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The oxygen-deficient bismuth oxide, Bi2O4, synthesized by a typical hydrothermal method using commercial NaBiO3·2H2O as a raw material only has a relatively low concentration of surface oxygen vacancies (OVs). How to improve the visible light photocatalytic performance of Bi2O4via tuning its surface OV concentration is still a huge challenge. In this study, improving the surface OVs of Bi2O4was successfully realized through the pretreatment of commercial NaBiO3·2H2O, including thermal treatment in air and hydrothermal treatment in 10 M NaOH solution, forming NaBiO3·xH2O intermediate products first, and then hydrothermal preparation of Bi2O4target products using NaBiO3·xH2O instead of commercial NaBiO3·2H2O as the precursor. The enhanced surface OV content not only narrows the band gap of Bi2O4and thus extends its optical response range but also captures more photoexcited electrons and thus increases the charge carriers’ separation efficiency and prolongs the charge carriers’ lifetime of Bi2O4. Among the above-mentioned two pretreatment methods, the effects of the hydrothermal pretreatment are superior to those of the thermal treatment, involving the increase of surface OVs, the optical harvesting capacity, and the charge carriers’ separation efficiency. Accordingly, Bi2O4prepared by the hydrothermal pretreatment route exhibits the optimal visible light catalytic performance toward the removal of methyl orange (MO) and phenol due to its most abundant surface OV concentration, which is 2.59 times and 4.26 times higher than that of Bi2O4synthesized directly by the commercial NaBiO3·2H2O route, respectively. Holes (h+) and superoxide radicals (•O2–) are identified as the main active species, while singlet oxygen (1O2) and hydroxyl radicals (•OH) are verified as the second and third important active species for organic pollutant removal, respectively. This work has developed a novel strategy to promote the catalytic performance of single Bi2O4induced by the enhanced surface OV concentration through the pretreatment of the precursor, commercial NaBiO3·2H2O.

Insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2, also called IMP2) plays an essential role in the development and maturation of germ cells and embryos and is a candidate gene for goat litter size, based on a previous genome-wide selective sweep analysis. In this study, the mRNA expression level of IGF2BP2was found to be significantly higher in a single-lamb group than in a multi-lamb group. Insertions/deletions (indels) within the goat IGF2BP2gene, including P4-Ins-13bp and P5-Del-12bp, were verified in 918 Shaanbei White Cashmere (SBWC) female goats. The minor allelic frequencies (MAFs) of P4-Ins-13bp and P5-Del-12bp loci were 0.349 and 0.295, respectively. Analysis using the Chi-square (χ2) test showed that the genotype (χ2=14.479, P=0.006) distribution of P4-Ins-13bp was significantly different between the single-lamb and multi-lamb groups. Correlation analysis demonstrated that P4-Ins-13bp was significantly associated with goat litter size (P=0.022), and individual goats with the homozygous deletion/deletion (DD) genotype produced more litters than other goats. Therefore, considered as a potential molecular marker significantly related to lambing traits, the P4-Ins-13bp mutation of the goat IGF2BP2gene can be used in goat breeding with practical molecular marker-assisted selection (MAS) to optimize female reproduction and improve economic efficiency in the goat industry.

Traditional wireless network coding methods often fail to achieve ideal collection efficiency under single-point-to-multipoint multi-layer networks, and the Coupon Collector's Problem aggravates the collection delay. This paper divides the network hierarchy into the source node, relay node and sink node, and proves the collection delay effect in multi-layer network through Markov chain analysis. Then we propose to use a small amount of feedback information to reduce the collection delay and the number of invalid codewords, and derive a new degree distribution formula. We propose a dynamic feedback adaptive coding (DFAC) model and propose an adaptive coding protocol (DFACP) based on DFAC. It shows that the DFAC model is superior to the traditional LT Codes and Growth codes protocol in terms of collection efficiency and other indicators, and the scheme has strong adaptive robustness in dynamic node changes.

