To evaluate and compare merits between intensity modulated radiotherapy and volumetric modulated arc-therapy radiotherapy techniques to determine which technique can achieve better treatment plan ...quality and efficient delivery.
The retrospective study was conducted at the Radiation Oncology Department of SanBorotlo Hospital, Vicenza, Italy, in 2019, and comprised data from Jan 2019 to Dec 2019 related to prostate and head-and-neck patients in whom Pinnacle³ treatment planning system was used for optimisation with different prescribed doses and target geometries for intensity modulated radiotherapy and volumetric modulated arc-therapy techniques. Treatment plans were simulated using 6MV photon beam of SynergyS® Linac (Linear accelerator). The plan quality was evaluated using dose-volume indices for planning target-volume and organs-at-risk. ArcCHECK™ phantom was used for dose agreement verification between planed and delivered doses.
Data of 8 patients was analysed. Intensity modulated radiotherapy and volumetric modulated arc-therapy treatment plan quality for prostate was found to be similar, but volumetric modulated arc-therapy had significant results for maximum dose (p=0.005). Intensity modulated radiotherapy and volumetric modulated arc-therapy plans for head-and-neck achieved adequate target coverage and sparing of organs at risk, and produced clinically acceptable treatment plans. The percentage of target coverage (p=0.001), dose maximum (p=0.013) and conformity index (p=0.000) were significant. A significant gain for all planning target volume dose-volume indices was noted (p<0.05). Volumetric modulated arc-therapy obtained better plan with significant values and improved sparing of organs at risk compared to intensity modulated radiotherapy for both prostate and head-and-neck treatments while maintaining doses to the organs at risk (p<0.05).
Dynamic arc mode of beam delivery provided increased degrees of freedom of volumetric modulated arc-therapy beam intensity modulation, depicting superior dose distribution than intensity modulated radiotherapy.
Breast cancer (BC) is the third leading cause of deaths in women globally. In general, histopathology images are recommended for early diagnosis and detailed analysis for BC. Thus, state-of-the-art ...classification models are required for the early prediction of BC using histopathology images. This study aims to develop an accurate and computationally feasible classification model named Biopsy Microscopic Image Cancer Network (BMIC_Net) to classify BC into eight distinct subtypes through deep learning (DL) and hierarchical classification approach. For experiments, the publicly available dataset BreakHis is used and splitted into training and testing set. Furthermore, data augmentation was performed on training set only and 4096 result-oriented features were extracted through DL. In order to improve the classification performance, feature reduction schemes were experimented to elicit the most discriminative feature subset. Finally, six machine-learning algorithms were analyzed to acquire the best results. The experimental results revealed that BMIC_Net outperformed existing baseline models by obtaining the highest accuracy of 95.48% for first-level classifier and 94.62% and 92.45% for second-level classifiers. Thus, this model can be deployed on a normal desktop machine in any healthcare center of less privileged areas in under-developing countries to serve as second opinion for breast cancer classification.
Abstract
The highly successful PBE functional and the modified Becke–Johnson exchange potential were used to calculate the structural, electronic, and optical properties of the vacancy-ordered double ...perovskites A
2
BX
6
(A = Rb, Cs; B = Sn, Pd, Pt; X = Cl, Br, and I) using the density functional theory, a first principles approach. The convex hull approach was used to check the thermodynamic stability of the compounds. The calculated parameters (lattice constants, band gap, and bond lengths) are in tune with the available experimental and theoretical results. The compounds, Rb
2
PdBr
6
and Cs
2
PtI
6
, exhibit band gaps within the optimal range of 0.9–1.6 eV, required for the single-junction photovoltaic applications. The photovoltaic efficiency of the studied materials was assessed using the spectroscopic-limited-maximum-efficiency (SLME) metric as well as the optical properties. The ideal band gap, high dielectric constants, and optimum light absorption of these perovskites make them suitable for high performance single and multi-junction perovskite solar cells.
