Integrating Seven Tools and Kaizen Approach in Evaluating Defects on Tofu Production Process

UKM Tofu ADA is a tofu producer that makes an effort to develop the quality standardization of the tofu production process. Managing tofu quality through maintaining the production process is challenging, resulting in no good tofu. Defective products cause economic loss and the inability to fulfill customer orders. This study aims to evaluate defects in the tofu production process using the Seven Tools and Kaizen approach. The results of this study configure three types of product defects. Namely, mushy, cracked, and crushed. The highest percentage of defects is mushy tofu, with 43.8%. The proposed improvement using kaizen analysis is the Kaizen Five-M Checklist

Generation of three-dimensional multiple spheroid model of olfactory ensheathing cells using floating liquid marbles

We describe a novel protocol for three-dimensional culturing of olfactory ensheathing cells (OECs), which can be used to understand how OECs interact with other cells in three dimensions. Transplantation of OECs is being trialled for repair of the paralysed spinal cord, with promising but variable results and thus the therapy needs improving. To date, studies of OEC behaviour in a multicellular environment have been hampered by the lack of suitable three-dimensional cell culture models. Here, we exploit the floating liquid marble, a liquid droplet coated with hydrophobic powder and placed on a liquid bath. The presence of the liquid bath increases the humidity and minimises the effect of evaporation. Floating liquid marbles allow the OECs to freely associate and interact to produce OEC spheroids with uniform shapes and sizes. In contrast, a sessile liquid marble on a solid surface suffers from evaporation and the cells aggregate with irregular shapes. We used floating liquid marbles to co-culture OECs with Schwann cells and astrocytes which formed natural structures without the confines of gels or bounding layers. This protocol can be used to determine how OECs and other cell types associate and interact while forming complex cell structuresJSJ was funded by a grant from the Perry Cross Spinal Research Foundation; NTN was funded from Griffith University through a start-up grant and a grant from the Griffith University Research Infrastructure Program; JAK was funded by an Australian Research Council Discovery Grant DP150104495; JT was funded by an Eskitis Institute scholarship; CO was funded by a Griffith Sciences scholarship; RV was funded by a Griffith University International Postgraduate Research Scholarshi

Functional characterization of a melon alcohol acyl-transferase gene family involved in the biosynthesis of ester volatiles. Identification of the crucial role of a threonine residue for enzyme activity

Volatile esters, a major class of compounds contributing to the aroma of many fruit, are synthesized by alcohol acyl-transferases (AAT). We demonstrate here that, in Charentais melon (Cucumis melo var. cantalupensis), AAT are encoded by a gene family of at least four members with amino acid identity ranging from 84% (Cm-AAT1/Cm-AAT2) and 58% (Cm-AAT1/Cm-AAT3) to only 22% (Cm-AAT1/Cm-AAT4). All encoded proteins, except Cm-AAT2, were enzymatically active upon expression in yeast and show differential substrate preferences. Cm-AAT1 protein produces a wide range of short and long-chain acyl esters but has strong preference for the formation of E-2-hexenyl acetate and hexyl hexanoate. Cm-AAT3 also accepts a wide range of substrates but with very strong preference for producing benzyl acetate. Cm-AAT4 is almost exclusively devoted to the formation of acetates, with strong preference for cinnamoyl acetate. Site directed mutagenesis demonstrated that the failure of Cm-AAT2 to produce volatile esters is related to the presence of a 268-alanine residue instead of threonine as in all active AAT proteins. Mutating 268-A into 268-T of Cm-AAT2 restored enzyme activity, while mutating 268-T into 268-A abolished activity of Cm-AAT1. Activities of all three proteins measured with the prefered substrates sharply increase during fruit ripening. The expression of all Cm-AAT genes is up-regulated during ripening and inhibited in antisense ACC oxidase melons and in fruit treated with the ethylene antagonist 1-methylcyclopropene (1-MCP), indicating a positive regulation by ethylene. The data presented in this work suggest that the multiplicity of AAT genes accounts for the great diversity of esters formed in melon

Reconstructing spring sea ice concentration in the Chukchi Sea over recent centuries: insights into the application of the PIP25 index

