Putative regulatory functions of SNPs associated with bronchial asthma, arterial hypertension and their comorbid phenotype.

Linkage disequilibrium (LD) of single nucleotide polymorphisms (SNPs) of TLR4/AL160272.2 (rs1927914, rs1928298, rs7038716, rs7026297, rs7025144) was estimated in the Slavs of West Siberia. We further investigated an association of SNPs in TLR4/AL160272.2 (rs1927914, rs7038716, rs7025144), SERPINA1 (rs1980616), ATXN2/BRAP (rs11065987), IL2RB (rs2284033), NT5C2 (rs11191582), CARD8 (rs11669386), ANG/RNASE4 (rs1010461), and ABTB2/ САТ (rs2022318) genes with bronchial asthma (BA), arterial hypertension (AH) and their comorbidity. Then, the disease-associated SNPs were annotated in silico in relation to their potential regulatory functions. Strong LD was detected between rs1928298 and rs1927914, as well as rs7026297 and rs7038716 in the Slavs of West Siberia. It was found that the rs1927914 G allele of the TLR4 gene and the rs1980616 C allele of the SERPINA1 gene are associated with the predisposition to BA. These SNPs can affect binding affinity of transcription factors of the Pou and Klf4 families, as well as the expression levels of the TLR4 and SERPINA1 genes. The rs11065987 allele A of the ATXN2/BRAP genes, the rs11669386 A allele of the CARD8 gene, the rs2284033 allele G of the IL2RB gene, and the rs11191582 allele G of the NT5C2 gene were associated with the risk of AH. These variants can alter binding affinity of the Hoxa9, Irf, RORalpha1 and HMG-IY transcription factors, as well as the expression levels of the ALDH2, CARD8, NT5C2, ARL3, and SFXN2 genes in blood cells/vessels/heart, respectively. The risk of developing a comorbid phenotype of AD and AH is associated with the A allele of rs7038716 and the T allele of rs7025144 of the TLR4/AL160272.2 genes, the A allele of rs1010461 of the ANG gene and the C allele of rs2022318 of the ABTB2/CAT genes. Variants rs7038716 and rs7025144 can change the expression levels of the TLR4 gene in blood cells, while rs1010461 and rs2022318 influence the expression levels of the ANG and RNASE4 genes as well as the CAT and ABTB2 genes in blood cells, lungs/vessels/heart

Angiomotin and angiomotin like proteins, their expression and correlation with angiogenesis and clinical outcome in human breast cancer

BACKGOUND: Angiomotin is a newly discovered molecule that regulates the migration and tubule formation of endothelial cells. It therefore has been implicated in the control of angiogenesis under physiological and pathological conditions. This study examined the expression of angiomotin and its analogues, angiomotin-like 1 (L1) and -like 2 (L2) in breast tumour tissues, and analysed their correlation with angiogenesis and clinical outcomes. METHODS: Human breast tissues (normal n = 32 and tumours n = 120) were used. The levels of expression of angiomotin, L1 and L2 were determined using reverse transcription PCR. Microvessels were stained using antibodies against PECAM, von Willebrand factor (factor 8, or vWF) and VE-cadherin. The transcript levels of angiomotin and its analogues were assessed against the clinical and pathological background, including long term survival (120 months). RESULTS: Breast cancer tissues expressed significantly higher levels of angiomotin transcript, compared with normal mammary tissues (33.1 ± 11 in normal versus 86.5 ± 13.7 in tumour tissues, p = 0.003). Both L1 and L2 were seen at marginally higher levels in tumour than normal tissues but the difference was not statistically significant. Levels of angiomotin were at significantly higher levels in grade 2 and grade 3 tumours compared with grade 1 (p < 0.01 and p = 0.05 respectively). The levels of angiomotin in tumours from patients who had metastatic disease were also significantly higher than those patients who remained disease free (p = 0.03). Multivariate analysis indicated that angiomotin transcript was an independent prognostic factor (p = 0.031). No significant correlations were seen between angiomotin-L1 and L2 with the clinical outcome. Furthermore, high levels of angiomotin transcript were associated with shorter overall survival (p < 0.05). There was a high degree of correlation between levels of vW factor and that of angiomotin (p < 0.05), but not angiomotin-L1 and angiomotin-L2. CONCLUSION: Angiomotin, a putative endothelial motility factor, is highly expressed in human breast tumour tissues and linked to angiogenesis. It links to the aggressive nature of breast tumours and the long term survival of the patients. These data point angiomotin as being a potential therapeutic target

Effective Rheology of Bubbles Moving in a Capillary Tube

We calculate the average volumetric flux versus pressure drop of bubbles moving in a single capillary tube with varying diameter, finding a square-root relation from mapping the flow equations onto that of a driven overdamped pendulum. The calculation is based on a derivation of the equation of motion of a bubble train from considering the capillary forces and the entropy production associated with the viscous flow. We also calculate the configurational probability of the positions of the bubbles.Comment: 4 pages, 1 figur

The Rts1 Regulatory Subunit of Protein Phosphatase 2A Is Required for Control of G1 Cyclin Transcription and Nutrient Modulation of Cell Size

