Simple and efficient expression of codon-optimized mouse leukemia inhibitory factor in Escherichia coli

Purpose: To obtain a higher yield of mouse leukemia inhibitory factor to maintain the proliferation potential of pluripotent stem cells at a low cost.Methods: A method was designed to produce recombinant mLIF protein (rmLIF) in Escherichia coli. Through analysis of rmLIF sequence, it was found that rare codons were interspersed. After mutation from rare codons to Escherichia coli (E. coli) preferred ones were selected, the mutated gene mLIFm was cloned into pET15b vector. The pET15b-mLIFm was then transformed into Rosetta-gami strain and induced with optimal conditions at 18 oC for 16 h. Mass spectrometry was carried out to identify the peptides.Results: After purification, the yield of the codon-optimized rmLIFm was 141 mg/L, compared with 110 mg/L for the original rmLIF. Mass spectral analysis showed the presence of four major peptides each with an intensity > 10 % at m/z 1031.57, 1539.82, 1412.01 and 2229.10 in mLIFm, respectively. Histagged rmLIFm fusion protein displayed the potential to maintain the morphology of undifferentiated mouse embryonic stem cells (mESCs), which were positive for mESCs markers (Oct-4, Nanog, Sox-2, stage-specific embryonic antigen-1).Conclusion: The findings provide a means to produce mLIF in a short, useful, cost-effective and environmentally-friendly manner, and thus lays a foundation for further studies of mLIF.Keywords: Leukemia inhibitory factor, Mutated gene, Protein expression, Purification, Stem cells, Peptides, Escherichia col

Fuzzy multilayer clustering and fuzzy label regularization for unsupervised person reidentification

Unsupervised person reidentification has received more attention due to its wide real-world applications. In this paper, we propose a novel method named fuzzy multilayer clustering (FMC) for unsupervised person reidentification. The proposed FMC learns a new feature space using a multilayer perceptron for clustering in order to overcome the influence of complex pedestrian images. Meanwhile, the proposed FMC generates fuzzy labels for unlabeled pedestrian images, which simultaneously considers the membership degree and the similarity between the sample and each cluster. We further propose the fuzzy label regularization (FLR) to train the convolutional neural network (CNN) using pedestrian images with fuzzy labels in a supervised manner. The proposed FLR could regularize the CNN training process and reduce the risk of overfitting. The effectiveness of our method is validated on three large-scale person reidentification databases, i.e., Market-1501, DukeMTMC-reID, and CUHK03

Outage and Capacity Performance Evaluation of Distributed MIMO Systems over a Composite Fading Channel

The exact closed-form expressions regarding the outage probability and capacity of distributed MIMO (DMIMO) systems over a composite fading channel are derived. This is achieved firstly by using a lognormal approximation to a gamma-lognormal distribution when a mobile station (MS) in the cell is in a fixed position, and the so-called maximum ratio transmission/selected combining (MRT-SC) and selected transmission/maximum ratio combining (ST-MRC) schemes are adopted in uplink and downlink, respectively. Then, based on a newly proposed nonuniform MS cell distribution model, which is more consistent with the MS cell hotspot distribution in an actual communication environment, the average outage probability and capacity formulas are further derived. Finally, the accuracy of the approximation method and the rationality of the corresponding theoretical analysis regarding the system performance are proven and illustrated by computer simulations

FVGWAS: Fast voxelwise genome wide association analysis of large-scale imaging genetic data

More and more large-scale imaging genetic studies are being widely conducted to collect a rich set of imaging, genetic, and clinical data to detect putative genes for complexly inherited neuropsychiatric and neurodegenerative disorders. Several major big-data challenges arise from testing genome-wide (NC > 12 million known variants) associations with signals at millions of locations (NV ~ 106) in the brain from thousands of subjects (n ~ 103). The aim of this paper is to develop a Fast Voxelwise Genome Wide Association analysiS (FVGWAS) framework to e ciently carry out whole-genome analyses of whole-brain data. FVGWAS consists of three components including a heteroscedastic linear model, a global sure independence screening (G-SIS) procedure, and a detection procedure based on wild bootstrap methods. Specifically, for standard linear association, the computational complexity is O(nNV NC) for voxelwise genome wide association analysis (VGWAS) method compared with O((NC + NV)n2) for FVGWAS. Simulation studies show that FVGWAS is an effcient method of searching sparse signals in an extremely large search space, while controlling for the family-wise error rate. Finally, we have successfully applied FVGWAS to a large-scale imaging genetic data analysis of ADNI data with 708 subjects, 193,275 voxels in RAVENS maps, and 501,584 SNPs, and the total processing time was 203,645 seconds for a single CPU. Our FVG-WAS may be a valuable statistical toolbox for large-scale imaging genetic analysis as the field is rapidly advancing with ultra-high-resolution imaging and whole-genome sequencing

Knowledge mapping concerning applications of nanocomposite hydrogels for drug delivery: A bibliometric and visualized study (2003–2022)

