Miracle-dz/UniFAR-FTUs huggingface dataset:
Electrocatalytic reduction of hemoglobin at a chemically modified electrode containing riboflavin

Chemically modified electrode (CME) exhibting electrocatalytic response toward hemoglobin (Hb) is constructed by constructed by absorbing the riboflavin mediator onto spectroscopic graphite surface. The electron transfer between the riboflavin functionality and the graphie is fast. The surface coverage is at most 9.6 × 10−10 mol cm−10. The modified electrode permits the electroreduction of hemoglobin to take place at a low potential corresponding to the reduction potential of the mediator molecule. For neutral and slightly acidic solutions, this corresponds to very modest negative potentials (vs.Ag/AgCi). Characterization of the performance of the CME is carried out. After 30 min of continuous potential scanning of pH6.8, 60% of the original coverage remains for the CME. The linear range of the calibration plot is 30–480 μmol/L. The effect of the solution pH on the electrocatalytic activity of the CME for hemoglobin reduction is investigated. Due to its high sensitivity and durability, this CME coulde be used as an analytical sensor for detecting hemoglobin in real samples.
BIOMARKERS OF THE ECOSYSTEM IN LEAD (PB) POLLUTED AREAS OF BAGHDAD CITY, IRAQ

From five major sites in Baghdad, samples of two types of plants and the surrounding soil were collected for the purpose of identifying vital signs and showing them in nature, the more intensive sampling to represent the spatial distribution of the risks of other elements in all Baghdad areas and focus on working spatial information about the idea of the relative risk between variables in environmental and biological factors in the food web. Results showed the presence of lead concentration in all plants but differ from one to other depending on the ability to absorb this element and content the terrestrial dominate plants species. Consecutively Eucalyptus camaldulensis, Ziziphus spina-christi, that means using it as a positive indicator of pollution, the distribution of this lead in all station area under this study showed a much greater accumulation in soil response pollution indices can be used to compare different pollution in sites and essential to understanding the current risks to all organism in region. The capacity to absorb and identify the elements in health risks according to Potential Ecological Risk Index (RI) and potential ecological risk factor (Tin) in dynamic modeling to predict changes in Pb concentration in environmental compartments exposure in response to reductions by calculating the concentration of the metal in the sample and its concentration in the reference value.
Makkah, Saudi Arabia

Objectives: Assess the level of BLS knowledge and CPR skills among dental students and faculty members at the College of Dentistry, Umm Al-Qura University, Makkah, Saudi Arabia. Methods: A cross-sectional study was conducted using a self-administered questionnaire consisting of 30 closed-ended questions on demographic data, knowledge, attitude, practice, and training status in BLS. CPR skills were evaluated using a training mannequin and software that provided real-time and summative feedback consistent with the American Heart Association (AHA) guidelines. Results: Sample size was 286, of which 210 subjects participated with a response rate of 73.4%. Of the respondents, 52% were males, and 48% were females. A significant number of faculty members knew about CPR and BLS, while the level of awareness among students was significantly lower. As regards to CPR skills low scores were recorded among trained faculty members and students. Conclusions: Faculty members and students at the College of Dentistry, Umm Al-Qura University had average knowledge and positive attitude about BLS and CPR. Despite previous training, skill levels among both students and faculty were poor. Therefore, repeated training courses are recommended to improve BLS knowledge, attitude, and skills to respond appropriately and manage emergencies.
Differences in On-the-Job Learning Across Firms

IZA DP No. 14473 JUNE 2021 Differences in On-the-Job Learning across Firms We present evidence consistent with large disparities across firms in the on-the-job learning their young employees experience, using administrative datasets from Brazil and Italy. We categorize firms into discrete “classes” using a clustering methodology which groups together firms with similar distributions of unexplained earnings growth. Equipped with this categorization of firms—which our conceptual framework interprets as skill-learning classes—we document three main results. First, Mincerian returns to experience vary substantially across experiences acquired in different firm classes, and the magnitude of this heterogeneity is associated with significant shifts across the distribution of early-career wage growth. Second, past experience at firms with better on-the-job learning is associated with subsequent jobs featuring greater non-routine task content. Third, firms’ observable characteristics only mildly predict on-the-job learning opportunities. Our findings hold among involuntarily displaced workers who have no seniority at their new jobs, which is consistent with a portable skills interpretation. JEL Classification: J24, J31
NBER WORKING PAPER SERIES WHAT DRIVES HOME MARKET ADVANTAGE?

