Roles of DNA Methylation in Color Alternation of Eastern Honey Bees (Apis cerana) Induced by the Royal Jelly of Western Honey Bees (Apis mellifera).

Honey bees have a very interesting phenomenon where the larval diets of two different honey bee species are exchanged, resulting in altered phenotypes, namely, a honey bee nutritional crossbreed. This is a classical epigenetic process, but its underlying mechanisms remain unclear. This study aims to investigate the contribution of DNA methylation to the phenotypic alternation of a Apis mellifera-Apis cerana nutritional crossbreed. We used a full nutritional crossbreed technique to rear A. cerana queens by feeding their larvae with A. mellifera royal-jelly-based diets in an incubator. Subsequently, we compared genome-wide methylation sequencing, body color, GC ratio, and the DMRs between the nutritional crossbreed, A. cerana queens (NQs), and control, A. cerana queens (CQs). Our results showed that the NQ's body color shifted to yellow compared to the black control queens. Genome methylation sequencing revealed that NQs had a much higher ratio of mCG than that of CQs. A total of 1020 DMGs were identified, of which 20 DMGs were enriched into key pathways for melanin synthesis, including tryptophan, tyrosine, dopamine, and phenylalanine KEGG pathways. Three key differentially methylated genes [OGDH, ALDH(NAD+) and ALDH7] showed a clear, altered DNA methylation in multiple CpG islands in NQs compared to CQs. Consequently, these findings revealed that DNA methylation participates in A. cerana-A. mellifera nutritional crossbreeding as an important epigenetic modification. This study serves as a model of cross-kingdom epigenetic mechanisms in insect body color induced by environmental factors.

Tuning Surface Defect States in Sputtered Titanium Oxide Electron Transport Layers for Enhanced Stability of Organic Photovoltaics.

Nonfullerene acceptors (NFAs) have dramatically improved the power conversion efficiency (PCE) of organic photovoltaics (OPV) in recent years; however, their device stability currently remains a bottleneck for further technological progress. Photocatalytic decomposition of nonfullerene acceptor molecules at metal oxide electron transport layer (ETL) interfaces has in several recent reports been demonstrated as one of the main degradation mechanisms for these high-performing OPV devices. While some routes for mitigating such degradation effects have been proposed, e.g., through a second layer integrated on the ETL surface, no clear strategy that complies with device scale-up and application requirements has been presented to date. In this work, it is demonstrated that the development of sputtered titanium oxide layers as ETLs in nonfullerene acceptor based OPV can lead to significantly enhanced device lifetimes. This is achieved by tuning the concentration of defect states at the oxide surface, via the reactive sputtering process, to mitigate the photocatalytic decomposition of NFA molecules at the metal oxide interlayers. Reduced defect state formation at the oxide surface is confirmed through X-ray photoelectron spectroscopy (XPS) studies, while the reduced photocatalytic decomposition of nonfullerene acceptor molecules is confirmed via optical spectroscopy investigations. The PBDB-T:ITIC organic solar cells show power conversion efficiencies of around 10% and significantly enhanced photostability. This is achieved through a reactive sputtering process that is fully scalable and industry compatible.

Differences in the luminal and mucosal gut microbiomes and metabolomes of oriental rat snake (Ptyas mucosus).

