Statističko optimiranje proizvodnje α-galaktozidaze submerznim uzgojem aktinomicete Streptomyces griseoloalbus primjenom metodologije odzivnih površina

α-Galactosidase production by a novel actinomycete strain Streptomyces griseoloalbus in shake flask culture was optimized using response surface methodology. Screening of variables to find their relative effect on α-galactosidase production was done using Plackett-Burman design. Out of the eleven factors screened, salinity, magnesium sulphate and temperature were found to influence the enzyme production significantly. The optimal levels of these variables and the effect of their mutual interactions on enzyme production were determined using Box-Behnken design. The interaction between salinity and magnesium sulphate concentration was found to enhance α-galactosidase production, whereas temperature exhibited an influence independent of the other two factors. Using this statistical optimization method, the α-galactosidase production was increased from 17 to 50 U/mL.Primjenom metodologije odzivnih površina optimirana je proizvodnja α-galaktozidaze s pomoću novog soja aktinomiceta Streptomyces griseoloalbus u pokusima na tresilici. Primjenom Plackett-Burmanova statističkog plana ispitan je utjecaj varijabli na proizvodnju α-galaktozidaze. Od jedanaest ispitanih faktora, na proizvodnju enzima bitno su utjecali salinitet, koncentracija magnezijeva sulfata i temperatura. Optimalne vrijednosti tih varijabli i njihovo uzajamno djelovanje na proizvodnju enzima određeno je primjenom Box-Behnken statističkog plana. Međusobnim utjecajem saliniteta i koncentracije magnezijeva sulfata poboljšana je proizvodnja α-galaktozidaze, za razliku od temperature čiji utjecaj nije ovisio o ta dva faktora. Primjenom takva postupka proizvodnja α-galaktozidaze povećana je sa 17 na 50 U/mL

Global overview of the management of acute cholecystitis during the COVID-19 pandemic (CHOLECOVID study)

Background: This study provides a global overview of the management of patients with acute cholecystitis during the initial phase of the COVID-19 pandemic. Methods: CHOLECOVID is an international, multicentre, observational comparative study of patients admitted to hospital with acute cholecystitis during the COVID-19 pandemic. Data on management were collected for a 2-month study interval coincident with the WHO declaration of the SARS-CoV-2 pandemic and compared with an equivalent pre-pandemic time interval. Mediation analysis examined the influence of SARS-COV-2 infection on 30-day mortality. Results: This study collected data on 9783 patients with acute cholecystitis admitted to 247 hospitals across the world. The pandemic was associated with reduced availability of surgical workforce and operating facilities globally, a significant shift to worse severity of disease, and increased use of conservative management. There was a reduction (both absolute and proportionate) in the number of patients undergoing cholecystectomy from 3095 patients (56.2 per cent) pre-pandemic to 1998 patients (46.2 per cent) during the pandemic but there was no difference in 30-day all-cause mortality after cholecystectomy comparing the pre-pandemic interval with the pandemic (13 patients (0.4 per cent) pre-pandemic to 13 patients (0.6 per cent) pandemic; P = 0.355). In mediation analysis, an admission with acute cholecystitis during the pandemic was associated with a non-significant increased risk of death (OR 1.29, 95 per cent c.i. 0.93 to 1.79, P = 0.121). Conclusion: CHOLECOVID provides a unique overview of the treatment of patients with cholecystitis across the globe during the first months of the SARS-CoV-2 pandemic. The study highlights the need for system resilience in retention of elective surgical activity. Cholecystectomy was associated with a low risk of mortality and deferral of treatment results in an increase in avoidable morbidity that represents the non-COVID cost of this pandemic

Novel esterases from microbes through classical and metagenomics approach: Studies on the enzymes and their applications