In the automobile industry, as in many tradable goods markets, firms earn their highest market share within their domestic market. This home market advantage persists despite substantial integration of international markets during the past several decades. The goal of this paper is to quantify the supplyand demand-driven sources of the home market advantage and to understand their implications for international trade and investment. Building on the random coefficients demand model developed by Berry, Levinsohn, and Pakes (1995), we estimate demand and supply in the automobile industry for nine countries across three continents, allowing for unobserved taste and cost variation at the car model and market levels. While trade and foreign production costs as well as taste heterogeneity matter for market outcomes, we find that preference for domestic brands is the single most important driver of home market advantage even after controlling for brand histories and dealer networks. A. Kerem Cosar Stockholm School of Economics Sveavägen 65, 113 83 Stockholm, Sweden kerem.cosar@gmail.com Paul L. E. Grieco The Pennsylvania State University Department of Economics 509 Kern Building University Park Pennsylvania, PA 16802, USA paul.grieco@gmail.com Shengyu Li Business School Durham University Mill Hill Lane Durham, DH1 3LB UK shengyu.li@durham.ac. uk Felix Tintelnot Department of Economics University of Chicago 5757 South University Avenue Chicago, IL 60637 and NBER tintelnot@uchicago.edu
Association study for vegetable pod yield and yield contributing traits in cluster bean [Cymopsis tetragonoloba (L.) Taub.] genotypes

An experiment was carried out to study the correlation between yield components and their direct and indirect effects on the vegetable pod yield in cluster bean using 15 genotypes. The correlation study revealed high significant positive association of pod yield per plant with plant height at 90 days after sowing (DAS) (0.51), number of branches per plant (0.54), number of branches per plant (0.54), days to first flowering (0.40) and days to first vegetable pod picking (0.39) and positive and significant correlation with plant height at 90 days after sowing (DAS) (0.37) while positively associated with days to 50 per cent flowering (0.27), number of cluster per plant (0.14), pod length (0.13) and ten pod weight (0.20), these were the characters responsible for maximum vegetable pod yield. The correlation was also positive for these characters. Hence, emphasis should be given for these characters, while making selection for high yielding genotypes in cluster bean.
An analysis of patients' perspectives on qualitative olfactory dysfunction using social media

Background: The impact of qualitative olfactory disorders is underestimated. Parosmia is the triggered perception of distorted odours whereas phantosmia is the perception of odours in the absence of a trigger. Both can arise from post-infectious anosmia and have increased substantially since the outbreak of COVID-19. Methodology/Principal: Thematic analysis of a social media support group for parosmia and phantosmia was used to articulate the perspectives and concerns of those affected by these debilitating olfactory disorders. Results: A novel symptom (olfactory perseveration) was identified where a triggered, identifiable, and usually unpleasant olfactory percept persisted in the absence of an ongoing stimulus. Fluctuations in intensity and duration of perseveration, parosmia and phantosmia were observed. Coffee, meat, onion, and toothpaste were identified as common triggers of these disorders, but people struggled to describe the distortions, using words associated with disgust and revulsion. Common strategies to avoid triggers may result in a diet lacking in both nutrition and reward. The emotional aspect of living with qualitative olfactory dysfunction was evident and highlighted the detrimental impact on mental health. Conclusions: The data acquired can inform rehabilitation strategies and drive our ongoing research into understanding the molecular triggers associated with parosmia, and research into patient benefit.
The SARS-CoV-2 antibody landscape is lower in magnitude for structural proteins, diversified for accessory proteins and stable long-term in children

