A Data-Driven Dimensionality Reduction Approach to Compare and Classify Lipid Force Fields

Molecular dynamics simulations of all-atom and coarse-grained lipid bilayer models are increasingly used to obtain useful insights for understanding the structural dynamics of these assemblies. In this context, one crucial point concerns the comparison of the performance and accuracy of classical force fields (FFs), which sometimes remains elusive. To date, the assessments performed on different classical potentials are mostly based on the comparison with experimental observables, which typically regard average properties. However, local differences of the structure and dynamics, which are poorly captured by average measurements, can make a difference, but these are nontrivial to catch. Here, we propose an agnostic way to compare different FFs at different resolutions (atomistic, united-atom, and coarse-grained), by means of a high-dimensional similarity metrics built on the framework of Smooth Overlap of Atomic Position (SOAP). We compare and classify a set of 13 FFs, modeling 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) bilayers. Our SOAP kernel-based metrics allows us to compare, discriminate, and correlate different FFs at different model resolutions in an unbiased, high-dimensional way. This also captures differences between FFs in modeling nonaverage events (originating from local transitions), for example, the liquid-to-gel phase transition in dipalmitoylphosphatidylcholine (DPPC) bilayers, for which our metrics allows us to identify nucleation centers for the phase transition, highlighting some intrinsic resolution limitations in implicit versus explicit solvent FFs

Automatic Middle-Out Optimisation of Coarse-Grained Lipid Force Fields

Automatic data-driven approaches are increasingly used to develop accurate molecular models. But the parameters of such automatically-optimised models are typically untransferable. Using a multi-reference approach in combination with an automatic optimisation engine (SwarmCGM), here we show that it is possible to optimise coarse-grained (CG) lipid models that are also transferable, generating optimised lipid force fields. The parameters of the CG lipid models are iteratively and simultaneously optimised against higher-resolution simulations (bottom-up) and experimental data (top-down references). Including different types of lipid bilayers in the training set guarantees the transferability of the optimised force field parameters. Tested against state-of-the-art CG lipid force fields, we demonstrate that SwarmCGM can systematically improve their parameters, enhancing the agreement with the experiments even for lipid types not included in the training set. The approach is general and can be used to improve existing CG lipid force fields, as well as to develop new custom ones.Comment: Paper (Pages 1-16) + Supporting Information (Pages 17-40

Myc, Cdk2 and cellular senescence: Old players, new game

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Magnetic interplay between π-electrons of open-shell porphyrins and d-electrons of their central transition metal ions

Magnetism is typically associated with d- or f-block elements, but can also appear in organic molecules with unpaired π-electrons. This has considerably boosted the interest in such organic materials with large potential for spintronics and quantum applications. While several materials showing either d/f or π-electron magnetism have been synthesized, the combination of both features within the same structure has only scarcely been reported. Open-shell porphyrins (Pors) incorporating d-block transition metal ions represent an ideal platform for the realization of such architectures. Herein, the preparation of a series of open-shell, π-extended Pors that contain magnetically active metal ions (i.e., CuII, CoII, and FeII) through a combination of in-solution and on-surface synthesis is reported. A detailed study of the magnetic interplay between π- and d-electrons in these metalloPors has been performed by scanning probe methods and density functional theory calculations. For the Cu and FePors, ferromagnetically coupled π-electrons are determined to be delocalized over the Por edges. For the CoPor, the authors find a Kondo resonance resulting from the singly occupied CoII dz2 orbital to dominate the magnetic fingerprint. The Fe derivative exhibits the highest magnetization of 3.67 μB (S≈2) and an exchange coupling of 16 meV between the π-electrons and the Fe d-state

Regulation of the Chemokine Receptor CXCR4 by Hypoxia

Cell adaptation to hypoxia (Hyp) requires activation of transcriptional programs that coordinate expression of genes involved in oxygen delivery (via angiogenesis) and metabolic adaptation (via glycolysis). Here, we describe that oxygen availability is a determinant parameter in the setting of chemotactic responsiveness to stromal-derived factor 1 (CXCL12). Low oxygen concentration induces high expression of the CXCL12 receptor, CXC receptor 4 (CXCR4), in different cell types (monocytes, monocyte-derived macrophages, tumor-associated macrophages, endothelial cells, and cancer cells), which is paralleled by increased chemotactic responsiveness to its specific ligand. CXCR4 induction by Hyp is dependent on both activation of the Hyp-inducible factor 1 α and transcript stabilization. In a relay multistep navigation process, the Hyp–Hyp-inducible factor 1 α–CXCR4 pathway may regulate trafficking in and out of hypoxic tissue microenvironments

Colorectal Cancer Stage at Diagnosis Before vs During the COVID-19 Pandemic in Italy