Romanov sheep are adapted to the extremely cold and harsh environment and display a distinctive grey color. Herein, we analyzed the population structure, genetic diversity, and selection signatures of Romanov sheep based on whole-genome sequencing data of 17 Romanov sheep, 114 individuals from other 10 European breeds. The results of PCA, ADMIXTURE, and NJ-tree showed that the Romanov sheep was closely related to other northern European breeds. A relative high level of genetic diversity, low inbreeding coefficient, and large effective population size was observed in Romanov sheep when compared with other European breeds. We then screened the genomic selection signatures of Romanov sheep using FST, XP-XLP, and XP-EHH methods. The most significant region under selection (CHR14:14.2 to 14.3 Mb) harbored a haplotype that contained MC1Rgene. Furthermore, this haplotype was also found in other grey-body breeds including Gotland sheep, Grey Tronder Sheep, and German grey heath sheep, suggesting that it was associated with the unique coat color of these breeds. We also found one region (CHR10:40.8Mb- 41.0Mb) harboring PCDH9gene which was potentially associated with cold environmental adaptation. In summary, this study identified candidate genes that were associated with the unique grey color and environmental adaptation in Romanov sheep, which provided a basis for understanding the genetic background and utilization of this breed.This study provided a comprehensive overview of genomic evaluation in Romanov sheep using whole genome sequence data, and we found an important haplotype of MC1Runique to grey coat color sheep.Romanov sheep is one of the most famous sheep breeds in the word, characterized by adaptability to harsh environment, high fertility, and unique coat color. Understanding its genetic architecture and signatures is of great value for its conservation and utilization. In this study, we analyzed whole-genome sequences of Romanov sheep as compared with 11 other European breeds, to explore for the population structure, genetic diversity, and selection signatures. We discovered a series of candidate genes that likely play a role in the grey coat color and cold adaptation of the Romanov sheep. In particular, we identified MC1Ras a strong candidate gene that determines the grey coat color.

Recent studies have highlighted that N6-methyladenosine (m6A) plays a significant role in tumorigenicity and progression. However, the mechanism of m6A modifications in the tumor microenvironment (TME) immune cell infiltration in cervical cancer (CC) remains unclear.Clinical and RNA sequencing data of 25 m6A RNA methylation regulators were acquired from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. LASSO Cox regression analysis was used to generate a prognostic risk signature. m6A modification patterns were identified based on the expression of 25 m6A regulators, and their correlation with TME immune cell-infiltrating characterization was analyzed. Principal component analysis was used to construct an m6A-scoring signature (m6A score) to evaluate the m6A modification patterns of individual CC samples and guide the selection of more effective immunotherapeutic strategies.Genetic and expression alterations of 25 m6A regulators were highly heterogeneous between CC and normal tissues. METTL14 and IGF2BP1 were selected to conduct the prognostic risk signature. Three m6A modification patterns were identified in 659 CC samples, which were associated with distinct clinical outcomes and biological pathways. The TME immune cell-infiltrating characterization of the three m6A modification patterns was highly consistent with 3 tumor immune phenotypes, including immune-excluded, immune-inflamed, and immune-desert phenotypes. Due to the heterogeneity of m6A modification patterns, an m6A scoring signature was established to evaluate the m6A modification patterns of individual CC samples. Univariate and multivariate Cox regression analyses revealed that the m6A score is a robust and independent prognostic biomarker for assessing the prognosis of CC patients. A low m6A score, characterized by higher somatic mutation and higher expression of proliferation-related and DNA repair-related genes, indicated poor overall survival. Activation of immune infiltration was exhibited by the high m6A score, which was likely to have a good response and clinical benefits to antiPD-1/L1 immunotherapy.This study highlights the prognostic value of 25 m6A regulators in CC. The m6A modification is related to immune regulation and the formation of TME heterogeneity and complexity. An m6A scoring signature to clarify the individual m6A modification pattern could enhance our understanding of TME immune cell-infiltrating characterization and guide immunotherapy strategies.