Meta-Analysis of Pulse Transition Features in Non-Invasive Blood Pressure Estimation Systems: Bridging Physiology and Engineering Perspectives.

The pulse transition features (PTFs), including pulse arrival time (PAT) and pulse transition time (PTT), hold significant importance in estimating non-invasive blood pressure (NIBP). However, the literature showcases considerable variations in terms of PTFs' correlation with blood pressure (BP), accuracy in NIBP estimation, and the comprehension of the relationship between PTFs and BP. This inconsistency is exemplified by the wide-ranging correlations reported across studies investigating the same feature. Furthermore, investigations comparing PAT and PTT have yielded conflicting outcomes. Additionally, PTFs have been derived from various bio-signals, capturing distinct characteristic points like the pulse's foot and peak. To address these inconsistencies, this study meticulously reviews a selection of such research endeavors while aligning them with the biological intricacies of blood pressure and the human cardiovascular system (CVS). Each study underwent evaluation, considering the specific signal acquisition locale and the corresponding recording procedure. Moreover, a comprehensive meta-analysis was conducted, yielding multiple conclusions that could significantly enhance the design and accuracy of NIBP systems. Grounded in these dual aspects, the study systematically examines PTFs in correlation with the specific study conditions and the underlying factors influencing the CVS. This approach serves as a valuable resource for researchers aiming to optimize the design of BP recording experiments, bio-signal acquisition systems, and the fine-tuning of feature engineering methodologies, ultimately advancing PTF-based NIBP estimation.

Forecasting seasonal variations in electricity consumption and electricity usage efficiency of industrial sectors using a grey modeling approach.

The aim of this research is to forecast seasonal fluctuations in electricity consumption, and electricity usage efficiency of industrial sectors and identify the impacts of the novel coronavirus disease 2019 (COVID-19). For this purpose, a new seasonal grey prediction model (AWBO-DGGM(1,1)) is proposed: it combines buffer operators and the DGGM(1,1) model. Based on the quarterly data of the industrial enterprises in Zhejiang Province of China from the first quarter of 2013 to the first quarter of 2020, the GM(1,1), DGGM(1,1), SVM, and AWBO-DGGM(1,1) models are employed, respectively, to simulate and forecast seasonal variations in electricity consumption, the added value, and electricity usage efficiency. The results indicate that the AWBO-DGGM(1,1) models can identify seasonal fluctuations and variations in time series data, and predict the impact of COVID-19 on industrial systems. The minimum mean absolute percentage errors (MAPEs) of the electricity consumption, added value, and electricity usage efficiency of industrial enterprises separately are 0.12%, 0.10%, and 3.01% in the training stage, while those in the test stage are 6.79%, 4.09%, and 2.25%, respectively. The electricity consumption, added value, and electricity usage efficiency of industrial enterprises in Zhejiang Province will still present a tendency to grow with seasonal fluctuations from 2020 to 2022. Of them, the added value is predicted to increase the fastest, followed by electricity consumption.

Simultaneous identification of multiple receptors of natural product using an optimized cDNA phage display cloning.

Simultaneously isolating more than one receptor of natural product remains a challenge to chemical genetics. Using cyclosporine A as an affinity probe and an optimized phage display cloning procedure, not only cyclophilin A, but also cyclophilin B was isolated as the full-length gene clone from a human brain cDNA library. This optimized protocol can be used to select protein targets of chemicals dependent on the binding affinity rather than on the relative abundance in cells.

Co-expression of Triosephosphate Isomerase, Fructose-1, 6-bisphosphate Aldolase and Fructose-1, 6-bisphosphatase in E.coli.

To establish a way to control or to decrease the daily increasing concentration of atmospheric CO(2), metabolically engineering Cyanobacteria was taken for the improvement of its efficiency of photosynthetic CO(2) fixation. As a preliminary stage of this study, three genes coding for three important Calvin cycle enzymes, i.e. triosephosphate isomerase (TPI), fructose-1, 6-bisphosphate aldolase(FBP aldolase),and fructose-1, 6-bisphosphatase(FBPase), respectively, have been cloned into one plasmid, pTrcFAT, which is controlled by promoter trc. Successful co-transcriptional expression of these three genes resulted inhigh yields of these enzymes under the induction of 0.25 mmol/L IPTG. Bioassay showed that the expressed enzymes from one liter of culture could directly catalyze DHAP conversion into 700 &mgr;mol of fructose-6-phosphate (F-6-P) per one minute. Furthermore, in order to introduce the three genes co-expression system into Cyanobacteria, a shuttle plasmid between E.coli and Cyanobacteria was constructed using plasmid pTrcFAT and a shuttle vector pDC-8, forming ashuttle plasmid pDCFAT-2 containing a dimer of the three genes co-expression operator. Successful co-expression in E.coli of pDCFAT-2 with higher full activity has been obtained. This shuttle was used to transform of Cyanobacteria Synechococcus sp. PCC 7942, and a few positive colonies were obtained.

Cloning and High Expression in E.coli of a Chimeric Gene Coding for Rice Fructose-l,6-bisphosphate Aldolase.

A chimeric gene (l 104 bp) coding for rice fructose-l,6-bisphosphate aldolase has been constructed by DNA recombination of a synthetic 5'- fragment (-24 to 272) and an RT-PCR amplified product at restriction site S fu I. The synthetic fragment was assembled from six oligonucleotides by T4 DNA ligase reaction according to a single-stranded DNA method (Chen H-B et al, Nucleic Acids Res 1990, 18, 871-878), the PCR amplified fragment (217 - 1 080) was obtained by carrying out a PCR in the presence of rice cDNA as the template and both the 5'- and the 3'- primers. The whole gene was successively cloned into plasmids pWR13 and pPLc2833, and highly expressed in E. coli to produce the expected product. After purification through stepwise precipitation and cation-exchange column chromatography, the recombinant aldolase showed an enzyme activity as high as (1l.0 +/- 0.3) units/mg with the turnover number = 27s(-1) and K(m) (FBP)=4.2 &mgr;M by two different methods.