Identifying therapeutic weak spots in cancer using network analysis

Mathematical network analysis has been proven to be a useful and powerful tool for biological networks including networks of protein interactions, gene similarity and metabolic interactions. Here I use network analysis to model human cancer and predict which genes or reactions are essential for cancer to allow it to grow or recovery from stress. A general assumption for biological networks is that the centrality of a node is in some way reflective of its biological importance. So I evaluated a wide range of weighted and unweighted node centralities and measures derived from centralities to predict reaction essentiality in metabolic networks. The metabolic networks are Mass Flow Graphs (MFGs), based on the Recon2 reconstruction of human metabolism and constrains on reaction fluxes from the PRIME algorithm. The edge weights in the networks are computed from Flux Balance Analysis (FBA) results in a selection of human cancer cell lines from NCI-60. I could not detect a direct connection between node essentiality and any centrality, but there is a correlation between the overall change of the centrality distribution in the inhibited condition compared to wild type and the inhibited reaction essentiality. With this I have found a promising network measure that can be used to predict possible drug targets. With MFGs a wide range of cellular conditions can be modelled, but only when we know what the cellular objective for FBA is. When cancer cells are put under stress through treatment, they adapt their metabolism to react to the stress. This dynamic process with fluctuating gene expression is difficult to capture in a metabolic network. A better way to analyse the recovery process is to extract which genes are active during which phase. I evaluated seven time points of gene expression data for multiple myeloma cells that were treated with a proteasome inhibitor (PI), which disrupts the protein recycling process. From the pairwise gene expression similarity I constructed network to cluster the genes into groups that are active at the same time. The networks were clustered with a random walk algorithm called Markov Stability and evaluated with gene enrichment analysis. From the resulting clusters, collaborators were able to extract tRNAs that activate a protein called GCN2 that is essential for recovery. Followup experiments showed that a combination of PI and GCN2 is lethal for multiple myeloma as well as a few other cancer cells.Open Acces

A small viral potassium ion channel with an inherent inward rectification

Some algal viruses have coding sequences for proteins with structural and functional characteristics of pore modules of complex K+ channels. Here we exploit the structural diversity among these channel orthologs to discover new basic principles of structure/function correlates in K+ channels. The analysis of three similar K+ channels with ≤ 86 amino acids (AA) shows that one channel (Kmpv1) generates an ohmic conductance in HEK293 cells while the other two (KmpvSP1, KmpvPL1) exhibit typical features of canonical Kir channels. Like Kir channels, the rectification of the viral channels is a function of the K+ driving force. Reconstitution of KmpvSP1 and KmpvPL1 in planar lipid bilayers showed rapid channel fluctuations only at voltages negative of the K+ reversal voltage. This rectification was maintained in KCl buffer with 1 mM EDTA, which excludes blocking cations as the source of rectification. This means that rectification of the viral channels must be an inherent property of the channel. The structural basis for rectification was investigated by a chimera between rectifying and non-rectifying channels as well as point mutations making the rectifier similar to the ohmic conducting channel. The results of these experiments exclude the pore with pore helix and selectivity filter as playing a role in rectification. The insensitivity of the rectifier to point mutations suggests that tertiary or quaternary structural interactions between the transmembrane domains are responsible for this type of gating

PEDIA: prioritization of exome data by image analysis.

PURPOSE: Phenotype information is crucial for the interpretation of genomic variants. So far it has only been accessible for bioinformatics workflows after encoding into clinical terms by expert dysmorphologists. METHODS: Here, we introduce an approach driven by artificial intelligence that uses portrait photographs for the interpretation of clinical exome data. We measured the value added by computer-assisted image analysis to the diagnostic yield on a cohort consisting of 679 individuals with 105 different monogenic disorders. For each case in the cohort we compiled frontal photos, clinical features, and the disease-causing variants, and simulated multiple exomes of different ethnic backgrounds. RESULTS: The additional use of similarity scores from computer-assisted analysis of frontal photos improved the top 1 accuracy rate by more than 20-89% and the top 10 accuracy rate by more than 5-99% for the disease-causing gene. CONCLUSION: Image analysis by deep-learning algorithms can be used to quantify the phenotypic similarity (PP4 criterion of the American College of Medical Genetics and Genomics guidelines) and to advance the performance of bioinformatics pipelines for exome analysis

Toward the integrated marine debris observing system

Plastics and other artificial materials pose new risks to the health of the ocean. Anthropogenic debris travels across large distances and is ubiquitous in the water and on shorelines, yet, observations of its sources, composition, pathways, and distributions in the ocean are very sparse and inaccurate. Total amounts of plastics and other man-made debris in the ocean and on the shore, temporal trends in these amounts under exponentially increasing production, as well as degradation processes, vertical fluxes, and time scales are largely unknown. Present ocean circulation models are not able to accurately simulate drift of debris because of its complex hydrodynamics. In this paper we discuss the structure of the future integrated marine debris observing system (IMDOS) that is required to provide long-term monitoring of the state of this anthropogenic pollution and support operational activities to mitigate impacts on the ecosystem and on the safety of maritime activity. The proposed observing system integrates remote sensing and in situ observations. Also, models are used to optimize the design of the system and, in turn, they will be gradually improved using the products of the system. Remote sensing technologies will provide spatially coherent coverage and consistent surveying time series at local to global scale. Optical sensors, including high-resolution imaging, multi- and hyperspectral, fluorescence, and Raman technologies, as well as SAR will be used to measure different types of debris. They will be implemented in a variety of platforms, from hand-held tools to ship-, buoy-, aircraft-, and satellite-based sensors. A network of in situ observations, including reports from volunteers, citizen scientists and ships of opportunity, will be developed to provide data for calibration/validation of remote sensors and to monitor the spread of plastic pollution and other marine debris. IMDOS will interact with other observing systems monitoring physical, chemical, and biological processes in the ocean and on shorelines as well as the state of the ecosystem, maritime activities and safety, drift of sea ice, etc. The synthesized data will support innovative multi-disciplinary research and serve a diverse community of users

