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

TGFBI Gene Mutation Analysis of Clinically Diagnosed Granular Corneal Dystrophy Patients Prior to PTK: A Pilot Study from Eastern China

This study investigated the TGFBI gene mutation types in outpatients clinically diagnosed with granular corneal dystrophy (GCD) prior to phototherapeutic keratectomy (PTK), also calculated the mutation rate of subjects with normal corneas, but positive family history. Clinical GCD outpatients and consanguineous family members were enrolled in this study. Among total 42 subjects: 24 patients from 23 unrelated families had typical signs of GCD on corneas; 5 patients from 5 unrelated families had atypical signs; 13 subjects from 11 unrelated families had no corneal signs but positive family history. Using Avellino gene test kit, the TGFBI mutation detection was performed on DNA samples from all subjects. 36 subjects were detected to carry heterozygous TGFBI gene mutations. Among 24 clinical GCD patients, the proportion of R124H, R555Q, R124L, R555W and R124C were 37.5%, 16.7%, 25.0%, 20.8% and 0%, respectively, and 2 patients had been diagnosed with GCD according to the opacities thriving after LASIK (R124H) and PRK (R555W). The mutation rate of 13 subjects having no signs but positive family history was 69.2%. R124H mutation is the most prominent mutation type among GCD outpatients in Eastern China. It is recommended to conduct gene detection for patients with positive family history prior to refractive surgeries

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

CT radiomics model combined with clinical and radiographic features for discriminating peripheral small cell lung cancer from peripheral lung adenocarcinoma

PurposeExploring a non-invasive method to accurately differentiate peripheral small cell lung cancer (PSCLC) and peripheral lung adenocarcinoma (PADC) could improve clinical decision-making and prognosis.MethodsThis retrospective study reviewed the clinicopathological and imaging data of lung cancer patients between October 2017 and March 2022. A total of 240 patients were enrolled in this study, including 80 cases diagnosed with PSCLC and 160 with PADC. All patients were randomized in a seven-to-three ratio into the training and validation datasets (170 vs. 70, respectively). The least absolute shrinkage and selection operator regression was employed to generate radiomics features and univariate analysis, followed by multivariate logistic regression to select significant clinical and radiographic factors to generate four models: clinical, radiomics, clinical-radiographic, and clinical-radiographic-radiomics (comprehensive). The Delong test was to compare areas under the receiver operating characteristic curves (AUCs) in the models.ResultsFive clinical-radiographic features and twenty-three selected radiomics features differed significantly in the identification of PSCLC and PADC. The clinical, radiomics, clinical-radiographic and comprehensive models demonstrated AUCs of 0.8960, 0.8356, 0.9396, and 0.9671 in the validation set, with the comprehensive model having better discernment than the clinical model (P=0.036), the radiomics model (P=0.006) and the clinical–radiographic model (P=0.049).ConclusionsThe proposed model combining clinical data, radiographic characteristics and radiomics features could accurately distinguish PSCLC from PADC, thus providing a potential non-invasive method to help clinicians improve treatment decisions

An Anti-Clustering Model for Stability Enhancement of a 3D Moving Particle Semi-Implicit Method and Two-Phase Coupling between MPS and Euler Grids

As a Lagrangian gridless particle method, the MPS (Moving Particle Semi-implicit) method has a wide engineering application. However, for complex 3D flows, unphysical pressure oscillations often occur and result in the failure of simulations. This paper compares the stability enhancement methods proposed by different researchers to develop a 3D, stable MPS method. The results indicate that the proposed methods are incapable of eliminating the particle clustering that leads to instability as the main source in coarser particle spacing cases. An anti-clustering model, referring to the SPH (Smoothed Particle Hydrodynamics) artificial viscosity model, is proposed to further reduce instability. Combining various proposed methods and models, several typical examples are simulated comparatively. The results are compared with those of the VOF (Volume of Fluid) model using commercial software to validate the accuracy and stability of the combination of the proposed methods and models. It is concluded that (1) 3D cases that adopt a high-order Laplacian model and high-order source terms in PPE are more accurate than those adopting the low-order operators; (2) the proposed anti-clustering model can produce a tuned interparticle force to prevent particle clustering and introduce no additional viscosity effects in the flow of the normal state, which plays a very positive role for further stability enhancement of MPS; (3) particle resolution significantly maintains simulation accuracy given the stable algorithms by the combination of stability enhancement methods. The 3D MPS method is coupled with the Euler grid (FLUENT V17 software, ANSYS, Pittsburgh, PA, USA) in two phases. In particular, the 3D MPS algorithm is used to calculate the liquid-phase change from the continuous to the dispersed, and the finite volume method based on the Euler grid is adopted to measure the corresponding gas-phase motion. The atomization of the liquid jet under static air flow is calculated and compared with the results of the VOF method, which can capture the continuous interface