Cochin University of Science And Technolog

Biobutanol from lignocellulosic biomass by a novel Clostridium sporogenes BE01

In the current study, a novel non-acetone forming butanol and ethanol producer Was isolated and identified. Based on the 16s rDNA sequence BLAST and phylogenetic analyses, it was found to have high similarity with the reported hydrogen producing strains of Clostridium sporogenes. Biochemical studies revealed that it is lipase and protease positive. The lipolytic and proteolytic properties are the very important characteristics of Clostridium sporogenes. Sugar utilization profile studies were positive for glucose, saccharose, cellobiose and weakly positive result to xylose. This study demonstrated C. sporogenes BE01, an isolate from NIIST is having potential to compete with existing, well known butanol producers with the advantage of no acetone in the final solvent mixture. Rice straw hydrolysate is a potent source of substrate for butanol production by C. sporogenes BE01. Additional supplementation of vitamins and minerals were avoided by using rice straw hydrolysate as substrate. Its less growth, due to the inhibitors present in the hydrolysate and also inhibition by products resulted in less efficient conversion of sugars to butanol. Calcium carbonate played an important role in improving the butanol production, by providing the buffering action during fermentation and stimulating the electron transport mediators and redox reactions favoring butanol production. Its capability to produce acetic acid, butyric acid and hydrogen in significant quantities during butanol production adds value to the conversion process of lignocellulosic biomass to butanol. High cell density fermentation by immobilizing the cells on to ceramic particles improved the solvents and VFA production. Reduced sugar utilization from the concentrated hydrolysate could be due to accumulation of inhibitors in the hydrolysate during concentration. Two-stage fermentation was very efficient with immobilized cells and high conversions of sugars to solvents and VFAs were achieved. The information obtained from the study would be useful to develop a feasible technology for conversion of lignocellulosic biomass to biobutanol.Cochin University Of Science And Technolog

Statistical Optimization of α-Galactosidase Production in Submerged Fermentation by Streptomyces griseoloalbus Using Response Surface Methodology

α-Galactosidase production by a novel actinomycete strain Streptomyces griseoloalbus in shake flask culture was optimized using response surface methodology. Screening of variables to find their relative effect on α-galactosidase production was done using Plackett-Burman design. Out of the eleven factors screened, salinity, magnesium sulphate and temperature were found to influence the enzyme production significantly. The optimal levels of these variables and the effect of their mutual interactions on enzyme production were determined using Box-Behnken design. The interaction between salinity and magnesium sulphate concentration was found to enhance α-galactosidase production, whereas temperature exhibited an influence independent of the other two factors. Using this statistical optimization method, the α-galactosidase production was increased from 17 to 50 U/mL

Preface new horizons in biotechnology – NHBT 2019

Producción CientíficaRelevance of Biotechnology for a sustainable living has increased over the past few decades by addressing the different domains including agriculture, food, health care, livestock management, energy, environment, climate change, waste management and a multitude of other areas. Today, the subject not only encompasses life sciences and engineering, but spans across most of the human activities, affecting and influencing every one. The subject is poised to tackle emerging challenges like rapidly spreading global pandemics by providing solutions in the form of vaccines or drugs, immune boosters and diagnostics. Green processes, renewable clean energy, super foods and nutraceuticals, biodegradable polymers and materials are but a few of the outcomes of development in this field. In wake of the rapid deterioration of land and water resources and environment catalysed by anthropogenic activities, urgent calls have to be made on addressing the issues of solid, liquid and chemical waste management, atmospheric pollution, and moving towards greener manufacturing processes and deriving energy through renewable routes for a sustainable development and improved quality of life. It may not be incorrect to say that the world needs to move towards a sustainable bio-economy for human race to persist on this planet

Robustness of FTIR-Based Ultrarapid COVID-19 Diagnosis Using PLS-DA

The World Health Organization (WHO) declared the Omicron variant (B.1.1.529) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the pathogen responsible for the Coronavirus disease 2019 (COVID-19) pandemic, as a variant of concern on 26 November 2021. By this time, 42% of the world’s population had received at least one dose of the vaccine against COVID-19. As on 1 October 2022, only 68% of the world population got the first dose of the vaccine. Although the vaccination is incredibly protective against severe complications of the disease and death, the highly contagious Omicron variant, compared to the Delta variant (B.1.617.2), has led the whole world into more chaotic situations. Furthermore, the virus has a high mutation rate, and hence, the possibility of a new variant of concern in the future cannot be ruled out. To face such a challenging situation, paramount importance should be given to rapid diagnosis and isolation of the infected patient. Current diagnosis methods, including reverse transcription-polymerase chain reaction and rapid antigen tests, face significant burdens during a COVID-19 wave. However, studies reported ultrarapid, reagent-free, cost-efficient, and non-destructive diagnosis methods based on chemometrics for COVID-19 and COVID-19 severity diagnosis. These studies used a smaller sample cohort to construct the diagnosis model and failed to discuss the robustness of the model. The current study systematically evaluated the robustness of the diagnosis models trained using smaller (real and augmented spectra) and larger (augmented spectra) datasets. The Monte Carlo cross-validation and permutation test results suggest that diagnosis using models trained by larger datasets was accurate and statistically significant (Q2 > 99% and AUROC = 100%)