Chi-square and Poissonian Data: Biases Even in the High-Count Regime and How to Avoid them

We demonstrate that two approximations to the chi^2 statistic as popularly employed by observational astronomers for fitting Poisson-distributed data can give rise to intrinsically biased model parameter estimates, even in the high counts regime, unless care is taken over the parameterization of the problem. For a small number of problems, previous studies have shown that the fractional bias introduced by these approximations is often small when the counts are high. However, we show that for a broad class of problem, unless the number of data bins is far smaller than \sqrt{N_c}, where N_c is the total number of counts in the dataset, the bias will still likely be comparable to, or even exceed, the statistical error. Conversely, we find that fits using Cash's C-statistic give comparatively unbiased parameter estimates when the counts are high. Taking into account their well-known problems in the low count regime, we conclude that these approximate chi^2 methods should not routinely be used for fitting an arbitrary, parameterized model to Poisson-distributed data, irrespective of the number of counts per bin, and instead the C-statistic should be adopted. We discuss several practical aspects of using the C-statistic in modelling real data. We illustrate the bias for two specific problems, measuring the count-rate from a lightcurve and obtaining the temperature of a thermal plasma from its X-ray spectrum measured with the Chandra X-ray observatory. In the context of X-ray astronomy, we argue the bias could give rise to systematically mis-calibrated satellites and a ~5-10% shift in galaxy cluster scaling relations.Comment: 9 pages, 2 figures. Accepted for publication in the Astrophysical Journa

Treatment selection for de Quervain's tenosynovitis based on the Michigan’s Hand Questionnaire

Objective: De Quervain's disease is a stenosing tenosynovitis of the first dorsal compartment. Treatment options include conservative measures, injections, and surgery. The main purpose of this study is to eliminate uncertainty in the choice of treatment and to recommend the appropriate treatment to the patient based on Michigan hand questionnaire. Material and Methods: The age, sex, and treatment modality of the patients were recorded retrospectively. Patients' Michigan outcomes were assessed, and patients were divided into three groups: Patients who benefited from conservative treatments (Group 1), from injections (Group 2), and from surgery (Group 3). Statistical analysis of the data was performed. Results: The mean age of the 56 patients (54 women, 2 men) was 35.1±11.4 years. There was a difference between all groups in total hand function and pain scores (p 0.05). Conclusion: Various methods have been described for De Quervain's tenosynovitis’s treatment. Choosing the right therapeutic steps for the right patients is important. It is possible to select treatment options by assessing overall hand function and activities of daily living with the Michigan Hand Outcome Questionnair

Investigation of awareness and anxiety levels of pregnant women during pandemic process

Objectives: It is currently unknown that how pregnant women deal with the Coronavirus disease and its results. The aim of this study is to evaluate the psychological impact of the coronavirus pandemic on pregnant women and to determine whether pregnant women have sufficient knowledge and awareness for a healthy antenatal process. Material and methods: This study was conducted at two centers. Regardless of the gestational age, a questionnaire was distributed to 1003 pregnant women in total, from which 51 original questions we prepared. Five hundred twenty-six participants were included in the study. The questionnaire was delivered using the QR code method. The questionnaires were answered online by participants via SurveyMonkey. Results: The period when anxiety was highest was the 2nd trimester, whereas women in the 1st trimester had the lowest level of anxiety. High levels of awareness were observed in patients with heart disease, but patients with diabetes mellitus had a high level of anxiety. Conclusions: It is important to maintain the mental and physical health of pregnant women, who are in a more delicate condition than other individuals in the society. In this regard, healthcare professionals have important duties such as taking necessary precautions and explaining the seriousness of the situation to pregnant women

Draft Genome Sequences of Two Heat-Resistant Mutant Strains (A52 and B41) of the Photosynthetic Hydrogen-Producing BacteriumRhodobacter capsulatus

The draft genome sequences of two heat-resistant mutant strains, A52 and B41, derived from Rhodobacter capsulatus DSM 1710, and with different hydrogen production levels, are reported here. These sequences may help understand the molecular basis of heat resistance and hydrogen production in R. capsulatus.Turkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK)Publisher's Versio

Impact of liquid lipid on development and stability of trimyristin nanostructured lipid carriers for oral delivery of resveratrol

Nanostructured lipid carriers (NLCs) have emerged as versatile carriers to improve oral bioavailability of poorly water-soluble drugs as well as to protect labile drugs from degradation and metabolism. Prepared by blending solid and liquid lipids, the choice of liquid lipid can have a great influence on their physicochemical characteristics and stability. The present work investigated the impact of six different liquid lipids with diverse chemical structures and hydrophilic and lipophilic balance (HLBs) on the critical quality attributes (CQAs) and storage stability of NLCs with trimyristin as solid lipid. Resveratrol (RES) was used as model drug as its low water solubility, poor bioavailability, rapid metabolism and clearance from systemic circulation restricts its clinical use despite its wide spectrum of biological activities. Liquid lipids investigated included, two triglycerides, one medium chain (C8) glycerol tricaprylate (GTC) and second, long chain (C18) glyceryl trioleate (GTO); two propylene glycol fatty acid esters, propylene glycol monocaprylate (PGMC) and propylene glycol monolaurate (PGML); fatty acid ester decyl oleate (DO) and a PEGylated lipid polyethylene glycol-8 caprylic/capric glycerides (PCG). Box–Behnken experimental design was employed to ascertain the effect of four independent factors viz. type of liquid lipid, amount of liquid lipid, amount of drug and surfactant concentration and interactions between these factors on the CQAs of NLCs as response variables viz. particle size (PS), polydispersity index (PDI), zeta potential (ZP), drug encapsulation efficiency (EE), and drug loading (DL). The relationship between various factors and responses was established by response surface methodology (RSM). The oils with higher lipophilicity C18 triglycerides (GTO) and C18 fatty acid ester DO yielded NLCs with lower PS as compared to the oils with lower lipophilicity (PGC, PGMC and PGML). Although increasing the concentration of liquid lipids had an upward trend on the PS of NLCs, its PDI was more predominantly influenced by the nature of liquid lipid. The characteristic of the liquid lipid influenced the DL remarkably which varied from 2.94 to 7.56%. The ZP of nanoparticles varied from −21.3 to −39.9 mV with liquid lipids with free hydroxyl groups and higher HLB playing a more prominent role contributing to the increase in the negative surface charge. The characteristics of liquid lipid influenced the depression of melting point of RES with maximum distortion of the crystal lattice was caused by PGMC and least by GTO. The two, long chain oleates, DO and GTO exhibited a shift of lipid peak in NLCs to higher melting points (116 and 111 °C) than the less lipophilic liquid lipids (103–104 °C). The attributes of liquid lipid also discriminate whether the particle growth during storage followed Oswald's ripening or coalescence. NLC containing GTO exhibited the highest stability in terms of maintenance of the PS and particle size distribution at 20 °C. This study provides vital insight on impact of liquid lipids and future strategy for rational design of stable NLC systems for delivery of various bio-actives for drug delivery applications

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages