Multi-tests for pore structure characterization-A case study using lamprophyre

The pore structure plays an important role to understand methane adsorption, storage and flow behavior of geological materials. In this paper, the multi-tests including N2 adsorption, mercury intrusion porosimetry (MIP) and CT reconstruction have been proposed on Tashan lamprophyre samples. The main findings are listed: (1) The pore size distribution has a broad range ranging from 2-100000nm, among which the adsorption pores (\u3c100nm) occupies the mainly specific surface areas and pore volume while the seepage pores (\u3e100nm) only account for 34% of total pore volume. (2) The lamprophyre open pores are mainly slit-like/plate-like and ink-bottle-shaped pores on a two-dimensional level. The lamprophyre 3D pore structure shows more stochastic and anisotropic extension on the z axis to form a complex pore system on a three-dimensional level. (3) The closed pores (\u3e647nm) occupy averaged 74.86% and 72.75% of total pores (\u3e647nm) volume and specific surface area indicating a poor connectivity pore system. The revealed results provide basic information for understanding the abnormal methane emission reasons in similar geological conditions with lamprophyre invasions

Profiling the peripheral blood T cell receptor repertoires of gastric cancer patients

Cancer driven by somatic mutations may express neoantigens that can trigger T-cell immune responses. Since T-cell receptor (TCR) repertoires play critical roles in anti-tumor immune responses for oncology, next-generation sequencing (NGS) was used to profile the hypervariable complementarity-determining region 3 (CDR3) of the TCR-beta chain in peripheral blood samples from 68 gastric cancer patients and 49 healthy controls. We found that most hyper-expanded CDR3 are individual-specific, and the gene usage of TRBV3-1 is more frequent in the tumor group regardless of tumor stage than in the healthy control group. We identified 374 hyper-expanded tumor-specific CDR3, which may play a vital role in anti-tumor immune responses. The patients with stage IV gastric cancer have higher EBV-specific CDR3 abundance than the control. In conclusion, analysis of the peripheral blood TCR repertoires may provide the biomarker for gastric cancer prognosis and guide future immunotherapy

Genome Sequencing of Sulfolobus sp. A20 from Costa Rica and Comparative Analyses of the Putative Pathways of Carbon, Nitrogen, and Sulfur Metabolism in Various Sulfolobus Strains

The genome of Sulfolobus sp. A20 isolated from a hot spring in Costa Rica was sequenced. This circular genome of the strain is 2,688,317 bp in size and 34.8% in G+C content, and contains 2591 open reading frames (ORFs). Strain A20 shares ~95.6% identity at the 16S rRNA gene sequence level and <30% DNA-DNA hybridization (DDH) values with the most closely related known Sulfolobus species (i.e., Sulfolobus islandicus and Sulfolobus solfataricus), suggesting that it represents a novel Sulfolobus species. Comparison of the genome of strain A20 with those of the type strains of S. solfataricus, Sulfolobus acidocaldarius, S. islandicus, and Sulfolobus tokodaii, which were isolated from geographically separated areas, identified 1801 genes conserved among all Sulfolobus species analyzed (core genes). Comparative genome analyses show that central carbon metabolism in Sulfolobus is highly conserved, and enzymes involved in the Entner-Doudoroff pathway, the tricarboxylic acid cycle and the CO2 fixation pathways are predominantly encoded by the core genes. All Sulfolobus species encode genes required for the conversion of ammonium into glutamate/glutamine. Some Sulfolobus strains have gained the ability to utilize additional nitrogen source such as nitrate (i.e., S. islandicus strain REY15A, LAL14/1, M14.25, and M16.27) or urea (i.e., S. islandicus HEV10/4, S. tokodaii strain7, and S. metallicus DSM 6482). The strategies for sulfur metabolism are most diverse and least understood. S. tokodaii encodes sulfur oxygenase/reductase (SOR), whereas both S. islandicus and S. solfataricus contain genes for sulfur reductase (SRE). However, neither SOR nor SRE genes exist in the genome of strain A20, raising the possibility that an unknown pathway for the utilization of elemental sulfur may be present in the strain. The ability of Sulfolobus to utilize nitrate or sulfur is encoded by a gene cluster flanked by IS elements or their remnants. These clusters appear to have become fixed at a specific genomic site in some strains and lost in other strains during the course of evolution. The versatility in nitrogen and sulfur metabolism may represent adaptation of Sulfolobus to thriving in different habitats.Fundación Nacional de Ciencias Naturales de China/[31130003]/NSFC/ChinaUniversidad de Costa Rica/[VI 801–B0–530]/UCR/Costa RicaUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Básicas::Centro de Investigación en Biología Celular y Molecular (CIBCM

Learned Smartphone ISP on Mobile GPUs with Deep Learning, Mobile AI & AIM 2022 Challenge: Report

