POST COVID MANAGEMENT OF ASTHMA IN CHRONIC ASTHMA PATIENT

Asthma is defined as a chronic inflammatory disease of the airways. The chronic inflammation is associated with airway hyper responsiveness (an exaggerated airway narrowing response to triggers, such as allergens and exercise), that leads to recurrent symptoms such as wheezing, dyspnea (shortness of breath), chest tightness and coughing. Asthma is associated with T helper cell type-2 (Th2) immune responses, which are typical of other atopic conditions. Various allergic (e.g., dust mites, cockroach residue, furred animals, moulds, pollens) and non-allergic (e.g., infections, tobacco smoke, cold air, exercise) triggers produce a cascade of immune-mediated events leading to chronic airway inflammation. The Present Review Discuss and Focus about the various Risk factor associated with Covid 19 influenced Asthma Patient with their Possible Management

Giant Magnetoimpedance Sensor for Structural Integrity Assessment of Engineering Components

Investigation is focused on the development of sensor based on giant magnetoimpedance (GMI) effect using soft magnetic Co66Fe2Si13B15Cr4 amorphous wire as sensing (core) element. The GMI property of the sensing element was utilized for fabrication of the sensor which is sensitive to the minute variation of the local magnetic field. The sensor output signal is calibrated with respect to external applied magnetic field and the sensitivity is found to be 56.11 mV/µT. The sensor shows a good linear response and its repeatability and reproducibility are observed to be satisfactory. The sensor is very much useful for detection of the localized magnetic field of service exposed engineering components within an external magnetic field using GMI sensor, and more specifically, to develop a GMI sensor for efficient monitoring of structural integrity of engineering components. The conventional non-destructive techniques like ultrasonic, eddy current, magnetic particle inspection are very useful to identify the defects or cracks. However, these methods are unsuitable for monitoring structural degradation. Since most of the structural components used in the industry are of ferromagnetic steel, the microstructural properties of the components due to their long service period influence the magnetic and mechanical properties. Therefore, the developed sensor could be used to detect the local magnetic field of the aging structure which changes with the microstructure of the component and thereby, assessing the integrity of the components

Development of GMI Based Sensing Device for Identification of Magnetic Phases in Steel

A giant magnetoimpedance (GMI) sensor based on CoFeSiBCr soft magnetic amorphous microwire of diameter 100 µm as a sensing element has been developed and the performances of the GMI sensor are carefully studied. The sensor measures the phase shift of the modulated signal in terms of voltage using balanced modulator/demodulator topology which has been calibrated in terms of localized magnetic field. The sensor shows a good linear response with the magnetic field. It has been tested at different conditions and repeatable of data has been observed. The sensitivity of the sensor has been observed to be 0.12 mV/Am-1. The sensor can be used to identify various magnetic phases in semi finished steel products. For an example, in duplex stainless steel where the material has austenite and ferrite components, the developed sensor can be utilized for the evaluation of volume fraction of each phase. Similarly, in 304 SS which undergoes stress induced martensite transformation can also be evaluated using the developed sensor

On the Microcanonical Entropy of a Black Hole

It has been suggested recently that the microcanonical entropy of a system may be accurately reproduced by including a logarithmic correction to the canonical entropy. In this paper we test this claim both analytically and numerically by considering three simple thermodynamic models whose energy spectrum may be defined in terms of one quantum number only, as in a non-rotating black hole. The first two pertain to collections of noninteracting bosons, with logarithmic and power-law spectra. The last is an area ensemble for a black hole with equi-spaced area spectrum. In this case, the many-body degeneracy factor can be obtained analytically in a closed form. We also show that in this model, the leading term in the entropy is proportional to the horizon area A, and the next term is ln A with a negative coefficient.Comment: 15 pages, 1 figur

Ab initio determination of the lifetime of the 62P3/26^2P_{3/2} state f or 207Pb+^{207}Pb^+ by relativistic many-body theory