Previous studies regarding the gastrointestinal biogeography of microbiomes generally focused on longitudinal comparisons, whereas few studies have compared luminal and mucosal microbiomes. Investigations of the snake gut microbiome have attracted interest because of the unique digestive physiology and hibernation behavior, but adequate sampling methods must be developed. Here, we used an omics approach combining 16S rRNA gene sequencing with untargeted metabolomics to profile the luminal and mucosal gut microbiomes and metabolomes in oriental rat snakes, with the goal of revealing the heterogeneity and co-occurrence at these sites. The α-diversity of the gut microbiome was significantly higher at mucosal sites than at luminal sites. Microbial composition also differed according to sampling site, with significant differences in the abundances of dominant phyla and genera, as well as ß-diversity clustering and distribution. Metabolome profiling revealed differences that were mainly related to cholinergic substances and nucleic acids. Analysis of variations in Kyoto Encyclopedia of Genes and Genomes functions of microbes and metabolites showed that the mucosal microbiome was more frequently involved in genetic information processing and cellular processes, whereas the luminal microbiome generally participated in metabolic regulation. Notably, we found a greater abundance of the opportunistic pathogen genus Escherichia-Shigella at luminal sites and higher levels of the lipid-regulator metabolite fenfluramine at mucosal sites. Despite the extensive differences between the two sampling sites, the results revealed similarities in terms of amplicon sequence variant composition and dominant core microbes. This pilot exploration of luminal and mucosal microbiomes and metabolites provides key insights to guide future research. KEY POINTS: • Snake luminal and mucosal microbiota was distinct in composition and function. • Metabolome profiling revealed differences related to different metabolites. • The pathogenic microbes are more likely to colonize the gut lumina.

Gastrointestinal Biogeography of Luminal Microbiota and Short-Chain Fatty Acids in Sika Deer (Cervus nippon).

The gut microbiota of sika deer has been widely investigated, but the spatial distribution of symbiotic microbes among physical niches in the gastrointestinal tract remains to be established. While feces are the most commonly used biological samples in these studies, the accuracy of fecal matter as a proxy of the microbiome at other gastrointestinal sites is as yet unknown. In the present study, luminal contents obtained along the longitudinal axis of deer gastrointestinal tract (rumen, reticulum, omasum, abomasum, small intestine, cecum, colon, and rectum) were subjected to 16S rRNA gene sequencing for profiling of the microbial composition, and samples from the rumen, small intestine, and cecum were subjected to metabolomic analysis to evaluate short-chain fatty acid (SCFA) profiles. Prevotella bacteria were the dominant gastric core microbes, while Christensenellaceae_R-7_group was predominantly observed in the intestine. While the eight gastrointestinal sites displayed variations in microbial diversity, abundance, and function, they could be clustered into stomach, small intestine, and large intestine segments, and the results further highlighted a specific microbial niche of the small intestine. SCFA levels in the rumen, small intestine, and cecum were significantly different, with Bacteroidetes and Spirochaetes were shown to play a critical role in SCFA production. Finally, the rectal microbial composition was significantly correlated with colonic and cecum communities but not those of the small intestine and four gastric sites. Quantification of the compositions and biogeographic relationships between gut microbes and SCFAs in sika deer should provide valuable insights into the interactions contributing to microbial functions and metabolites. IMPORTANCE Feces or specific segments of the gastrointestinal tract (in particular, the rumen) were sampled to explore the gut microbiome. The gastrointestinal biogeography of the luminal microbiota in ruminants, which is critical to guide accurate sampling for different purposes, is poorly understood at present. The microbial community of the rectal sample (as a proxy of fecal sample) showed higher correlation with those of other large intestinal sites relative to the small intestine or stomach, suggesting that the microbial composition is specifically shaped by the unique physiological characteristics of different gastrointestinal niches. In addition, significant differences in microbiomes and SCFAs were observed among the different gastrointestinal sites.

Comparison of Different Machine Models Based on Multi-Phase Computed Tomography Radiomic Analysis to Differentiate Parotid Basal Cell Adenoma From Pleomorphic Adenoma.

Objective: This study explored the value of different radiomic models based on multiphase computed tomography in differentiating parotid pleomorphic adenoma (PA) and basal cell tumor (BCA) concerning the predominant phase and the optimal radiomic model. Methods: This study enrolled 173 patients with pathologically confirmed parotid tumors (training cohort: n=121; testing cohort: n=52). Radiomic features were extracted from the nonenhanced, arterial, venous, and delayed phases CT images. After dimensionality reduction and screening, logistic regression (LR), K-nearest neighbor (KNN) and support vector machine (SVM) were applied to develop radiomic models. The optimal radiomic model was selected by using ROC curve analysis. Univariate and multivariable logistic regression was performed to analyze clinical-radiological characteristics and to identify variables for developing a clinical model. A combined model was constructed by integrating clinical and radiomic features. Model performances were assessed by ROC curve analysis. Results: A total of 1036 radiomic features were extracted from each phase of CT images. Sixteen radiomic features were considered valuable by dimensionality reduction and screening. Among radiomic models, the SVM model of the arterial and delayed phases showed superior predictive efficiency and robustness (AUC, training cohort: 0.822, 0.838; testing cohort: 0.752, 0.751). The discriminatory capability of the combined model was the best (AUC, training cohort: 0.885; testing cohort: 0.834). Conclusions: The diagnostic performance of the arterial and delayed phases contributed more than other phases. However, the combined model demonstrated excellent ability to distinguish BCA from PA, which may provide a non-invasive and efficient method for clinical decision-making.

