Data-driven learning how oncogenic gene expression locally alters heterocellular networks

Developing drugs increasingly relies on mechanistic modeling and simulation. Models that capture causal relations among genetic drivers of oncogenesis, functional plasticity, and host immunity complement wet experiments. Unfortunately, formulating such mechanistic cell-level models currently relies on hand curation, which can bias how data is interpreted or the priority of drug targets. In modeling molecular-level networks, rules and algorithms are employed to limit a priori biases in formulating mechanistic models. Here we combine digital cytometry with Bayesian network inference to generate causal models of cell-level networks linking an increase in gene expression associated with oncogenesis with alterations in stromal and immune cell subsets from bulk transcriptomic datasets. We predict how increased Cell Communication Network factor 4, a secreted matricellular protein, alters the tumor microenvironment using data from patients diagnosed with breast cancer and melanoma. Predictions are then tested using two immunocompetent mouse models for melanoma, which provide consistent experimental results

Venerische Krankheiten: Redigirt von Prof. Neisser nd Dr. Schäffer in Breslau

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VASCo: computation and visualization of annotated protein surface contacts

<p>Abstract</p> <p>Background</p> <p>Structural data from crystallographic analyses contain a vast amount of information on protein-protein contacts. Knowledge on protein-protein interactions is essential for understanding many processes in living cells. The methods to investigate these interactions range from genetics to biophysics, crystallography, bioinformatics and computer modeling. Also crystal contact information can be useful to understand biologically relevant protein oligomerisation as they rely in principle on the same physico-chemical interaction forces. Visualization of crystal and biological contact data including different surface properties can help to analyse protein-protein interactions.</p> <p>Results</p> <p>VASCo is a program package for the calculation of protein surface properties and the visualization of annotated surfaces. Special emphasis is laid on protein-protein interactions, which are calculated based on surface point distances. The same approach is used to compare surfaces of two aligned molecules. Molecular properties such as electrostatic potential or hydrophobicity are mapped onto these surface points. Molecular surfaces and the corresponding properties are calculated using well established programs integrated into the package, as well as using custom developed programs. The modular package can easily be extended to include new properties for annotation. The output of the program is most conveniently displayed in PyMOL using a custom-made plug-in.</p> <p>Conclusion</p> <p>VASCo supplements other available protein contact visualisation tools and provides additional information on biological interactions as well as on crystal contacts. The tool provides a unique feature to compare surfaces of two aligned molecules based on point distances and thereby facilitates the visualization and analysis of surface differences.</p

DMTs and Covid-19 severity in MS: a pooled analysis from Italy and France

We evaluated the effect of DMTs on Covid-19 severity in patients with MS, with a pooled-analysis of two large cohorts from Italy and France. The association of baseline characteristics and DMTs with Covid-19 severity was assessed by multivariate ordinal-logistic models and pooled by a fixed-effect meta-analysis. 1066 patients with MS from Italy and 721 from France were included. In the multivariate model, anti-CD20 therapies were significantly associated (OR&nbsp;=&nbsp;2.05, 95%CI&nbsp;=&nbsp;1.39–3.02, p&nbsp;&lt;&nbsp;0.001) with Covid-19 severity, whereas interferon indicated a decreased risk (OR&nbsp;=&nbsp;0.42, 95%CI&nbsp;=&nbsp;0.18–0.99, p&nbsp;=&nbsp;0.047). This pooled-analysis confirms an increased risk of severe Covid-19 in patients on anti-CD20 therapies and supports the protective role of interferon

Quantifying system disturbance and recovery from historical mining-derived metal contamination at Brotherswater, northwest England

The final publication is available at Springer via https://doi.org/10.1007/s10933-016-9907-1Metal ore extraction in historical times has left a legacy of severe contamination in aquatic ecosystems around the world. In the UK, there are ongoing nationwide surveys of present-day pollution discharged from abandoned mines but few assessments of the magnitude of contamination and impacts that arose during historical metal mining have been made. We report one of the first multi-centennial records of lead (Pb), zinc (Zn) and copper (Cu) fluxes into a lake (Brotherswater, northwest England) from point-sources in its catchment (Hartsop Hall Mine and Hogget Gill processing plant) and calculate basin-scale inventories of those metals. The pre-mining baseline for metal contamination has been established using sediment cores spanning the past 1,500 years and contemporary material obtained through sediment trapping. These data enabled the impact of 250 years of local, small-scale mining (1696 – 1942) to be quantified and an assessment of the trajectory towards system recovery to be made. The geochemical stratigraphy displayed in twelve sediment cores show strong correspondence to the documented history of metal mining and processing in the catchment. The initial onset in 1696 was detected, peak Pb concentrations (>10,000 µg g-1) and flux (39.4 g m-2 y-1) corresponded to the most intensive mining episode (1863-1871) and 20th century technological enhancements were reflected as a more muted sedimentary imprint. After careful evaluation, we used these markers to augment a Bayesian age-depth model of the independent geochronology obtained using radioisotope dating (14C, 210Pb, 137Cs and 241Am). Total inventories of Pb, Zn and Cu for the lake basin during the period of active mining were 15,415 kg, 5,897 kg and 363 kg, respectively. The post-mining trajectories for Pb and Zn project a return to pre-mining levels within 54-128 years for Pb and 75-187 years for Zn, although future remobilisation of metal-enriched catchment soils and floodplain sediments could perturb this recovery. We present a transferable paleolimnological approach that highlights flux-based assessments are vital to accurately establish the baseline, impact and trajectory of mining-derived contamination for a lake catchment