Isolation and optimization of Asparaginase producing bacteria in solid state fermentation by Plackett-Burman desighn

زمینه و هدف: این تحقیق به روش تخمیر در بستر جامد به منظور بررسی انواع بسترهای جامد در تولید آنزیم آسپارژیناز توسط سویه ی جداسازی شده از منطقه لاکان استان گیلان از جنس باسیلوس انجام گردید. روش بررسی: در این بررسی تجربی جهت جداسازی باکتری های تولید کننده ال آسپارژیناز از محیط کشت M9 استفاده شد. جهت غربالگری در بستر جامد از بسترهای مختلف سبوس برنج، ساقه برنج، سبوس گندم و ساقه گندم به عنوان منابع کربن و همچنین از عصاره مخمر، پپتون، آسپارژین، تریپتون به عنوان منابع نیتروژن استفاده شد. جهت بهینه سازی محیط کشت و بررسی اثر منابع کربن و نیتروژن بر میزان تولید آنزیم آسپارژیناز با استفاده از روش Plackett-Burman تعداد 12 آزمایش در 2 سطح طراحی شد؛ سپس انواع بسترهای جامد با تغییر فاکتورهای تأثیرگذار در تولید آنزیم مورد ارزیابی قرار گرفت. یافته ها: بهترین بستر جامد، بستر سبوس برنج و بهترین منبع ازت آسپارژین، بیشترین تأثیر را در افزایش تولید آنزیم از خود نشان دادند. بهترین شرایط تولید آنزیم به دست آمده در بستر جامد در میزان غلظت سبوس برنج 5/1 وزنی/ وزنی و میزان غلظت آسپاراژین 5/0 وزنی/ وزنی و دمای 30 درجه سانتی گراد و به مدت زمان 72 ساعت به میزان 24/69 واحد آنزیم بر گرم مشاهده گردید. نتیجه گیری: در این تحقیق میزان تولید آنزیم با استفاده از سبوس برنج به عنوان منبع کربن در بستر جامد پس از بهینه سازی نسبت به شرایط بهینه سازی نشده افزایش قابل ملاحظه داش

No Initial Elevation on Personality Self-Reports in an Online Convenience Sample

Research shows that people’s self-reports may be biased by an initial elevation phenomenon in which ratings are higher the first time that people take a survey as compared to the second and subsequent times. Apart from the fact that this phenomenon exists, and that it might bias ratings for negative subjective experiences more strongly than positive ones, little else is known. In the present study, we examined whether the initial elevation phenomenon occurs for commonly used trait measures, such as ratings on personality inventories and life satisfaction. We hypothesized that the initial elevation phenomenon may be associated with the (un)desirability of the content of the self-report items such that scores for undesirable facets would show initial elevation and scores for desirable facets would show the reverse. We tested this in an online convenience sample (N = 3,329) using 5 facets of a personality inventory and a single item measure of life satisfaction. Our hypotheses were not supported. Our findings suggest that at least for online convenience samples, ratings on personality inventories and life satisfaction are not strongly impacted by initial elevation

Assessing Validity and Bias of Within- Person Variability in Affect and Personality

Within-person variability in affect (e.g., Neuroticism) and personality have been linked to well-being. These are measured either by asking people to report how variable they are or to give multiple reports on the construct and calculating a within-person standard deviation adjusted for confounding by the person-level mean. The two measures are weakly correlated with one another and the links of variability with well-being depend on which measure researchers use. Recent research suggests that people’s repeated ratings may be biased by response styles. In a 7-day study (N = 399) with up to five measurements per day, we confirmed that the measures of variability lacked sufficient convergent validity to be used interchangeably. We found only 1 significant correlation (of 10) between variability in repeated ratings of affect or personality and variability in repeated ratings of a theoretically unrelated construct (i.e., features of images). There was very little evidence supporting the response styles hypothesis

Not all effects are indispensable: Psychological science requires verifiable lines of reasoning for whether an effect matters

