Water uptake by biomass burning aerosol at sub- and supersaturated conditions: closure studies and implications for the role of organics

We investigate the CCN activity of freshly emitted biomass burning particles and their hygroscopic growth at a relative humidity (RH) of 85%. The particles were produced in the Mainz combustion laboratory by controlled burning of various wood types. The water uptake at sub- and supersaturations is parameterized by the hygroscopicity parameter, κ (c.f. Petters and Kreidenweis, 2007). For the wood burns, κ is low, generally around 0.06. The main emphasis of this study is a comparison of κ derived from measurements at sub- and supersaturated conditions (κG and κCCN), in order to see whether the water uptake at 85% RH can predict the CCN properties of the biomass burning particles. Differences in κGand κCCN can arise through solution non-idealities, the presence of slightly soluble or surface active compounds, or non-spherical particle shape. We find that κG and κCCN agree within experimental uncertainties (of around 30%) for particle sizes of 100 and 150 nm; only for 50 nm particles is κCCN larger than κG by a factor of 2. The magnitude of this difference and its dependence on particle size is consistent with the presence of surface active organic compounds. These compounds mainly facilitate the CCN activation of small particles, which form the most concentrated solution droplets at the point of activation. The 50 nm particles, however, are only activated at supersaturations higher than 1% and are therefore of minor importance as CCN in ambient clouds. By comparison with the actual chemical composition of the biomass burning particles, we estimate that the hygroscopicity of the water-soluble organic carbon (WSOC) fraction can be represented by a κWSOC value of approximately 0.2. The effective hygroscopicity of a typical wood burning particle can therefore be represented by a linear mixture of an inorganic component with κ ≅ 0.6, a WSOC component with κ ≅ 0.2, and an insoluble component with κ = 0

Optical Detection of a Single Nuclear Spin

We propose a method to optically detect the spin state of a 31-P nucleus embedded in a 28-Si matrix. The nuclear-electron hyperfine splitting of the 31-P neutral-donor ground state can be resolved via a direct frequency discrimination measurement of the 31-P bound exciton photoluminescence using single photon detectors. The measurement time is expected to be shorter than the lifetime of the nuclear spin at 4 K and 10 T.Comment: 4 pages, 3 figure

Ab-initio calculation of the 6Li{}^6Li binding energy with the Hybrid Multideterminant scheme

We perform an ab-initio calculation for the binding energy of ${}^6Li$ using the CD-Bonn 2000 NN potential renormalized with the Lee-Suzuki method. The many-body approach to the problem is the Hybrid Multideterminant method. The results indicate a binding energy of about $31 MeV$, within a few hundreds KeV uncertainty. The center of mass diagnostics are also discussed.Comment: 18 pages with 3 figures. More calculations added, to be published in EPJ

Identification of genetic variants that impact gene co-expression relationships using large-scale single-cell data

Background: Expression quantitative trait loci (eQTL) studies show how genetic variants affect downstream gene expression. Single-cell data allows reconstruction of personalized co-expression networks and therefore the identification of SNPs altering co-expression patterns (co-expression QTLs, co-eQTLs) and the affected upstream regulatory processes using a limited number of individuals. Results: We conduct a co-eQTL meta-analysis across four scRNA-seq peripheral blood mononuclear cell datasets using a novel filtering strategy followed by a permutation-based multiple testing approach. Before the analysis, we evaluate the co-expression patterns required for co-eQTL identification using different external resources. We identify a robust set of cell-type-specific co-eQTLs for 72 independent SNPs affecting 946 gene pairs. These co-eQTLs are replicated in a large bulk cohort and provide novel insights into how disease-associated variants alter regulatory networks. One co-eQTL SNP, rs1131017, that is associated with several autoimmune diseases, affects the co-expression of RPS26 with other ribosomal genes. Interestingly, specifically in T cells, the SNP additionally affects co-expression of RPS26 and a group of genes associated with T cell activation and autoimmune disease. Among these genes, we identify enrichment for targets of five T-cell-activation-related transcription factors whose binding sites harbor rs1131017. This reveals a previously overlooked process and pinpoints potential regulators that could explain the association of rs1131017 with autoimmune diseases. Conclusion: Our co-eQTL results highlight the importance of studying context-specific gene regulation to understand the biological implications of genetic variation. With the expected growth of sc-eQTL datasets, our strategy and technical guidelines will facilitate future co-eQTL identification, further elucidating unknown disease mechanisms.</p

Identification of genetic variants that impact gene co-expression relationships using large-scale single-cell data

Background: Expression quantitative trait loci (eQTL) studies show how genetic variants affect downstream gene expression. Single-cell data allows reconstruction of personalized co-expression networks and therefore the identification of SNPs altering co-expression patterns (co-expression QTLs, co-eQTLs) and the affected upstream regulatory processes using a limited number of individuals. Results: We conduct a co-eQTL meta-analysis across four scRNA-seq peripheral blood mononuclear cell datasets using a novel filtering strategy followed by a permutation-based multiple testing approach. Before the analysis, we evaluate the co-expression patterns required for co-eQTL identification using different external resources. We identify a robust set of cell-type-specific co-eQTLs for 72 independent SNPs affecting 946 gene pairs. These co-eQTLs are replicated in a large bulk cohort and provide novel insights into how disease-associated variants alter regulatory networks. One co-eQTL SNP, rs1131017, that is associated with several autoimmune diseases, affects the co-expression of RPS26 with other ribosomal genes. Interestingly, specifically in T cells, the SNP additionally affects co-expression of RPS26 and a group of genes associated with T cell activation and autoimmune disease. Among these genes, we identify enrichment for targets of five T-cell-activation-related transcription factors whose binding sites harbor rs1131017. This reveals a previously overlooked process and pinpoints potential regulators that could explain the association of rs1131017 with autoimmune diseases. Conclusion: Our co-eQTL results highlight the importance of studying context-specific gene regulation to understand the biological implications of genetic variation. With the expected growth of sc-eQTL datasets, our strategy and technical guidelines will facilitate future co-eQTL identification, further elucidating unknown disease mechanisms.</p

Distribution of solids in the rings of the HD 163296 disk: a multiwavelength study

Interstellar matter and star formationStars and planetary system