Background: Nanocomposite Hydrogels (NHs) are 3D molecular networks formed by physically or covalently crosslinking polymer with nanoparticles or nanostructures, which are particularly suitable for serving as carriers for drug delivery systems. Many articles pertaining to the applications of Nanocomposite Hydrogels for drug delivery have been published, however, the use of bibliometric and visualized analysis in this area remains unstudied. The purpose of this bibliometric study intended to comprehensively analyze the knowledge domain, research hotspots and frontiers associated with the applications of Nanocomposite Hydrogels for drug delivery.Methods: We identified and retrieved the publications concerning the applications of NHs for drug delivery between 2003 and 2022 from Web of Science Core Collection Bibliometric and visualized analysis was utilized in this investigative study.Results: 631 articles meeting the inclusion criteria were identified and retrieved from WoSCC. Among those, 2,233 authors worldwide contributed in the studies, accompanied by an average annual article increase of 24.67%. The articles were co-authored by 764 institutions from 52 countries/regions, and China published the most, followed by Iran and the United States. Five institutions published more than 40 papers, namely Univ Tabriz (n = 79), Tabriz Univ Med Sci (n = 70), Islamic Azad Univ (n = 49), Payame Noor Univ (n = 42) and Texas A&M Univ (n = 41). The articles were published in 198 journals, among which the International Journal of Biological Macromolecules (n = 53) published the most articles, followed by Carbohydrate Polymers (n = 24) and ACS Applied Materials and Interfaces (n = 22). The top three journals most locally cited were Carbohydrate Polymers, Biomaterials and Advanced materials. The most productive author was Namazi H (29 articles), followed by Bardajee G (15 articles) and Zhang J (11 articles) and the researchers who worked closely with other ones usually published more papers. “Doxorubicin,” “antibacterial” and “responsive hydrogels” represent the current research hotspots in this field and “cancer therapy” was a rising research topic in recent years. “(cancer) therapeutics” and “bioadhesive” represent the current research frontiers.Conclusion: This bibliometric and visualized analysis offered an investigative study and comprehensive understanding of publications regarding the applications of Nanocomposite Hydrogels for drug delivery from 2003 to 2022. The outcome of this study would provide insights for researchers in the field of Nanocomposite Hydrogels applications for drug delivery

Rapamycin Enhances Mitophagy and Attenuates Apoptosis After Spinal Ischemia-Reperfusion Injury

The spinal cord is extremely vulnerable to ischemia-reperfusion (I/R) injury, and the mitochondrion is the most crucial interventional target. Rapamycin can promote autophagy and exert neuroprotective effects in several diseases of the central nervous system. However, the impact of rapamycin via modulating mitophagy and apoptosis after spinal cord ischemia-reperfusion injury remains unclear. This study was undertaken to investigate the potential role of rapamycin in modulating mitophagy and mitochondria-dependent apoptosis using the spinal cord ischemia-reperfusion injury (SCIRI) mouse model. We found that rapamycin significantly (p < 0.05) enhanced mitophagy by increasing the translocation of p62 and Parkin to the damaged mitochondria in the mouse spinal cord injury model. At the same time, rapamycin significantly (p < 0.05) decreased mitochondrial apoptosis related protein (Apaf-1, Caspase-3, Caspase-9) expression by inhibiting Bax translocation to the mitochondria and the release of the cytochrome c from the mitochondria. After 24 h following SCIRI, rapamycin treatment reduced the TUNEL+ cells in the spinal cord ischemic tissue and improved the locomotor function in these mice. Our results therefore demonstrate that rapamycin can improve the locomotor function by promoting mitophagy and attenuating SCIRI -induced apoptosis, indicating its potential therapeutic application in a spinal cord injury

Pharmacokinetic Comparison of Ferulic Acid in Normal and Blood Deficiency Rats after Oral Administration of Angelica sinensis, Ligusticum chuanxiong and Their Combination

Radix Angelica Sinensis (RAS) and Rhizome Ligusticum (RLC) combination is a popular herb pair commonly used in clinics for treatment of blood deficiency syndrome in China. The aim of this study is to compare the pharmacokinetic properties of ferulic acid (FA), a main bioactive constituent in both RAS and RLC, between normal and blood deficiency syndrome animals, and to investigate the influence of compatibility of RAS and RLC on the pharmacokinetic of FA. The blood deficiency rats were induced by injecting 2% Acetyl phenylhydrazine (APH) on the first day, every other day, to a total of five times, at the dosage of 100, 50, 50, 30, 30 mg/kg body mass, respectively. Quantification of FA in rat plasma was achieved by using a simple and rapid HPLC method. Plasma samples were collected at different time points to construct pharmacokinetic profiles by plotting drug concentration versus time, and estimate pharmacokinetic parameters. Between normal and blood deficiency model groups, both AUC(0–t) and Cmax of FA in blood deficiency rats after RAS-RLC extract administration increased significantly (P < 0.05), while clearance (CL) decreased significantly. Among three blood deficiency model groups, t1/2α, Vd, AUC(0–t) and AUC(0–∞) all increased significantly in the RAS-RLC extract group compared with the RAS group. The results indicated that FA was absorbed better and eliminated slower in blood deficiency rats; RLC could significantly prolong the half-life of distribution, increase the volume of distribution and the absorption amount of FA of RAS in blood deficiency rats, which may be due to the synergic action when RAS and RLC were used together to treat blood deficiency syndrome

Schizophrenia-associated somatic copy-number variants from 12,834 cases reveal recurrent NRXN1 and ABCB11 disruptions

While germline copy-number variants (CNVs) contribute to schizophrenia (SCZ) risk, the contribution of somatic CNVs (sCNVs)—present in some but not all cells—remains unknown. We identified sCNVs using blood-derived genotype arrays from 12,834 SCZ cases and 11,648 controls, filtering sCNVs at loci recurrently mutated in clonal blood disorders. Likely early-developmental sCNVs were more common in cases (0.91%) than controls (0.51%, p = 2.68e−4), with recurrent somatic deletions of exons 1–5 of the NRXN1 gene in five SCZ cases. Hi-C maps revealed ectopic, allele-specific loops forming between a potential cryptic promoter and non-coding cis-regulatory elements upon 5′ deletions in NRXN1. We also observed recurrent intragenic deletions of ABCB11, encoding a transporter implicated in anti-psychotic response, in five treatment-resistant SCZ cases and showed that ABCB11 is specifically enriched in neurons forming mesocortical and mesolimbic dopaminergic projections. Our results indicate potential roles of sCNVs in SCZ risk