The relationship between red blood cell deformability metrics and perfusion of an artificial microvascular network

The ability of red blood cells (RBC) to undergo a wide range of deformations while traversing the microvasculature is crucial for adequate perfusion. Interpretation of RBC deformability measurements performed in vitro in the context of microvascular perfusion has been notoriously difficult. This study compares the measurements of RBC deformability performed using micropore filtration and ektacytometry with the RBC ability to perfuse an artificial microvascular network (AMVN). Human RBCs were collected from healthy consenting volunteers, leukoreduced, washed and exposed to graded concentrations (0% – 0.08%) of glutaraldehyde (a non-specific protein cross-linker) and diamide (a spectrin-specific protein cross-linker) to impair the deformability of RBCs. Samples comprising cells with two different levels of deformability were created by adding non-deformable RBCs (hardened by exposure to 0.08% glutaraldehyde) to the sample of normal healthy RBCs. Ektacytometry indicated a nearly linear decline in RBC deformability with increasing glutaraldehyde concentration. Micropore filtration showed a significant reduction only for concentrations of glutaraldehyde higher than 0.04%. Neither micropore filtration nor ektacytometry measurements could accurately predict the AMVN perfusion. Treatment with diamide reduced RBC deformability as indicated by ektacytometry, but had no significant effect on either micropore filtration or the AMVN perfusion. Both micropore filtration and ektacytometry showed a linear decline in effective RBC deformability with increasing fraction of non-deformable RBCs in the sample. The corresponding decline in the AMVN perfusion plateaued above 50%, reflecting the innate ability of blood flow in the microvasculature to bypass occluded capillaries. Our results suggest that in vitro measurements of RBC deformability performed using either micropore filtration or ektacytometry may not represent the ability of same RBCs to perfuse microvascular networks. Further development of biomimetic tools for measuring RBC deformability (e.g. the AMVN) could enable a more functionally relevant testing of RBC mechanical properties

The UV Scattering Halo of the Central Source Associated with Eta Carinae

We have made an extensive study of the UV spectrum of Eta Carinae, and find that we do not directly observe the star and its wind in the UV. Because of dust along our line of sight, the UV light that we observe arises from bound-bound scattering at large impact parameters. We obtain a reasonable fit to the UV spectrum by using only the flux that originates outside 0.033". This explains why we can still observe the primary star in the UV despite the large optical extinction -- it is due to the presence of an intrinsic coronagraph in the Eta Carinae system, and to the extension of the UV emitting region. It is not due to peculiar dust properties alone. We have computed the spectrum of the purported companion star, and show that it could only be directly detected in the UV spectrum preferentially in the Far Ultraviolet Spectroscopic Explorer (FUSE) spectral region (912-1175 Ang.). However, we find no direct evidence for a companion star, with the properties indicated by X-ray studies and studies of the Weigelt blobs, in UV spectra. This might be due to reprocessing of the companion's light by the dense stellar wind of the primary. Broad FeII and [FeII] emission lines, which form in the stellar wind, are detected in spectra taken in the SE lobe, 0.2" from the central star. The wind spectrum shows some similarities to the spectra of the B & D Weigelt blobs, but also shows some marked differences in that high excitation lines, and lines pumped by Ly-alpha, are not seen. The detection of the broad lines lends support to our interpretation of the UV spectrum, and to our model for Eta Carinae.Comment: To appear in ApJ. 57 pages with 18 figure

Recon 2.2: from reconstruction to model of human metabolism.

IntroductionThe human genome-scale metabolic reconstruction details all known metabolic reactions occurring in humans, and thereby holds substantial promise for studying complex diseases and phenotypes. Capturing the whole human metabolic reconstruction is an on-going task and since the last community effort generated a consensus reconstruction, several updates have been developed.ObjectivesWe report a new consensus version, Recon 2.2, which integrates various alternative versions with significant additional updates. In addition to re-establishing a consensus reconstruction, further key objectives included providing more comprehensive annotation of metabolites and genes, ensuring full mass and charge balance in all reactions, and developing a model that correctly predicts ATP production on a range of carbon sources.MethodsRecon 2.2 has been developed through a combination of manual curation and automated error checking. Specific and significant manual updates include a respecification of fatty acid metabolism, oxidative phosphorylation and a coupling of the electron transport chain to ATP synthase activity. All metabolites have definitive chemical formulae and charges specified, and these are used to ensure full mass and charge reaction balancing through an automated linear programming approach. Additionally, improved integration with transcriptomics and proteomics data has been facilitated with the updated curation of relationships between genes, proteins and reactions.ResultsRecon 2.2 now represents the most predictive model of human metabolism to date as demonstrated here. Extensive manual curation has increased the reconstruction size to 5324 metabolites, 7785 reactions and 1675 associated genes, which now are mapped to a single standard. The focus upon mass and charge balancing of all reactions, along with better representation of energy generation, has produced a flux model that correctly predicts ATP yield on different carbon sources.ConclusionThrough these updates we have achieved the most complete and best annotated consensus human metabolic reconstruction available, thereby increasing the ability of this resource to provide novel insights into normal and disease states in human. The model is freely available from the Biomodels database (http://identifiers.org/biomodels.db/MODEL1603150001)

