Formulation and characterisation of nanosuspension of herbal extracts for enhanced antiradical potential

Nanotechnology is a promising technique to increase the bioavailability of herbal medicines. This paper presents the nanosuspension approach for increasing the aqueous solubility and thereby bioactivity of important herbal extracts. Nanosuspensions of the seeds of three plants extract (Silybum marianum, Elettaria cardamomum and Coriandrum sativum) were prepared by using polyvinyl alcohol (1.5% w/v) as a stabiliser. Prepared nanoparticles were characterised by scanning electron microscope. Activity of nanosuspension formulation was assessed by using four in vitro antioxidant assays. S. marianum, E. cardamomum and C. sativum particle size was observed to fall in range of 446.1 ± 112.6, 456.63 ± 339.2 and 432.1 ± 172.8 nm, respectively, most of the particles were having spherical shape and smooth topology. These synthesised nanoparticles were found to be more effective against quenching free radical than their crude extracts and standards [butylated hydroxyl toluene and ascorbic acid]. C. sativum nanosuspension showed most free radical scavenging potential against 2,2-diphenyl-1-picrylhdrazyl (DPPH) and superoxide free radical scavenging assays (IC₅₀ 0.59 ± 0.01 and 0.81 ± 0.11 mg/ml). S. marianum nanosuspension was found to be most effective against DPPH radicals scavenging (IC₅₀ 0.34 ± 0.02 mg/ml). It was concluded that nanosuspension of herbal medicines potentiates the antioxidant potential.     

EFFECT OF REDUCTION CONDITIONS ON THE ACTIVITY OF Ni/γAl2O3 CATALYST FOR METHANATION REACTION

The effect of reduction conditions, mainly reduction temperature and duration time on the activity of Ni/γAl₂O₃ catalyst were studied for a methanation reaction in a gradientless Berty reactor. The methanation reaction was investigated using a feed containing CO (6.7 mole%), H₂ (26 mole%) and the balance being nitrogen at a pressure of 30 psig and a fixed temperature of 350°C. The reduction temperature was varying from 250 to 500°C, in order to investigate its effect on the methanation reaction. The methanation activity of the catalyst increased to a maximum by increasing the reduction temperature up to a maximum at 300-350°C and showed a slight negative decline afterward. The second parameter investigated was reduction duration time which was varied from 2 to 16 hours. It was observed that the methanation reaction activity increased by increasing the reduction duration time up to 6 hours. After six hours, there was no increase in activity. Based on the finding of this investigation, a recommended set of reduction conditions is given: reduction temperature of 300°C and a duration time of six hours.     

Meat as a functional food with special reference to probiotic sausages

Consumers believe that foods are associated directly to their health. Today foods are not only used to satisfy our hunger but also to provide indispensible nutrients for humans and these nutrients having the health benefits regarding in controlling the diseases. The market for functional foods has seen a sharp rise in demand in the recent years. This has driven researchers to multiply their efforts in producing functional meat products also. Feed manipulation and post-mortem modification of meat coupled with enrichment of bioactive compounds are gaining importance. This review discusses the candidate ingredients and strategies, utilized in crafting such functional meat products, and the notable developments and commercial successes in functional meat industry. Dry fermented sausages meet the conditions required to carry viable probiotic microbes. This article enlists various microorganisms that are being commercially used in functional food products and potential bacteria for probiotic sausage production.     

Improving Routine Immunization Coverage Through Optimally Designed Predictive Models

Routine immunization (RI) of children is the most effective and timely public health intervention for decreasing child mortality rates around the globe. Pakistan being a low-and-middle-income-country (LMIC) has one of the highest child mortality rates in the world occurring mainly due to vaccine-preventable diseases (VPDs). For improving RI coverage, a critical need is to establish potential RI defaulters at an early stage, so that appropriate interventions can be targeted towards such population who are identified to be at risk of missing on their scheduled vaccine uptakes. In this paper, a machine learning (ML) based predictive model has been proposed to predict defaulting and non-defaulting children on upcoming immunization visits and examine the effect of its underlying contributing factors. The predictive model uses data obtained from Paigham-e-Sehat study having immunization records of 3,113 children. The design of predictive model is based on obtaining optimal results across accuracy, specificity, and sensitivity, to ensure model outcomes remain practically relevant to the problem addressed. Further optimization of predictive model is obtained through selection of significant features and removing data bias. Nine machine learning algorithms were applied for prediction of defaulting children for the next immunization visit. The results showed that the random forest model achieves the optimal accuracy of 81.9% with 83.6% sensitivity and 80.3% specificity. The main determinants of vaccination coverage were found to be vaccine coverage at birth, parental education, and socio-economic conditions of the defaulting group. This information can assist relevant policy makers to take proactive and effective measures for developing evidence based targeted and timely interventions for defaulting children.     

DISTINÏCT: Data poISoning atTacks dectectIon usiNg optÏmized jaCcarddisTance

Machine Learning (ML) systems often involve a re-training process to make better predictions and classifications. This re-training process creates a loophole and poses a security threat for ML systems. Adversaries leverage this loophole and design data poisoning attacks against ML systems. Data poisoning attacks are a type of attack in which an adversary manipulates the training dataset to degrade the ML system’s performance. Data poisoning attacks are challenging to detect, and even more difficult to respond to, particularly in the Internet of Things (IoT) environment. To address this problem, we proposed DISTINÏCT, the first proactive data poisoning attack detection framework using distance measures. We found that Jaccard Distance (JD) can be used in the DISTINÏCT (among other distance measures) and we finally improved the JD to attain an Optimized JD (OJD) with lower time and space complexity. Our security analysis shows that the DISTINÏCT is secure against data poisoning attacks by considering key features of adversarial attacks. We conclude that the proposed OJD-based DISTINÏCT is effective and efficient against data poisoning attacks where in-time detection is critical for IoT applications with large volumes of streaming data.     

