Hypolipidaemic effects of synbiotic yoghurt in rabbits Sarfraz, Farkhandah; Farooq, Umar; Shafi, Afshan ...
International journal of dairy technology,
November 2019, 2019-11-00, 20191101, Letnik:
72, Številka:
4
Journal Article
Recenzirano
The hypolipidaemic effects of synbiotic yoghurt prepared using Lactobacillus acidophilus, fructooligosaccharide (FOS) and isomaltooligosaccharide (IMOS) were assessed through biological study. ...Hyperlipidaemia‐induced rabbits were fed on a diet containing different levels of synbiotic yoghurt, and the blood of the animals was analysed for lipid profile on a weekly basis. There were significant reductions in total cholesterol (124.00 ± 7.10 mg/dL), triglycerides (155.00 ± 8.88 mg/dL), low‐density lipoprotein levels (13.27 ± 0.76 mg/dL) and very low‐density lipoprotein levels (57.04 ± 3.27 mg/dL), whereas high‐density lipoprotein levels (53.70 ± 0.35 mg/dL) were increased. On the basis of these results, it was concluded that the synbiotic yoghurt possessed a significant hypolipidaemic potential.
Multi‐environmental tolerant hydrogels have received significant attention and are promising for application as smart materials in multiple environments (e.g., water, oil, freezing, and dry). ...However, the macroscopic change and anti‐swelling mechanisms of organohydrogels in different solvents and their corresponding applications have not been adequately harnessed. Herein, an ionic organohydrogel with excellent mechanical properties and unique behaviors (information identification and encryption) and mechanical sensing in multiple environments is prepared. The prepared organohydrogel shows an obvious transparent change in different solvents owing to the microphase separation in poor solvents and swelling in suitable solvents, and can be treated as a dynamic information memory device for recording and encrypting information. Furthermore, owing to the interaction between water and dimethylsulfoxide (DMSO), the organohydrogel demonstrates a prominent freezing resistance (−90 to 20 °C) and moisturizing retention properties (76% after 15 days). In addition, the ionic conductive hydrogel exhibits outstanding human motion detection and physiological signal response and displays a stable mechanical sensing performance in freezing, dry conditions, and oil or water environments. It is envisioned that the design strategies and mechanistic investigation of organohydrogels may be promising for application as bio‐sensors and information‐recognition platforms in harsh environments.
In summary, the designed organohydrogel provides a novel strategy for high‐performance hydrogels by using a visual microphase separation and hydrophobic association of the organohydrogel segments. It is envisioned that the designed organohydrogel materials may be promising for application in information‐recognition platforms with information identification and encryption functions and can be applied as multipurpose sensors in harsh environments.
Background Zinc (Zn) deficiency is one of the important abiotic factors limiting rice productivity world-wide and also a widespread nutritional disorder affecting human health. Given that rice is a ...staple for populations in many countries, studies of Zn dynamics and management in rice soils is of great importance. Scope Changing climate is forcing the growers to switch from conventional rice transplanting in flooded soils to water-saving cultivation, including aerobic rice culture and alternate wetting and drying system. As soil properties are changed with altered soil and water management, which is likely to affect Zn solubility and plant availability and should be considered before Zn management in rice. In this review, we critically appraise the role of Zn in plant biology and its dynamics in soil and rice production systems. Strategies and options to improve Zn uptake and partitioning efficiency in rice by using agronomic, breeding and biotechnological tools are also discussed. Conclusions Although soil application of inorganic Zn fertilizers is widely used, organic and chelated sources are better from economic and environmental perspectives. Use of other methods of Zn application (such as seed treatment, foliar application etc., in association with mycorrhizal fungi) may improve Zn-use efficiency in rice. Conventional breeding together with modern genomic and biotechnological tools may result in development of Zn-efficient rice genotypes that should be used in conjunction with judicious fertilization to optimize rice yield and grain Zn content.
Abstract The impact of fish oil concentration on the oxidative stability of microcapsules through the spray drying process using chitosan and maltodextrin as wall material was studied. Emulsions were ...prepared with different Tuna fish oil (TFO) content (TFO-10%, TFO20%, TF030% TF0-40%) while wall material concentration was kept constant. Microencapsulated powder resulting from emulsion prepared with high fish oil load have high moisture content, wettability, total oil and low encapsulation efficiency, hygroscopicity and bulk tapped density. Oxidative stability was evaluated periodically by placing microcapsules at room temperature. Microcapsules prepared with TFO-10% presented high oxidative stability in terms of peroxide value (2.94±0.04) and anisidine value (1.54±0.02) after 30 days of storage. It was concluded that optimal amounts of fish oil for microencapsulation are 10% and 20% using chitosan and maltodextrin that extended its shelf life during study period.