IMPORTANCE Delays in screening programs and the reluctance of patients to seek medical attention because of the outbreak of SARS-CoV-2 could be associated with the risk of more advanced colorectal cancers at diagnosis. OBJECTIVE To evaluate whether the SARS-CoV-2 pandemic was associated with more advanced oncologic stage and change in clinical presentation for patients with colorectal cancer. DESIGN, SETTING, AND PARTICIPANTS This retrospective, multicenter cohort study included all 17 938 adult patients who underwent surgery for colorectal cancer from March 1, 2020, to December 31, 2021 (pandemic period), and from January 1, 2018, to February 29, 2020 (prepandemic period), in 81 participating centers in Italy, including tertiary centers and community hospitals. Follow-up was 30 days from surgery. EXPOSURES Any type of surgical procedure for colorectal cancer, including explorative surgery, palliative procedures, and atypical or segmental resections. MAIN OUTCOMES AND MEASURES The primary outcome was advanced stage of colorectal cancer at diagnosis. Secondary outcomes were distant metastasis, T4 stage, aggressive biology (defined as cancer with at least 1 of the following characteristics: signet ring cells, mucinous tumor, budding, lymphovascular invasion, perineural invasion, and lymphangitis), stenotic lesion, emergency surgery, and palliative surgery. The independent association between the pandemic period and the outcomes was assessed using multivariate random-effects logistic regression, with hospital as the cluster variable. RESULTS A total of 17 938 patients (10 007 men [55.8%]; mean [SD] age, 70.6 [12.2] years) underwent surgery for colorectal cancer: 7796 (43.5%) during the pandemic period and 10 142 (56.5%) during the prepandemic period. Logistic regression indicated that the pandemic period was significantly associated with an increased rate of advanced-stage colorectal cancer (odds ratio [OR], 1.07; 95%CI, 1.01-1.13; P = .03), aggressive biology (OR, 1.32; 95%CI, 1.15-1.53; P < .001), and stenotic lesions (OR, 1.15; 95%CI, 1.01-1.31; P = .03). CONCLUSIONS AND RELEVANCE This cohort study suggests a significant association between the SARS-CoV-2 pandemic and the risk of a more advanced oncologic stage at diagnosis among patients undergoing surgery for colorectal cancer and might indicate a potential reduction of survival for these patients

Force characterization for a submerged velocity cap in unsteady flows

Coastal facilities such as desalination plant or a nuclear power plant need a continuous discharge of salty water to carry out their functions. Hereby an intake structure, such as a velocity cap, can be used to take in water from the sea. These intakes are open seafloor founded constructions mounted at a water depth ranging between 10 and 20 meters. In order to design such an intake cap in an offshore environment, the action of waves and in general of unsteady flows is the most important design load to be accounted for. This thesis has the aim to investigate the nature of the forces and turning moment acting on the structure in presence of waves and to provide tools, in the form of hydrodynamic coefficients, that can be used to compute the design loads. The analysis is based at first on experimental records collected during a previous campaign including force measurements and PIV recordings. The measurements are then used to validate a CFD model in OpenFOAM. Structure-induced turbulence is shown to be fundamental to define the total loads on the structure in the numerical model. The use of a turbulence closure is in fact observed to be needed in order to come to a validation of the CFD model. Even if the flow separation around the cap is not always accurately predicted, the peak of the inline force is estimated by the model with an error of 8%. In the case of the vertical load the error observed reaches up to 15% but part of the mismatch is attributed to a bias in the experimental records. The CFD tool is then used to generate additional test cases on solitary waves and regular waves in order to expand the scope of this research. The hydrodynamic force coefficients are defined fitting both the experimental records and the load estimates of the numerical model by means of the weighted least squares method. The inline force characterization follows the theory of the Morison equation which is shown to provide a good fit in all analyzed cases. Good agreement is found between numerical and experimental results with regards to the estimate of the inertia coefficient while the numerical estimate of the drag coefficient is up to 19 % lower than the experimental estimate. Vertical force and overturning moment signals are originally fitted with the most common formulas used in literature which however produced poor fits to the force and moment signals. New equations are suggested therefore to come to a better characterization of these loads. The best fits for the vertical force are found with an equation that includes the effect of the horizontal drag, the vertical drag and of the vertical inertia, while in the case of the turning moment the best fits are obtained with a combination of horizontal drag, vertical drag, horizontal inertia and vertical inertia.Civil Engineerin

Classifying soft self-assembled materials via unsupervised machine learning of defects

Unlike molecular crystals, soft self-assembled fibres, micelles, vesicles, etc., exhibit a certain order in the arrangement of their constitutive monomers, but also high structural dynamicity and variability. Defects and disordered local domains that continuously form-and-repair in their structures impart to such materials unique adaptive and dynamical properties, which make them, e.g., capable to communicate with each other. However, objective criteria to compare such complex dynamical features and to classify soft supramolecular materials are non-trivial to attain. Here we show a data-driven workflow allowing us to achieve this goal. Building on unsupervised clustering of Smooth Overlap of Atomic Position (SOAP) data obtained from equilibrium molecular dynamics simulations, we can compare a variety of soft supramolecular assemblies via a robust SOAP metric. This provides us with a data-driven "defectometer" to classify different types of supramolecular materials based on the structural dynamics of the ordered/disordered local molecular environments that statistically emerge within them.Comment: 19 pages, 6 figures, and Supporting Information .pdf fil