Relativistic coupled-cluster(RCC) theory has been employed to calculate the life time of the $6 ^2P_{3/2}$ state of single ionized lead($^{207}Pb$) to an accurac y of 3% and compared with the corresponding value obtained using second order r elativistic many-body perturbation theory(RMBPT). This is one of the very few ap plications of this theory to excited state properties of heavy atomic systems. C ontributions from the different electron correlation effects are given explicitl y

(5′S)-8,5′-Cyclo-2′-deoxyguanosine Is a Strong Block to Replication, a Potent pol V-Dependent Mutagenic Lesion, and Is Inefficiently Repaired in Escherichia coli

8,5′-Cyclopurines, making up an important class of ionizing radiation-induced tandem DNA damage, are repaired only by nucleotide excision repair (NER). They accumulate in NER-impaired cells, as in Cockayne syndrome group B and certain Xeroderma Pigmentosum patients. A plasmid containing (5′S)-8,5′-cyclo-2′-deoxyguanosine (S-cdG) was replicated in Escherichia coli with specific DNA polymerase knockouts. Viability was \u3c1% in the wild-type strain, which increased to 5.5% with SOS. Viability decreased further in a pol II- strain, whereas it increased considerably in a pol IV- strain. Remarkably, no progeny was recovered from a pol V- strain, indicating that pol V is absolutely required for bypassing S-cdG. Progeny analyses indicated that S-cdG is significantly mutagenic, inducing ∼34% mutation with SOS. Most mutations were S-cdG → A mutations, though S-cdG → T mutation and deletion of 5′C also occurred. Incisions of purified UvrABC nuclease on S-cdG, S-cdA, and C8-dG-AP on a duplex 51-mer showed that the incision rates are C8-dG-AP \u3e S-cdA \u3e S-cdG. In summary, S-cdG is a major block to DNA replication, highly mutagenic, and repaired slowly in E. coli

Incorporation of enzyme concentrations into FBA and identification of optimal metabolic pathways

<p>Abstract</p> <p>Background</p> <p>In the present article, we propose a method for determining optimal metabolic pathways in terms of the level of concentration of the enzymes catalyzing various reactions in the entire metabolic network. The method, first of all, generates data on reaction fluxes in a pathway based on steady state condition. A set of constraints is formulated incorporating weighting coefficients corresponding to concentration of enzymes catalyzing reactions in the pathway. Finally, the rate of yield of the target metabolite, starting with a given substrate, is maximized in order to identify an optimal pathway through these weighting coefficients.</p> <p>Results</p> <p>The effectiveness of the present method is demonstrated on two synthetic systems existing in the literature, two pentose phosphate, two glycolytic pathways, core carbon metabolism and a large network of carotenoid biosynthesis pathway of various organisms belonging to different phylogeny. A comparative study with the existing extreme pathway analysis also forms a part of this investigation. Biological relevance and validation of the results are provided. Finally, the impact of the method on metabolic engineering is explained with a few examples.</p> <p>Conclusions</p> <p>The method may be viewed as determining an optimal set of enzymes that is required to get an optimal metabolic pathway. Although it is a simple one, it has been able to identify a carotenoid biosynthesis pathway and the optimal pathway of core carbon metabolic network that is closer to some earlier investigations than that obtained by the extreme pathway analysis. Moreover, the present method has identified correctly optimal pathways for pentose phosphate and glycolytic pathways. It has been mentioned using some examples how the method can suitably be used in the context of metabolic engineering.</p

Global, regional, and national burden of chronic kidney disease, 1990–2017 : a systematic analysis for the Global Burden of Disease Study 2017

