Premature Stage Research Articles

Nonsteroidal anti-inflammatory drugs as antipyretics and modulators of a molecular clock(s) in the appendix of Sauromatum venosum inflorescence.

The appendix of the Sauromatum senosum inflorescence is a striking example of thermogenesis in plants. On the day of opening, the Sauromatum appendix becomes hot, reaching up to 32 °C. Aspirin, salicylic acid and 2,6-dihydroxybenzoic acid, a subclass of NSAIDs, induce a temperature rise from three mitochondrial sources: alternative oxidase, F1 FO -ATP synthase and adenine nucleotide translocator. This temperature rise is synchronized and compounded under various light/dark regimes. We studied the effect of different subgroups of NSAIDs on the temperature rise. Tissue slices of appendix of Sauromatum and Arum italicum inflorescences at a pre-mature stage were treated with the three inducers in combination with one NSAID under constant light or darkness and under different photoperiods. Temperature rise generated by the three heat sources in the presence of inducers and different non-selective NSAIDs were not compounded and occurred at three different times. Under constant light, DuP-697, ibuprofen, flurbiprofen, acetaminophen and diclofenac suppressed the temperature rise induced by the three salicylates. Desynchronization and delayed temperature rise were detected with 6/42-h light/ dark and 15/33-h light/dark regimes in the presence of celecoxib and ibuprofen. With a 24/24-h light/dark regime, temperature rise was suppressed in the presence of ibuprofen. There were differences in response to individual NSAIDs between appendix tissue of A. italicum and S. venosum. Mitochondrial energy balance is affected by NSAIDs. There is an interaction between light/dark regime and temperature rise and a relationship between timing mechanism and temperature rise.

Molecular Genomic Study of Inhibin Molecule Production through Granulosa Cell Gene Expression in Inhibin-Deficient Mice.

Inhibin is a molecule that belongs to peptide hormones and is excreted through pituitary gonadotropins stimulation action on the granulosa cells of the ovaries. However, the differential regulation of inhibin and follicle-stimulating hormone (FSH) on granulosa cell tumor growth in mice inhibin-deficient females is not yet well understood. The objective of this study was to evaluate the role of inhibin and FSH on the granulosa cells of ovarian follicles at the premature antral stage. This study stimulated immature wild-type (WT) and Inhibin-α knockout (Inha−/−) female mice with human chorionic gonadotropin (hCG) and examined hCG-induced gene expression changes in granulosa cells. Also, screening of differentially expressed genes (DEGs) was performed in the two groups under study. In addition, related modules to external traits and key gene drivers were determined through Weighted Gene Co-Expression Network Analysis (WGCNA) algorithm. The results identified a number of 1074 and 931 DEGs and 343 overlapping DEGs (ODEGs) were shared in the two groups. Some 341 ODEGs had high relevance and consistent expression direction, with a significant correlation coefficient (r2 = 0.9145). Additionally, the gene co-expression network of selected 153 genes showed 122 nodes enriched to 21 GO biological processes (BP) and reproduction and 3 genes related to genomic pathways. By using principal component analysis (PCA), the 14 genes in the regulatory network were fixed and the cumulative proportion of fitted top three principal components was 94.64%. In conclusion, this study revealed the novelty of using ODEGs for investigating the inhibin and FSH hormone pathways that might open the way toward gene therapy for granulosa cell tumors. Also, these genes could be used as biomarkers for tracking the changes in inhibin and FSH hormone from the changes in the nutrition pattern.

Detection and classification of tumor in brain using visual geometry group

Now a day’s brain tumor detection is an important matter in computer aided diagnosis for medical applications. The classification process is important and plays a vital role to diagnosis the brain tumors. The existing method concentrates on brain tumor detection, features extraction and classification. Though the traditional classification Algorithms is suffered from less accuracy and takes more time for execution. To enhance the premature stage brain tumor detection and classification, the main intension of this paper is to extract features, classification of brain tumor using VGG-16 Architecture. By using this method we achieved maximum accuracy of 99%, minimum loss, less time for execution,F1 score, sensitivity etc., as compare to CNN, for this method execution we collected the data from kaggle dataset, Brain MRI images of 2065 patients, out of which 1445 images are cancerous and 620 images are non cancerous.

