scholarly journals Recombinant polypeptide of Mycobacterium leprae as a potential tool for serological detection of leprosy

AMB Express ◽  
2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Marcelo dos Santos Barbosa ◽  
Iara Beatriz Andrade de Sousa ◽  
Simone Simionatto ◽  
Sibele Borsuk ◽  
Silvana Beutinger Marchioro
Keyword(s):  
Large Scale ◽  
Mycobacterium Leprae ◽  
Detection Methods ◽  
Recombinant Polypeptide ◽  
Cell Reactivity ◽  
Tertiary Structures ◽  
Leprosy Patients ◽  
T Cell Reactivity ◽  
Prevention Methods ◽  
Scale Detection

AbstractCurrent prevention methods for the transmission of Mycobacterium leprae, the causative agent of leprosy, are inadequate as suggested by the rate of new leprosy cases reported. Simple large-scale detection methods for M. leprae infection are crucial for early detection of leprosy and disease control. The present study investigates the production and seroreactivity of a recombinant polypeptide composed of various M. leprae protein epitopes. The structural and physicochemical parameters of this construction were assessed using in silico tools. Parameters like subcellular localization, presence of signal peptide, primary, secondary, and tertiary structures, and 3D model were ascertained using several bioinformatics tools. The resultant purified recombinant polypeptide, designated rMLP15, is composed of 15 peptides from six selected M. leprae proteins (ML1358, ML2055, ML0885, ML1811, ML1812, and ML1214) that induce T cell reactivity in leprosy patients from different hyperendemic regions. Using rMLP15 as the antigen, sera from 24 positive patients and 14 healthy controls were evaluated for reactivity via ELISA. ELISA-rMLP15 was able to diagnose 79.17% of leprosy patients with a specificity of 92.86%. rMLP15 was also able to detect the multibacillary and paucibacillary patients in the same proportions, a desirable addition in the leprosy diagnosis. These results summarily indicate the utility of the recombinant protein rMLP15 in the diagnosis of leprosy and the future development of a viable screening test.

Interrogating CD8+ T cell reactivity on a genome-wide scale

2019 ◽  
Vol 11 (506) ◽  
pp. eaaz0302
Author(s):  
Kamila Naxerova
Keyword(s):  
T Cell ◽  
Large Scale ◽  
Cd8 T Cell ◽  
Cell Reactivity ◽  
Human T Cell ◽  
Genome Wide ◽  
A Genome ◽  
T Cell Antigens ◽  
Wide Scale ◽  
T Cell Reactivity

A new method enables large-scale identification of human T cell antigens.

Security Concern and Countermeasures for Cheating in Visual Cryptography

2018 ◽  
Vol 6 (8) ◽  
pp. 277
Author(s):  
Ekta Y
Keyword(s):  
Communication System ◽  
Visual Cryptography ◽  
Detection Methods ◽  
Information Communication ◽  
New Approach ◽  
The World ◽  
Visual Cryptography Scheme ◽  
Prevention Methods ◽  
Security Concern

As IT sector is ruling the world now,confidentiality and security of information has become the most important inseparable aspect in information communication system. Keeping in view the same, a new approach called Visual Cryptography (VC) has been suggested by many researchers but there are some limitations with this scheme and cheating is one of the main problem among them. This paper intends to show the basis of cheating in VC in terms of cheating process, its detection methods and its prevention methods suggested by various researchers along with their merits and demerits. Finally, a good Cheating Immune Visual Cryptography Scheme (CIVCS) has been discussed which states the properties to be adopted by every Visual Cryptography scheme to make it immune to cheating attacks.