The role of mobile cameras increased dramatically over the past few years, leading to more and more research in automatic image quality enhancement and RAW photo processing. In this Mobile AI challenge, the target was to develop an efficient end-to-end AI-based image signal processing (ISP) pipeline replacing the standard mobile ISPs that can run on modern smartphone GPUs using TensorFlow Lite. The participants were provided with a large-scale Fujifilm UltraISP dataset consisting of thousands of paired photos captured with a normal mobile camera sensor and a professional 102MP medium-format FujiFilm GFX100 camera. The runtime of the resulting models was evaluated on the Snapdragon's 8 Gen 1 GPU that provides excellent acceleration results for the majority of common deep learning ops. The proposed solutions are compatible with all recent mobile GPUs, being able to process Full HD photos in less than 20-50 milliseconds while achieving high fidelity results. A detailed description of all models developed in this challenge is provided in this paper

The prognostic value of whole-genome DNA methylation in response to Leflunomide in patients with Rheumatoid Arthritis

ObjectiveAlthough Leflunomide (LEF) is effective in treating rheumatoid arthritis (RA), there are still a considerable number of patients who respond poorly to LEF treatment. Till date, few LEF efficacy-predicting biomarkers have been identified. Herein, we explored and developed a DNA methylation-based predictive model for LEF-treated RA patient prognosis.MethodsTwo hundred forty-five RA patients were prospectively enrolled from four participating study centers. A whole-genome DNA methylation profiling was conducted to identify LEF-related response signatures via comparison of 40 samples using Illumina 850k methylation arrays. Furthermore, differentially methylated positions (DMPs) were validated in the 245 RA patients using a targeted bisulfite sequencing assay. Lastly, prognostic models were developed, which included clinical characteristics and DMPs scores, for the prediction of LEF treatment response using machine learning algorithms.ResultsWe recognized a seven-DMP signature consisting of cg17330251, cg19814518, cg20124410, cg21109666, cg22572476, cg23403192, and cg24432675, which was effective in predicting RA patient’s LEF response status. In the five machine learning algorithms, the support vector machine (SVM) algorithm provided the best predictive model, with the largest discriminative ability, accuracy, and stability. Lastly, the AUC of the complex model(the 7-DMP scores with the lymphocyte and the diagnostic age) was higher than the simple model (the seven-DMP signature, AUC:0.74 vs 0.73 in the test set).ConclusionIn conclusion, we constructed a prognostic model integrating a 7-DMP scores with the clinical patient profile to predict responses to LEF treatment. Our model will be able to effectively guide clinicians in determining whether a patient is LEF treatment sensitive or not

Structural, Stability, Dynamic and Binding Properties of the ALS-Causing T46I Mutant of the hVAPB MSP Domain as Revealed by NMR and MD Simulations

T46I is the second mutation on the hVAPB MSP domain which was recently identified from non-Brazilian kindred to cause a familial amyotrophic lateral sclerosis (ALS). Here using CD, NMR and molecular dynamics (MD) simulations, we characterized the structure, stability, dynamics and binding capacity of the T46I-MSP domain. The results reveal: 1) unlike P56S which we previously showed to completely eliminate the native MSP structure, T46I leads to no significant disruption of the native secondary and tertiary structures, as evidenced from its far-UV CD spectrum, as well as Cα and Cβ NMR chemical shifts. 2) Nevertheless, T46I does result in a reduced thermodynamic stability and loss of the cooperative urea-unfolding transition. As such, the T46I-MSP domain is more prone to aggregation than WT at high protein concentrations and temperatures in vitro, which may become more severe in the crowded cellular environments. 3) T46I only causes a 3-fold affinity reduction to the Nir2 peptide, but a significant elimination of its binding to EphA4. 4) EphA4 and Nir2 peptide appear to have overlapped binding interfaces on the MSP domain, which strongly implies that two signaling networks may have a functional interplay in vivo. 5) As explored by both H/D exchange and MD simulations, the MSP domain is very dynamic, with most loop residues and many residues on secondary structures highly fluctuated or/and exposed to bulk solvent. Although T46I does not alter overall dynamics, it does trigger increased dynamics of several local regions of the MSP domain which are implicated in binding to EphA4 and Nir2 peptide. Our study provides the structural and dynamic understanding of the T46I-causing ALS; and strongly highlights the possibility that the interplay of two signaling networks mediated by the FFAT-containing proteins and Eph receptors may play a key role in ALS pathogenesis

Complexity absorption : A processual strategic approach to corporate entrepreneurship strategy

The author Haina Zhang acknowledges the support of research grant received from the Lancaster University Research Committee (award reference: SGS21/33). The author is also grateful to Professor David Brown for his suggestions on earlier version of this paper.Peer reviewedPublisher PD

Association between professional identity and humanistic caring ability in Chinese nursing students: a cross-sectional study in Changsha, Hunan, China

AbstractHumanistic caring (HC) is a key ability that nurses need. We aimed to explore factors related to humanistic caring ability (HCA) among Chinese nursing students and the association between professional identity (PI) and HCA. A cross-sectional survey was conducted. HCA of Nursing Undergraduates Assessment Scale (HCANU) and PI Scale for Nurse Students (PIQNS) were displayed. Linear regression analysis and Pearson correlation analysis were used. Education (β=-.161, P = .009), dimensions of professional self-image (β=.271, P = .028), career choice independence (β=.228, P < .001), and social comparison and self-reflection (β=-.102, P = .180) were independent predictors of HCA. PI (r = .578, P < .001) was associated with HCA. An association between PI and HCA has been found among nursing students. PI is an important consideration in the development, implementation, and evaluation of interventions for HCA