CT-based radiomics analysis of different machine learning models for differentiating benign and malignant parotid tumors.

OBJECTIVES: This study aimed to explore and validate the value of different radiomics models for differentiating benign and malignant parotid tumors preoperatively. METHODS: This study enrolled 388 patients with pathologically confirmed parotid tumors (training cohort: n = 272; test cohort: n = 116). Radiomics features were extracted from CT images of the non-enhanced, arterial, and venous phases. After dimensionality reduction and selection, radiomics models were constructed by logistic regression (LR), support vector machine (SVM), and random forest (RF). The best radiomic model was selected by using ROC curve analysis. Univariate and multivariable logistic regression was applied to analyze clinical-radiological characteristics and identify variables for developing a clinical model. A combined model was constructed by incorporating radiomics and clinical features. Model performances were assessed by ROC curve analysis, and decision curve analysis (DCA) was used to estimate the models' clinical values. RESULTS: In total, 2874 radiomic features were extracted from CT images. Ten radiomics features were deemed valuable by dimensionality reduction and selection. Among radiomics models, the SVM model showed greater predictive efficiency and robustness, with AUCs of 0.844 in the training cohort; and 0.840 in the test cohort. Ultimate clinical features constructed a clinical model. The discriminatory capability of the combined model was the best (AUC, training cohort: 0.904; test cohort: 0.854). Combined model DCA revealed optimal clinical efficacy. CONCLUSIONS: The combined model incorporating radiomics and clinical features exhibited excellent ability to distinguish benign and malignant parotid tumors, which may provide a noninvasive and efficient method for clinical decision making. KEY POINTS: The current study is the first to compare the value of different radiomics models (LR, SVM, and RF) for preoperative differentiation of benign and malignant parotid tumors. A CT-based combined model, integrating clinical-radiological and radiomics features, is conducive to distinguishing benign and malignant parotid tumors, thereby improving diagnostic performance and aiding treatment.

Differences in Fecal Microbiome and Antimicrobial Resistance between Captive and Free-Range Sika Deer under the Same Exposure of Antibiotic Anthelmintics.

This study aimed to compare the fecal microbiome and antimicrobial resistance between captive and free-range sika deer with the same exposure to antibiotic anthelmintics. The taxonomic differences mainly involved significant changes in the dominant phyla, genera, and species. Linear discriminant analysis effect size (LEfSe) analysis revealed that 22 taxa were significantly different between the two groups. The KEGG analysis showed that the fecal microbiome metabolic function, and all level 2 categories in metabolism had higher abundance in the free-range deer. Based on the carbohydrate-active enzyme (CAZy) database analysis, glycoside hydrolases and carbohydrate-binding modules showed remarkable differences between the two groups. Regarding antibiotic resistance, tetQ and lnuC dominated the antibiotic resistance ontology (ARO) terms, and tetracycline and lincosamide resistance dominated the antimicrobial resistance patterns. Furthermore, the lnuC, ErmF, and tetW/N/W AROs and lincosamide resistance showed higher abundance in the captive deer, suggesting that captivity may yield more serious resistance issues because of the differences in greenfeed diet, breeding density, and/or housing environment. The results also revealed important associations between the phylum Proteobacteria, genus Prevotella, and major antibiotic resistance genes. Although the present study was a pilot study with a limited sample size that was insufficient control for some potential factors, it serves as the metagenomic study on the microbial communities and antimicrobial resistance in sika deer. IMPORTANCE We used a metagenomic approach to investigate whether and how captive and free-range impact the microbial communities and antimicrobial resistance in sika deer. The results provide solid evidence of the significant impacts on the microbial composition and function in captive and free-range sika deer. Interestingly, although the sika deer had the same exposure to antibiotic anthelmintics, the antimicrobial resistances were affected by the breeding environment.