The emerging roles of extracellular vesicles in ovarian cancer

2020 ◽  
Vol 21 ◽  
Author(s):  
Yin-xue Wang ◽  
Yi-xiang Wang ◽  
Yi-ke Li ◽  
Shi-yan Tu ◽  
Yi-qing Wang
Keyword(s):  
Ovarian Cancer ◽  
Extracellular Vesicles ◽  
Large Scale ◽  
Current Treatment ◽  
Detection Methods ◽  
Drug Resistant ◽  
Apoptotic Bodies ◽  
Biological Mechanisms ◽  
Gynecological Malignancy ◽  
Resistance To Chemotherapy

: Ovarian cancer (OC) is one of the deadliest gynecological malignancy. Epithelial ovarian cancer (EOC) is its most common form. OC has both a poor prognosis and a high mortality rate due to the difficulties of early diagnosis, the limitation of current treatment and resistance to chemotherapy. Extracellular vesicles is a heterogeneous group of cellderived submicron vesicles which can be detected in body fluids, and it can be classified into three main types including exosomes, micro-vesicles, and apoptotic bodies. Cancer cells can produce more EVs than healthy cells. Moreover, the contents of these EVs have been found distinct from each other. It has been considered that EVs shedding from tumor cells may be implicated in clinical applications. Such as a tool for tumor diagnosis, prognosis and potential treatment of certain cancers. In this review, we provide a brief description of EVs in diagnosis, prognosis, treatment, drug-resistant of OC. Cancer-related EVs show powerful influences on tumors by various biological mechanisms. However, the contents mentioned above remain in the laboratory stage and there is a lack of large-scale clinical trials, and the maturity of the purification and detection methods is a constraint. In addition, amplification of oncogenes on ecDNA is remarkably prevalent in cancer, it may be possible that ecDNA can be encapsulated in EVs and thus detected by us. In summary, much more research on EVs needs to be perform to reveal breakthroughs in OC and to accelerate the process of its application on clinic.

Recent Advancement in the Diagnosis and Treatment of Leprosy

2018 ◽  
Vol 18 (18) ◽  
pp. 1550-1558
Author(s):  
Muhammad Aamir ◽  
Asma Sadaf ◽  
Sehroon Khan ◽  
Shagufta Perveen ◽  
Afsar Khan
Keyword(s):  
Vitamin D ◽  
Drug Treatment ◽  
Mycobacterium Leprae ◽  
Neglected Diseases ◽  
Specific Drug ◽  
Genetic Studies ◽  
Vitamin D Receptors ◽  
Micro Rnas ◽  
Leprosy Patients ◽  
Skin Biopsies

Background: Many of the tropical diseases are neglected by the researchers and medicinal companies due to lack of profit and other interests. The Drugs for Neglected Diseases initiative (DNDi) is established to overcome the problems associated with these neglected diseases. According to a report published by the WHO, leprosy (Hansen's disease) is also a neglected infectious disease. Methods: A negligible amount of advancements has been made in last few decades which includes the tools of diagnosis, causes, treatment, and genetic studies of the bacterium (Mycobacterium leprae) that causes leprosy. The diagnosis of leprosy at earlier stages is important for its effective treatment. Recent studies on vitamin D and its receptors make leprosy diagnosis easier at earlier stages. Skin biopsies and qPCR are the other tools to identify the disease at its initial stages. Results: Until now a specific drug for the treatment of leprosy is not available, therefore, Multi-Drug Therapy (MDT) is used, which is hazardous to health. Besides Mycobacterium leprae, recently a new bacterium Mycobacterium lepromatosis was also identified as a cause of leprosy. During the last few years the genetic studies of Mycobacterium leprae, the role of vitamin D and vitamin D receptors (VDR), and the skin biopsies made the treatment and diagnosis of leprosy easier at early stages. The studies of micro RNAs (miRNAs) made it easy to differentiate leprosy from other diseases especially from tuberculosis. Conclusion: Leprosy can be distinguished from sarcoidosis by quantitative study of reticulin fibers present in skin. The treatment used until now for leprosy is multi-drug treatment. The complete genome identification of Mycobacterium leprae makes the research easy to develop target specified drugs for leprosy. Rifampicin, identified as a potent drug, along with other drugs in uniform multi-drug treatment, has a significant effect when given to leprosy patients at initial stages. These are effective treatments but a specific drug for leprosy is still needed to be identified. The current review highlights the use of modern methods for the identification of leprosy at its earlier stages and the effective use of drugs alone as well as in combination.