In this study, we aimed to reconstruct spring (April–June) sea ice changes in the western Arctic Ocean over recent centuries (ca. the last 250 years) by measuring biomarker distributions in a multicore (ARA01B-03MUC) retrieved from the Chukchi Shelf region and to evaluate outcomes against known or modelled estimates of sea ice conditions. Specifically, we analyzed for the Arctic sea ice proxy IP _25 and assessed the suitability of a further highly branched isoprenoid (HBI) lipid (HBI III), epi-brassicasterol, and dinosterol as complementary biomarkers for use with the so-called phytoplankton marker-IP _25 index (PIP _25 ; P _III IP _25 , P _B IP _25 , and P _D IP _25 , respectively). The presence of IP _25 throughout core ARA01B-03MUC confirms the occurrence of seasonal sea ice at the study site over recent centuries. From a semi-quantitative perspective, all three PIP _25 indices gave different trends, with some dependence on the balance factor c , a term used in the calculation of the PIP _25 index. P _III IP _25 -derived spring sea ice concentration (SpSIC) estimates using a c value of 0.63, determined previously from analysis of Barents Sea surface sediments, were likely most reliable, since SpSIC values were high throughout the record (SpSIC > 78%), consistent with the modern context for the Chukchi Sea and the mean SpSIC record of the 41 CMIP5 climate models over recent centuries. P _B IP _25 -based SpSIC estimates were also high (SpSIC 108%−127%), albeit somewhat over-estimated, when using a c value of 0.023 obtained from a pan-Arctic distribution of surface sediments. In contrast, P _D IP _25 values using a pan-Arctic c value of 0.11, and PIP _25 data based on the mean biomarker concentrations from ARA01B-03MUC, largely underestimated sea ice conditions (SpSIC as low as 13%), and exhibited poor agreement with instrumental records or model outputs. On the other hand, P _B IP _25 values using a c factor based on mean IP _25 and epi-brassicasterol concentrations exhibited a decline towards the core top, which resembled recent decreasing changes in summer sea ice conditions for the Chukchi Sea; however, further work is needed to test the broader spatial generality of this observation

Simple estimators of the intensity of seasonal occurrence

<p>Abstract</p> <p>Background</p> <p>Edwards's method is a widely used approach for fitting a sine curve to a time-series of monthly frequencies. From this fitted curve, estimates of the seasonal intensity of occurrence (i.e., peak-to-low ratio of the fitted curve) can be generated.</p> <p>Methods</p> <p>We discuss various approaches to the estimation of seasonal intensity assuming Edwards's periodic model, including maximum likelihood estimation (MLE), least squares, weighted least squares, and a new closed-form estimator based on a second-order moment statistic and non-transformed data. Through an extensive Monte Carlo simulation study, we compare the finite sample performance characteristics of the estimators discussed in this paper. Finally, all estimators and confidence interval procedures discussed are compared in a re-analysis of data on the seasonality of monocytic leukemia.</p> <p>Results</p> <p>We find that Edwards's estimator is substantially biased, particularly for small numbers of events and very large or small amounts of seasonality. For the common setting of rare events and moderate seasonality, the new estimator proposed in this paper yields less finite sample bias and better mean squared error than either the MLE or weighted least squares. For large studies and strong seasonality, MLE or weighted least squares appears to be the optimal analytic method among those considered.</p> <p>Conclusion</p> <p>Edwards's estimator of the seasonal relative risk can exhibit substantial finite sample bias. The alternative estimators considered in this paper should be preferred.</p

microPIR: An Integrated Database of MicroRNA Target Sites within Human Promoter Sequences

Background: microRNAs are generally understood to regulate gene expression through binding to target sequences within 39-UTRs of mRNAs. Therefore, computational prediction of target sites is usually restricted to these gene regions. Recent experimental studies though have suggested that microRNAs may alternatively modulate gene expression by interacting with promoters. A database of potential microRNA target sites in promoters would stimulate research in this field leading to more understanding of complex microRNA regulatory mechanism. Methodology: We developed a database hosting predicted microRNA target sites located within human promoter sequences and their associated genomic features, called microPIR (microRNA-Promoter Interaction Resource). microRNA seed sequences were used to identify perfect complementary matching sequences in the human promoters and the potential target sites were predicted using the RNAhybrid program..15 million target sites were identified which are located within 5000 bp upstream of all human genes, on both sense and antisense strands. The experimentally confirmed argonaute (AGO) binding sites and EST expression data including the sequence conservation across vertebrate species of each predicted target are presented for researchers to appraise the quality of predicted target sites. The microPIR database integrates various annotated genomic sequence databases, e.g. repetitive elements, transcription factor binding sites, CpG islands, and SNPs, offering users the facility to extensively explore relationships among target sites and other genomi