The impact of anthelmintic treatment on gut bacterial and fungal communities in diagnosed parasite-free sika deer Cervus nippon.

The gut microbiota, including both bacterial and fungal communities, plays vital roles in the gut homeostasis of animals, and antibiotics can lead to disorders of these microbial communities. The use of anthelmintic treatment to control parasitic infection has long been a standard practice, although its impact on the gut microbiota of healthy sika deer is relatively unknown. This study used next-generation sequencing based on 16S/18S/ITS rRNA genes to investigate the shifts in fecal bacterial and fungal communities in parasite-free sika deer after treatment with fenbendazole and ivermectin tablets. The α-diversity of both bacterial and fungal communities was significantly decreased (P < 0.05) after treatment, as were the bacterial genus Bacteroides and fungal genus Candida (P < 0.05). The results of ß-diversity, LEfSe analysis, core community's analysis, taxonomic composition, and functional prediction of fungal and bacterial communities confirmed the substantial impacts of anthelmintic treatment on the function and structure of the intestinal microbiota of sika deer. Nevertheless, many lines of evidence, including ß-diversity, LEfSe analysis and functional prediction analysis, suggested that the anthelmintics exerted more significant influences on fungal communities than on bacterial communities, suggesting that more attention should be paid to the changes in fungal communities of sika deer under anthelmintic treatment. The present study provides evidence to support the assumption that anthelmintic drugs modify the gut microbiota of deer and serves as the first trial to test the potential effects of anthelmintics on mycobiota in ruminants using high-throughput sequencing techniques. Key Points • Anthelmintic treatment showed significant effects on the gut microbiota of sika deer. • Fungi were more strongly affected by anthelmintic treatment than bacteria. • The profile of mycobiota provides essential data that were previously absent.

Stable quantum key distribution using a silicon photonic transceiver.

The wider deployment of commercial quantum key distribution (QKD) may benefit from an integrated system with reduced cost, small form-of-factor and high robutness. Silicon photonic circuits are good candidates while their performance stability in some contexts remains a challenge. We demonstrate a silicon photonic QKD transceiver based on time-bin protocol. The stability of the transceiver is investigated and a feedback function is proposed to improve the temperature-dependent performance of the transceiver. With the help of a faster data-processing ability, such scheme can facilitate more application scenarios, therefore achieving wider implementation of QKD in the future.

Ultrafast Structural Dynamics along the ß-γ Phase Transition Path in MnAs.

We investigate the orthorhombic distortion and the structural dynamics of epitaxial MnAs layers on GaAs(001) using static and time-resolved x-ray diffraction. Laser-induced intensity oscillations of Bragg reflections allow us to identify the optical phonon associated with orthorhombic distortion and to follow its softening along the path towards an undistorted phase of hexagonal symmetry. The frequency of this mode falls in the THz range, in agreement with recent calculations. Incomplete softening suggests that the ß-γ transformation deviates from a purely second-order displacive transition.

High-Throughput Analysis Reveals Seasonal Variation of the Gut Microbiota Composition Within Forest Musk Deer (Moschus berezovskii).

