On the derivatives of a family of analytic functions

For $\beta< 1$, n = 0, 1, 2, . . ., and $-\pi <\alpha\leq\pi$, we let $M_n(\alpha,\beta)$ denote the family of functions $f(z) = z +\ldots$ that are analytic in the unit disk and satisfy there the condition $Re\{(D^n f)'+\frac{1+e^{i\alpha}}{2(n+1)}z(D^n f)''\}>\beta$, where $D^n f(z)$ is the Hadamard product or convolution of f with $z/(1 − z){n+1}$. We prove the inclusion relations $M_{n+1}(\alpha,\beta) \subset M_n(\alpha,\beta$, and $M_n(\alpha,\beta) < M_n(\pi,\beta), \beta < 1$. Extreme points, as well as integral and convolution characterizations, are found. This leads to coefficient bounds and other extremal properties. The special cases $M_0(\alpha,0)\equiv \mathcal{L}_\alpha$, $M_n(\pi,\beta)\equiv M_n(\beta)$ have previously been studied [16], [1]

On Some Subclasses of Harmonic Functions Defined by Fractional Calculus

The purpose of this paper is to study subclasses of normalized harmonic functions with positive real part using fractional derivative. Sharp estimates for coefficients and distortion theorems are given

COVID-19 Disease Severity in Persons Infected with Omicron BA.1 and BA.2 Sublineages and Association with Vaccination Status

[No abstract available

Infinite ergodic theory and Non-extensive entropies

We bring into account a series of result in the infinite ergodic theory that we believe that they are relevant to the theory of non-extensive entropie

Complement C5a and clinical markers as predictors of COVID-19 disease severity and mortality in a multi-ethnic population

Coronavirus disease-2019 (COVID-19) was declared as a pandemic by WHO in March 2020. SARS-CoV-2 causes a wide range of illness from asymptomatic to life-threatening. There is an essential need to identify biomarkers to predict disease severity and mortality during the earlier stages of the disease, aiding treatment and allocation of resources to improve survival. The aim of this study was to identify at the time of SARS-COV-2 infection patients at high risk of developing severe disease associated with low survival using blood parameters, including inflammation and coagulation mediators, vital signs, and pre-existing comorbidities. This cohort included 89 multi-ethnic COVID-19 patients recruited between July 14th and October 20th 2020 in Doha, Qatar. According to clinical severity, patients were grouped into severe (n=33), mild (n=33) and asymptomatic (n=23). Common routine tests such as complete blood count (CBC), glucose, electrolytes, liver and kidney function parameters and markers of inflammation, thrombosis and endothelial dysfunction including complement component split product C5a, Interleukin-6, ferritin and C-reactive protein were measured at the time COVID-19 infection was confirmed. Correlation tests suggest that C5a is a predictive marker of disease severity and mortality, in addition to 40 biological and physiological parameters that were found statistically significant between survivors and non-survivors. Survival analysis showed that high C5a levels, hypoalbuminemia, lymphopenia, elevated procalcitonin, neutrophilic leukocytosis, acute anemia along with increased acute kidney and hepatocellular injury markers were associated with a higher risk of death in COVID-19 patients. Altogether, we created a prognostic classification model, the CAL model (C5a, Albumin, and Lymphocyte count) to predict severity with significant accuracy. Stratification of patients using the CAL model could help in the identification of patients likely to develop severe symptoms in advance so that treatments can be targeted accordingly

SnoRNAs and miRNAs networks underlying COVID-19 disease severity

There is a lack of predictive markers for early and rapid identification of disease progression in COVID-19 patients. Our study aims at identifying microRNAs (miRNAs)/small nucleolar RNAs (snoRNAs) as potential biomarkers of COVID-19 severity. Using differential expression analysis of microarray data (n = 29), we identified hsa-miR-1246, ACA40, hsa-miR-4532, hsa-miR-145-5p, and ACA18 as the top five differentially expressed transcripts in severe versus asymptomatic, and ACA40, hsa-miR-3609, ENSG00000212378 (SNORD78), hsa-miR-1231, hsa-miR-885-3p as the most significant five in severe versus mild cases. Moreover, we found that white blood cell (WBC) count, absolute neutrophil count (ANC), neutrophil (%), lymphocyte (%), red blood cell (RBC) count, hemoglobin, hematocrit, D-Dimer, and albumin are significantly correlated with the identified differentially expressed miRNAs and snoRNAs. We report a unique miRNA and snoRNA profile that is associated with a higher risk of severity in a cohort of SARS-CoV-2 infected patients. Altogether, we present a differential expression analysis of COVID-19-associated microRNA (miRNA)/small nucleolar RNA (snoRNA) signature, highlighting their importance in SARS-CoV-2 infection

Performance evaluation of five ELISA kits for detecting anti-SARS-COV-2 IgG antibodies

