Numerical evaluation of spinal reconstruction using a 3D printed vertebral body replacement implant: effects of material anisotropy

Background and objectiveArtificial vertebral implants have been widely used for functional reconstruction of vertebral defects caused by tumors or trauma. However, the evaluation of their biomechanical properties often neglects the influence of material anisotropy derived from the host bone and implant’s microstructures. Hence, this study aims to investigate the effect of material anisotropy on the safety and stability of vertebral reconstruction.Material and methodsTwo finite element models were developed to reflect the difference of material properties between linear elastic isotropy and nonlinear anisotropy. Their biomechanical evaluation was carried out under different load conditions including flexion, extension, lateral bending and axial rotation. These performances of two models with respect to safety and stability were analyzed and compared quantitatively based on the predicted von Mises stress, displacement and effective strain.ResultsThe maximum von Mises stress of each component in both models was lower than the yield strength of respective material, while the predicted results of nonlinear anisotropic model were generally below to those of the linear elastic isotropic model. Furthermore, the maximum von Mises stress of natural vertebra and reconstructed system was decreased by 2–37 MPa and 20–61 MPa, respectively. The maximum reductions for the translation displacement of the artificial vertebral body implant and motion range of whole model were reached to 0.26 mm and 0.77°. The percentage of effective strain elements on the superior and inferior endplates adjacent to implant was diminished by up to 19.7% and 23.1%, respectively.ConclusionAfter comprehensive comparison, these results indicated that the finite element model with the assumption of linear elastic isotropy may underestimate the safety of the reconstruction system, while misdiagnose higher stability by overestimating the range of motion and bone growth capability

Vegetation response to climate zone dynamics and its impacts on surface soil water content and albedo in China

Extensive research has focused on the response of vegetation to climate change, including potential mechanisms and resulting impacts. Although many studies have explored the relationship between vegetation and climate change in China, research on spatiotemporal distribution changes of climate regimes using natural vegetation as an indicator is still lacking. Further, limited information is available on the response of vegetation to shifts in China's regional climatic zones. In this study, we applied Mann-Kendall, and correlation analysis to examine the variabilities in temperature, precipitation, surface soil water, normalised difference vegetation index (NDVI), and albedo in China from 1982 to 2012. Our results indicate significant shifts in the distribution of Koppen-Geiger climate classes in China from 12.08% to 18.98% between 1983 and 2012 at a significance level of 0.05 (MK). The percentage areas in the arid and continental zones expanded at a rate of 0.004%/y and 0.12%/y, respectively, while the percentage area in the temperate and alpine zones decreased by -0.05%/y and - 0.07%/y. Sensitivity fitting results between simulated and observed changes identified temperature to be a dominant control on the dynamics of temperate (r(2)= 0.98) and alpine (r(2)= 0.968) zones, while precipitation was the dominant control on the changes of arid (r(2) = 0.856) and continental (r(2) = 0.815) zones. The response of the NDVI to albedo infers a more pronounced radiative response in temperate (r = -0.82, pPeer reviewe

Diversity analyses of bacterial symbionts in four Sclerodermus (Hymenoptera: Bethylidae) parasitic wasps, the dominant biological control agents of wood-boring beetles in China

ObjectiveSclerodermus wasps are important biocontrol agents of a class of wood borers. Bacterial symbionts influence the ecology and biology of their hosts in a variety of ways, including the formation of life-long beneficial or detrimental parasitic infections. However, only a few studies have explored the species and content of the symbionts in the Sclerodermus species.MethodsHere, a high-throughput sequencing study of the V3-V4 region of the 16S ribosomal RNA gene revealed a high level of microbial variety in four Sclerodermus waps, and their diversities and functions were also predictedResultsThe three most prevalent phyla of microorganisms in the sample were Firmicutes, Bacteroides, and Proteus. The KEEG pathways prediction results indicated that the three pathways with the highest relative abundances in the S. sichuanensis species were translation, membrane transport, and nucleotide metabolism. These pathways differed from those observed in S. guani, S. pupariae, and S. alternatusi, which exhibited carbohydrate metabolism, membrane transport, and amino acid metabolism, respectively. Bacteroides were found to be abundant in several species, whereas Wolbachia was the most abundant among S. sichuanensis, with a significant negative correlation between temperature and carriage rate.ConclusionsThese results offer insights into the microbial communities associated with the bethylid wasps, which is crucial for understanding how to increase the reproductive capacity of wasps, enhance their parasitic effects, and lower cost in biocontrol

A Robust and Powerful Set-Valued Approach to Rare Variant Association Analyses of Secondary Traits in Case-Control Sequencing Studies

In many case-control designs of genome-wide association (GWAS) or next generation sequencing (NGS) studies, extensive data on secondary traits that may correlate and share the common genetic variants with the primary disease are available. Investigating these secondary traits can provide critical insights into the disease etiology or pathology, and enhance the GWAS or NGS results. Methods based on logistic regression (LG) were developed for this purpose. However, for the identification of rare variants (RVs), certain inadequacies in the LG models and algorithmic instability can cause severely inflated type I error, and significant loss of power, when the two traits are correlated and the RV is associated with the disease, especially at stringent significance levels. To address this issue, we propose a novel set-valued (SV) method that models a binary trait by dichotomization of an underlying continuous variable, and incorporate this into the genetic association model as a critical component. Extensive simulations and an analysis of seven secondary traits in a GWAS of benign ethnic neutropenia show that the SV method consistently controls type I error well at stringent significance levels, has larger power than the LG-based methods, and is robust in performance to effect pattern of the genetic variant (risk or protective), rare or common variants, rare or common diseases, and trait distributions. Because of the SV method’s striking and profound advantage, we strongly recommend the SV method be employed instead of the LG-based methods for secondary traits analyses in case-control sequencing studies