Background Health system planning requires careful assessment of chronic kidney disease (CKD) epidemiology, but data for morbidity and mortality of this disease are scarce or non-existent in many countries. We estimated the global, regional, and national burden of CKD, as well as the burden of cardiovascular disease and gout attributable to impaired kidney function, for the Global Burden of Diseases, Injuries, and Risk Factors Study 2017. We use the term CKD to refer to the morbidity and mortality that can be directly attributed to all stages of CKD, and we use the term impaired kidney function to refer to the additional risk of CKD from cardiovascular disease and gout. Methods The main data sources we used were published literature, vital registration systems, end-stage kidney disease registries, and household surveys. Estimates of CKD burden were produced using a Cause of Death Ensemble model and a Bayesian meta-regression analytical tool, and included incidence, prevalence, years lived with disability, mortality, years of life lost, and disability-adjusted life-years (DALYs). A comparative risk assessment approach was used to estimate the proportion of cardiovascular diseases and gout burden attributable to impaired kidney function. Findings Globally, in 2017, 1·2 million (95% uncertainty interval [UI] 1·2 to 1·3) people died from CKD. The global all-age mortality rate from CKD increased 41·5% (95% UI 35·2 to 46·5) between 1990 and 2017, although there was no significant change in the age-standardised mortality rate (2·8%, −1·5 to 6·3). In 2017, 697·5 million (95% UI 649·2 to 752·0) cases of all-stage CKD were recorded, for a global prevalence of 9·1% (8·5 to 9·8). The global all-age prevalence of CKD increased 29·3% (95% UI 26·4 to 32·6) since 1990, whereas the age-standardised prevalence remained stable (1·2%, −1·1 to 3·5). CKD resulted in 35·8 million (95% UI 33·7 to 38·0) DALYs in 2017, with diabetic nephropathy accounting for almost a third of DALYs. Most of the burden of CKD was concentrated in the three lowest quintiles of Socio-demographic Index (SDI). In several regions, particularly Oceania, sub-Saharan Africa, and Latin America, the burden of CKD was much higher than expected for the level of development, whereas the disease burden in western, eastern, and central sub-Saharan Africa, east Asia, south Asia, central and eastern Europe, Australasia, and western Europe was lower than expected. 1·4 million (95% UI 1·2 to 1·6) cardiovascular disease-related deaths and 25·3 million (22·2 to 28·9) cardiovascular disease DALYs were attributable to impaired kidney function. Interpretation Kidney disease has a major effect on global health, both as a direct cause of global morbidity and mortality and as an important risk factor for cardiovascular disease. CKD is largely preventable and treatable and deserves greater attention in global health policy decision making, particularly in locations with low and middle SDI

Gradient Descent Optimization in Gene Regulatory Pathways

BACKGROUND: Gene Regulatory Networks (GRNs) have become a major focus of interest in recent years. Elucidating the architecture and dynamics of large scale gene regulatory networks is an important goal in systems biology. The knowledge of the gene regulatory networks further gives insights about gene regulatory pathways. This information leads to many potential applications in medicine and molecular biology, examples of which are identification of metabolic pathways, complex genetic diseases, drug discovery and toxicology analysis. High-throughput technologies allow studying various aspects of gene regulatory networks on a genome-wide scale and we will discuss recent advances as well as limitations and future challenges for gene network modeling. Novel approaches are needed to both infer the causal genes and generate hypothesis on the underlying regulatory mechanisms. METHODOLOGY: In the present article, we introduce a new method for identifying a set of optimal gene regulatory pathways by using structural equations as a tool for modeling gene regulatory networks. The method, first of all, generates data on reaction flows in a pathway. A set of constraints is formulated incorporating weighting coefficients. Finally the gene regulatory pathways are obtained through optimization of an objective function with respect to these weighting coefficients. The effectiveness of the present method is successfully tested on ten gene regulatory networks existing in the literature. A comparative study with the existing extreme pathway analysis also forms a part of this investigation. The results compare favorably with earlier experimental results. The validated pathways point to a combination of previously documented and novel findings. CONCLUSIONS: We show that our method can correctly identify the causal genes and effectively output experimentally verified pathways. The present method has been successful in deriving the optimal regulatory pathways for all the regulatory networks considered. The biological significance and applicability of the optimal pathways has also been discussed. Finally the usefulness of the present method on genetic engineering is depicted with an example

Structures of (5′S)-8,5′-Cyclo-2′-deoxyguanosine Mismatched with dA or dT

pubs.acs.org/cr