ObjectivesTo evaluate and compare the performances of five commercial ELISA assays (EDI, AnshLabs, Dia.Pro, NovaTec, and Lionex) for detecting anti-SARS-CoV-2 IgG. Methods70 negative control samples (collected before the COVID-19 pandemic) and samples from 101 RT-PCR-confirmed SARS-CoV-2 patients (collected at different time points from symptoms onset: ≤7, 8-14, and >14 days) were used to compare the sensitivity, specificity, agreement, positive and negative predictive values of each assay with RT-PCR. A concordance assessment between the five assays was also conducted. Cross-reactivity with other HCoV, non-HCoV respiratory viruses, non-respiratory viruses, and nuclear antigens was investigated. ResultsLionex showed the highest specificity (98.6%, 95%CI: 92.3-99.8), followed by EDI and Dia.Pro (97.1%, 95%CI: 90.2-99.2), NovaTec (85.7%, 95%CI: 75.7-92.1), then AnshLabs (75.7%, 95%CI: 64.5-84.2). All ELISA kits cross-reacted with one anti-MERS IgG positive sample except Lionex. The sensitivity was low during the early stages of the disease but improved over time. After 14 days from symptoms onset, Lionex and NovaTec showed the highest sensitivity at 87.9% (95%CI: 72.7-95.2) and 86.4% (95%CI: 78.5-91.7), respectively. The agreement with RT-PCR results based on Cohen’s kappa was as follows: Lionex (0.89)> NovaTec (0.70)> Dia.Pro (0.69)> AnshLabs (0.63)> EDI (0.55). ConclusionThe Lionex ELISA, which measures antibodies solely to the S1 protein, demonstrated the best performance.This work was made possible by grant No. RRC-2-032 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors. GKN would like to acknowledge funds from Qatar University's internal grant QUERG-CMED-2020-2

Herd immunity against severe acute respiratory syndrome coronavirus 2 infection in 10 communities, qatar

We investigated what proportion of the population acquired severe acute respiratory syndrome coronavirus 2 (SARSCoV- 2) infection and whether the herd immunity threshold has been reached in 10 communities in Qatar. The study included 4,970 participants during June 21-September 9, 2020. Antibodies against SARS-CoV-2 were detected by using an electrochemiluminescence immunoassay. Seropositivity ranged from 54.9% (95% CI 50.2%-59.4%) to 83.8% (95% CI 79.1%-87.7%) across communities and showed a pooled mean of 66.1% (95% CI 61.5%-70.6%). A range of other epidemiologic measures indicated that active infection is rare, with limited if any sustainable infection transmission for clusters to occur. Only 5 infections were ever severe and 1 was critical in these young communities; infection severity rate of 0.2% (95% CI 0.1%-0.4%). Specifi c communities in Qatar have or nearly reached herd immunity for SARS-CoV-2 infection: 65%-70% of the population has been infected.This study was supported by the Hamad Medical Corporation, Ministry of Public Health, and the Biomedical Research Program and the Biostatistics, Epidemiology, and Biomathematics Research Core, both atScopu

SARS-CoV-2 infection hospitalization, severity, criticality, and fatality rates in Qatar.

The SARS-CoV-2 pandemic resulted in considerable morbidity and mortality as well as severe economic and societal disruptions. Despite scientific progress, true infection severity, factoring both diagnosed and undiagnosed infections, remains poorly understood. This study aimed to estimate SARS-CoV-2 age-stratified and overall morbidity and mortality rates based on analysis of extensive epidemiological data for the pervasive epidemic in Qatar, a country where < 9% of the population are ≥ 50 years. We show that SARS-CoV-2 severity and fatality demonstrate a striking age dependence with low values for those aged < 50 years, but rapidly growing rates for those ≥ 50 years. Age dependence was particularly pronounced for infection criticality rate and infection fatality rate. With Qatar's young population, overall SARS-CoV-2 severity and fatality were not high with < 4 infections in every 1000 being severe or critical and < 2 in every 10,000 being fatal. Only 13 infections in every 1000 received any hospitalization in acute-care-unit beds and < 2 in every 1000 were hospitalized in intensive-care-unit beds. However, we show that these rates would have been much higher if Qatar's population had the demographic structure of Europe or the United States. Epidemic expansion in nations with young populations may lead to considerably lower disease burden than currently believed

SARS-CoV-2 infection hospitalization, severity, criticality, and fatality rates

AbstractBackgroundThis study aimed to estimate the age-stratified and overall morbidity and mortality rates of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection based on an analysis of the pervasive SARS-CoV-2 epidemic in Qatar, a country with &lt;9% of the population being ≥50 years of age.MethodsInfection disease outcomes were investigated using a Bayesian approach applied to an age-structured mathematical model describing SARS-CoV-2 transmission and disease progression in the population. The model was fitted to infection and disease time-series and age-stratified data. Two separate criteria for classifying morbidity were used: one based on actual recorded hospital admission (acute-care or intensive-care-unit hospitalization) and one based on clinical presentation as per World Health Organization classification of disease severity or criticality.ResultsAll outcomes showed very strong age dependence, with low values for those &lt;50 years of age, but rapidly growing rates for those ≥50 years of age. The strong age dependence was particularly pronounced for infection criticality rate and infection fatality rate. Infection acute-care and intensive-care-unit bed hospitalization rates were estimated at 13.10 (95% CI: 12.82-13.24) and 1.60 (95% CI: 1.58-1.61) per 1,000 infections, respectively. Infection severity and criticality rates were estimated at 3.06 (95% CI: 3.01-3.10) and 0.68 (95% CI: 0.67-0.68) per 1,000 infections, respectively. Infection fatality rate was estimated at 1.85 (95% CI: 1.74-1.95) per 10,000 infections.ConclusionsSARS-CoV-2 severity and fatality in Qatar was not high and demonstrated a very strong age dependence with &lt;4 infections in every 1,000 being severe or critical and &lt;2 in every 10,000 being fatal. Epidemic expansion in nations with young populations may lead to lower disease burden than previously thought.</jats:sec