SVSI: Fast and Powerful Set-Valued System Identification Approach to Identifying Rare Variants in Sequencing Studies for Ordered Categorical Traits: SVSIfor Genetic Association Studies

For genetic association studies that involve an ordered categorical phenotype, we usually either regroup multiple categories of the phenotype into two categories (“cases” and “controls”) and then apply the standard logistic regression (LG), or apply ordered logistic (oLG) or ordered probit (oPRB) regression which accounts for the ordinal nature of the phenotype. However, these approaches may lose statistical power or may not control type I error rate due to their model assumption and/or instable parameter estimation algorithm when the genetic variant is rare or sample size is limited. Here to solve this problem, we propose a set-valued (SV) system model, which assumes that an underlying continuous phenotype follows a normal distribution, to identify genetic variants associated with an ordinal categorical phenotype. We couple this model with a set-valued system identification algorithm to identify all the key system parameters. Simulations and two real data analyses show that SV and LG accurately controlled the Type I error rate even at a significance level of 10−6 but not oLG and oPRB in some cases. LG had significantly smaller power than the other three methods due to disregarding of the ordinal nature of the phenotype, and SV had similar or greater power than oLG and oPRB. For instance, in a simulation with data generated from an additive SV model with odds ratio of 7.4 for a phenotype with three categories, a single nucleotide polymorphism with minor allele frequency of 0.75% and sample size of 999 (333 per category), the power of SV, oLG and LG models were 70%, 40% and <1%, respectively, at a significance level of 10−6. Thus, SV should be employed in genetic association studies for ordered categorical phenotype

KCNQ1OT1 promotes ovarian cancer progression via modulating MIR‐142‐5p/CAPN10 axis

Abstract Background Long non‐coding RNA (lncRNA) has been regarded as crucial regulator for cancer progression. Roles of KCNQ1 opposite strand/antisense transcript 1 (KCNQ1OT1) in cancers including osteosarcoma and colon cancer have been previously reported. However, its role in ovarian cancer (OC) remains unclear. Methods Expression level of KCNQ1OT1 on OC cells and normal cell was analyzed with quantitative real‐time PCR. Gain and loss‐of‐function experiments were performed to analyze the biological roles of KCNQ1OT1 in OC. Moreover, whether KCNQ1OT1 functions its role via mediating MICRORNA‐142‐5p (MIR‐142‐5p)/calpain 10 (CAPN10) axis was analyzed. In addition, effects of KCNQ1OT1, MIR‐142‐5p, and CAPN10 on overall survival of OC patients were analyzed at Kaplan–Meier plotter website. Results We showed KCNQ1OT1 was elevated expression in OC cells and indicated poorer overall survival of OC patients. Besides, we found KCNQ1OT1 could promote OC cell proliferation and migration in vitro. Moreover, MIR‐142‐5p was found reduced expression, while CAPN10 was found elevated expression in OC cells compared with normal cell. Kaplan–Meier curve analysis showed low MIR‐142‐5p or high CAPN10 expression were indicators for poorer overall survival of OC patients. At length, we showed KCNQ1OT1 could regulate OC development via MIR‐142‐5p/CAPN10 axis. Conclusions Taken together, KCNQ1OT1 upregulates CAPN10 expression via sponging MIR‐142‐5p, thus promoting the proliferation and migration of OC

Evaluation of Foam Gel Compound Profile Control and Flooding Technology in Low-Permeability Reservoirs

In the waterflooding development of fractured ultra-low permeability reservoirs, the heterogeneity is becoming increasingly serious. The development of large fracture channels leads to serious water channelling and low recovery, and the effect of conventional profile control is not ideal. This paper proposed gel foam composite profile control and flooding technology to solve the above problems. Herein, the new intelligent gel and foaming agent systems were optimized through laboratory experiments, and their performance was evaluated. The new intelligent gel system has the characteristics of low viscosity, easy preparation, good injection, slow cross-linking, high strength, and long-term effectiveness. The injection parameters were optimized, and the indoor injection scheme was formulated, that is, the optimal injection volumes of gel and foam slugs were 0.3 and 0.6 PV, respectively. The injection sequence of composite slugs was to inject gel slugs first, then foam slugs. The injection mode of air foam slugs was multiple rounds of small slug injection. The final recovery rate in the indoor dual tube oil displacement experiment reached 35.01%, increasing by 23.69%. Furthermore, an oil output increase of 899 t and an average water cut decrease of 5% were acquired in the oil field test. It shows that the injection scheme can effectively improve oil recovery. The gel foam compound profile control and flooding technology herein has good adaptability in similar reservoirs and has good promotion prospects

Alkali Treatment for Improving Isomerization Performance of Pt/ZSM-5

A series of alkali-treated ZSM-5 samples were prepared in order to adjust acidity and pore structure of ZSM-5. The effects of acidity and pore structure on n-hexane isomerization performance of Pt/ZSM-5 were investigated. The crystalline structure, acidity, and textural properties were measured by X-ray diffraction, NH3 temperature-programmed desorption, and N-2 adsorption-desorption, respectively. The results indicated that the mild alkali treatment led to a distinct decrease in the strong acid sites on ZSM-5 and the isomerization activity of Pt/ZSM-5. However, severe alkali treatment resulted in the increase of the strong acid sites, as well as the formation of new mesopores, accompanied by the significant increase in the isomerization activity. It was proposed that the isomerization activity was dependent on the amount of strong acid sites over ZSM-5 and irrelevant to its pore structure, while the distribution of isomers was related to the pore structure, the conversion of n-hexane, and independent of the acidity of ZSM-5