The gut microbiota plays a key role in the nutritional ecology of ruminants, and host diet has a significant effect on these microbial communities. Longitudinal studies assessing variation of seasonal microbiota in animals can provide a comparative context for interpreting the adaptive significance of such changes. However, few studies have investigated the effects of seasonally-related dietary shifts on the gut microbial communities of endangered forest musk deer (FMD), and the national breeding programs need this information to promote the growth of captive populations. The present study applied bacterial 16S rRNA genes based on high-throughput sequencing to profile the fecal microbial communities of FMD across four seasons. Microbial diversity was higher in seasons with dry leaf diets (winter and spring) compared to seasons with fresh leaf diets (summer and autumn). The dominant microbial phyla were Firmicutes and Bacteroidetes, and the core bacterial taxa also comprised mostly (94.40% of shared OTUs) Firmicutes (37 taxa) and Bacteroidetes (6 taxa), which were relatively stable across different seasons. The Firmicutes-Bacteroidetes ratio declined in seasons with fresh leaf diets relative to seasons with dry leaf diets, and the dominant genera among the four seasons showed no significant variation in abundance. This work explores the seasonal variation in the microbial communities of FMD for the first time, and reveals how gut microbial community dynamics vary seasonally in accordance with differences in dietary plants (fresh and dry leaf). These results indicate that the annual cyclic reconfiguration of FMD gut microbiota could be associated with shifts in dietary nutrients, which is important information to inform captive FMD management.

Magnetically Hard Fe3Se4 Embedded in Bi2Se3 Topological Insulator Thin Films Grown by Molecular Beam Epitaxy.

We investigated the structural, magnetic, and electronic properties of Bi2Se3 epilayers containing Fe grown on GaAs(111) by molecular beam epitaxy. It is shown that, in the window of growth parameters leading to Bi2Se3 epilayers with optimized quality, Fe atom clustering leads to the formation of FexSey inclusions. These objects have platelet shape and are embedded within Bi2Se3. Monoclinic Fe3Se4 is identified as the main secondary phase through detailed structural measurements. Due to the presence of the hard ferrimagnetic Fe3Se4 inclusions, the system exhibits a very large coercive field at low temperature and room temperature magnetic ordering. Despite this composite structure and the proximity of a magnetic phase, the surface electronic structure of Bi2Se3 is preserved, as shown by the persistence of a gapless Dirac cone at Γ.

Combinatorial growth and anisotropy control of self-assembled epitaxial ultrathin alloy nanowires.

Self-assembled vertical epitaxial nanostructures form a new class of heterostructured materials that has emerged in recent years. Interestingly, such kind of architectures can be grown using combinatorial processes, implying sequential deposition of distinct materials. Although opening many perspectives, this combinatorial nature has not been fully exploited yet. This work demonstrates that the combinatorial character of the growth can be further exploited in order to obtain alloy nanowires coherently embedded in a matrix. This issue is illustrated in the case of a fully epitaxial system: CoxNi1-x nanowires in CeO2/SrTiO3(001). The advantage brought by the ability to grow alloys is illustrated by the control of the magnetic anisotropy of the nanowires when passing from pure Ni wires to CoxNi1-x alloys. Further exploitation of this combinatorial approach may pave the way toward full three-dimensional heteroepitaxial architectures through axial structuring of the wires.

A novel mutation in FHL1 in a family with X-linked scapuloperoneal myopathy: phenotypic spectrum and structural study of FHL1 mutations.

An X-linked myopathy was recently associated with mutations in the four-and-a-half-LIM domains 1 (FHL1) gene. We identified a family with late onset, slowly progressive weakness of scapuloperoneal muscles in three brothers and their mother. A novel missense mutation in the LIM2 domain of FHL1 (W122C) co-segregated with disease in the family. The phenotype was less severe than that in other reported families. Muscle biopsy revealed myopathic changes with FHL1 inclusions that were ubiquitin- and desmin-positive. This mutation provides additional evidence for X-linked myopathy caused by a narrow spectrum of mutations in FHL1, mostly in the LIM2 domain. Molecular dynamics (MD) simulations of the newly identified mutation and five previously published missense mutations in the LIM2 domain revealed no major distortions of the protein structure or disruption of zinc binding. There were, however, increases in the nonpolar, solvent-accessible surface area in one or both of two clusters of residues, suggesting that the mutant proteins have a variably increased propensity to aggregate. Review of the literature shows a wide range of phenotypes associated with mutations in FHL1. However, recognizing the typical scapuloperoneal phenotype and X-linked inheritance pattern will help clinicians arrive at the correct diagnosis.