A Film Bulk Acoustic Resonator-Based Sensor with AlN Piezoelectric Material for Detecting Ethanol and Acetone

Measurement of a volatile solution is essential for laboratory safety and hospital clinic safety. In this paper, we present an ethanol-sensing and acetone-sensing device using an AlN piezoelectric material-based film bulk acoustic resonator (FBAR). In order to realize volatile solution sensing, the AlN-based FBAR was designed, fabricated, and characterized. In our sensor structure, the upper electrode is a Ti/Au (30 nm/150 nm) composite electrode, the bottom electrode is Mo material with 150 nm thickness, and the piezoelectric sensing material is 0.8 μm thickness AlN. We conducted the experiment of ethanol measurement and acetone measurement by using this FBAR detector on the probe station within the vector network analyzer. The resonance frequency of the FBAR detector decreased as the concentration of ethanol increases, while under the circumstance of acetone concentration increasing, the detector’s response is the opposite. The sensing mechanisms of both ethanol measurement and acetone measurement are discussed in this paper, demonstrating that this FBAR detector could be able to distinguish acetone from ethanol due to different sensing mechanisms

Graphene Based FET Biosensor for Organic-Phosphorous Sample Detection and the Enzymatic Analysis

Our paper presents a flexible enzymatic acetylcholinesterase graphene based FET biosensor of the target organic phosphorous. The sensor’s purpose is to detect pesticide residues in the field of food safety. In our sensor design, the material is graphene with its functionalization, and graphene based FET structure will be discussed in one section of this paper. The mechanism of this graphene sensor is the enzymatic linked reaction on a sensor surface. The enzyme is fixed on the sensor surface by the linker 3-mercapto propionic acid. Measurement experiments using the biosensor were performed for detecting the concentration of isocarbophos (an organophosphate). The enzymatic biosensor has successfully detected 100 μg/mL isocarbophos from the water sample, presenting a significant detection limit index for organophosphate detection

Graphene Based FET Biosensor for Organic-Phosphorous Sample Detection and the Enzymatic Analysis

Our paper presents a flexible enzymatic acetylcholinesterase graphene based FET biosensor of the target organic phosphorous. The sensor’s purpose is to detect pesticide residues in the field of food safety. In our sensor design, the material is graphene with its functionalization, and graphene based FET structure will be discussed in one section of this paper. The mechanism of this graphene sensor is the enzymatic linked reaction on a sensor surface. The enzyme is fixed on the sensor surface by the linker 3-mercapto propionic acid. Measurement experiments using the biosensor were performed for detecting the concentration of isocarbophos (an organophosphate). The enzymatic biosensor has successfully detected 100 μg/mL isocarbophos from the water sample, presenting a significant detection limit index for organophosphate detection

Geomorphologic Analysis of Small River Basin within the Framework of Fractal Tree

This paper presents the modified framework of geomorphologic analysis based on the concept of fractal tree. Especially, it is intended to provide hydrologic practitioners with the information on the fractal property of small river basins. To this end, the complete drainage path network is applied to a growth process of a fractal tree for the basin of interest by connecting a channel network to overland drainage pathways. The growth process of a fractal tree would occur only within the limited region possessing channel flow properties in a natural river basin. The exponent of the intra basin type of Hack’s law could show a variable trend in small river basins mainly due to anisotropic property of the catchment planform. The bifurcation process of a drainage path network might be more sensitive to the growth step of the fractal tree than the meandering process of drainage path segment. The fractal dimension from the sinuosity of a channel segment is relatively stable compared to the one from the bifurcation process of the network, so that the geomorphologic features of a small river basin can be characterized by the anisotropic property of catchment planform as well as the bifurcation property of drainage path network with the growth of the fractal tree

Parametric study for MP-PIC simulation of bubbling fluidized beds with Geldart A particles

This is a parametric study for multi-phase particle in cell (MP-PIC) simulation of bubbling fluidized beds with Geldart A particles using the open source MFIX program. The main parameters have been studied including drag models, grid resolution and number of particles per parcel (PPP). And the calculated axial/radial solid distribution and bed height are compared with the experimental data for validation. It is shown that the drag model can significantly affect the calculation results of bubbling fluidized bed with Geldart A particles. Specifically, the Energy Minimization Multi-scale (EMMS) bubbling drag model can predict right bubbling phenomenon and also improve the accuracy compared to the homogeneous drag model. Bubble analysis shows that there exists a stable average bubble diameter when the bed becomes stable. The average bubble circularities are about 0.5 for the two bubbling bed studied in this work, even though they have different average bubble diameter. Parameter analysis shows that the accuracy of the calculated results improves with decreasing grid size or PPP. There exists a threshold value for grid size/PPP, below which, grid/PPP independent result can be obtained. The PPP plays the similar role to grid resolution in MP-PIC simulation. (C) 2018 Elsevier B.V. All rights reserved.</p