Friedewald's formula (FF) is the most widely used formula in clinical practice to calculate low-density lipoprotein cholesterol (LDLC) from total cholesterol (TC), triglyceride (TG) and high-density lipoprotein cholesterol (HDLC). But this formula frequently underestimates LDLC. The aim of this study was to derive a regression equation (RE) to abolish the underestimation and to compare the performance of RE and FF in Bangladeshi population. RE was derived from 531 lipid profiles (equation derivation group) for the calculation of LDLC by multiple linear regression analysis. The RE was then used to calculate LDLC in another 952 subjects (equation validation group). LDLC calculated by RE and FF were compared with measured LDLC by appropriate statistical analyses. In equation validation group, measured LDLC, LDLC calculated by RE and FF were 2.97±0.81, 2.91±0.80 and 2.72±0.93 mmol/L respectively. Precision (r) was 0.9525 for RE and 0.9193 for FF. Passing & Bablok linear regression equations against measured LDLC were y = 0.9792x + 0.007 for RE and y = 1.1412x -0.6781 for FF. Accuracy within ±12% of measured LDLC was 79% and 57% for RE and FF, respectively. The derived RE is more accurate than FF for the calculation of LDLC in Bangladeshi population.

Yeast extract is extensively applied in various food industries as a food additive to enhance to flavor of food products or as a vitamin supplement. It is also considered as a crucial component of microbiological media. The current study was conducted to optimize a process for the production of yeast extract by using Baker’s yeast (Saccharomyces cerevisiae). The cultivation of yeast biomass was performed in a stirred fermenter. The influence of numerous physical and chemical parameters such as carbon and nitrogen sources, temperature, pH and agitation were evaluated on the production of yeast cells by employing one factor at a time approach and optimum conditions for the production of maximum yeast biomass was determined. The maximum growth was attained using molasses as a substrate at 30ºC supplemented with urea at 150 rpm with pH 4.5. After fermentation, cells were separated by centrifugation and were ruptured by adopting different techniques and autolysis was found the most viable method. Various techniques were applied to dry the yeast extract and the spray dryer was appeared as most effective one. Yeast extract acquired after drying was subjected to various analysis including protein and solid content estimation and amino acid profiling and compared with commercial yeast extract. The dried yeast extract was incorporated in media preparations to grow various microorganisms including yeast, fungi and bacteria and considerable growth was observed. These promising results indicated that the developed process is a cost effective alternative approach for the production of yeast extract.

This study enlightens the methods used for the identification as well as the growth of Spirulina species in Pakistan. Spirulina was identified based on morphology using microscopic technique along with its biochemical identification using SDS PAGE. After the endorsement of spirulina species via microscopy and SDS PAGE, Spirulina was subjected to growth in Zarrouk’s media. Efficacy of growth was observed using three different methods Tubular photobioreactors, Fed-batch photobioreactors, and Attached cultivation which boosts the yield of Spirulina biomass via improving its biochemical composition. Hence, it concludes that production of the Spirulina using tubular photobioreactors on pilot-scale yields cost-effective benefits and provides us with an enhanced biochemical content ratio of Spirulina and can easily be identified by using several approaches including biochemical, molecular, and microscopic methods.

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S tarch is an important macromolecule and the main source of carbohydrates in food. Chemically, it is a glucose polymer with amylose and amylopectin as structural components. Amylose, which makes up approximately 20% of starch, is made up of linear alpha-1, 4 linked glucose units. Whereas, amylopectin is a highly branched glucose polymer with alpha-1, 4 linked residues and alpha-1, 6 linkage at the branching point. It makes up about 80% of starch. Starch hydrolysis is a key process in many industries that is carried out preferably by amylases (Wang et al., 2022;Chorfa et al., 2022;Gan and Evers, 2022;Fuentes-Zaragoza et al., 2010). Amylases are categorized into beta amylases with EC (Enzyme Commission number) 3.2.1.2, glucoamylases (EC: 3.2.1.3) and alpha amylases with (EC: 3.2.1.1).