scholarly journals Insectivorous songbirds as early indicators of future defoliation by spruce budworm

2021 ◽  
Author(s):  
Marion Germain ◽  
Daniel Kneeshaw ◽  
Louis De Grandpré ◽  
Mélanie Desrochers ◽  
Patrick M. A. James ◽  
...  
Keyword(s):  
Large Scale ◽  
Spatial Scales ◽  
Spruce Budworm ◽  
Detection Methods ◽  
Maximum Probability ◽  
Point Count ◽  
Probability Of Presence ◽  
Time Lagged ◽  
One Year ◽  
Local Sampling

Abstract Context Although the spatiotemporal dynamics of spruce budworm outbreaks have been intensively studied, forecasting outbreaks remains challenging. During outbreaks, budworm-linked warblers (Tennessee, Cape May, and bay-breasted warbler) show a strong positive response to increases in spruce budworm, but little is known about the relative timing of these responses. Objectives We hypothesized that these warblers could be used as sentinels of future defoliation of budworm host trees. We examined the timing and magnitude of the relationships between defoliation by spruce budworm and changes in the probability of presence of warblers to determine whether they responded to budworm infestation before local defoliation being observed by standard detection methods. Methods We modelled this relationship using large-scale point count surveys of songbirds and maps of cumulative time-lagged defoliation over multiple spatial scales (2–30 km radius around sampling points) in Quebec, Canada. Results All three warbler species responded positively to defoliation at each spatial scale considered, but the timing of their response differed. Maximum probability of presence of Tennessee and Cape May warbler coincided with observations of local defoliation, or provided a one year warning, making them of little use to guide early interventions. In contrast, the probability of presence of bay-breasted warbler consistently increased 3–4 years before defoliation was detectable. Conclusions Early detection is a critical step in the management of spruce budworm outbreaks and rapid increases in the probability of presence of bay-breasted warbler could be used to identify future epicenters and target ground-based local sampling of spruce budworm.

scholarly journals Uni-Temporal Multispectral Imagery for Burned Area Mapping with Deep Learning

2021 ◽  
Vol 13 (8) ◽  
pp. 1509
Author(s):  
Xikun Hu ◽  
Yifang Ban ◽  
Andrea Nascetti
Keyword(s):  
Deep Learning ◽  
Large Scale ◽  
Multiple Scales ◽  
Detection Methods ◽  
Burned Area ◽  
Landsat 8 ◽  
Multispectral Imagery ◽  
Burned Areas ◽  
Local Climate Zones ◽  
Sentinel 2

Accurate burned area information is needed to assess the impacts of wildfires on people, communities, and natural ecosystems. Various burned area detection methods have been developed using satellite remote sensing measurements with wide coverage and frequent revisits. Our study aims to expound on the capability of deep learning (DL) models for automatically mapping burned areas from uni-temporal multispectral imagery. Specifically, several semantic segmentation network architectures, i.e., U-Net, HRNet, Fast-SCNN, and DeepLabv3+, and machine learning (ML) algorithms were applied to Sentinel-2 imagery and Landsat-8 imagery in three wildfire sites in two different local climate zones. The validation results show that the DL algorithms outperform the ML methods in two of the three cases with the compact burned scars, while ML methods seem to be more suitable for mapping dispersed burn in boreal forests. Using Sentinel-2 images, U-Net and HRNet exhibit comparatively identical performance with higher kappa (around 0.9) in one heterogeneous Mediterranean fire site in Greece; Fast-SCNN performs better than others with kappa over 0.79 in one compact boreal forest fire with various burn severity in Sweden. Furthermore, directly transferring the trained models to corresponding Landsat-8 data, HRNet dominates in the three test sites among DL models and can preserve the high accuracy. The results demonstrated that DL models can make full use of contextual information and capture spatial details in multiple scales from fire-sensitive spectral bands to map burned areas. Using only a post-fire image, the DL methods not only provide automatic, accurate, and bias-free large-scale mapping option with cross-sensor applicability, but also have potential to be used for onboard processing in the next Earth observation satellites.

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