Chemistry of Protein-Phenolic Interactions Toward the Microbiota and Microbial Infections

Along with health concerns, interest in plants as food and bioactive phytochemical sources has been increased in the last few decades. Phytochemicals as secondary plant metabolites have been the subject of many studies in different fields. Breakthrough for research interest on this topic is re-juvenilized with rising relevance in this global pandemics\u27 era. The recent COVID-19 pandemic attracted the attention of people to viral infections and molecular mechanisms behind these infections. Thus, the core of the present review is the interaction of plant phytochemicals with proteins as these interactions can affect the functions of co-existing proteins, especially focusing on microbial proteins. To the best of our knowledge, there is no work covering the protein-phenolic interactions based on their effects on microbiota and microbial infections. The present review collects and defines the recent data, representing the interactions of phenolic compounds -primarily flavonoids and phenolic acids- with various proteins and explores how these molecular-level interactions account for the human health directly and/or indirectly, such as increased antioxidant properties and antimicrobial capabilities. Furthermore, it provides an insight about the further biological activities of interacted protein-phenolic structure from an antiviral activity perspective. The research on the protein-phenolic interaction mechanisms is of great value for guiding how to take advantage of synergistic effects of proteins and polyphenolics for future medical and nutritive approaches and related technologies

Functional linear models for interval-valued data

Aggregation of large databases in a specific format is a frequently used process to make the data easily manageable. Interval-valued data is one of the data types that is generated by such an aggregation process. Using traditional methods to analyze interval-valued data results in loss of information, and thus, several interval-valued data models have been proposed to gather reliable information from such data types. On the other hand, recent technological developments have led to high dimensional and complex data in many application areas, which may not be analyzed by traditional techniques. Functional data analysis is one of the most commonly used techniques to analyze such complex datasets. While the functional extensions of much traditional statistical techniques are available, the functional form of the interval-valued data has not been studied well. This article introduces the functional forms of some well-known regression models that take interval-valued data. The proposed methods are based on the function-on-function regression model, where both the response and predictor/s are functional. Through several Monte Carlo simulations and empirical data analysis, the finite sample performance of the proposed methods is evaluated and compared with the state-of-the-art

Thyroid function in healthy and unhealthy preterm newborns

Background: The thyroid gland and hormonal regulation are among the most important systems to be investigated in pre-term infants. This study sought to investigate thyroid hormone levels of healthy and unhealthy pre-term infants. Methods: The prospective study included 53 consecutive premature infants admitted to the neonatal intensive care unit within a duration of one year. Of these preterm babies, 20 were healthy, while 33 had problems such as asphyxia or RDS. Venous blood samples were collected at baseline 0-24 hours, 7 and 14 days and FT3, FT4, and TSH levels were determined. Other data recorded included demographic characteristics of the patients and clinical variables. Results: The most frequent health problems were RDS (87.9%), sepsis (30.3%), and retinopathy of prematurity (24.2%). The mean TSH levels showed a consistent decline at three consequent measurements in both groups, which were always significantly lower in unhealthy pre-terms. In both groups, TSH levels showed significant decreases on Day 7 and Day 14 compared to the baseline levels (p<005). The levels of FT3 and FT4 consistently showed significant correlations with gestational week and birth weight at each of the three measurements. Conclusion: Pre-term infants, especially those having problems, have significant hypothyroxinemia that may require thyroid hormone replacement therapy

A comparative ID migraine screener study in ophthalmology, ENT and neurology out-patient clinics

Migraine is more likely to be misdiagnosed in patients with comorbid diseases. Not only primary care physicians, but also specialists might misdiagnose it due to the lack of diagnostic criteria awareness. The ID migraine test is a reliable screening instrument that may facilitate and accelerate migraine recognition. This study aimed to compare the prevalence and characteristics of migraine in a large sample of patients admitted to clinics of ophthalmology (OC), ear, nose and throat diseases (ENTC) and neurology (NC), as well as to validate the use of the ID migraine test in OC and ENTC settings. This was a multicentre (11 cites) study of out-patients admitting either to NC, ENTC or OC of the study sites during five consecutive working days within 1 week. From each of the clinics, 100 patients were planned to be recruited. All recruited patients were interviewed and those having a headache complaint received an ID migraine test and were examined for headache diagnosis by a neurologist, blinded to the ID migraine test result. A total of 2625 subjects were recruited. Only 1.3% of OC patients and 5.4% of ENTC patients have been admitted with a primary complaint of headache, whereas the percentage of NC patients suffering from headache was 37.6%. Whereas 138 patients (19.3%) in OC, 154 (17.3%) in ENTC and 347 (34%) in NC were found to be ID migraine test positive, 149 patients (20.8%) in OC, 142 (16%) in ENTC and 338 (33.1%) in NC were diagnosed with migraine. The sensitivity, specificity, and positive and negative predictive ratios of the ID migraine test were found to be similar in all clinics. An important fraction of the patients admitted to NC, as well as to OC and ENTC, for headache and/or other complaints were found out to have migraine by means of a simple screening test. This study validated the ID migraine test as a sensitive and specific tool in OC and ENTC, encouraging its use as a screening instrument.Pfizer-Türkiy

Non-Standard Errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants

Combined searches for the production of supersymmetric top quark partners in proton-proton collisions at root s=13 TeV

A combination of searches for top squark pair production using proton-proton collision data at a center-of-mass energy of 13 TeV at the CERN LHC, corresponding to an integrated luminosity of 137 fb(-1) collected by the CMS experiment, is presented. Signatures with at least 2 jets and large missing transverse momentum are categorized into events with 0, 1, or 2 leptons. New results for regions of parameter space where the kinematical properties of top squark pair production and top quark pair production are very similar are presented. Depending on themodel, the combined result excludes a top squarkmass up to 1325 GeV for amassless neutralino, and a neutralinomass up to 700 GeV for a top squarkmass of 1150 GeV. Top squarks with masses from 145 to 295 GeV, for neutralino masses from 0 to 100 GeV, with a mass difference between the top squark and the neutralino in a window of 30 GeV around the mass of the top quark, are excluded for the first time with CMS data. The results of theses searches are also interpreted in an alternative signal model of dark matter production via a spin-0 mediator in association with a top quark pair. Upper limits are set on the cross section for mediator particle masses of up to 420 GeV