Quality of Processed Cheddar Cheese as a Function of Emulsifying Salt Replaced by κ-Carrageenan

Hydrocolloids act as stabilizer and thickening agents, thus able to replace emulsifying salts. The present study was planned to use к-carrageenan in the production of processed cheddar cheese and to explore its effect on physico-chemical and textural properties of processed cheddar cheeses. Different concentration of ?-carrageenan were used with gradual decrease in salt contents along with natural cheese, fat, and water to prepare processed cheddar cheese. The prepared samples were analyzed for physico-chemical and sensory attributes at storage interval of 45 days during and after 90 days. With the increase in hydrocolloid concentration, stiffer product was obtained and meltability of the samples decreased than control. Processed cheddar cheese samples having 0.15% к-carrageenan with 2% emulsifying salt (1.34% sodium citrate and 0.66% disodium phosphates) were found more acceptable in terms of physico-chemical and sensory attributes, but all sensory attributes got fewer score with the passage of storage time.     

Functional role of bioactive peptides with special reference to cheeses

Growing perception about diet in relation to health has extended the necessity to explore the biologically active components present in native foods. In this review, bioactive peptides released from cheeses that may have important physiological functions are discussed. Bioactive encrypted peptides can be generated from precursor milk proteins during food processing via enzymatic hydrolysis and fermentation. Generally, biofunctionalities of peptides are latent within precursor proteins. Bioactive peptides liberated from cheeses exhibit numerous potential therapeutic roles: for example, angiotensinogen‐converting enzyme (ACE) inhibition, antioxidant, anti‐thrombotic, anti‐microbial, anti‐cancer and anti‐inflammatory. This article critically focuses on the functional roles of bioactive peptides derived from different cheeses.     

Texture,flavor, and sensory quality of buffalo milk Cheddar cheese as influenced by reducing sodium salt content

The adverse health effects of dietary sodium demand the production of cheese with reduced salt content. The study was aimed to assess the effect of reducing the level of sodium chloride on the texture, flavor, and sensory qualities of Cheddar cheese. Cheddar cheese was manufactured from buffalo milk standardized at 4% fat level by adding sodium chloride at 2.5, 2.0, 1.5, 1.0, and 0.5% (wt/wt of the curd obtained). Cheese samples were ripened at 6 to 8°C for 180 d and analyzed for chemical composition after 1 wk; for texture and proteolysis after 1, 60, 120, and 180 d; and for volatile flavor compounds and sensory quality after 180 d of ripening. Decreasing the salt level significantly reduced the salt-in-moisture and pH and increased the moisture-in-nonfat-substances and water activity. Cheese hardness, toughness, and crumbliness decreased but proteolysis increased considerably on reducing the sodium content and during cheese ripening. Lowering the salt levels appreciably enhanced the concentration of volatile compounds associated with flavor but negatively affected the sensory perception. We concluded that salt level in cheese can be successfully reduced to a great extent if proteolysis and development of off-flavors resulted by the growth of starter and nonstarter bacteria can be controlled.     

A comprehensive ligninolytic pre-treatment approach from lignocellulose green biotechnology to produce bio-ethanol

In the present study, we developed a novel ligninolytic enzymes based pre-treatment method for lignocellulosic wheat straw to depolymerize lignin and expose the cellulose polymers to produce bio-ethanol. Wheat straw was pre-treated with ligninolytic enzymes extract produced from Ganoderma lucidum under optimum solid state fermentation conditions. The pre-treated biomass was further subjected to the enzymatic hydrolysis by the crude unprocessed cellulases (β-1,4 endoglucanase, 53.5 ± 1.24 U/mL; β-1,4 exoglucanase, 41.3 ± 1.31 U/mL; β-1,4 glucosidase, 46.8 ± 1.43 U/mL; and xylanase 39 ± 2.2 U/mL) produced by Trichoderma harzaianum. Under optimal conditions for enzymatic saccharification, 10% (w/v) of pre-treated biomass was hydrolyzed completely and converted to 72.5 and 2.4 g/L of glucose and xylose, respectively. Initial time screening Sequential Saccharification and Fermentation (SSF) of the concentrated enzymatic hydrolyzate (10%, w/v) by Saccharomyces cerevisiae produced 22.6 g/L ethanol in a fermented medium after 72 h of temperature controlled incubation at 37 °C. For maximum ethanol production, different physical and nutritional parameters like pH, temperature, substrate level and inoculum sizes were optimized. Under optimal conditions ethanol production of 33.5 g/L was obtained from ligninolytic treated residual (wheat straw) biomass.     

Some indications from instability results about the effectiveness of wall heating as a control option for channel flow

This paper is a review of some of our recent work on the effect of wall heating on the stability of laminar flow in a channel. The summary of our results, some of them unexpected, is as follows. Viscosity stratification has very little effect on transient growth, whereas it results in linear mode stabilising or destabilising by an order of magnitude. It has hitherto been accepted that heat diffusivity does not affect stability. This is however true only for linear instability, transient growth is affected by an order of magnitude. Unusually, the growth is spanwise-independent and not in the form of streamwise vortices. It is also shown that flow is destabilised by secondary modes as the viscosity ratio increases. However, the viscosity ratio has no role in the selection of the pattern of Λ vortices.