Psychological researchers currently lack guidance for how to make claims about and evaluate the practical relevance and significance of observed effect sizes, i.e. whether a finding will have impact when translated to a different context of application. Although psychologists have recently highlighted theoretical justifications for why small effect sizes might be practically relevant, such justifications fail to provide the information necessary for evaluation and falsification. Claims about whether an observed effect size is practically relevant need to consider both the mechanisms amplifying and counteracting practical relevance, as well as the assumptions underlying each mechanism at play. To provide guidance for making claims about whether an observed effect size is practically relevant in such a way that the claims can be systematically evaluated, we present examples of widely applicable mechanisms and the key assumptions needed for justifying whether an observed effect size can be expected to generalize to different contexts. Routine use of these mechanisms to justify claims about practical relevance has the potential to make researchers’ claims about generalizability substantially more transparent. This transparency can help move psychological science towards a more rigorous assessment of when psychological findings can be applied in the world

Validity of Self-reported Hypertension and Factors Related to Discordance Between Self-reported and Objectively Measured Hypertension: Evidence From a Cohort Study in Iran

Objectives Self-reporting can be used to determine the incidence and prevalence of hypertension (HTN). The present study was conducted to determine the validity of self-reported HTN and to identify factors affecting discordance between self-reported and objectively measured HTN in participants in the Ravansar Non-Communicable Diseases (RaNCD) cohort. Methods The RaNCD cohort included permanent residents of Ravansar, Iran aged 35-65 years. Self-reported data were collected before clinical examinations were conducted by well-trained staff members. The gold standard for HTN was anti-hypertensive medication use and blood pressure measurements. The sensitivity, specificity, positive and negative predictive values, and overall accuracy of self-reporting were calculated. Univariate and multivariate logistic regression were used to examine the discordance between self-reported HTN and the gold standard. Results Of the 10 065 participants in the RaNCD, 4755 (47.4%) were male. The prevalence of HTN was 16.8% based on self-reporting and 15.7% based on medical history and HTN measurements. Of the participants with HTN, 297 (18.8%) had no knowledge of their disease, and 313 (19.9%) had not properly controlled their HTN despite receiving treatment. The sensitivity, specificity, and kappa for self-reported HTN were 75.5%, 96.4%, and 73.4%, respectively. False positives became more likely with age, body mass index (BMI), low socioeconomic status, and female sex, whereas false negatives became more likely with age, BMI, high socioeconomic status, smoking, and urban residency. Conclusions The sensitivity and specificity of self-reported HTN were acceptable, suggesting that this method can be used for public health initiatives in the absence of countrywide HTN control and detection programs

Examining the reproducibility of meta-analyses in psychology:A preliminary report

Meta-analyses are an important tool to evaluate the literature. It is essential that meta-analyses can easily be reproduced to allow researchers to evaluate the impact of subjective choices on meta-analytic effect sizes, but also to update meta-analyses as new data comes in, or as novel statistical techniques (for example to correct for publication bias) are developed. Research in medicine has revealed meta-analyses often cannot be reproduced. In this project, we examined the reproducibility of meta-analyses in psychology by reproducing twenty published meta-analyses. Reproducing published meta-analyses was surprisingly difficult. 96% of meta-analyses published in 2013-2014 did not adhere to reporting guidelines. A third of these meta-analyses did not contain a table specifying all individual effect sizes. Five of the 20 randomly selected meta-analyses we attempted to reproduce could not be reproduced at all due to lack of access to raw data, no details about the effect sizes extracted from each study, or a lack of information about how effect sizes were coded. In the remaining meta-analyses, differences between the reported and reproduced effect size or sample size were common. We discuss a range of possible improvements, such as more clearly indicating which data were used to calculate an effect size, specifying all individual effect sizes, adding detailed information about equations that are used, and how multiple effect size estimates from the same study are combined, but also sharing raw data retrieved from original authors, or unpublished research reports. This project clearly illustrates there is a lot of room for improvement when it comes to the transparency and reproducibility of published meta-analyses