Aptamers have drawn considerable attention as newly emerging molecular recognition elements in clinical diagnostics, drug delivery, therapeutics, environmental monitoring, and food safety analyses. ...As the in vitro screening antibody analogs, aptamers are enabled to recognize various types of targets with high affinity and specificity like or even superior to antibodies. However, the restrictions and inefficiency of selection have been hampering their wider application. Among various modified systematic evolution of ligands by exponential enrichment (SELEX) methods, capillary electrophoresis (CE)-SELEX holds multiple functions and advantages with the powerful qualitative and quantitative analysis capabilities, less consumption of sample and analytical reagent, natural binding environment, higher screening efficiency, and availability in multiple modes. This review summarizes the key developments in the area of CE-SELEX by leading research groups, including our teams' ten years of research and experience to help researchers fully understand and utilize CE-SELEX. Aptamers' history, applications, as well as the SELEX developments, have been briefly described; the advantages of CE-SELEX are highlighted compared with the conventional SELEX methods. Further, we describe some essential CE-SELEX models and provide an overview of the CE-SELEX, including the targets and ssDNA library, every technical point in the selection process, and post-SELEX protocol. We expect this review will inspire more researchers to have insight into the screening problems from CE-SELEX viewpoint and will help to improve the selection efficiency and probability of success to meet the growing needs of aptamers' discovery in bioanalytical and medical fields.
In the present study, silver nanoparticles (AgNPs) were synthesized by using aqueous leaves extract of Skimmia laureola at room temperature. The color change in reaction mixture (pale yellow to dark ...brown) was observed during synthesis process. Biosynthesized silver nanoparticles showed surface Plasmon resonance at around 460nm. The spherical and hexagonal shapes and crystalline nature of silver nanoparticles were confirmed by SEM and XRD analysis. The bioactive chemicals constituent of leaf extract of S. laureola such as tritepenoids, skimmidiol and coumarins, were mainly involved in the synthesis of silver nanoparticles. Furthermore, antibacterial potential of aqueous extract of S. laureola leaf and biosynthesized silver nanoparticles found to be potent agent against tested human pathogens and it is suitable nanomaterial for biomedical application.
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•We report a novel ecofriendly medicinal plant resource Skimmia laureola for rapid biofabrication of silver nanoparticles.•Skimmia laureola extract composite with AgNPs showed enhanced antimicrobial potential.•Silver nanoparticles (AgNPs) were spherical in shape.
•Outreach and access to advisory and financial services is restricted due various socio-economic barriers.•Farmers often use agricultural credit for non-farm purposes.•Limited economic opportunities, ...household dependence and increasing cost of production are the reasons behind credit misuse.•Access and use of agricultural advisory services improves crop productivity.•Productivity gains of using agricultural credit depend on its proper utilization for on-farm purposes.
Current agricultural growth in most of the developing countries including Pakistan is stagnant due to huge gaps between actual and potential crop productivity. Better access to agricultural advisory and financial services may play an important role in enhancing crop productivity. Using a dataset of 240 farmers collected through face-to-face interviews in 48 villages of district Sargodha in Punjab, Pakistan, this study analyzes farmers’ access to and use of farm advisory and financial services, its impact on wheat productivity and barriers to their access. The results of the study revealed that farmers rely more on informal sources for agricultural advisory and credit services than public or private sources. However, the quality of private advisory and credit services was reported better than other sources due to its easy availability and processing. Small land holdings, lack of education and high interest rates were some of the key barriers that restrict farmers’ access to both services. Further, the study also found that majority of the farmers (accessors) use agricultural credit for non-farm activities for several reasons. Moreover, the study found significant differences in the wheat productivity for farmers who had simultaneous access to both services compared to those who have access to at least one or none of the services. The study findings showed that access to agricultural advisory services improves wheat productivity. However, productivity gains of using agricultural credit are mainly associated with its proper utilization for agricultural purposes. The study suggests enhancing the outreach and quality of public advisory services through hiring and training extension staff. Furthermore, misuse of agricultural credit and barriers that restrict farmers’ access to advisory and credit services need to be eliminated through implementing effective policies and monitoring provided services.
