Infection and Infertility

Infection is a multifactorial process, which can be induced by a virus, bacterium, or parasite. It may cause many diseases, including obesity, cancer, and infertility. In this chapter, we focus our attention on the association of infection and fertility alteration. Numerous studies have suggested that genetic polymorphisms influencing infection are associated with infertility. So we also review the genetic influence on infection and risk of infertility

Identification of DNA motif pairs on paired sequences based on composite heterogeneous graph

MotivationThe interaction between DNA motifs (DNA motif pairs) influences gene expression through partnership or competition in the process of gene regulation. Potential chromatin interactions between different DNA motifs have been implicated in various diseases. However, current methods for identifying DNA motif pairs rely on the recognition of single DNA motifs or probabilities, which may result in local optimal solutions and can be sensitive to the choice of initial values. A method for precisely identifying DNA motif pairs is still lacking.ResultsHere, we propose a novel computational method for predicting DNA Motif Pairs based on Composite Heterogeneous Graph (MPCHG). This approach leverages a composite heterogeneous graph model to identify DNA motif pairs on paired sequences. Compared with the existing methods, MPCHG has greatly improved the accuracy of motifs prediction. Furthermore, the predicted DNA motifs demonstrate heightened DNase accessibility than the background sequences. Notably, the two DNA motifs forming a pair exhibit functional consistency. Importantly, the interacting TF pairs obtained by predicted DNA motif pairs were significantly enriched with known interacting TF pairs, suggesting their potential contribution to chromatin interactions. Collectively, we believe that these identified DNA motif pairs held substantial implications for revealing gene transcriptional regulation under long-range chromatin interactions

Adsorption Mechanism of Cu-Doped SnO 2

The content of hydrogen is a key quantity in condition assessment and fault diagnosis of power transformer. Based on the density functional theory (DFT), the adsorption mechanism of Cu-doped SnO2 surface toward H2 has been systematically studied in this work. Firstly, the relaxation, the bond length, and overlap population of both the pure and Cu-doped SnO2 are computed. To determine the optimal doping position, the formation energies of four potential sites (i.e., Sn5c, Sn6c, Sn5c-s, and Sn6c-s) are then compared with each other. The adsorption energy and the electronic structure of SnO2 surface are analysed and discussed in detail. Furthermore, to estimate the partial atomic charges and the electrical conductance, the Mulliken population analysis is also performed. It has been found that the bridge oxygen is the most favourable position. The partial density of states of H2 after adsorption is broadened and shifted close to the Fermi level. A large amount of charges would be transferred and then released back into its conduction band, leading to the reduction of resistance and the enhancement of sensitivity toward H2. The results of this work provide references for SnO2-based sensor design

FACILE SYNTHESIS OF FUNCTIONALIZED UiO-66-TYPE MOFs FOR CO2 ADSORPTION

The metal-organic frameworks (MOFs) UiO-66-NH2, UiO-66-2,5-(OH)2, UiO-66-NO2, UiO-66-NDC, and UiO-66-BPDC were synthesized under solvothermal conditions using different functionalized organic linkers. The structures and properties of the samples were characterized by X-ray diffraction, Fourier transform infrared spectroscopy, thermogravimetric analysis, scanning electron microscopy, and nitrogen adsorption-desorption isotherms. The crystal structures of these functionalized UiO-66(Zr) forms were similar. A series of functionalized UiO-66(Zr) samples were used in the adsorption of carbon dioxide (CO2). UiO-66-NH2 had the highest CO2 adsorption capacity (about 3.35 mmol g-1) due to its small polar -NH2 group. The performance of UiO-66-NH2 in CO2 adsorption at different temperatures was also determined. The amino-functionalized material possessed better adsorption properties at 273 K than at 303 K, while the CO2 working capacity of UiO-66-NH2 was fully recovered after cyclic regeneration

Identification and characterization of a 25-lncRNA prognostic signature for early recurrence in hepatocellular carcinoma