Justify your alpha

Benjamin et al. proposed changing the conventional “statistical significance” threshold (i.e.,the alpha level) from p ≤ .05 to p ≤ .005 for all novel claims with relatively low prior odds. They provided two arguments for why lowering the significance threshold would “immediately improve the reproducibility of scientific research.” First, a p-value near .05provides weak evidence for the alternative hypothesis. Second, under certain assumptions, an alpha of .05 leads to high false positive report probabilities (FPRP2 ; the probability that a significant finding is a false positive

Estimating global injuries morbidity and mortality : methods and data used in the Global Burden of Disease 2017 study

Background: While there is a long history of measuring death and disability from injuries, modern research methods must account for the wide spectrum of disability that can occur in an injury, and must provide estimates with sufficient demographic, geographical and temporal detail to be useful for policy makers. The Global Burden of Disease (GBD) 2017 study used methods to provide highly detailed estimates of global injury burden that meet these criteria. Methods: In this study, we report and discuss the methods used in GBD 2017 for injury morbidity and mortality burden estimation. In summary, these methods included estimating cause-specific mortality for every cause of injury, and then estimating incidence for every cause of injury. Non-fatal disability for each cause is then calculated based on the probabilities of suffering from different types of bodily injury experienced. Results: GBD 2017 produced morbidity and mortality estimates for 38 causes of injury. Estimates were produced in terms of incidence, prevalence, years lived with disability, cause-specific mortality, years of life lost and disability-adjusted life-years for a 28-year period for 22 age groups, 195 countries and both sexes. Conclusions: GBD 2017 demonstrated a complex and sophisticated series of analytical steps using the largest known database of morbidity and mortality data on injuries. GBD 2017 results should be used to help inform injury prevention policy making and resource allocation. We also identify important avenues for improving injury burden estimation in the future

Estimating global injuries morbidity and mortality : methods and data used in the Global Burden of Disease 2017 study

Background While there is a long history of measuring death and disability from injuries, modern research methods must account for the wide spectrum of disability that can occur in an injury, and must provide estimates with sufficient demographic, geographical and temporal detail to be useful for policy makers. The Global Burden of Disease (GBD) 2017 study used methods to provide highly detailed estimates of global injury burden that meet these criteria. Methods In this study, we report and discuss the methods used in GBD 2017 for injury morbidity and mortality burden estimation. In summary, these methods included estimating cause-specific mortality for every cause of injury, and then estimating incidence for every cause of injury. Non-fatal disability for each cause is then calculated based on the probabilities of suffering from different types of bodily injury experienced. Results GBD 2017 produced morbidity and mortality estimates for 38 causes of injury. Estimates were produced in terms of incidence, prevalence, years lived with disability, cause-specific mortality, years of life lost and disability-adjusted life-years for a 28-year period for 22 age groups, 195 countries and both sexes. Conclusions GBD 2017 demonstrated a complex and sophisticated series of analytical steps using the largest known database of morbidity and mortality data on injuries. GBD 2017 results should be used to help inform injury prevention policy making and resource allocation. We also identify important avenues for improving injury burden estimation in the future.Peer reviewe

Mapping local patterns of childhood overweight and wasting in low- and middle-income countries between 2000 and 2017

A double burden of malnutrition occurs when individuals, household members or communities experience both undernutrition and overweight. Here, we show geospatial estimates of overweight and wasting prevalence among children under 5 years of age in 105 low- and middle-income countries (LMICs) from 2000 to 2017 and aggregate these to policy-relevant administrative units. Wasting decreased overall across LMICs between 2000 and 2017, from 8.4% (62.3 (55.1–70.8) million) to 6.4% (58.3 (47.6–70.7) million), but is predicted to remain above the World Health Organization’s Global Nutrition Target of <5% in over half of LMICs by 2025. Prevalence of overweight increased from 5.2% (30 (22.8–38.5) million) in 2000 to 6.0% (55.5 (44.8–67.9) million) children aged under 5 years in 2017. Areas most affected by double burden of malnutrition were located in Indonesia, Thailand, southeastern China, Botswana, Cameroon and central Nigeria. Our estimates provide a new perspective to researchers, policy makers and public health agencies in their efforts to address this global childhood syndemic