A novel pyruvate kinase and its application in lactic acid production under oxygen deprivation in Corynebacterium glutamicum

BACKGROUND: Pyruvate kinase (Pyk) catalyzes the generation of pyruvate and ATP in glycolysis and functions as a key switch in the regulation of carbon flux distribution. Both the substrates and products of Pyk are involved in the tricarboxylic acid cycle, anaplerosis and energy anabolism, which places Pyk at a primary metabolic intersection. Pyks are highly conserved in most bacteria and lower eukaryotes. Corynebacterium glutamicum is an industrial workhorse for the production of various amino acids and organic acids. Although C. glutamicum was assumed to possess only one Pyk (pyk1, NCgl2008), NCgl2809 was annotated as a pyruvate kinase with an unknown role. RESULTS: Here, we identified that NCgl2809 was a novel pyruvate kinase (pyk2) in C. glutamicum. Complementation of the WTΔpyk1Δpyk2 strain with the pyk2 gene restored its growth on d-ribose, which demonstrated that Pyk2 could substitute for Pyk1 in vivo. Pyk2 was co-dependent on Mn(2+) and K(+) and had a higher affinity for ADP than phosphoenolpyruvate (PEP). The catalytic activity of Pyk2 was allosterically regulated by fructose 1,6-bisphosphate (FBP) activation and ATP inhibition. Furthermore, pyk2 and ldhA, which encodes l-lactate dehydrogenase, were co-transcribed as a bicistronic mRNA under aerobic conditions and pyk2 deficiency had a slight effect on the intracellular activity of Pyk. However, the mRNA level of pyk2 in the wild-type strain under oxygen deprivation was 14.24-fold higher than that under aerobic conditions. Under oxygen deprivation, pyk1 or pyk2 deficiency decreased the generation of lactic acid, and the overexpression of either pyk1 or pyk2 increased the production of lactic acid as the activity of Pyk increased. Fed-batch fermentation of the pyk2-overexpressing WTΔpyk1 strain produced 60.27 ± 1.40 g/L of lactic acid, which was a 47% increase compared to the parent strain under oxygen deprivation. CONCLUSIONS: Pyk2 functioned as a pyruvate kinase and contributed to the increased level of Pyk activity under oxygen deprivation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12896-016-0313-6) contains supplementary material, which is available to authorized users

Automatic Analysis of Large-scale Nanopore Data Using Hidden Markov Models

In this paper we developed a modified Hidden Markov Model (HMM) to analyze the raw nanopore experimental data. Traditionally, prior to further analysis the measured nanopore data must be pre-filtered, but the filtering usually distorts the waveform of the blockage current, especially for rapid translocations and bumping blockages. The HMM is known to be robust with respect to strong noise and thus suitable for processing the raw nanopore data, but its performance is susceptible to the setting of initial parameters. To overcome this problem, we use the Fuzzy c-Means (FCM) algorithm to initialize the HMM parameters in this work. Then we use the Viterbi training algorithm to optimize the HMM. Finally, both the simulated and experimental data analysis results are presented to show the effectiveness of the proposed method for detection of the nanopore current blockage events in analytical chemistry.publishedVersio

Visualizing the diffusion of digital mammography in New York State

Digital mammography saw rapid adoption during the first decade of the 2000s. According to data maintained by the Food and Drug Administration, which regulates mammography machines, fewer than 1 percent of the machines in 2001 were digital. By 2014, this figure had risen to 94%. We were interested in identifying the times and locations where the technology was introduced within the state of New York as a way of illustrating the uneven introduction of this technology. While the diffusion of medical innovation has been well-studied, there have not been many instances where maps or geographic information science methods have been used to inform the interpretation. Here we illustrate the adoption of digital mammography in New York as of 2005, 2008, and 2011

Effect of Heart Rate Variability Biofeedback Training on Score and Stress Level of Shooting Athletes

This study aimed to explore the impact of a 12-week emWave pro-based heart rate variability biofeedback training followed by a 2-week follow-up on shooters' performance, stress levels, and heart rate variability (HRV). Thirty-six shooters aged 18-24 (18 experimental, 18 control) participated. The experimental group underwent 12 weeks of biofeedback and shooting training, while the control group only received shooting training. Results showed significant improvements in performance, stress levels, and HRV parameters in the experimental group, reflecting enhanced parasympathetic activity. Biofeedback reduced training and competition stress, improving overall performance and stability during matches, emphasizing its effectiveness in shooter training

MPCPA: Multi-Center Privacy Computing with Predictions Aggregation based on Denoising Diffusion Probabilistic Model

Privacy-preserving computing is crucial for multi-center machine learning in many applications such as healthcare and finance. In this paper a Multi-center Privacy Computing framework with Predictions Aggregation (MPCPA) based on denoising diffusion probabilistic model (DDPM) is proposed, in which conditional diffusion model training, DDPM data generation, a classifier, and strategy of prediction aggregation are included. Compared to federated learning, this framework necessitates fewer communications and leverages high-quality generated data to support robust privacy computing. Experimental validation across multiple datasets demonstrates that the proposed framework outperforms classic federated learning and approaches the performance of centralized learning with original data. Moreover, our approach demonstrates robust security, effectively addressing challenges such as image memorization and membership inference attacks. Our experiments underscore the efficacy of the proposed framework in the realm of privacy computing, with the code set to be released soon

Dehydrogenation of formic acid over Pd/C catalysts: Insight into the cold plasma treatment

Safe and efficient generation of renewable hydrogen via dehydrogenation of cheap and sustainable formic acid using supported Pd catalysts has attracted significant interest. Non-thermal (cold) plasma is demonstrably a fast...</p

Retracted “Serum amyloid P down-regulates CCL-1 expression, and inhibits Ras/MAPK signaling and development of breast cancer”

This article previously published in Volume 17 Issue 16 of this journal in September 2017 has been retracted in line with the guidelines from the Committee on Publication Ethics (COPE,http://publicationethics.org/ resources/guidelines). Retraction: Ding S, Li H, Li X, Wang W, Du X, Dong G, Zhang P. Serum amyloid P down-regulates CCL-1 expression, and inhibits Ras/MAPK signaling and development of breast cancer. Trop J Pharm Res 2017; 16(9):2089-2095 doi: http://dx.doi.org/10.4314/tjpr.v16i9.7 To the editor: The figures in the paper were plagiarized partly from an earlier published article, Qi et al, P-selectinmediated tablet adhesion promoters tumor growth. Oncotarget 2015;30:6(9):6584–6596, and data from a master's thesis submitted by Bin Li under the supervision of Professor Lijing Wang and Professor Cuiling Qi. Sincerely, Cuiling Qi and Lijing Wang