105 research outputs found
PDBinf: A rules based system for nonstandard amino acid and nucleotide recognition in RDKit
Lightning talk at 2023 RDKit UGM. Describes work on loading PDB files into RDKit using cif templates to assign bond orders
Automated analysis and benchmarking of GCMC simulation programs in application to gas adsorption.
<p>In this work we set out to evaluate the computational performance of several popular Monte Carlo simulation programs, namely Cassandra, DL Monte, Music, Raspa and Towhee, in modelling gas adsorption in crystalline materials. We focus on the reference case of adsorption in IRMOF-1 at 208 K. To critically assess their performance, we first establish some criteria which allow us to make this assessment on a consistent basis. Specifically, the total computational time required for a program to complete a simulation of an adsorption point, consists of the time required for equilibration plus time required to generate a specific number of uncorrelated samples of the property of interest. Our analysis shows that across different programs there is a wide difference in the statistical value of a single MC step, however their computational performance is quite comparable. We further explore the use of energy grids and energy bias techniques, as well as the efficiency of the parallel execution of the simulations. The test cases developed are made openly available as a resource for the community, and can be used for validation and as a template for further studies.</p
Assessment Report of the CNRS (Centre National de la Recherche Scientifique)
The Centre national de la recherche scientifique (CNRS) is a public scientific and technological institution under the supervision of the minister in charge of research. Its main missions, defined by decree, are i) to carry out, alone or with its partners, all research of interest to the advancement of science and the economic, social, and cultural progress of the nation; ii) to contribute to the application and use of the results of this research; iii) to develop scientific information and access to research work and data, by promoting the use of the French language; (iv) to contribute to training in and through research.
The CNRS covers all fields of science. It is organized into ten scientific Institutes. It had a total budget of €3.7 billion in 2021, €2.8 billion (76%) of which came from public subsidies allocated by the French national government, and €0.9 billion (24%) of which came from own-source revenue. The staff represented 31,876 FTE (full-time equivalent), including 23,873 FTE permanent staff and 8,003 non-permanent staff.
The CNRS research activities are organized into more than 1,000 research units (or laboratories), which are almost always shared with other institutions, mainly universities or other national research organizations and “grandes écoles”. They are called “joint research units” (in French “unités mixtes de recherche” or “UMRs”). There are 109,800 persons in CNRS UMRs, i.e. over 40% of the total workforce of the French public research ecosystem; 27% of them are CNRS employees. The CNRS UMRs are spread among more than 80 cities in France.
The international assessment committee was tasked by the High Council for evaluation of research and higher education (Hcéres) with conducting an external assessment of the CNRS for the 2017-2021 period. The committee consisted of scientists and leaders from the worlds of universities, research organizations, technology transfer organizations, and business and industry. The review was concerned with the CNRS in its entirety as well as its interplay with the French research and higher education eco system, but not with a detailed review of the constituent Institutes or of particular scientific disciplines.
The assessment process entailed a review of a self-assessment report that was prepared by CNRS leadership, and a succession of committee meetings prior to a week-long in-person review that occurred May 8-12, 2023. The agenda for the in-person visit included extensive discussions with CNRS leadership, including for each of the 10 constituent Institutes, visits to university sites and UMRs, on-site meetings with junior and senior scientists and support staff, and meetings with CNRS partners universities, corporations and French and European national research organizations. More details on the agenda of the visit are provided at the end of the report. The committee is very grateful for the support it received from Hcéres and the CNRS teams throughout the review
Traffic-related pollution and asthma prevalence in children. Quantification of associations with nitrogen dioxide.
Ambient nitrogen dioxide is a widely available measure of traffic-related air pollution and is inconsistently associated with the prevalence of asthma symptoms in children. The use of this relationship to evaluate the health impact of policies affecting traffic management and traffic emissions is limited by the lack of a concentration-response function based on systematic review and meta-analysis of relevant studies. Using systematic methods, we identified papers containing quantitative estimates for nitrogen dioxide and the 12 month period prevalence of asthma symptoms in children in which the exposure contrast was within-community and dominated by traffic pollution. One estimate was selected from each study according to an a priori algorithm. Odds ratios were standardised to 10 μg/m(3) and summary estimates were obtained using random- and fixed-effects estimates. Eighteen studies were identified. Concentrations of nitrogen dioxide were estimated for the home address (12) and/or school (8) using a range of methods; land use regression (6), study monitors (6), dispersion modelling (4) and interpolation (2). Fourteen studies showed positive associations but only two associations were statistically significant at the 5 % level. There was moderate heterogeneity (I(2) = 32.8 %) and the random-effects estimate for the odds ratio was 1.06 (95 % CI 1.00 to 1.11). There was no evidence of small study bias. Individual studies tended to have only weak positive associations between nitrogen dioxide and asthma prevalence but the summary estimate bordered on statistical significance at the 5 % level. Although small, the potential impact on asthma prevalence could be considerable because of the high level of baseline prevalence in many cities. Whether the association is causal or indicates the effects of a correlated pollutant or other confounders, the estimate obtained by the meta-analysis would be appropriate for estimating impacts of traffic pollution on asthma prevalence
Estimation of changes in air pollution emissions, concentrations and exposure during the COVID-19 outbreak in the UK
Low-dose TNF augments fracture healing in normal and osteoporotic bone by up-regulating the innate immune response
The mechanism by which trauma initiates healing remains unclear. Precise understanding of these events may define interventions for accelerating healing that could be translated to the clinical arena. We previously reported that addition of low-dose recombinant human TNF (rhTNF) at the fracture site augmented fracture repair in a murine tibial fracture model. Here, we show that local rhTNF treatment is only effective when administered within 24h of injury, when neutrophils are the major inflammatory cell infiltrate. Systemic administration of anti-TNF impaired fracture healing. Addition of rhTNF enhanced neutrophil recruitment and promoted recruitment of monocytes through CCL2 production. Conversely, depletion of neutrophils or inhibition of the chemokine receptor CCR2 resulted in significantly impaired fracture healing. Fragility, or osteoporotic, fractures represent a major medical problem as they are associated with permanent disability and premature death. Using a murine model of fragility fractures, we found that local rhTNF treatment improved fracture healing during the early phase of repair. If translated clinically, this promotion of fracture healing would reduce the morbidity and mortality associated with delayed patient mobilization
Identification of Novel Antimalarial Chemotypes via Chemoinformatic Compound Selection Methods for a High-Throughput Screening Program against the Novel Malarial Target, PfNDH2: Increasing Hit Rate via Virtual Screening Methods
Malaria is responsible for approximately 1 million deaths annually; thus, continued efforts to discover new antimalarials are required. A HTS screen was established to identify novel inhibitors of the parasite's mitochondrial enzyme NADH:quinone oxidoreductase (PfNDH2). On the basis of only one known inhibitor of this enzyme, the challenge was to discover novel inhibitors of PfNDH2 with diverse chemical scaffolds. To this end, using a range of ligand-based chemoinformatics methods, ~17000 compounds were selected from a commercial library of ~750000 compounds. Forty-eight compounds were identified with PfNDH2 enzyme inhibition IC(50) values ranging from 100 nM to 40 μM and also displayed exciting whole cell antimalarial activity. These novel inhibitors were identified through sampling 16% of the available chemical space, while only screening 2% of the library. This study confirms the added value of using multiple ligand-based chemoinformatic approaches and has successfully identified novel distinct chemotypes primed for development as new agents against malaria
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