Background Early recurrence is the major cause of poor prognosis in hepatocellular carcinoma (HCC). Long non-coding RNAs (lncRNAs) are deeply involved in HCC prognosis. In this study, we aimed to establish a prognostic lncRNA signature for HCC early recurrence. Methods The lncRNA expression profile and corresponding clinical data were retrieved from total 299 HCC patients in TCGA database. LncRNA candidates correlated to early recurrence were selected by differentially expressed gene (DEG), univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses. A 25-lncRNA prognostic signature was constructed according to receiver operating characteristic curve (ROC). Kaplan-Meier and multivariate Cox regression analyses were used to evaluate the performance of this signature. ROC and nomogram were used to evaluate the integrated models based on this signature with other independent clinical risk factors. Gene set enrichment analysis (GSEA) was used to reveal enriched gene sets in the high-risk group. Tumor infiltrating lymphocytes (TILs) levels were analyzed with single sample Gene Set Enrichment Analysis (ssGSEA). Immune therapy response prediction was performed with TIDE and SubMap. Chemotherapeutic response prediction was conducted by using Genomics of Drug Sensitivity in Cancer (GDSC) pharmacogenomics database. Results Compared to low-risk group, patients in high-risk group showed reduced disease-free survival (DFS) in the training (p < 0.0001) and validation cohort (p = 0.0132). The 25-lncRNA signature, AFP, TNM and vascular invasion could serve as independent risk factors for HCC early recurrence. Among them, the 25-lncRNA signature had the best predictive performance, and combination of those four risk factors further improves the prognostic potential. Moreover, GSEA showed significant enrichment of “E2F TARGETS”, “G2M CHECKPOINT”, “MYC TARGETS V1” and “DNA REPAIR” pathways in the high-risk group. In addition, increased TILs were observed in the low-risk group compared to the high-risk group. The 25-lncRNA signature negatively associates with the levels of some types of antitumor immune cells. Immunotherapies and chemotherapies prediction revealed differential responses to PD-1 inhibitor and several chemotherapeutic drugs in the low- and high-risk group. Conclusions Our study proposed a 25-lncRNA prognostic signature for predicting HCC early recurrence, which may guide postoperative treatment and recurrence surveillance in HCC patients

Value Distribution and Uniqueness Results of Zero-Order Meromorphic Functions to Their q-Shift

We investigate value distribution and uniqueness problems of meromorphic functions with their q-shift. We obtain that if f is a transcendental meromorphic or entire function of zero order, and Q z is a polynomial, then af n qz f z − Q z has infinitely many zeros, where q ∈ C \ {0}, a is nonzero constant, and n ≥ 5 or n ≥ 3 . We also obtain that zero-order meromorphic function share is three distinct values IM with its q-difference polynomial P f , and if lim sup r → ∞ N r, f /T r, f &lt; 1, then f ≡ P f

Value Distribution and Uniqueness Results of Zero-Order Meromorphic Functions to Their q-Shift

We investigate value distribution and uniqueness problems of meromorphic functions with their q-shift. We obtain that if f is a transcendental meromorphic (or entire) function of zero order, and Q(z) is a polynomial, then afn(qz)+f(z)−Q(z) has infinitely many zeros, where q∈ℂ∖{0}, a is nonzero constant, and n≥5 (or n≥3). We also obtain that zero-order meromorphic function share is three distinct values IM with its q-difference polynomial P(f), and if limsup r→∞(N(r,f)/T(r,f))<1, then f≡P(f)

Cash holdings, the internal capital market, and capital allocation efficiency in listed companies

AbstractThe rise in firm-level cash asset ratios has become a prominent trend in countries around the world which may further influence the capital allocation efficiency. This study analysed the inefficient effect of cash holdings on the capital allocation by combining the internal capital market theory with principal–agent theory and asymmetric information theory. The theoretical hypotheses were tested using linear panel regression models based on financial data from Chinese listed enterprises. We found that corporations holding more cash assets had lower capital allocation efficiency than those with fewer cash assets, which is consistent with agency theory and asymmetric information theory. Internal capital markets exacerbated this adverse effect. Additional testing was conducted to examine the heterogeneity of this effect between different types of ownership and strategy; the findings showed that an increase in cash holdings had a greater marginal impact on overinvestment among privately owned enterprises and underinvestment among state-owned enterprises. Internal capital market operation alleviated the problem of overinvestment but exacerbated the problem of underinvestment in privately owned enterprises, whereas it increased overinvestment in state-owned enterprises. The results suggested that different types of enterprises should deal with the inefficient effect of cash assets based on the causes of inefficient investment

A Hybrid Indoor Ambient Light and Vibration Energy Harvester for Wireless Sensor Nodes

To take advantage of applications where both light and vibration energy are available, a hybrid indoor ambient light and vibration energy harvesting scheme is proposed in this paper. This scheme uses only one power conditioning circuit to condition the combined output power harvested from both energy sources so as to reduce the power dissipation. In order to more accurately predict the instantaneous power harvested from the solar panel, an improved five-parameter model for small-scale solar panel applying in low light illumination is presented. The output voltage is increased by using the MEMS piezoelectric cantilever arrays architecture. It overcomes the disadvantage of traditional MEMS vibration energy harvester with low voltage output. The implementation of the maximum power point tracking (MPPT) for indoor ambient light is implemented using analog discrete components, which improves the whole harvester efficiency significantly compared to the digital signal processor. The output power of the vibration energy harvester is improved by using the impedance matching technique. An efficient mechanism of energy accumulation and bleed-off is also discussed. Experiment results obtained from an amorphous-silicon (a-Si) solar panel of 4.8 × 2.0 cm2 and a fabricated piezoelectric MEMS generator of 11 × 12.4 mm2 show that the hybrid energy harvester achieves a maximum efficiency around 76.7%