Microbial functional metabolism drives the effects of exogenous additives on carbon storage and degradation during aerobic composting

This study conducted composting experiments using cow manure and wheat straw, employing five different treatment methods (CK, magnetized water treatment-M, magnetized water combined with biochar treatment-SM, magnetized water combined with ferrous sulfate treatment-FM, magnetized water combined with Bacillus megaterium treatment-GM), aiming to accelerate the composting maturation process and reduce carbon loss. The results of the experiments showed that the SM treatment entered the thermophilic phase on the second day and lasted for 9 days, resulting in the best maturation effect. The FM treatment increased the carbon content in the compost, effectively preserving carbon sources. principal component analysis analysis revealed significant differences in microbial community structures due to different treatments. Additionally, structural equation modeling observations indicated that different treatments affected the compost environment, thereby influencing microbial activity and carbon content. Overall, the SM treatment positively affected the compost maturation process, while the FM treatment effectively preserved carbon sources in the compost

Cloning and Comparative Studies of Seaweed Trehalose-6-Phosphate Synthase Genes

The full-length cDNA sequence (3219 base pairs) of the trehalose-6-phosphate synthase gene of Porphyra yezoensis (PyTPS) was isolated by RACE-PCR and deposited in GenBank (NCBI) with the accession number AY729671. PyTPS encodes a protein of 908 amino acids before a stop codon, and has a calculated molecular mass of 101,591 Daltons. The PyTPS protein consists of a TPS domain in the N-terminus and a putative TPP domain at the C-terminus. Homology alignment for PyTPS and the TPS proteins from bacteria, yeast and higher plants indicated that the most closely related sequences to PyTPS were those from higher plants (OsTPS and AtTPS5), whereas the most distant sequence to PyTPS was from bacteria (EcOtsAB). Based on the identified sequence of the PyTPS gene, PCR primers were designed and used to amplify the TPS genes from nine other seaweed species. Sequences of the nine obtained TPS genes were deposited in GenBank (NCBI). All 10 TPS genes encoded peptides of 908 amino acids and the sequences were highly conserved both in nucleotide composition (>94%) and in amino acid composition (>96%). Unlike the TPS genes from some other plants, there was no intron in any of the 10 isolated seaweed TPS genes

Automatic monitoring and quantitative characterization of sedimentation dynamics for non-homogenous systems based on image profile analysis

NoSedimentation of non-homogeneous systems is the typical phenomenon indicating the physical instability as a key measure to the quality control of the preparation products. Currently, the determination methods for the sedimentation of non-homogeneous preparations are based on manual measurement or semi-quantitative observation, lacking of either automation or quantitative dynamic analysis. The purpose of this research was to realize automatic and quantitative monitoring of the sedimentation dynamics for non-homogenous systems as suspension, emulsions at laboratory level. Non-contact measurement method has been established to determine the sedimentation behaviors in a standard quartz tube for sedimentation, with internal diameter and height 23 mm and 215 mm, respectively, with controlled temperature and light intensity. As high performance camera has been equipped, the sedimentation images with high spatial and temporal resolution could be acquired, which can continuously capture sedimentation images with the resolution of 2048 x 2048 pixel at a maximum rate of 60 slides/s. All the pictures were processed to extract the luminance matrix top-down along the fixed vertical midline of each picture, which implied sedimentation characteristics of the system at the moment the picture was taken. Combining all the luminance matrixes along vertical middle lines of the pictures, a time-luminance matrix profile was obtained. Digital image processing techniques were used to eliminate interference and establish a three-dimensional surface model of the sedimentation dynamics. Then, the derivative mutation algorithm has been developed for the intelligent identification of sedimentation interface with threshold optimization so as to quantitatively analyze the sedimentation dynamics with visualization. The sedimentation curve and sedimentation dynamic equation of the non-homogeneous system were finally outputted by numerical fitting. The methodology was validated for great significance in determinations of small volume samples, parallel control multiple batches, and long period of time automatic measurement. (C) 2015 Elsevier B.V. All rights reserved

Are medical record front page data suitable for risk adjustment in hospital performance measurement? Development and validation of a risk model of in-hospital mortality after acute myocardial infarction

Objectives To develop a model of in-hospital mortality using medical record front page (MRFP) data and assess its validity in case-mix standardisation by comparison with a model developed using the complete medical record data.Design A nationally representative retrospective study.Setting Representative hospitals in China, covering 161 hospitals in modelling cohort and 156 hospitals in validation cohort.Participants Representative patients admitted for acute myocardial infarction. 8370 patients in modelling cohort and 9704 patients in validation cohort.Primary outcome measures In-hospital mortality, which was defined explicitly as death that occurred during hospitalisation, and the hospital-level risk standardised mortality rate (RSMR).Results A total of 14 variables were included in the model predicting in-hospital mortality based on MRFP data, with the area under receiver operating characteristic curve of 0.78 among modelling cohort and 0.79 among validation cohort. The median of absolute difference between the hospital RSMR predicted by hierarchical generalised linear models established based on MRFP data and complete medical record data, which was built as ‘reference model’, was 0.08% (10th and 90th percentiles: −1.8% and 1.6%). In the regression model comparing the RSMR between two models, the slope and intercept of the regression equation is 0.90 and 0.007 in modelling cohort, while 0.85 and 0.010 in validation cohort, which indicated that the evaluation capability from two models were very similar.Conclusions The models based on MRFP data showed good discrimination and calibration capability, as well as similar risk prediction effect in comparison with the model based on complete medical record data, which proved that MRFP data could be suitable for risk adjustment in hospital performance measurement