ESG Disclosure and the Cost of Capital: Is There a Ratcheting Effect over Time?

In recent years, the CSR disclosure–firm risk relationship has raised the acute interest of capital providers, regulators, debtholders, and academic researchers. In addition to the mounting corporate social responsibility (CSR) disclosure issues, one particular area that has increasingly attracted the attention of academics, practitioners, and policymakers is the dynamic of CSR disclosure. The effects of institutional pressures and the relative nature of reputation have amplified expectations over time, resulting in a dynamic CSR disclosure strategy to meet those expectations. However, studies on the relationship between CSR disclosure and firm risk over time are still in their premature stages. Thus, this paper seeks to contribute to the literature on firm risk and CSR disclosure by examining the effect of ESG disclosure on the cost of capital over time. The study examines a sample of 430 S&P 500 US firms observed over the 2011 to 2019 period. Our results indicate that the three dimensions do not have the same effect. Governance disclosure decreases the cost of capital during the first years, and in later years, the effect becomes positive. Over time, social disclosure increases the cost of capital. However, environmental disclosure shows a negative and significant effect on the cost of capital during the first years but no significant effect later in time. Our results contribute to explaining the dynamic effect of CSR disclosure. A predominant feature to consider is the evolution of CSR disclosure over time. Steadily, US firms are moving away from some CSR disclosure activities to others. However, firms that abandoned some existing CSR disclosure commitments may face aggressive responses from stakeholders. US firms have to be more cautious when linking CSR disclosure to firm risk over time, recognizing the long-term benefits and drawbacks of CSR disclosure.

Academic reading as a social practice in higher education

In this study, an undergraduate teacher education course is used to explore whether and how academic reading seminars reflect the theoretical notion of academic literacies and provide a learning environment for developing academic and professional learning and engagement. The data analyzed in this article are transcribed recordings of small group activities where students discuss scientific articles based on a template. First, our empirical analysis shows that the use of the template facilitated dialogical discussions and the development of a cognitive skillset and disciplinary categories when used in a social setting. Second, we found that the most challenging part of designing a reading practice related to the academic literacies tradition was fostering a dialogical environment for discussing the validity of findings across different contexts and provide for discussions encompassing complexity, nuances, and meaning making. We found traces of such discussions in all the transcripts; however, many examples were in a premature stage. The paper concludes with a discussion on, and some suggestions for, further development of the template used in the reading seminars.

Metagenomics analyses of microbial dynamics associated with putative flavor development in mash fermentation of sake

Sake is a traditional alcoholic beverage in Japan. To examine the impact of co-fermentation on microbial composition, fermentation with and without pineapple was conducted. The dynamics of microbial communities during fermentation were investigated using the metagenomics of 16S rRNA and internal transcribed spacers. In regular (RS) and co-fermented (CS) sakes, the fungal microbiota was dominated by Saccharomyces. Hierarchical clustering and non-metric multidimensional scaling identified two phases of bacterial succession. Compared with the dividing point between phases in RS, the transition in CS was delayed by five days. In both experiments, Leuconostoc dominated the premature stage and was replaced by Erwinia in the maturation stage; the alcohol tolerators of Staphylococcus and Bacillus were persistent. In RS, bacterial succession was characterized by a dramatic decrease in Pseudomonas in the maturation stage, whereas it occurred earlier in the premature stage in CS. Nineteen genera were exclusively found in CS, suggesting that co-fermentation may nurture diverse bacteria that enrich the sake flavor. Analysis of functional pathways by PICRUSt2 revealed that sugar alcohol degradation was fundamental to fermentation, whereas flavor-rich CS was attributable to the activation of l-arginine biosynthesis and amine and polyamine degradation. Aerococcus was positively correlated with enzymes involved in phenylethyl metabolism.