Quantum-circuit design for efficient simulations of many-body quantum dynamics

We construct an efficient autonomous quantum-circuit design algorithm for creating efficient quantum circuits to simulate Hamiltonian many-body quantum dynamics for arbitrary input states. The resultant quantum circuits have optimal space complexity and employ a sequence of gates that is close to optimal with respect to time complexity. We also devise an algorithm that exploits commutativity to optimize the circuits for parallel execution. As examples, we show how our autonomous algorithm constructs circuits for simulating the dynamics of Kitaev's honeycomb model and the Bardeen-Cooper-Schrieffer model of superconductivity. Furthermore we provide numerical evidence that the rigorously proven upper bounds for the simulation error here and in previous work may sometimes overestimate the error by orders of magnitude compared to the best achievable performance for some physics-inspired simulations.Comment: 20 Pages, 6 figure

Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use.

Tobacco and alcohol use are leading causes of mortality that influence risk for many complex diseases and disorders1. They are heritable2,3 and etiologically related4,5 behaviors that have been resistant to gene discovery efforts6-11. In sample sizes up to 1.2 million individuals, we discovered 566 genetic variants in 406 loci associated with multiple stages of tobacco use (initiation, cessation, and heaviness) as well as alcohol use, with 150 loci evidencing pleiotropic association. Smoking phenotypes were positively genetically correlated with many health conditions, whereas alcohol use was negatively correlated with these conditions, such that increased genetic risk for alcohol use is associated with lower disease risk. We report evidence for the involvement of many systems in tobacco and alcohol use, including genes involved in nicotinic, dopaminergic, and glutamatergic neurotransmission. The results provide a solid starting point to evaluate the effects of these loci in model organisms and more precise substance use measures

Ubiquitous problem of learning system parameters for dissipative two-level quantum systems: Fourier analysis versus Bayesian estimation

We compare the accuracy, precision and reliability of different methods for estimating key system parameters for two-level systems subject to Hamiltonian evolution and decoherence. It is demonstrated that the use of Bayesian modelling and maximum likelihood estimation is superior to common techniques based on Fourier analysis. Even for simple two-parameter estimation problems, the Bayesian approach yields higher accuracy and precision for the parameter estimates obtained. It requires less data, is more flexible in dealing with different model systems, can deal better with uncertainty in initial conditions and measurements, and enables adaptive refinement of the estimates. The comparison results shows that this holds for measurements of large ensembles of spins and atoms limited by Gaussian noise as well as projection noise limited data from repeated single-shot measurements of a single quantum device

Predictors of loss to follow up among patients with type 2 diabetes mellitus attending a private not for profit urban diabetes clinic in Uganda : a descriptive retrospective study

BACKGROUND: Although the prevalence of type 2 diabetes mellitus is increasing in Uganda, data on loss to follow up (LTFU) of patients in care is scanty. We aimed to estimate proportions of patients LTFU and document associated factors among patients attending a private not for profit urban diabetes clinic in Uganda. METHODS: We conducted a descriptive retrospective study between March and May 2017. We reviewed 1818 out-patient medical records of adults diagnosed with type 2 diabetes mellitus registered between July 2003 and September 2016 at St. Francis Hospital - Nsambya Diabetes clinic in Uganda. Data was extracted on: patients' registration dates, demographics, socioeconomic status, smoking, glycaemic control, type of treatment, diabetes mellitus complications and last follow-up clinic visit. LTFU was defined as missing collecting medication for six months or more from the date of last clinic visit, excluding situations of death or referral to another clinic. We used Kaplan-Meier technique to estimate time to defaulting medical care after initial registration, log-rank test to test the significance of observed differences between groups. Cox proportional hazards regression model was used to determine predictors of patients' LTFU rates in hazard ratios (HRs). RESULTS: Between July 2003 and September 2016, one thousand eight hundred eighteen patients with type 2 diabetes mellitus were followed for 4847.1 person-years. Majority of patients were female 1066/1818 (59%) and 1317/1818 (72%) had poor glycaemic control. Over the 13 years, 1690/1818 (93%) patients were LTFU, giving a LTFU rate of 34.9 patients per 100 person-years (95%CI: 33.2-36.6). LTFU was significantly higher among males, younger patients (< 45 years), smokers, patients on dual therapy, lower socioeconomic status, and those with diabetes complications like neuropathy and nephropathy. CONCLUSION: We found high proportions of patients LTFU in this diabetes clinic which warrants intervention studies targeting the identified risk factors and strengthening follow up of patients