The key molecular event that marks entry into the cell cycle is transcription of G1 cyclins, which bind and activate cyclin-dependent kinases. In yeast cells, initiation of G1 cyclin transcription is linked to achievement of a critical cell size, which contributes to cell-size homeostasis. The critical cell size is modulated by nutrients, such that cells growing in poor nutrients are smaller than cells growing in rich nutrients. Nutrient modulation of cell size does not work through known critical regulators of G1 cyclin transcription and is therefore thought to work through a distinct pathway. Here, we report that Rts1, a highly conserved regulatory subunit of protein phosphatase 2A (PP2A), is required for normal control of G1 cyclin transcription. Loss of Rts1 caused delayed initiation of bud growth and delayed and reduced accumulation of G1 cyclins. Expression of the G1 cyclin CLN2 from an inducible promoter rescued the delayed bud growth in rts1Δ cells, indicating that Rts1 acts at the level of transcription. Moreover, loss of Rts1 caused altered regulation of Swi6, a key component of the SBF transcription factor that controls G1 cyclin transcription. Epistasis analysis revealed that Rts1 does not work solely through several known critical upstream regulators of G1 cyclin transcription. Cells lacking Rts1 failed to undergo nutrient modulation of cell size. Together, these observations demonstrate that Rts1 is a key player in pathways that link nutrient availability, cell size, and G1 cyclin transcription. Since Rts1 is highly conserved, it may function in similar pathways in vertebrates

Nonlinear wave interaction in coastal and open seas -- deterministic and stochastic theory

We review the theory of wave interaction in finite and infinite depth. Both of these strands of water-wave research begin with the deterministic governing equations for water waves, from which simplified equations can be derived to model situations of interest, such as the mild slope and modified mild slope equations, the Zakharov equation, or the nonlinear Schr\"odinger equation. These deterministic equations yield accompanying stochastic equations for averaged quantities of the sea-state, like the spectrum or bispectrum. We discuss several of these in depth, touching on recent results about the stability of open ocean spectra to inhomogeneous disturbances, as well as new stochastic equations for the nearshore

A time-resolved proteomic and prognostic map of COVID-19

COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. We characterized the time-dependent progression of the disease in 139 COVID-19 inpatients by measuring 86 accredited diagnostic parameters, such as blood cell counts and enzyme activities, as well as untargeted plasma proteomes at 687 sampling points. We report an initial spike in a systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution, and immunomodulation. We identify prognostic marker signatures for devising risk-adapted treatment strategies and use machine learning to classify therapeutic needs. We show that the machine learning models based on the proteome are transferable to an independent cohort. Our study presents a map linking routinely used clinical diagnostic parameters to plasma proteomes and their dynamics in an infectious disease

A proteomic survival predictor for COVID-19 patients in intensive care

Global healthcare systems are challenged by the COVID-19 pandemic. There is a need to optimize allocation of treatment and resources in intensive care, as clinically established risk assessments such as SOFA and APACHE II scores show only limited performance for predicting the survival of severely ill COVID-19 patients. Additional tools are also needed to monitor treatment, including experimental therapies in clinical trials. Comprehensively capturing human physiology, we speculated that proteomics in combination with new data-driven analysis strategies could produce a new generation of prognostic discriminators. We studied two independent cohorts of patients with severe COVID-19 who required intensive care and invasive mechanical ventilation. SOFA score, Charlson comorbidity index, and APACHE II score showed limited performance in predicting the COVID-19 outcome. Instead, the quantification of 321 plasma protein groups at 349 timepoints in 50 critically ill patients receiving invasive mechanical ventilation revealed 14 proteins that showed trajectories different between survivors and non-survivors. A predictor trained on proteomic measurements obtained at the first time point at maximum treatment level (i.e. WHO grade 7), which was weeks before the outcome, achieved accurate classification of survivors (AUROC 0.81). We tested the established predictor on an independent validation cohort (AUROC 1.0). The majority of proteins with high relevance in the prediction model belong to the coagulation system and complement cascade. Our study demonstrates that plasma proteomics can give rise to prognostic predictors substantially outperforming current prognostic markers in intensive care

Alignment of the ALICE Inner Tracking System with cosmic-ray tracks

37 pages, 15 figures, revised version, accepted by JINSTALICE (A Large Ion Collider Experiment) is the LHC (Large Hadron Collider) experiment devoted to investigating the strongly interacting matter created in nucleus-nucleus collisions at the LHC energies. The ALICE ITS, Inner Tracking System, consists of six cylindrical layers of silicon detectors with three different technologies; in the outward direction: two layers of pixel detectors, two layers each of drift, and strip detectors. The number of parameters to be determined in the spatial alignment of the 2198 sensor modules of the ITS is about 13,000. The target alignment precision is well below 10 micron in some cases (pixels). The sources of alignment information include survey measurements, and the reconstructed tracks from cosmic rays and from proton-proton collisions. The main track-based alignment method uses the Millepede global approach. An iterative local method was developed and used as well. We present the results obtained for the ITS alignment using about 10^5 charged tracks from cosmic rays that have been collected during summer 2008, with the ALICE solenoidal magnet switched off.Peer reviewe

First measurement of the |t|-dependence of coherent J/ψ photonuclear production

The first measurement of the cross section for coherent J/ψ photoproduction as a function of |t|, the square of the momentum transferred between the incoming and outgoing target nucleus, is presented. The data were measured with the ALICE detector in ultra-peripheral Pb–Pb collisions at a centre-of-mass energy per nucleon pair sNN=5.02TeV with the J/ψ produced in the central rapidity region |y|<0.8, which corresponds to the small Bjorken-x range (0.3−1.4)×10−3. The measured |t|-dependence is not described by computations based only on the Pb nuclear form factor, while the photonuclear cross section is better reproduced by models including shadowing according to the leading-twist approximation, or gluon-saturation effects from the impact-parameter dependent Balitsky–Kovchegov equation. These new results are therefore a valid tool to constrain the relevant model parameters and to investigate the transverse gluonic structure at very low Bjorken-x.publishedVersio