Interrogating the Tailoring Steps of Pactamycin Biosynthesis and Accessing New Pactamycin Analogues

Pactamycin is a bacteria‐derived aminocyclitol antibiotic with a wide‐range of biological activity. Its chemical structure and potent biological activities have made it an interesting lead compound for drug discovery and development. Despite its unusual chemical structure, many aspects of its formation in nature remain elusive. Using a combination of genetic inactivation and metabolic analysis, we investigated the tailoring processes of pactamycin biosynthesis in Streptomyces pactum. The results provide insights into the sequence of events during the tailoring steps of pactamycin biosynthesis and explain the unusual production of various pactamycin analogues by S. pactum mutants. We also identified two new pactamycin analogues that have better selectivity indexes than pactamycin against malarial parasites.     

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.     

In vitro Digestibility of Raw Starches Extracted from five Yam (Dioscorea spp.) Species Grown in Jamaica

Starch granules from Round leaf yellow yam, Negro yam, Sweet yam, Bitter yam and Chinese yam grown in Jamaica were isolated and characterized. The amylose content, granular size, crystallinity, and digestibility by α‐amylase were determined. The granules obtained were of three crystalline types. Round leaf yellow yam, Negro yam and Sweet yam were found to be type‐B, while Chinese yam and Bitter yam were type‐C and type‐A, respectively. Round leaf yellow yam had the highest amylose content (26.5%) while Chinese yam had the lowest (11.1%). The granule size varied between 1–3 μm for Chinese yam and 16–42 μm for Round leaf yellow yam. Significant variations in digestibility of the granules were observed. Raw starches from Chinese yam and Bitter yam were the most susceptible to α‐amylase digestion (porcine pancreatic α‐amylase, pH 5.5, 0.02% CaCl₂, 40°C, 24 h) with 21.27 ± 0.01% and 18.11 ± 0.02% degradation, respectively, while Round leaf yellow yam, Negro yam and Sweet yam starches were the least susceptible, with 13.74 ± 0.03%, 14.98 ± 0.08%, and 15.32 ± 0.04% enzymatic degradation, respectively.     

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.     

Network virtualization in energy-efficient office environments

The rising costs of energy and world-wide desire to reduce CO₂ emissions has led to an increased concern over the energy efficiency of information and communication technology. Whilst much of this concern has focused on data centres, office environments (and the computing equipment that they contain) have also been identified as a significant consumer of energy. Office environments offer great potential for energy savings, given that computing equipment often remains powered for 24 h per day, and for a large part of this period is underutilised or idle. This paper proposes an energy-efficient office management approach based on resource virtualization, power management, and resource sharing. Evaluations indicate that about 75% energy savings are achievable in office environments without a significant interruption of provided services. A core element of this office management is a peer-to-peer network that interconnects office hosts, achieves addressing and mediation, and manages energy efficiency within the office environment. Several peer-to-peer approaches are suggested and discussed in this paper. Two of the approaches are evaluated, based on a discrete-event simulation.     

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.