Background: Children are less clinically affected by SARS-CoV-2 infection than adults with the majority of cases being mild or asymptomatic and the differences in infection outcomes are poorly understood. The kinetics, magnitude and landscape of the antibody response may impact the clinical severity and serological diagnosis of COVID-19. Thus, a comprehensive investigation of the antibody landscape in children and adults is needed. Methods: We tested 254 plasma from 122 children with symptomatic and asymptomatic SARS-CoV-2 infections in Hong Kong up to 206 days post symptom onset, including 146 longitudinal samples from 58 children. Adult COVID-19 patients and pre-pandemic controls were included for comparison. We assessed antibodies to a 14-wide panel of SARS-CoV-2 structural and accessory proteins by Luciferase Immunoprecipitation System (LIPS). Findings: Children have lower levels of Spike and Nucleocapsid antibodies than adults, and their cumulative humoral response is more expanded to accessory proteins (NSP1 and Open Reading Frames (ORFs)). Sensitive serology using the three N, ORF3b, ORF8 antibodies can discriminate COVID-19 in children. Principal component analysis revealed distinct serological signatures in children and the highest contribution to variance were responses to non-structural proteins ORF3b, NSP1, ORF7a and ORF8. Longitudinal sampling revealed maintenance or increase of antibodies for at least 6 months, except for ORF7b antibodies which showed decline. It was interesting to note that children have higher antibody responses towards known IFN antagonists: ORF3b, ORF6 and ORF7a. The diversified SARS-CoV-2 antibody response in children may be an important factor in driving control of SARS-CoV-2 infection.
Assessing psychosis risk using quantitative markers of disorganised speech

Recent work has suggested that disorganised speech might be a powerful predictor of later psychotic illness in clinical high risk subjects. To that end, several automated measures to quantify disorganisation of transcribed speech have been proposed. However, it remains unclear which measures are most predictive of psychosis-onset, how different measures relate to each other and what the best strategies are to elicit disorganised speech from participants. Here, we assessed the ability of twelve automated Natural Language Processing markers to differentiate transcribed speech excerpts from subjects at clinical high risk for psychosis (N=25), first episode psychosis patients (N=16) and healthy control subjects (N=13; N=54 in total). In-line with previous work, several of these measures showed significant differences between groups, including semantic coherence and speech graph connectivity. We also proposed two additional measures of repetition and whether speech was on topic, the latter of which exhibited significant group differences and outperformed the prior, related measure of tangentiality. Most measures examined were only weakly related to each other, suggesting they provide complementary information and that combining different measures could provide additional power to predict the onset of psychotic illness. Finally, we compared the ability of transcribed speech generated using different tasks to differentiate the groups. Speech generated from picture descriptions of the Thematic Apperception Test and a story re-telling task outperformed free speech, suggesting that choice of speech generation method may be an important consideration. Overall, quantitative speech markers represent a promising direction for future diagnostic applications for psychosis risk.
The Joint Impact of COVID-19 Vaccination and Non-Pharmaceutical Interventions on Infections, Hospitalizations, and Mortality: An Agent-Based Simulation

Background: Vaccination against SAR-CoV-2 has the potential to significantly reduce transmission and COVID-19 morbidity and mortality. This modeling study simulated the comparative and joint impact of COVID-19 vaccine efficacy and coverage with and without non-pharmaceutical interventions (NPIs) on total infections, hospitalizations, and deaths. Methods: An agent-based simulation model was employed to estimate incident SARS-CoV-2 infections and COVID-19-associated hospitalizations and deaths over 1.5 years for the State of North Carolina, a population of roughly 10.5 million. Vaccine efficacy of 50% and 90% and vaccine coverage of 25%, 50%, and 75% (at the end of a 6-month distribution period) were evaluated. Six vaccination scenarios were simulated with NPIs (i.e., reduced mobility, school closings, face mask usage) maintained and removed during the period of vaccine distribution. Results: In the worst-case vaccination scenario (50% efficacy and 25% coverage), approximately 2.2 million new SARS-CoV-2 infections occurred with NPIs removed and approximately 900,000 infections with NPIs maintained. In contrast, in the best-case scenario (90% efficacy and 75% coverage), there were 458,087 new infections with NPIs maintained and 535,019 with NPIs maintained. When NPIs were removed, 50% efficacy and 75% coverage reduced infection risk by a greater magnitude than 90% efficacy and 25% coverage (absolute risk reduction 13% and 8%, respectively). Conclusion: Simulation results suggest that, as NPIs are removed, higher vaccination coverage with less efficacious vaccines can contribute to a larger reduction in risk of SAR-CoV-2 infection than compared to more efficacious vaccines at lower coverage. Furthermore, premature lifting of NPIs while vaccines are distributed may result in substantial increases in infections, hospitalizations, and deaths. Overall, our findings highlight the need for well-resourced and coordinated efforts to achieve high vaccine coverage and continued adherence to NPIs to end the current pandemic.
Response to Letter to the Editor on “Breast Cancer Resistance Protein (ABCG2) Determines Distribution of Genistein Phase II Metabolites: Reevaluation of the Roles of ABCG2 in the Disposition of Genistein”

