Lessons and perspectives for applications of stochastic models in biological and cancer research

The effects of randomness, an unavoidable feature of intracellular environments, are observed at higher hierarchical levels of living matter organization, such as cells, tissues, and organisms. Additionally, the many compounds interacting as a well-orchestrated network of reactions increase the difficulties of assessing these systems using only experiments. This limitation indicates that elucidation of the dynamics of biological systems is a complex task that will benefit from the establishment of principles to help describe, categorize, and predict the behavior of these systems. The theoretical machinery already available, or ones to be discovered to help solve biological problems, might play an important role in these processes. Here, we demonstrate the application of theoretical tools by discussing some biological problems that we have approached mathematically: fluctuations in gene expression and cell proliferation in the context of loss of contact inhibition. We discuss the methods that have been employed to provide the reader with a biologically motivated phenomenological perspective of the use of theoretical methods. Finally, we end this review with a discussion of new research perspectives motivated by our results

Genetic mechanisms of critical illness in COVID-19.

Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice

Lessons and perspectives for applications of stochastic models in biological and cancer research

The effects of randomness, an unavoidable feature of intracellular environments, are observed at higher hierarchical levels of living matter organization, such as cells, tissues, and organisms. Additionally, the many compounds interacting as a well-orchestrated network of reactions increase the difficulties of assessing these systems using only experiments. This limitation indicates that elucidation of the dynamics of biological systems is a complex task that will benefit from the establishment of principles to help describe, categorize, and predict the behavior of these systems. The theoretical machinery already available, or ones to be discovered to help solve biological problems, might play an important role in these processes. Here, we demonstrate the application of theoretical tools by discussing some biological problems that we have approached mathematically: fluctuations in gene expression and cell proliferation in the context of loss of contact inhibition. We discuss the methods that have been employed to provide the reader with a biologically motivated phenomenological perspective of the use of theoretical methods. Finally, we end this review with a discussion of new research perspectives motivated by our results

Limited inhibition of multiple nodes in a driver network blocks metastasis

Metastasis suppression by high-dose, multi-drug targeting is unsuccessful due to network heterogeneity and compensatory network activation. Here, we show that targeting driver network signaling capacity by limited inhibition of core pathways is a more effective anti-metastatic strategy. This principle underlies the action of a physiological metastasis suppressor, Raf Kinase Inhibitory Protein (RKIP), that moderately decreases stress-regulated MAP kinase network activity, reducing output to transcription factors such as pro-metastastic BACH1 and motility-related target genes. We developed a low-dose four-drug mimic that blocks metastatic colonization in mouse breast cancer models and increases survival. Experiments and network flow modeling show limited inhibition of multiple pathways is required to overcome variation in MAPK network topology and suppress signaling output across heterogeneous tumor cells. Restricting inhibition of individual kinases dissipates surplus signal, preventing threshold activation of compensatory kinase networks. This low-dose multi-drug approach to decrease signaling capacity of driver networks represents a transformative, clinically relevant strategy for anti-metastatic treatment

Search for new physics in dijet angular distributions using proton-proton collisions at root s=13 TeV and constraints on dark matter and other models

An Erratum to this article was published on 29 April 2022: https://doi.org/10.1140/epjc/s10052-022-10278-0search is presented for physics beyond the standard model, based on measurements of dijet angular distributions in proton-proton collisions at root s = 13 TeV. The data collected with the CMS detector at the LHC correspond to an integrated luminosity of 35.9 fb(-1). The observed distributions, corrected to particle level, are found to be in agreement with predictions from perturbative quantum chromodynamics that include electroweak corrections. Constraints are placed on models containing quark contact interactions, extra spatial dimensions, quantum black holes, or dark matter, using the detector-level distributions. In a benchmark model where only left-handed quarks participate, contact interactions are excluded at the 95% confidence level up to a scale of 12.8 or 17.5 TeV, for destructive or constructive interference, respectively. The most stringent lower limits to date are set on the ultraviolet cutoff in the Arkani-Hamed-Dimopoulos-Dvali model of extra dimensions. In the Giudice-Rattazzi-Wells convention, the cutoff scale is excluded up to 10.1 TeV. The production of quantum black holes is excluded for masses below 5.9 and 8.2 TeV, depending on the model. For the first time, lower limits between 2.0 and 4.6 TeV are set on the mass of a dark matter mediator for (axial-)vector mediators, for the universal quark coupling g(q) = 1.0.Peer reviewe

Intravenous NPA for the treatment of infarcting myocardium early: InTIME-II, a double-blind comparison on of single-bolus lanoteplase vs accelerated alteplase for the treatment of patients with acute myocardial infarction