Search for new particles in events with energetic jets and large missing transverse momentum in proton-proton collisions at root s=13 TeV

A search is presented for new particles produced at the LHC in proton-proton collisions at root s = 13 TeV, using events with energetic jets and large missing transverse momentum. The analysis is based on a data sample corresponding to an integrated luminosity of 101 fb(-1), collected in 2017-2018 with the CMS detector. Machine learning techniques are used to define separate categories for events with narrow jets from initial-state radiation and events with large-radius jets consistent with a hadronic decay of a W or Z boson. A statistical combination is made with an earlier search based on a data sample of 36 fb(-1), collected in 2016. No significant excess of events is observed with respect to the standard model background expectation determined from control samples in data. The results are interpreted in terms of limits on the branching fraction of an invisible decay of the Higgs boson, as well as constraints on simplified models of dark matter, on first-generation scalar leptoquarks decaying to quarks and neutrinos, and on models with large extra dimensions. Several of the new limits, specifically for spin-1 dark matter mediators, pseudoscalar mediators, colored mediators, and leptoquarks, are the most restrictive to date.Peer reviewe

MUSiC : a model-unspecific search for new physics in proton-proton collisions at root s=13TeV

Results of the Model Unspecific Search in CMS (MUSiC), using proton-proton collision data recorded at the LHC at a centre-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 35.9 fb(-1), are presented. The MUSiC analysis searches for anomalies that could be signatures of physics beyond the standard model. The analysis is based on the comparison of observed data with the standard model prediction, as determined from simulation, in several hundred final states and multiple kinematic distributions. Events containing at least one electron or muon are classified based on their final state topology, and an automated search algorithm surveys the observed data for deviations from the prediction. The sensitivity of the search is validated using multiple methods. No significant deviations from the predictions have been observed. For a wide range of final state topologies, agreement is found between the data and the standard model simulation. This analysis complements dedicated search analyses by significantly expanding the range of final states covered using a model independent approach with the largest data set to date to probe phase space regions beyond the reach of previous general searches.Peer reviewe

Measurement of prompt open-charm production cross sections in proton-proton collisions at root s=13 TeV

The production cross sections for prompt open-charm mesons in proton-proton collisions at a center-of-mass energy of 13TeV are reported. The measurement is performed using a data sample collected by the CMS experiment corresponding to an integrated luminosity of 29 nb(-1). The differential production cross sections of the D*(+/-), D-+/-, and D-0 ((D) over bar (0)) mesons are presented in ranges of transverse momentum and pseudorapidity 4 < p(T) < 100 GeV and vertical bar eta vertical bar < 2.1, respectively. The results are compared to several theoretical calculations and to previous measurements.Peer reviewe

Measurement of the azimuthal anisotropy of Y(1S) and Y(2S) mesons in PbPb collisions at root s(NN)=5.02 TeV

The second-order Fourier coefficients (v(2)) characterizing the azimuthal distributions of Y(1S) and Y(2S) mesons produced in PbPb collisions at root s(NN) = 5.02 TeV are studied. The Y mesons are reconstructed in their dimuon decay channel, as measured by the CMS detector. The collected data set corresponds to an integrated luminosity of 1.7 nb(-1). The scalar product method is used to extract the v2 coefficients of the azimuthal distributions. Results are reported for the rapidity range vertical bar y vertical bar < 2.4, in the transverse momentum interval 0 < pT < 50 GeV/c, and in three centrality ranges of 10-30%, 30-50% and 50-90%. In contrast to the J/psi mesons, the measured v(2) values for the Y mesons are found to be consistent with zero. (C) 2021 The Author(s). Published by Elsevier B.V.Peer reviewe

Combined searches for the production of supersymmetric top quark partners in proton-proton collisions at root s=13 TeV

A combination of searches for top squark pair production using proton-proton collision data at a center-of-mass energy of 13 TeV at the CERN LHC, corresponding to an integrated luminosity of 137 fb(-1) collected by the CMS experiment, is presented. Signatures with at least 2 jets and large missing transverse momentum are categorized into events with 0, 1, or 2 leptons. New results for regions of parameter space where the kinematical properties of top squark pair production and top quark pair production are very similar are presented. Depending on themodel, the combined result excludes a top squarkmass up to 1325 GeV for amassless neutralino, and a neutralinomass up to 700 GeV for a top squarkmass of 1150 GeV. Top squarks with masses from 145 to 295 GeV, for neutralino masses from 0 to 100 GeV, with a mass difference between the top squark and the neutralino in a window of 30 GeV around the mass of the top quark, are excluded for the first time with CMS data. The results of theses searches are also interpreted in an alternative signal model of dark matter production via a spin-0 mediator in association with a top quark pair. Upper limits are set on the cross section for mediator particle masses of up to 420 GeV

Observation of tW production in the single-lepton channel in pp collisions at root s=13 TeV

A measurement of the cross section of the associated production of a single top quark and a W boson in final states with a muon or electron and jets in proton-proton collisions at root s = 13 TeV is presented. The data correspond to an integrated luminosity of 36 fb(-1) collected with the CMS detector at the CERN LHC in 2016. A boosted decision tree is used to separate the tW signal from the dominant t (t) over bar background, whilst the subleading W+jets and multijet backgrounds are constrained using data-based estimates. This result is the first observation of the tW process in final states containing a muon or electron and jets, with a significance exceeding 5 standard deviations. The cross section is determined to be 89 +/- 4 (stat) +/- 12 (syst) pb, consistent with the standard model.Peer reviewe