Generation of heterozygous PKD1 mutant pigs exhibiting early-onset renal cyst formation

AbstractAutosomal dominant polycystic kidney disease (ADPKD) is the most common inherited kidney disease, manifesting as the progressive development of fluid-filled renal cysts. In approximately half of all patients with ADPKD, end-stage renal disease results in decreased renal function. In this study, we used CRISPR-Cas9 and somatic cell cloning to produce pigs with the unique mutation c.152_153insG (PKD1insG/+). Pathological analysis of founder cloned animals and progeny revealed that PKD1insG/+ pigs developed many pathological conditions similar to those of patients with heterozygous mutations in PKD1. Pathological similarities included the formation of macroscopic renal cysts at the neonatal stage, number and cystogenic dynamics of the renal cysts formed, interstitial fibrosis of the renal tissue, and presence of a premature asymptomatic stage. Our findings demonstrate that PKD1insG/+ pigs recapitulate the characteristic symptoms of ADPKD.Autosomal dominant polycystic kidney disease (ADPKD) is a genetic disorder characterized by the formation of cysts within the kidneys. The authors generated PKD1 heterozygous knockout (PKD1insG/+) pigs by CRISPR-Cas9 and somatic cell cloning techniques. The founder cloned animals and progeny showed the renal cyst formation from the neonatal stage, interstitial fibrosis of the renal tissue, and the presence of a premature asymptomatic stage. Their findings demonstrate that PKD1insG/+ pigs recapitulate the characteristic symptoms of ADPKD.

Reproductive potential and histological profiling of the wild female anadromous shad (Tenualosa ilisha) in lower Meghna Estuary, Bangladesh

Hilsha shad (Tenualosa ilisha, Hamilton 1822) is the most commercially important and national fish of Bangladesh, belongs to the family of Clupeidae of the Clupeiformes. The study was conducted to identify the seasonal gonadal cycles through histological study and the peak breeding season combining histological and Gonado Somatic Index (GSI). One hundred and twenty fish samples with an average weight of 756.75±6.25 g was collected from the Tentulia river for the study throughout the year. Monthly mean GSI values of females ranged from 6.36±0.69 to 15.02±1.33. The lowest mean GSI value was found in December and the highest GSI value was in October. From the histological observation of the ovary, early perinucleolar stage, late perinucleolar stage, yolk vesicle stage, yolk granule stage, pre-mature and mature stages were identified. The highest percentage (75%) of mature oocytes and peak breeding season were observed in October and the breeding season continues from October to November. These results will be helpful for fishery managers to impose adequate regulations for sustainable fishery management in Bangladesh.

Automated Detection of Nonmelanoma Skin Cancer Based on Deep Convolutional Neural Network.

One of the deadliest diseases is skin cancer, especially melanoma. The high resemblance between different skin lesions such as melanoma and nevus in the skin colour images increases the complexity of identification and diagnosis. An efficient automated early detection system for skin cancer detection is essential in order to save human lives, time, and effort. In this article, an automatic skin lesion classification system using a pretrained deep learning network and transfer learning was proposed. Here, diagnosing melanoma in premature stages, a detection system has been designed which contains the following digital image processing techniques. First, dermoscopy images of skin were taken and this is subjected to a preprocessing step for noise removal and postprocessing step for image enhancement. Then the processed image undergoes image segmentation using k-means and modified k-means clustering. Second, using feature extraction technology, Gray Level Co-occurrence Matrix, and first order statistics, characteristics are extracted. Features are selected on the basis of Harris Hawks optimization (HHO). Finally, various classifiers are used for predicting the stages and efficiency of the proposed work. Measures of well-known quantities, sensitivity, precision, accuracy, and specificity are used in assessing the efficiency of the suggested method, where higher values were obtained. Compared to the current methods, it is found that the classification rate exceeded the output of the current approaches in the performance of the proposed approach.

