Fast approximation methods for credit portfolio risk calculations

Credit risk is one of the main risks financial institutions are exposed to. Within the last two decades, simulation-based credit portfolio models became extremely popular and replaced closed-form analytical ones as computers became more powerful. However, especially for non-homogenous and non-granular portfolios, a full simulation of a credit portfolio model is still time consuming, which can be disadvantageous within some use cases like credit pricing or within stress testing situations where results must be available very quickly. For this purpose, we investigate if methods based on artificial intelligence (AI) can be helpful to approximate a credit portfolio model. We compare the performance of AI-based methods within three different use cases with suitable non AI-based regression methods. As a result, we see that AI-based methods can generally capture portfolio characteristics and speed-up calculations but - depending on the specific use case and the availability of training data - they are not necessarily always the best choice. Particularly, considering the time and costs for collecting data and training of the complex algorithms, non-AI-based methods can be as good as or even better than AI-based ones, while requiring less computational effort

HIV-infected T cells are migratory vehicles for viral dissemination

After host entry through mucosal surfaces, HIV-1 disseminates to lymphoid tissues to establish a generalized infection of the immune system. The mechanisms by which this virus spreads among permissive target cells locally during early stages of transmission, and systemically during subsequent dissemination are not known1. In vitro studies suggest that formation of virological synapses (VSs) during stable contacts between infected and uninfected T cells greatly increases the efficiency of viral transfer2. It is unclear, however, if T cell contacts are sufficiently stable in vivo to allow for functional synapse formation under the conditions of perpetual cell motility in epithelial3 and lymphoid tissues4. Here, using multiphoton intravital microscopy (MP-IVM), we examined the dynamic behavior of HIV-infected T cells in lymph nodes (LNs) of humanized mice. We found that most productively infected T cells migrated robustly, resulting in their even distribution throughout the LN cortex. A subset of infected cells formed multinucleated syncytia through HIV envelope (Env)-dependent cell fusion. Both uncoordinated motility of syncytia as well as adhesion to CD4+ LN cells led to the formation of long membrane tethers, increasing cell lengths to up to 10 times that of migrating uninfected T cells. Blocking the egress of migratory T cells from LNs into efferent lymph, and thus interrupting T cell recirculation, limited HIV dissemination and strongly reduced plasma viremia. Thus, we have found that HIV-infected T cells are motile, form syncytia, and establish tethering interactions that may facilitate cell-to-cell transmission through VSs. While their migration in LNs spreads infection locally, T cell recirculation through tissues is important for efficient systemic viral spread, suggesting new molecular targets to antagonize HIV infection

Directional Sensitivity of Cortical Neurons Towards TMS Induced Electric Fields

We derived computationally efficient average response models of different types of cortical neurons, which are subject to external electric fields from Transcranial Magnetic Stimulation. We used 24 reconstructions of pyramidal cells (PC) from layer 2/3, 245 small, nested, and large basket cells from layer 4, and 30 PC from layer 5 with different morphologies for deriving average models. With these models, it is possible to efficiently estimate the stimulation thresholds depending on the underlying electric field distribution in the brain, without having to implement and compute complex neuron compartment models. The stimulation thresholds were determined by exposing the neurons to TMS-induced electric fields with different angles, intensities, pulse waveforms, and field decays along the somato-dendritic axis. The derived average response models were verified by reference simulations using a high-resolution realistic head model containing several million neurons. The relative errors of the estimated thresholdsbetween the average model and the reference model ranged between -3% and 3.7% in 98% of the cases, while the computation time was only a fraction of a second compared to several weeks. Finally, we compared the model behavior to TMS experiments and observed high correspondence to the orientation sensitivity of motor evoked potentials. The derived models were compared to the classical cortical column cosine model and to simplified ball-and-stick neurons. It was shown that both models oversimplify the complex interplay between the electric field and the neurons and do not adequately represent the directional sensitivity of the different cell types The derived models are simple to apply and only require the TMS induced electric field in the brain as input variable. The models and code are available to the general public in open-source repositories for integration into TMS studies to estimate the expected stimulation thresholds for an improved dosing and treatment planning in the future.Peer reviewe

Directional Sensitivity of Cortical Neurons Towards TMS Induced Electric Fields - data and code

Data and code from the publication: Weise et al. (2023), Directional Sensitivity of Cortical Neurons Towards TMS Induced Electric Field

An Autoinhibited State in the Structure of Thermotoga maritima NusG

NusG is a conserved regulatory protein interacting with RNA polymerase (RNAP) and other proteins to form multicomponent complexes that modulate transcription. The crystal structure of Thermotoga maritima NusG (TmNusG) shows a three-domain architecture, comprising well-conserved amino-terminal (NTD) and carboxy-terminal (CTD) domains with an additional, species-specific domain inserted into the NTD. NTD and CTD directly contact each other, occluding a surface of the NTD for binding to RNAP and a surface on the CTD interacting either with transcription termination factor Rho or transcription antitermination factor NusE. NMR spectroscopy confirmed the intramolecular NTD-CTD interaction up to the optimal growth temperature of Thermotoga maritima. The domain interaction involves a dynamic equilibrium between open and closed states and contributes significantly to the overall fold stability of the protein. Wild-type TmNusG and deletion variants could not replace endogenous Escherichia coil NusG, suggesting that the NTD-CTD interaction of TmNusG represents an autoinhibited state

Maturation of lymph node fibroblastic reticular cells from myofibroblastic precursors is critical for antiviral immunity.

The stromal scaffold of the lymph node (LN) paracortex is built by fibroblastic reticular cells (FRCs). Conditional ablation of lymphotoxin-β receptor (LTβR) expression in LN FRCs and their mesenchymal progenitors in developing LNs revealed that LTβR-signaling in these cells was not essential for the formation of LNs. Although T cell zone reticular cells had lost podoplanin expression, they still formed a functional conduit system and showed enhanced expression of myofibroblastic markers. However, essential immune functions of FRCs, including homeostatic chemokine and interleukin-7 expression, were impaired. These changes in T cell zone reticular cell function were associated with increased susceptibility to viral infection. Thus, myofibroblasic FRC precursors are able to generate the basic T cell zone infrastructure, whereas LTβR-dependent maturation of FRCs guarantees full immunocompetence and hence optimal LN function during infection