expression) and streptavidin (→ peptide load). Mean peptide loading (MFI of streptavidin signal) is indicated. (B) CD4+ T cell response. DC from HLA-DR4tg mice (left panel) and from HLA-DR1tg mice (right panel) were pulsed for 4 h with indicated amounts of HA 306–318 peptide in the absence (open circle) and presence (closed circle) of 250 µM AdEtOH. The cells were used to challenge HA 306–318 specific, HLA-DR4-restricted 8475/94 cells and HLA-DR1-restricted EvHA/X5 T cell hybridoma cells, respectively. Background proliferation was measured in absence of peptide (dashed line).</p

Adverse Effect of Early Epileptic Seizures in Patients Receiving Endovascular Therapy for Acute Stroke

The aim of this study was to analyze epileptic seizures and their impact on outcome in patients with stroke treated with endovascular therapy