Growing up with systemic racism in the USA

Growing up with systemic racism in the USA

Therapeutic Options for the Treatment of 2019-Novel Coronavirus in India: A Review

Purpose: As of from 30 Jan to 31 May, 2020, more than 182,143 confirmed cases reported in India along with 86,984 recovered cases and 5164 deceased cases of COVID-19. More than 53 countries are also affected with this pandemic virus. However, the lack of specific drugs to prevent/treat this pandemic disease is a major problem at this current scenario. In this regard, this systemic review was conducted to identify the therapeutic approaches and researches which are ongoing in India against COVID-19. Methods: We had screened Google Scholar database with the keywords nCoV, corona virus in India, effect of SARS-CoV-2 in India, 2019-nCoV, treatment pattern in India for nCoV and therapy used to treat nCoV in India. In the final review we had included a total of 49 articles. Results: As a result we had found that Indian Council of Medical Research and NIH have given a standard guideline of Hydroxychloroquine and other antiviral drugs for nCoV, and also there are various researches going on related to nCoV treatment like, chemicals from natural products, herbs and spices commonly used in India, combination therapy of lopinavir and ritonavir, ultra-violet radiation therapy, molecular dynamic (MD) simulations of molecules for vaccine preparation, Convalescent plasma transfusion (CPT) therapy and many more. Conclusions: New drugs and therapy are in the premature stage for this hazardous pandemic. We need more time to gain the detailed knowledge of the life cycle of the nCoV, which can speed up the drug/vaccine development process against nCoV.

Supplemental foliar applied mixture of amino acids and seaweed extract improved vegetative growth, yield and quality of citrus fruit

Poor tree nutrient management significantly reduce productivity and quality of citrus fruit. Hence in three separate experiments, exogenous supplemental application of 0.5 mL L−1 ‘Primo’ (Ascophylum nodosum seaweed extract + amino acid and) + 0.01% ‘Tween 20′) was sprayed on citrus cvs. ‘Kinnow’, ‘Feutrell's Early’ mandarins and ‘Blood Red’ orange trees. Trees were sprayed at full bloom (T2), fruit setting (T3), full bloom + fruit setting (T4), or full bloom + fruit setting + premature (T5) stages at a same concentration. Unsprayed trees of each cvs. were kept as control (T1). In contrast to untreated control trees, the application of 0.05% Primo at full bloom + fruit setting stage caused significant increase in leaf N (28%), K (36%), Mn (24.4%), Zn (15.8%), tree height (28.5%), fruit weight tree−1 (42.6%), fruits tree−1 (28.6%), marketable fruit (9%), fruit size (11.5%), SSC (16%), SSC:TA ratio (26.8%), reducing sugars (37.5%), ascorbic acid (21.8%) and total phenolic contents (42%) in ‘Kinnow’ mandarins. Likewise, sprayed trees of ‘Feutrell's Early’ in T4 exhibits higher leaf N (27%), Fe (11.9%), Zn (26.4%), fruit weight tree−1 (28.5%), fruits tree−1 (40%), marketable fruit (12.7%), fruit size (15.9%), juice weight percentage (17.6%), taste (23%), SSC (15.7%) and total sugars (42%). Whereas, in case of ‘Blood Red’ oranges, same treatment (T4) resulted in highest level of leaf N (50%), Fe (15%), tree height (37%), leaf size (38.8%), fruit weight tree−1 (42%), number of fruits tree−1 (45%), marketable fruit (8%), juice weight percentage (15.6%), SSC (19%), SSC:TA ratio (43.8%), reducing sugars (45%) and total phenolic contents (28%) than control. In addition, reduction in fruit drop, peel thickness and TA were also observed in treated trees of all cvs. as compared to untreated control. In conclusion, supplemental application of 0.5 mL L−1 ‘Primo’ at full bloom + fruit setting stages improved vegetative growth, productivity and quality of ‘Kinnow’, ‘Feutrell's Early’ and ‘Blood Red’ fruits.

Identification of Diabetic Retinopathy (DR) using Image Processing

Diabetes appears in two varieties: Type-1 and Type-2. The former is chronic and can last for years together, whereas the latter can be cured if identified and treated at a premature stage. The symptoms of diabetes affecting the eyes appear very subtle and hence, identifying irregularities in retinal images is a demanding process for medical practitioners. Thus, there was a need to find a method to detect these abnormalities by observing the retinal images non-invasively. After going through research projects and recent developments in identifying DR, we found various techniques/strategies employed, their advantages and drawbacks followed by the objective of overall findings, and the importance of a good DR detection system. Our proposed method calls to attention the importance of early screening, using geometrical relations, multiple thresholding methods and usage of convolutional neural networks as means of overcoming the factors that stand as obstacles in timely detection.