The purpose of this letter is to respond to a comment made by Dr. Alvarez to our recently published article ([Yang et al., 2012][1]). We thank Dr. Alvarez for her interest and comments. We take this opportunity to reemphasize that the conclusion of our article breaks away from a conventional wisdom
Deep learning driven quantification of interstitial fibrosis in kidney biopsies

Interstitial fibrosis and tubular atrophy (IFTA) on a renal biopsy are strong indicators of disease chronicity and prognosis. Techniques that are typically used for IFTA grading remain manual, leading to variability among pathologists. Accurate IFTA estimation using computational techniques can reduce this variability and provide quantitative assessment by capturing the pathologic features. Using trichrome-stained whole slide images (WSIs) processed from human renal biopsies, we developed a deep learning (DL) framework that captured finer pathological structures at high resolution and overall context at the WSI-level to predict IFTA grade. WSIs (n=67) were obtained from The Ohio State University Wexner Medical Center (OSUWMC). Five nephropathologists independently reviewed them and provided fibrosis scores that were converted to IFTA grades: <=10% (None or minimal), 11-25% (Mild), 26-50% (Moderate), and >50% (Severe). The model was developed by associating the WSIs with the IFTA grade determined by majority voting (reference estimate). Model performance was evaluated on WSIs (n=28) obtained from the Kidney Precision Medicine Project (KPMP). There was good agreement on the IFTA grading between the pathologists and the reference estimate (Kappa=0.622). The accuracy of the DL model was 71.8% on OSUWMC and 65.0% on KPMP datasets, respectively. Identification of salient image regions by combining microscopic and WSI-level pathological features yielded visual representations that were consistent with the pathologist-based IFTA grading. Our approach to analyzing microscopic- and WSI-level changes in renal biopsies attempts to mimic the pathologist and provides a regional and contextual estimation of IFTA. Such methods can assist clinicopathologic diagnosis.
Laboratory biomarkers of COVID-19 disease severity and outcome: Findings from a developing country