Resumo Foi estudado o impacto da concentração de óleo de peixe na estabilidade oxidativa de microcápsulas por meio do processo de secagem por atomização, utilizando quitosana e maltodextrina como material de parede. As emulsões foram preparadas com diferentes teores de óleo de atum (TFO) (TFO-10%, TFO20%, TF030% TF0-40%), enquanto a concentração de material de parede foi mantida constante. O pó microencapsulado resultante da emulsão preparada com alta carga de óleo de peixe tem alto teor de umidade, molhabilidade e óleo total e baixa eficiência de encapsulação, higroscopicidade e densidade extraída a granel. A estabilidade oxidativa foi avaliada periodicamente colocando microcápsulas à temperatura ambiente. As microcápsulas preparadas com TFO-10% apresentaram alta estabilidade oxidativa em termos de valor de peróxido (2,94 ± 0,04) e valor de anisidina (1,54 ± 0,02) após 30 dias de armazenamento. Concluiu-se que as quantidades ideais de óleo de peixe para microencapsulação são de 10% e 20% usando quitosana e maltodextrina que prolongaram sua vida útil durante o período de estudo.
Currently, the world faces an existential threat of climate change, and every government across the globe is trying to come up with strategies to tackle the severity of climate change in every way ...possible. To this end, the use of clean energy rather than fossil fuel energy sources is critical, as it can reduce greenhouse gas emissions and pave the way for carbon neutrality. This study examines the impact of the energy cleanability gap on four different climate vulnerabilities, such as ecosystem, food, health, and housing vulnerabilities, considering 47 European and non-European high-income countries. The study considers samples from 2002 to 2019. This study precedes the empirical analysis in the context of a quadratic relationship between the energy cleanability gap and climate vulnerability. The study uses system-generalized methods of the moment as the main technique, while panel quantile regression is a robustness analysis. Fixed effect and random effect models have also been incorporated. The study finds that the energy cleanability gap and all four climate vulnerabilities demonstrate a U-shaped relationship in both European and non-European countries, implying that when the energy cleanability gap increases, climate vulnerability decreases, but after reaching a certain threshold, it starts to increase. Development expenditure is found to be negatively affecting food and health vulnerabilities in European nations, while it increases food vulnerability and decreases health vulnerability in non-European nations. Regarding industrialization's impact on climate vulnerabilities, the study finds opposite effects for the European and non-European economies. On the other hand, for both groups, trade openness decreases climate vulnerabilities. Based on these results, the study recommends speeding up the energy transition process from fossil fuel energy resources towards clean energy resources to obtain carbon neutrality in both European and non-European groups.
Maternal health is an important aspect of women’s health during pregnancy, childbirth, and the postpartum period. Specifically, during pregnancy, different health factors like age, blood disorders, ...heart rate, etc. can lead to pregnancy complications. Detecting such health factors can alleviate the risk of pregnancy-related complications. This study aims to develop an artificial neural network-based system for predicting maternal health risks using health data records. A novel deep neural network architecture, DT-BiLTCN is proposed that uses decision trees, a bidirectional long short-term memory network, and a temporal convolutional network. Experiments involve using a dataset of 1218 samples collected from maternal health care, hospitals, and community clinics using the IoT-based risk monitoring system. Class imbalance is resolved using the synthetic minority oversampling technique. DT-BiLTCN provides a feature set to obtain high accuracy results which in this case are provided by the support vector machine with a 98% accuracy. Maternal health exploratory data analysis reveals that the health conditions which are the strongest indications of health risk during pregnancy are diastolic and systolic blood pressure, heart rate, and age of pregnant women. Using the proposed model, timely prediction of health risks associated with pregnant women can be made thus mitigating the risk of health complications which helps to save lives.
Purpose
This study aims to explore the potential determinants of customers’ satisfaction with the Islamic banking system and highlights the fact that both internal and external factors play key roles ...in customer satisfaction (CS) during the COVID-19 pandemic.
Design/methodology/approach
Primary data from six Islamic banks (Al Baraka Bank Ltd, BankIslami Pakistan Ltd, Burj Bank Ltd, Dubai Islamic Bank Ltd, Meezan Bank Ltd and MCB-Islamic Bank Ltd) were analysed using a binary logit method.