Prediction of Cardiovascular Disease Using Machine Learning Technique—A Modern Approach

Cardio Vascular disease (CVD), involving the heart and blood vessels is one of the most leading causes of death throughout the world. There are several risk factors for causing heart diseases like sedentary lifestyle, unhealthy diet, obesity, diabetes, hypertension, smoking and consumption of alcohol, stress, hereditary factory etc. Predicting cardiovascular disease and improving and treating the risk factors at an early stage are of paramount importance to save the precious life of a human being. At present, the highly stressful life with bad lifestyle activities causes heart disease at a very young age. The main aim of this research is to predict the premature heart disease based on machine learning algorithms. This paper deals with a novel approach using the machine learning algorithm for predicting the cardiovascular disease at the premature stage itself. Support Vector Machine (SVM) is used for segregating the CVD patients based on their symptoms and medical observation. The experimentation results by using the proposed method will facilitate the medical practitioners to provide suitable treatment for the patients on time. A sophisticated model has been developed with the current approach to examine the various stages of CVD and the performance metrics used have given effective and fruitful results as compared to other machine learning techniques.

Numerical surfaces of fractional Zika virus model with diffusion effect of mosquito‐borne and sexually transmitted disease

This paper analyzes the dynamics of fractional partial differential equation (FPDE) model of Zika virus that incorporates diffusion using Atangana–Baleanu (AB) fractional derivative. Zika virus disease is an infection transmitted predominantly by the bite of an infected Aedes species mosquito and may be a severe epidemic if not contained in its premature stages. The q‐homotopy analysis transform method is employed to analyze and compute the solutions for this nonlinear partial differential model, and the fractional derivative is defined in Atangana–Baleanu sense. We determine some new approximate numerical results for different values of parameters of alpha. Numerical models focused on various distributions of the population help to explain how the spread of humans and mosquitoes influences the disease's transmission. With the utilization fixed‐point hypothesis, the existence and uniqueness of the solutions obtained for the proposed model are presented.

Graphene–Gold Nanohybrid-Based Surface-Enhanced Raman Scattering Platform on a Portable Easy-to-Use Centrifugal Prototype for Liquid Biopsy Detection of Circulating Breast Cancer Cells

Although, cancer is considered as a localized disease in its premature stages, in certain types of cells, it results in metastasis, which accounts for over 90% of the total cancer deaths in the wor...

Increased prevalence of premature coronary atherosclerosis after preeclampsia

Abstract Background Women with preeclampsia have increased risk of manifest coronary artery disease later in life. However, it remains unknown if and when premature coronary atherosclerotic stages can be identified. This knowledge could enable early intervention in women considered at high risk for future manifest coronary artery disease. Purpose Using cardiac computed tomography, we aimed to investigate the prevalence of premature coronary atherosclerosis in women with previous preeclampsia in comparison with women from the general population. Methods Women, aged 40–55 years, with previous preeclampsia were recruited in the CPH-PRECIOUS study and compared 1:1 with age- and parity-matched women from the CGPS. Both groups underwent a cardiac computed tomography, including a contrast-enhanced coronary computed tomography angiography and a non-contrast coronary artery calcium scoring, as well as an overall assessment of cardiovascular risk factors imbedded in an extensive questionnaire. Cardiac computed tomography examinations were analysed blindly. The main outcome of the study was the prevalence of any coronary atherosclerosis defined as any plaque at coronary computed tomography angiography or a calcium score >0 in case of a non-diagnostic coronary computed tomography angiography. Results A total of 1,424 women were included (715 women with previous preeclampsia and 709 controls from the general population). Women with previous preeclampsia were more likely to have cardiovascular risk factors (hypertension, dyslipidaemia, diabetes mellitus). The prevalence of any coronary atherosclerosis was significantly higher in the preeclampsia group (27.4% vs. 20.0%) (P=0.001). A calcium score >0 was also more prevalent in the preeclampsia group (16.6% vs. 11.8%) (P=0.009). Preeclampsia remained an independent risk factor for the presence of any coronary atherosclerosis after adjusting for cardiovascular risk factors (age, hypertension, dyslipidaemia, diabetes, smoking, body mass index, parity) (OR=1.37, 95% CI (1.05–1.79), P=0.021). Conclusion Women with previous preeclampsia are more likely show premature signs of coronary atherosclerosis compared with an age- and parity matched control group from the general population. Preeclampsia is an independent risk factor for premature coronary atherosclerosis. Funding Acknowledgement Type of funding sources: Foundation. Main funding source(s): The Danish Heart FoundationSkibsreder Per Henriksen, R og Hustrus FondKong Christian den Tiendes FondBrødrene Hartmanns FondHans og Nora Buchards FondArvid Nilssons FondAnita og Tage Therkelsens FondLægefondenAase og Ejnar Danielsens FondHjertecentrets Forskningsudvalg (Rigshospitalet)Direktør Kurt Bønnelycke og Hustru Fru Grethe Bønnelyckes FondLægeforeningens ForskningsfondTorben & Alice Frimodt FondHenry og Astrid Møllers Fond