Breast cancer is a common and fatal disease among women worldwide. Therefore, the early and precise diagnosis of breast cancer plays a pivotal role to improve the prognosis of patients with this ...disease. Several studies have developed automated techniques using different medical imaging modalities to predict breast cancer development. However, few review studies are available to recapitulate the existing literature on breast cancer classification. These studies provide an overview of the classification, segmentation, or grading of many cancer types, including breast cancer, by using traditional machine learning approaches through hand-engineered features. This review focuses on breast cancer classification by using medical imaging multimodalities through state-of-the-art artificial deep neural network approaches. It is anticipated to maximize the procedural decision analysis in five aspects, such as types of imaging modalities, datasets and their categories, pre-processing techniques, types of deep neural network, and performance metrics used for breast cancer classification. Forty-nine journal and conference publications from eight academic repositories were methodically selected and carefully reviewed from the perspective of the five aforementioned aspects. In addition, this study provided quantitative, qualitative, and critical analyses of the five aspects. This review showed that mammograms and histopathologic images were mostly used to classify breast cancer. Moreover, about 55% of the selected studies used public datasets, and the remaining used exclusive datasets. Several studies employed augmentation, scaling, and image normalization pre-processing techniques to minimize inconsistencies in breast cancer images. Several types of shallow and deep neural network architecture were employed to classify breast cancer using images. The convolutional neural network was utilized frequently to construct an effective breast cancer classification model. Some of the selected studies employed a pre-trained network or developed new deep neural networks to classify breast cancer. Most of the selected studies used accuracy and area-under-the-curve metrics followed by sensitivity, precision, and F-measure metrics to evaluate the performance of the developed breast cancer classification models. Finally, this review presented 10 open research challenges for future scholars who are interested to develop breast cancer classification models through various imaging modalities. This review could serve as a valuable resource for beginners on medical image classification and for advanced scientists focusing on deep learning-based breast cancer classification through different medical imaging modalities.
Diabetic cardiomyopathy - A comprehensive updated review Murtaza, Ghulam; Virk, Hafeez Ul Hassan; Khalid, Muhammad ...
Progress in cardiovascular diseases,
July-August 2019, 2019 Jul - Aug, 2019-07-00, Letnik:
62, Številka:
4
Journal Article
Recenzirano
Diabetes causes cardiomyopathy and increases the risk of heart failure independent of hypertension and coronary heart disease. This condition called “Diabetic Cardiomyopathy” (DCM) is becoming a ...well- known clinical entity. Recently, there has been substantial research exploring its molecular mechanisms, structural and functional changes, and possible development of therapeutic approaches for the prevention and treatment of DCM. This review summarizes the recent advancements to better understand fundamental molecular abnormalities that promote this cardiomyopathy and novel therapies for future research. Additionally, different diagnostic modalities, up to date screening tests to guide clinicians with early diagnosis and available current treatment options has been outlined.
Soliton solutions are of utmost importance among traveling wave solutions since they act as a bridge between mathematics and physics. This paper investigates time fractional form of fifth-order ...Sawada–Kotera equation resulting in different forms of exact and approximate soliton solutions including singular, periodic and dark soliton solutions. The time fractional derivative is used in the Caputo sense throughout the study. The effectiveness of trial equation method is seen in determining exact solutions, whereas residual power series method is employed for its high precision and reliability in calculating approximate solutions of the model. Multiple soliton solutions are also determined by the aid of Hirota’s method. The results are compared with a numerical method, and the graphical representation of all the obtained solutions is shown for different values of the fractional parameter. The time evolution of all solutions is also represented in 2D plots. These findings are highly encouraging to explore other nonlinear fractional models.
Trace heavy metals, such as arsenic, cadmium, lead, chromium, nickel, and mercury, are important environmental pollutants, particularly in areas with high anthropogenic pressure. In addition to these ...metals, copper, manganese, iron, and zinc are also important trace micronutrients. The presence of trace heavy metals in the atmosphere, soil, and water can cause serious problems to all organisms, and the ubiquitous bioavailability of these heavy metal can result in bioaccumulation in the food chain which especially can be highly dangerous to human health. This study reviews the heavy metal contamination in several areas of Pakistan over the past few years, particularly to assess the heavy metal contamination in water (ground water, surface water, and waste water), soil, sediments, particulate matter, and vegetables. The listed contaminations affect the drinking water quality, ecological environment, and food chain. Moreover, the toxicity induced by contaminated water, soil, and vegetables poses serious threat to human health.
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