Aims to compare the efficacy and safety of lanoteplase, a single-bolus thrombolytic drug derived from alteplase tissue plasminogen activator, with the established accelerated alteplase regimen in patients presenting within 6 h of onset of ST elevation acute myocardial infarction. Methods and Results 15 078 patients were recruited from 855 hospitals worldwide and randomized in a 2:1 ratio to receive either lanoteplase 120 KU. kg-1 as a single intravenous bolus, or up to 100 mg accelerated alteplase given over 90 min. The primary end-point was all-cause mortality at 30 days and the hypothesis was that the two treatments would be equivalent. By 30 days, 6.61% of alteplase-treated patients and 6.75% lanoteplase-treated patients had died (relative risk 1.02). Total stroke occurred in 1.53% alteplase- and 1.87% lanoteplase-treated patients (ns); haemorrhagic stroke rates were 0.64% alteplase and 1.12% lanoteplase (P=0.004). The net clinical deficit of 30-day death or non-fatal disabling stroke was 7.0% and 7.2%, respectively. By 6 months, 8.8% of alteplase-treated patients and 8.7% of lanoteplase-treated patients had died. Conclusion Single-bolus weight-adjusted lanoteplase is an effective thrombolytic agent, equivalent to alteplase in terms of its impact on survival and with a comparable risk-benefit profile. The single-bolus regimen should shorten symptoms to treatment times and be especially convenient for emergency department or out-of-hospital administration. (C) 2000 The European Society of Cardiology

Measurement of pseudorapidity distributions of charged particles in proton-proton collisions at sqrt(s) = 8 TeV by the CMS and TOTEM experiments

Pseudorapidity ( $\eta$ ) distributions of charged particles produced in proton–proton collisions at a centre-of-mass energy of 8 $~\text {TeV}$ are measured in the ranges $|\eta | < 2.2$ and $5.3 < |\eta | < 6.4$ covered by the CMS and TOTEM detectors, respectively. The data correspond to an integrated luminosity of $\mathcal {L} = 45 \mu {\mathrm {b}}^{-1}$ . Measurements are presented for three event categories. The most inclusive category is sensitive to 91–96 % of the total inelastic proton–proton cross section. The other two categories are disjoint subsets of the inclusive sample that are either enhanced or depleted in single diffractive dissociation events. The data are compared to models used to describe high-energy hadronic interactions. None of the models considered provide a consistent description of the measured distributions

Search for high-mass exclusive γγ\gamma\gamma→\to WW and γγ\gamma\gamma→\to ZZ production in proton-proton collisions at s\sqrt{s} = 13 TeV

A search is performed for exclusive high-mass $\gamma\gamma$$\to$ WW and $\gamma\gamma$$\to$ ZZ production in proton-proton collisions using intact forward protons reconstructed in near-beam detectors, with both weak bosons decaying into boosted and merged jets. The analysis is based on a sample of proton-proton collisions collected by the CMS and TOTEM experiments at $\sqrt{s}$ = 13 TeV, corresponding to an integrated luminosity of 100 fb$^{−1}$. No excess above the standard model background prediction is observed, and upper limits are set on the pp → pWWp and pp → pZZp cross sections in a fiducial region defined by the diboson invariant mass m(VV) > 1 TeV (with V = W, Z) and proton fractional momentum loss 0.04 < $ξ$ < 0.20. The results are interpreted as new limits on dimension-6 and dimension-8 anomalous quartic gauge couplings.[graphic not available: see fulltext

Evidence for X(3872) in Pb-Pb Collisions and Studies of its Prompt Production at sNN\sqrt {s_{NN}}=5.02 TeV

The first evidence for X(3872) production in relativistic heavy ion collisions is reported. The $X(3872)$ production is studied in lead-lead (Pb-Pb) collisions at a center-of-mass energy of $\sqrt {s_{NN}}$ 5.02 TeV per nucleon pair, using the decay chain $X(3872) → J/ψ π^+ π^− → μ^+ μ^- π^+ π^−$. The data were recorded with the CMS detector in 2018 and correspond to an integrated luminosity of 1.7 nb$^{-1}$. The measurement is performed in the rapidity and transverse momentum ranges $|y|<$ 1.6 and 15$< p_T <$ 50 GeV/c. The significance of the inclusive $X(3872)$ signal is 4.2 standard deviations. The prompt $X(3872)$ to $ψ2S$ yield ratio is found to be $ρ^{Pb-Pb} =1.08±0.49(stat)±0.52(syst)$, to be compared with typical values of 0.1 for pp collisions. This result provides a unique experimental input to theoretical models of the $X(3872)$ production mechanism, and of the nature of this exotic state