Experimental investigation on effects of gasoline premixed - Al2O3 additive blended fish oil biodiesel fuelled HCCI-DI engine

A HCCI-DI engine is examined using fish oil bio-fuel at various proportions with neat diesel in DI fuels and petrol as the pilot energy. 20% of petrol is admitted as premixed fuel and the 80% of the charge is injected straight away to chamber at 23°bTDC. The effect of Al2O3 nano additive on DI engine is also investigated. An investigational observation is analysed with DI engine. First, HCCI-DI engine firing is compared at premature stage of combustion. Upto 1.84% improvements in the brake thermal efficiency is witnessed at petrol mixed HCCI-DI engine compared as DI combustion. The blending of Al2O3 nano additive showed 5.88% increase in the performance of the engine. Significant reduction in NOx is observed from the HCCI-DI ignition matched via DI combustion. Fish oil biodiesel fuelled combustion showed decrease in the HC besides CO issues

Adoption of Pharmacogenomic Testing: A Marketing Perspective.

Pharmacogenomics is becoming an important part of clinical practice and it is considered one of the basic pillars of personalised medicine. However, the rate of pharmacogenomics adoption is still low in many healthcare systems, especially in low- or middle-income countries. The low level of awareness of healthcare specialists could be a potential reason due to which pharmacogenomics application is still in a premature stage but there are several other barriers that impede the aforementioned process, including the lack of the proper promotion of pharmacogenomic testing among interested stakeholders, such as healthcare professionals and biomedical scientists. In this study, we outline the available marketing theories and innovation that are applied to personalized medicine interventions that would catalyze the adoption of pharmacogenomic testing services in clinical practice. We also present the current ethical and legal framework about genomic data and propose ways to tackle the main concerns mentioned in the literature and to improve the marketing perspective of PGx.

Fatty Acid Profile and Proximate Composition of Gonads from Wild Echinometra vanbrunti during an Annual Cycle: Suitability for Human Consumption

ABSTRACT Human consumption of sea urchin gonads has led to overexploitation of commercial species, and the search for new marketable species to promote the recovery of exploited populations. Echinometra vanbrunti is a promising candidate for commercial exploitation. Its annual reproductive cycle has an effect on the proximate composition of the gonads; if they were to be consumed, the best quality in biochemical composition was determined to be from December to May, when nutritive phagocytes uphold the highest contents of protein and lipid. They possess considerable levels of omega-3 essential fatty acids, predominantly eicosapentaenoic and docosahexaenoic (DHA) acids, quite important for human nutrition. A subtle trend of higher DHA levels during the growing, premature, and mature gonadal stages of females and males was observed, though it is strongly influenced by diet and environment. A program to protect and regulate the sustainable extraction needs to be put in place before commercial exploitation.