Aim: To identify laboratory biomarkers that predict disease severity and outcome among COVID-19 patients admitted to the Millennium COVID-19 Care Center in Ethiopia. Methods: A retrospective cohort study was conducted among 429 RT-PCR confirmed COVID-19 patients who were on follow up from July to October 2020 and with complete clinical and laboratory data. Data was described using frequency tables. Robust Poisson regression model was used to identify predictors of COVID-19 disease severity where adjusted relative risk (RR), P-value and 95% CI for RR were used to test significance and interpretation of results. Binary Logistic regression model was used to assess the presence of statistically significant association between the explanatory variables and COVID-19 disease outcome where adjusted odds ratio, P-value and 95% CI for adjusted odds ratio were used for testing significance and interpretation of results Results: Among the 429 patients studied, 182 (42.4%) had Severe disease at admission and the rest 247 (57.6%) had Non-severe disease (15.6% mild and 42.0% moderate). Regarding disease outcome, 45 (10.5%) died and 384 (89.5%) were discharged alive. Age group (ARR= 1.779, 95% CI= 1.405- 2.252, p-value < 0.0001), Neutrophil to Lymphocyte ratio (NLR) (ARR= 4.769, 95% CI= 2.419 - 9.402 p-value <0.0001), Serum glutamic oxaloacetic transaminase (SGOT) (ARR= 1.358, 95% CI= 1.109- 1.662 p-value=0.003), Sodium (ARR= 1.321, 95% CI= 1.091- 1.600 p-value=0.004) and Potassium (ARR= 1.269, 95% CI= 1.059-1.521 p-value=0.010) were found to be significant predictors of COVID-19 disease severity. The following factors were significantly associated with COVID-19 disease outcome; age group (AOR= 2.767, 95% CI= 1.099 - 6.067, p-value=0.031), white blood cell count (AOR= 4.253, 95% CI= 1.918 - 9.429, p-value=0.0001) and sodium level (AOR= 3.435, 95% CI= 1.439, 8.198, p-value=0.005). Conclusions: The laboratory markers of NLR of above three, raised SGOT and deranged sodium and potassium levels (both hypo- and hyper-states) were found to be significant predictors of developing severe COVID-19 disease. In addition, deranged values of white blood cell count and sodium levels were significantly associated with worse outcome of the disease. Therefore, assessing and monitoring these laboratory markers at the earliest stage of the disease could have a considerable impact in halting disease progression and death. Key words: COVID-19, Laboratory biomarkers, retrospective cohort, robust Poisson regression, logistic regression model, Ethiopia
The Impact of the November 2020 English National Lockdown on COVID-19 case counts

In the UK the epidemic of COVID-19 continues to pose a significant threat to public health. On the 14th October the English government introduced a tier system for control of the epidemic but just 3 weeks later a National lockdown across all areas of England was implemented. When English areas emerged from Lockdown many were placed in different tiers (most typically moved up at least one tier). However, the effectiveness of the tier system has been challenged by the emergence of a new variant of SARS-CoV-2 which appears to be much more infectious. In addition, from early November a trial mass testing service was being run in Liverpool. We used publicly available data of daily cases by local authority (local government areas) and estimated the reproductive rate (R value) of the epidemic based on 7-day case numbers compared with the previous 7-day period. There was a clear surge in infections from a few days before to several days after the lockdown was implemented. But this surge was almost exclusively associated with Tier 1 and Tier 2 authorities. In Tier 3 authorities where hospitality venues were only allowed to operate as restaurants there was no such surge. After this initial surge, cases declined in all three tiers with the R value dropping to a mean of about 0.7 independent of tier. London, The South East and East of England Regions saw rising infection rates in the last week or so of lockdown primarily in children of secondary school age. We could find no obvious benefit of the trial mass screening programme in Liverpool city. We conclude that in Tiers 1 and 2 much of the beneficial impact of the national lockdown was lost probably because of the leak of its likely implementation five days early leading to increased socialising in these areas before the start of lockdown. We further conclude that given that the new variant is estimated to have an R value of between 0.39 and 0.93 greater than previous variants, any lockdown as strict as the November one would be insufficient to reverse the increase in infections by itself. The value of city-wide mass testing to control the epidemic remains uncertain.
Race and ethnicity do not impact eligibility for remdesivir: A single-center experience

As the Coronavirus-2019 (COVID-19) pandemic continues, multiple therapies are rapidly being tested for efficacy in clinical trials. Clinical trials should be racially and ethnically representative of the population that will eventually benefit from these medications. There are multiple potential barriers to racial and ethnic minority enrollment in clinical trials, one of which could be that inclusion and exclusion criteria select for certain racial or ethnic groups disproportionately. In this observational cohort study at a single health care system, we examined if there were differences in eligibility for treatment with remdesivir based on clinical trial criteria for racial and ethnic minorities compared to non-Hispanic Whites. 201 electronic medical record charts were reviewed manually. Self-identified Whites were older than other racial or ethnic groups. At the time of presentation, Black, Latinx, and White participants met inclusion criteria for remdesivir at similar rates (72%, 80%, and 73% respectively), exclusion criteria at similar rates (43%, 38% and 49% for Black, Latinx and White participants respectively). In this study, there was no difference in eligibility for remdesivir based on race or ethnicity alone.