Optimum medium components for biosurfactant production by Klebsiella pneumoniae WMF02 utilizing sludge palm oil as a substrate

In the present study, optimizing critical nutritional constituents was attempted as a primary strategy to improve biosurfactant production from Klebsiella pneumoniae WMF02 in liquid state fermentation utilizing sludge palm oil as a substrate. One-factor-at-a-time (OFAT) optimization was employed to evaluate the effects of sludge palm oil (SPO), sucrose, MgSO4, FeSO4, NaNO3 and K2HPO4 on surface tension reductivity. Sucrose was selected as a co-substrate over glucose in production media. The optimal levels of the aforementioned variables were (g/l) sucrose 5.0, MgSO4 0.4, FeSO4 0.3, NaNO3 2.0, and K2HPO4 4.0, with SPO concentration of 4% (v/v). The optimized medium shows surface tension reduction from 36.2 mN/m (non-optimized medium) to 25.70 mN/m. Preliminary biosurfactant identification indicated that the biosurfactant produced was phospholipids in nature

CDPS-IoT: Cardiovascular Disease Prediction System Based on IoT using Machine Learning

Internet of Things, Machine learning, and Cloud computing are the emerging domains of information communication and technology. These techniques can help to save the life of millions in the medical assisted environment and can be utilized in health-care system where health expertise is less available. Fast food consumption increased from the past few decades, which makes up cholesterol, diabetes, and many more problems that affect the heart and other organs of the body. Changing lifestyle is another parameter that results in health issues including cardio-vascular diseases. Affirming to the World Health Organization, the cardiovascular diseases, or heart diseases lead to more death than any other disease globally. The objective of this research is to analyze the available data pertaining to cardiovascular diseases for prediction of heart diseases at an earlier stage to prevent it from occurring. The dataset of heart disease patients was taken from Jammu and Kashmir, India and stored over the cloud. Stored data is then pre-processed and further analyzed using machine learning techniques for the prediction of heart diseases. The analysis of the dataset using numerous machines learning techniques like Random Forest, Decision Tree, Naive based, K-nearest neighbors, and Support Vector Machine revealed the performance metrics (F1 Score, Precision and Recall) for all the techniques which shows that Naive Bayes is better without parameter tuning while Random Forest algorithm proved as the best technique with hyperparameter tuning. In this paper, the proposed model is developed in such a systematic way that the clinical data can be obtained through the use of IoT with the help of available medical sensors to predict cardiovascular diseases on a real-time basis

Investigating the role of molecular interactions in polymorphism of mefenamic acid in ethyl acetate solution

Mefenamic acid, a widely used nonsteroidal anti-inflammatory and analgesic agent, is one of the active pharmaceutical ingredients that exhibit polymorphisms. This study reports a combined experimental and molecular dynamics simulation study of mefenamic acid crystallization in ethyl acetate. The solid-state characterization of the polymorph produced using Fourier transform infrared spectroscopy (FTIR), X-Ray powder diffractometer (XPRD), and differential scanning calorimetry (DSC) analysis show the characteristic of Form I, which were N-H stretching at 3313cm-1, two endothermic peaks, and significant XPRD peaks at 6.3°, 13.8°, 15.9°, 21.3°, and 26.3°. The molecular dynamics simulations were performed using COMPASS force field available in the Material Studio 5.5 simulation package. The simulations were run for equilibration with a time step of 1 fs for a period of 250 ps and 2000 ps simulation in NVE (constant number of atoms, volume and energy) and NPT (constant number of atoms, pressure and temperature) thermodynamic ensemble, respectively. The trajectory files from the simulation were analyzed for radial distribution function (RDF) to investigate the intermolecular interactions. The simulation results showed strong solute-solute and solute-solvent interactions, which were O1MA•••H15MA and O1EA•••H15MA. These findings revealed the presence of hydrogen bonds that contributes to the solvation and formation of hydrogen motif in polymorphic Form I of mefenamic acid during crystallization with ethyl acetate as a solvent

Bioprotein Production from Agricultural Waste and Cheaper Carbon Source: Fulfilling the Hope of Millions

The necessity for exploring unconventional, non-agricultural means of food production, especially of proteins, has created a demand for the formulation of innovative and alternative protein rich food sources having a high nutritional value which are non competitive with food for human consumption, economically feasible and locally available. Thus, the production of bioproteins (proteins derived from micro-organisms) by fermentation of agricultural waste products is one of the most promising approaches of biotechnological innovations for increasing the availability of proteins. In addition to high quality, quantity will be more comparable to farm animals due to rapid growth rate of microorganisms and high production of bioproteins. Due to the increasing demand for bioproteins, the efficient strains, substrate and method must be used for high yield product. Moreover, increasing concern about pollution that occurs from agricultural and industrial waste has stimulated interest in converting waste materials into commercially valuable products. Therefore, this study emphasized on microbiological transformation of pineapple waste, which contains valuable components like sucrose, glucose, fructose and other nutrients. Phanerochaete chrysosporium PC-13(PC2094) was used as potential strain after screening various microorganism and agricultural wastes

Biosurfactant as the next antimicrobial agents in pharmaceutical applications

The number of patients with antimicrobial resistance is growing as a result of new emerging microbes or overuse of antibiotics. A new substitute to the existing antimicrobial agents is important in time to come to control the mortality rate in the global population. Natural substances, like biosurfactants or commonly known as microbial surfactants could be a potential antimicrobial agent to medical personnel’s consideration as some biosurfactants exhibits antimicrobial activity. Hence, this paper will briefly highlight some of the findings from contemporary researchers who have tested different biosurfactants for potential antimicrobial activity

Utilization of palm sludge for biosurfactant production

Demand for surfactant chemicals for household cleaning products, personal care sectors, agriculture, food, pharmaceutical, and environmental industries is steadily increasing. According to 2013 Acmite Market Intelligence report [1], the world markets of surfactants reached US$26.8 billion in 2012, experiencing 10 in the coming years and by 2016, the market is expected to reach US$31.1 billion. However, due to the potential hazard of synthetic surfactant toward human health and the increasing consumer demand for chemical product, both effective and environmentally compatible, it is natural to turn to the microbial world to fulfill this demand by means of biosurfactant utilization. Microbial-derived surfactants are produced on living surface, mostly microbial cell surface or excreted extracellularly and contain hydrophilic and hydrophobic moieties capable of reducing surface tension and interfacial tension between individual molecules at the surface and interface. Such properties exhibit excellent detergency, emulsifying, foaming, and dispersing traits, which can be applied in various industries. It is also commercially promising alternatives to chemically synthesized surfactants due to their inherent biodegradability, lower toxicity, better foaming properties, and greater stability toward temperature and pH [2]. However, large-scale production of biosurfactant is still at its infancy due to expensive raw material, low production yield, and high purification cost. Selection of inexpensive and nutrient-rich raw materials is crucial to the economics of the process because they highly influence the overall production cost. Recently, several renewable substrates, especially from oily-based agroindustrial wastes, have been extensively studied for microbial surfactant production as it confers cost-free or low-cost feed stocks [3]. Mercade et al. [4] reported use of olive oil mill effluent for rhamnolipid production by Pseudomonas sp. Soap stick oil has been used for rhamnolipid production with P. aeruginosa [5]. Mulligan and Cooper used water collected during drying of fuel grade peat [6]. Raza et al. [7] evaluate waste frying oil from canola, corn, and soybean as a substrate for rhamnolipid production by Pseudomonas aeruginosa mutant EBN-8. Several studies with water-immiscible raw material such as plant-derived oils and oil wastes have shown that they can act as effective and cheap raw materials for biosurfactant production. Biosurfactant products obtained by using water-soluble carbon sources such as glycerol, glucose, mannitol, and ethanol are reported to be inferior to that obtained with water-immiscible substrate such as n-alkanes and olive oil [8,9]. Banat [10] observed little biosurfactant production when cells were grown on a readily available carbon sources. The production of biosurfactant was triggered only when all the soluble carbon was consumed and when a water-immiscible hydrocarbon was available. Rapeseed oil [11], canola oil, babassu oil, and corn oil [12,13] are plant-derived oils that have been used as raw material for biosurfactant production. Similarly, vegetable oils such as sunflower and soybean oils [14,15] were used for the production of rhamnolipid, sophorolipid, and mannosylerythritol lipid biosurfactants by various microorganisms. Despite ongoing research using unconventional sources, selection of appropriate waste substrate is still a challenge. Researchers are facing the problem of finding a waste with the right balance of carbohydrates and lipids to support optimal growth of microorganisms and maximum production of biosurfactant [16]. Search for new strains for high productivity is also a challenge for the widespread application of microbial surfactants. In addition, process conditions improvement through statistical optimization can be implemented as one of the effective approaches to increase the production yield of biosurfactant. Enhanced product yield, closer conformance or the process output to target requirement and reduced process variability, development time, and cost can be realized by the application of statistical experimental design techniques in bioprocess development and optimization [17]. Therefore, the aim of this chapter is to demonstrate investigation and results on an inexpensive raw material derived from palm oil refinery waste for biosurfactant production by potential isolated strain as well as enhancing the development process through series of optimization studies of nutritional requirement for maximum biosurfactant production. For this, a lab research was conducted by the authors

Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings: Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation: As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and developm nt investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens

Elective cancer surgery in COVID-19-free surgical pathways during the SARS-CoV-2 pandemic: An international, multicenter, comparative cohort study

PURPOSE As cancer surgery restarts after the first COVID-19 wave, health care providers urgently require data to determine where elective surgery is best performed. This study aimed to determine whether COVID-19–free surgical pathways were associated with lower postoperative pulmonary complication rates compared with hospitals with no defined pathway. PATIENTS AND METHODS This international, multicenter cohort study included patients who underwent elective surgery for 10 solid cancer types without preoperative suspicion of SARS-CoV-2. Participating hospitals included patients from local emergence of SARS-CoV-2 until April 19, 2020. At the time of surgery, hospitals were defined as having a COVID-19–free surgical pathway (complete segregation of the operating theater, critical care, and inpatient ward areas) or no defined pathway (incomplete or no segregation, areas shared with patients with COVID-19). The primary outcome was 30-day postoperative pulmonary complications (pneumonia, acute respiratory distress syndrome, unexpected ventilation). RESULTS Of 9,171 patients from 447 hospitals in 55 countries, 2,481 were operated on in COVID-19–free surgical pathways. Patients who underwent surgery within COVID-19–free surgical pathways were younger with fewer comorbidities than those in hospitals with no defined pathway but with similar proportions of major surgery. After adjustment, pulmonary complication rates were lower with COVID-19–free surgical pathways (2.2% v 4.9%; adjusted odds ratio [aOR], 0.62; 95% CI, 0.44 to 0.86). This was consistent in sensitivity analyses for low-risk patients (American Society of Anesthesiologists grade 1/2), propensity score–matched models, and patients with negative SARS-CoV-2 preoperative tests. The postoperative SARS-CoV-2 infection rate was also lower in COVID-19–free surgical pathways (2.1% v 3.6%; aOR, 0.53; 95% CI, 0.36 to 0.76). CONCLUSION Within available resources, dedicated COVID-19–free surgical pathways should be established to provide safe elective cancer surgery during current and before future SARS-CoV-2 outbreaks

Elective Cancer Surgery in COVID-19-Free Surgical Pathways During the SARS-CoV-2 Pandemic: An International, Multicenter, Comparative Cohort Study.

PURPOSE: As cancer surgery restarts after the first COVID-19 wave, health care providers urgently require data to determine where elective surgery is best performed. This study aimed to determine whether COVID-19-free surgical pathways were associated with lower postoperative pulmonary complication rates compared with hospitals with no defined pathway. PATIENTS AND METHODS: This international, multicenter cohort study included patients who underwent elective surgery for 10 solid cancer types without preoperative suspicion of SARS-CoV-2. Participating hospitals included patients from local emergence of SARS-CoV-2 until April 19, 2020. At the time of surgery, hospitals were defined as having a COVID-19-free surgical pathway (complete segregation of the operating theater, critical care, and inpatient ward areas) or no defined pathway (incomplete or no segregation, areas shared with patients with COVID-19). The primary outcome was 30-day postoperative pulmonary complications (pneumonia, acute respiratory distress syndrome, unexpected ventilation). RESULTS: Of 9,171 patients from 447 hospitals in 55 countries, 2,481 were operated on in COVID-19-free surgical pathways. Patients who underwent surgery within COVID-19-free surgical pathways were younger with fewer comorbidities than those in hospitals with no defined pathway but with similar proportions of major surgery. After adjustment, pulmonary complication rates were lower with COVID-19-free surgical pathways (2.2% v 4.9%; adjusted odds ratio [aOR], 0.62; 95% CI, 0.44 to 0.86). This was consistent in sensitivity analyses for low-risk patients (American Society of Anesthesiologists grade 1/2), propensity score-matched models, and patients with negative SARS-CoV-2 preoperative tests. The postoperative SARS-CoV-2 infection rate was also lower in COVID-19-free surgical pathways (2.1% v 3.6%; aOR, 0.53; 95% CI, 0.36 to 0.76). CONCLUSION: Within available resources, dedicated COVID-19-free surgical pathways should be established to provide safe elective cancer surgery during current and before future SARS-CoV-2 outbreaks