Machine Learning of Free Energies in Chemical Compound Space Using Ensemble Representations: Reaching Experimental Uncertainty for Solvation

Free energies govern the behavior of soft and liquid matter, and improving their predictions could have a large impact on the development of drugs, electrolytes or homogeneous catalysts. Unfortunately, it is challenging to devise an accurate description of effects governing solvation such as hydrogen-bonding, van der Waals interactions, or conformational sampling. We present a Free energy Machine Learning (FML) model applicable throughout chemical compound space and based on a representation that employs Boltzmann averages to account for an approximated sampling of configurational space. Using the FreeSolv database, FML's out-of-sample prediction errors of experimental hydration free energies decay systematically with training set size, and experimental uncertainty (0.6 kcal/mol) is reached after training on 490 molecules (80\% of FreeSolv). Corresponding FML model errors are also on par with state-of-the art physics based approaches. To generate the input representation for a new query compound, FML requires approximate and short molecular dynamics runs. We showcase its usefulness through analysis of FML solvation free energies for 116k organic molecules (all force-field compatible molecules in QM9 database) identifying the most and least solvated systems, and rediscovering quasi-linear structure property relationships in terms of simple descriptors such as hydrogen-bond donors, number of NH or OH groups, number of oxygen atoms in hydrocarbons, and number of heavy atoms. FML's accuracy is maximal when the temperature used for the molecular dynamics simulation to generate averaged input representation samples in training is the same as for the query compounds. The sampling time for the representation converges rapidly with respect to the prediction error

Insight in modulation of inflammation in response to diclofenac intervention: a human intervention study

Background. Chronic systemic low-grade inflammation in obese subjects is associated with health complications including cardiovascular diseases, insulin resistance and diabetes. Reducing inflammatory responses may reduce these risks. However, available markers of inflammatory status inadequately describe the complexity of metabolic responses to mild anti-inflammatory therapy. Methods. To address this limitation, we used an integrative omics approach to characterize modulation of inflammation in overweight men during an intervention with the non-steroidal anti-inflammatory drug diclofenac. Measured parameters included 80 plasma proteins, >300 plasma metabolites (lipids, free fatty acids, oxylipids and polar compounds) and an array of peripheral blood mononuclear cells (PBMC) gene expression products. These measures were submitted to multivariate and correlation analysis and were used for construction of biological response networks. Results. A panel of genes, proteins and metabolites, including PGE2 and TNF-alpha, were identified that describe a diclofenac-response network (68 genes in PBMC, 1 plasma protein and 4 plasma metabolites). Novel candidate markers of inflammatory modulation included PBMC expression of annexin A1 and caspase 8, and the arachidonic acid metabolite 5,6-DHET. Conclusion. In this study the integrated analysis of a wide range of parameters allowed the development of a network of markers responding to inflammatory modulation, thereby providing insight into the complex process of inflammation and ways to assess changes in inflammatory status associated with obesity. Trial registration. The study is registered as NCT00221052 in clinicaltrials.gov database. © 2010 van Erk et al; licensee BioMed Central Ltd

Regulation of the phytoplankton heme b iron pool during the North Atlantic spring bloom

CITATION: Louropoulou, E., et al. 2019. Regulation of the phytoplankton heme b iron pool during the North Atlantic spring bloom. Frontiers in Microbiology, 10:1566, doi:10.3389/fmicb.2019.01566.The original publication is available at https://www.frontiersin.orgHeme b is an iron-containing co-factor in hemoproteins. Heme b concentrations are low (0.7 μm) from the North Atlantic Ocean (GEOVIDE cruise – GEOTRACES section GA01), which spanned several biogeochemical regimes. We examined the relationship between heme b abundance and the microbial community composition, and its utility for mapping iron limited phytoplankton. Heme b concentrations ranged from 0.16 to 5.1 pmol L⁻² (median = 2.0 pmol L⁻², n = 62) in the surface mixed layer (SML) along the cruise track, driven mainly by variability in biomass. However, in the Irminger Basin, the lowest heme b levels (SML: median = 0.53 pmol L⁻², n = 12) were observed, whilst the biomass was highest (particulate organic carbon, median = 14.2 μmol L⁻², n = 25; chlorophyll a: median = 2.0 nmol L⁻², n = 23) pointing to regulatory mechanisms of the heme b pool for growth conservation. Dissolved iron (DFe) was not depleted (SML: median = 0.38 nmol L⁻², n = 11) in the Irminger Basin, but large diatoms (Rhizosolenia sp.) dominated. Hence, heme b depletion and regulation is likely to occur during bloom progression when phytoplankton class-dependent absolute iron requirements exceed the available ambient concentration of DFe. Furthermore, high heme b concentrations found in the Iceland Basin and Labrador Sea (median = 3.4 pmol L⁻², n = 20), despite having similar DFe concentrations to the Irminger Basin, were attributed to an earlier growth phase of the extant phytoplankton populations. Thus, heme b provides a snapshot of the cellular activity in situ and could both be used as indicator of iron limitation and contribute to understanding phytoplankton adaptation mechanisms to changing iron supplies.https://www.frontiersin.org/articles/10.3389/fmicb.2019.01566/fullPublisher's versio