Findings
The results showed that internal factors such as hand sanitisation facilities, strict compliance with wearing a mask before entering the bank, the distance between customers and dealing officers, an organised network of branches (in terms of health safety protocols), the behaviour of dealing officers and extended banking hours contributed significantly to enhancing the satisfaction of Islamic banking customers during the pandemic in Pakistan. The results showed that high service charges on loans have a significant adverse impact on CS. Concerning external factors, the results showed that mass media platforms that can update customers about new services and customer transactions’ processing timing, the number of operational branches in the pandemic period, available parking space in front of a bank and recommendations from family and friends to open an account with a particular bank increase CS levels.
Practical implications
The study’s results will be helpful for the policymakers and practitioners to design such policies that can promote the Islamic banking system in developing countries such as Pakistan.
Originality/value
Under the pandemic situation, the present study highlights the internal and external determinants of Islamic banking customers’ satisfaction in Pakistan. The study provides a foundation for Islamic Banks to revise their policy frameworks and marketing strategies to attract customer interest and improve their satisfaction levels.
Accurate annotation of protein functions is important for a profound understanding of molecular biology. A large number of proteins remain uncharacterized because of the sparsity of available ...supporting information. For a large set of uncharacterized proteins, the only type of information available is their amino acid sequence. This motivates the need to make sequence based computational techniques that can precisely annotate uncharacterized proteins. In this paper, we propose DeepSeq – a deep learning architecture – that utilizes only the protein sequence information to predict its associated functions. The prediction process does not require handcrafted features; rather, the architecture automatically extracts representations from the input sequence data. Results of our experiments with DeepSeq indicate significant improvements in terms of prediction accuracy when compared with other sequence-based methods. Our deep learning model achieves an overall validation accuracy of 86.72%, with an F1 score of 71.13%. We achieved improved results for protein function prediction problem through DeepSeq, by utilizing sequence only information. Moreover, using the automatically learned features and without any changes to DeepSeq, we successfully solved a different problem i.e. protein function localization, with no human intervention. Finally, we discuss how the same architecture can be used to solve even more complicated problems such as prediction of 2D and 3D structure as well as protein-protein interactions.
Microbe organisms make up approximately 60% of the earth's living matter and the human body is home to millions of microbe organisms. Microbes are microbial threats to health and may lead to several ...diseases in humans like toxoplasmosis and malaria. The microbiological toxoplasmosis disease in humans is widespread, with a seroprevalence of 3.6-84% in sub-Saharan Africa. This necessitates an automated approach for microbe organisms detection. The primary objective of this study is to predict microbe organisms in the human body. A novel hybrid microbes classifier (HMC) is proposed in this study which is based on a decision tree classifier and extra tree classifier using voting criteria. Experiments involve different machine learning and deep learning models for detecting ten different living microforms of life. Results suggest that the proposed HMC approach achieves a 98% accuracy score, 98% geometric mean score, 97% precision score, and 97% Cohen Kappa score. The proposed model outperforms employed models, as well as, existing state-of-the-art models. Moreover, the k-fold cross-validation corroborates the results as well. The research helps microbiologists identify the type of microbe organisms with high accuracy and prevents many diseases through early detection.
•Three-dimensional flow over an exponentially stretched surface is discussed.•Model is developed for MHD stagnation point flow of water-based nanofluid.•Three nanoparticles namely Copper oxide, ...Alumina and Magnetite are considered.•Dominant effects of important parameters on heated wall within the boundary layer domain and influence of nanoparticles are discussed.•Skin friction and local Nusselt number are graphed to ascertain flow and heat transfer rate at the surface.
In the present paper a theoretical investigation is performed to analyze heat and mass transport enhancement of water-based nanofluid for three dimensional (3D) MHD stagnation-point flow caused by an exponentially stretched surface. Water is considered as a base fluid. There are three (3) types of nanoparticles considered in this study namely, CuO (Copper oxide), Fe3O4 (Magnetite), and Al2O3 (Alumina) are considered along with water. In this problem we invoked the boundary layer phenomena and suitable similarity transformation, as a result our three dimensional non-linear equations of describing current problem are transmuted into nonlinear and non-homogeneous differential equations involving ordinary derivatives. We solved the final equations by applying homotopy analysis technique. Influential outcomes of aggressing parameters involved in this study, effecting profiles of temperature field and velocity are explained in detail. Graphical results of involved parameters appearing in considered nanofluid are presented separately. It is worth mentioning that Skin-friction along x and y-direction is maximum for Copper oxide-water nanofluid and minimum for Alumina-water nanofluid. Result for local Nusselt number is maximum for Copper oxide-water nanofluid and is minimum for magnetite-water nanofluid.
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