Inverse correlation between PDGFC expression and lymphocyte infiltration in human papillary thyroid carcinomas

<p>Abstract</p> <p>Background</p> <p>Members of the PDGF family have been suggested as potential biomarkers for papillary thyroid carcinomas (PTC). However, it is known that both expression and stimulatory effect of PDGF ligands can be affected by inflammatory cytokines. We have performed a microarray study in a collection of PTCs, of which about half the biopsies contained tumour-infiltrating lymphocytes or thyroiditis. To investigate the expression level of PDGF ligands and receptors in PTC we measured the relative mRNA expression of all members of the PDGF family by qRT-PCR in 10 classical PTC, eight clinically aggressive PTC, and five non-neoplastic thyroid specimens, and integrated qRT-PCR data with microarray data to enable us to link PDGF-associated gene expression profiles into networks based on recognized interactions. Finally, we investigated potential influence on PDGF mRNA levels by the presence of tumour-infiltrating lymphocytes.</p> <p>Methods</p> <p>qRT-PCR was performed on <it>PDGFA</it>, <it>PDGFB</it>, <it>PDGFC</it>, <it>PDGFD</it>, <it>PDGFRA PDGFRB </it>and a selection of lymphocyte specific mRNA transcripts. Semiquantitative assessment of tumour-infiltrating lymphocytes was performed on the adjacent part of the biopsy used for RNA extraction for all biopsies, while direct quantitation by qRT-PCR of lymphocyte-specific mRNA transcripts were performed on RNA also subjected to expression analysis. Relative expression values of PDGF family members were combined with a cDNA microarray dataset and analyzed based on clinical findings and PDGF expression patterns. Ingenuity Pathway Analysis (IPA) was used to elucidate potential molecular interactions and networks.</p> <p>Results</p> <p>PDGF family members were differentially regulated at the mRNA level in PTC as compared to normal thyroid specimens. Expression of <it>PDGFA </it>(p = 0.003), <it>PDGFB </it>(p = 0.01) and <it>PDGFC </it>(p = 0.006) were significantly up-regulated in PTCs compared to non-neoplastic thyroid tissue. In addition, expression of <it>PDGFC </it>was significantly up-regulated in classical PTCs as compared to clinically aggressive PTCs (p = 0.006), and <it>PDGFRB </it>were significantly up-regulated in clinically aggressive PTCs (p = 0.01) as compared to non-neoplastic tissue. Semiquantitative assessment of lymphocytes correlated well with quantitation of lymphocyte-specific gene expression. Further more, by combining TaqMan and microarray data we found a strong inverse correlation between <it>PDGFC </it>expression and the expression of lymphocyte specific mRNAs.</p> <p>Conclusion</p> <p>At the mRNA level, several members of the PDGF family are differentially expressed in PTCs as compared to normal thyroid tissue. Of these, only the <it>PDGFC </it>mRNA expression level initially seemed to distinguish classical PTCs from the more aggressive PTCs. However, further investigation showed that <it>PDGFC </it>expression level correlated inversely to the expression of several lymphocyte specific genes, and to the presence of lymphocytes in the biopsies. Thus, we find that <it>PDGFC </it>mRNA expression were down-regulated in biopsies containing infiltrated lymphocytes or thyroiditis. No other PDGF family member could be linked to lymphocyte specific gene expression in our collection of PTCs biopsies.</p

High-resolution analysis of HLA class I alterations in colorectal cancer

BACKGROUND: Previous studies indicate that alterations in Human Leukocyte Antigen (HLA) class I expression are frequent in colorectal tumors. This would suggest serious limitations for immunotherapy-based strategies involving T-cell recognition. Distinct patterns of HLA surface expression might conceal different immune escape mechanisms employed by the tumors and are worth further study. METHOD: We applied four-color multiparameter flow cytometry (FCM), using a large panel of alloantigen-specific anti-HLA-A and -B monoclonal antibodies, to study membranous expression of individual HLA alleles in freshly isolated colorectal cancer cell suspensions from 21 patients. RESULTS: Alterations in HLA class I phenotype were observed in 8 (38%) of the 21 tumors and comprised loss of a single A or B alleles in 4 cases, and loss of all four A and B alleles in the other 4 cases. Seven of these 8 tumors were located on the right side of the colon, and those showing loss of both HLA-A and -B membranous expression were all of the MSI-H phenotype. CONCLUSION: FCM allows the discrimination of complex phenotypes related to the expression of HLA class I. The different patterns of HLA class I expression might underlie different tumor behavior and influence the success rate of immunotherapy

Good practice guidelines for long-term ecoacoustic monitoring in the UK: with a particular focus on terrestrial biodiversity at the human-audible frequency range

Passive acoustic monitoring has great potential as a cost-effective method for long-term biodiversity monitoring. However, to maximise its efficacy, standardisation of survey protocols is necessary to ensure data are comparable and permit reliable inferences. The aim of these guidelines is to outline a basic long-term acoustic monitoring protocol that can be adapted to suit a range of projects according to specific objectives and size