The composition and function of bacterial communities in Bombyx mori (Lepidoptera: Bombycidae) changed dramatically with infected fungi: A new potential to culture Cordyceps cicadae.

Cordyceps cicadae (Hypocreales: Cordycipitaceae) is a renowned entomopathogenic fungus used as herbal medicine in China. However, wild C. cicadae resources have been threatened by heavy harvesting. We hypothesised that Bombyx mori L. (Lepidoptera: Bombycidae) could be a new alternative to cultivate C. cicadae due to the low cost of rearing. Bacterial communities are crucial for the formation of Cordyceps and for promoting the production of metabolites. To better understand the bacterial community structure associated with Cordyceps, three Claviciptaceae fungi were used to explore the pathogenicity of the silkworms. Here, fifth-instar silkworms were infected with C. cicadae, Cordyceps cateniannulata (Hypocreales: Cordycipitaceae) and Beauveria bassiana (Hypocreales: Cordycipitaceae). Subsequently, we applied high-throughput sequencing to explore the composition of bacterial communities in silkworms. Our results showed that all three fungi were highly pathogenic to silkworms, which suggests that silkworms have the potential to cultivate Cordyceps. After fungal infection, the diversity of bacterial communities in silkworms decreased significantly, and the abundance of Staphylococcus increased in mummified larvae, which may play a role in the death process when the host suffers infection by entomopathogenic fungi. Furthermore, there were high similarities in the bacterial community composition and function in the C. cicadae and C. cateniannulata infected samples, and the phylogenetic analysis suggested that these similarities may be related to the fungal phylogenetic relationship. Our findings reveal that infection with different entomopathogenic fungi affects the composition and function of bacterial communities in silkworms and that the bacterial species associated with Cordyceps are primarily host dependent, while fungal infection affects bacterial abundance.

Mapping Oxidation and Wafer Cleaning to Device Characteristics Using Physics-Assisted Machine Learning.

It is always highly desired to have a well-defined relationship between the chemistry in semiconductor processing and the device characteristics. With the shrinkage of technology nodes in the semiconductors roadmap, it becomes more complicated to understand the relation between the device electrical characteristics and the process parameters such as oxidation and wafer cleaning procedures. In this work, we use a novel machine learning approach, i.e., physics-assisted multitask and transfer learning, to construct a relationship between the process conditions and the device capacitance voltage curves. While conventional semiconductor processes and device modeling are based on a physical model, recently, the machine learning-based approach or hybrid approaches have drawn significant attention. In general, a huge amount of data is required to train a machine learning model. Since producing data in the semiconductor industry is not an easy task, physics-assisted artificial intelligence has become an obvious choice to resolve these issues. The predicted C-V uses the hybridization of physics, and machine learning provides improvement while the coefficient of determination (R 2) is 0.9442 for semisupervised multitask learning (SS-MTL) and 0.9253 for transfer learning (TL), referenced to 0.6108 in the pure machine learning model using multilayer perceptrons. The machine learning architecture used in this work is capable of handling data sparsity and promotes the usage of advanced algorithms to model the relationship between complex chemical reactions in semiconductor manufacturing and actual device characteristics. The code is available at https://github.com/albertlin11/moscapssmtl.

DNA methylation inhibitor, decitabine, promotes MGC803 gastric cancer cell migration and invasion via the upregulation of NEDD4­1.

Gastric cancer is the fourth most common cancer type and the second leading cause of cancer­associated mortality worldwide. Metastasis is a crucial feature of its progression. DNA methylation provides a key epigenetic signature in the epigenetic regulation pathway, and is implicated in transcriptional regulation. CpG sites, which are associated with gene transcriptional activity, are underrepresented in the mammalian genome and tend to be clustered within CpG islands (CGIs) located in the vicinity of the transcription start sites of the majority of the protein­coding genes in humans. The DNA methylation inhibitor, decitabine (DAC), has been demonstrated to be active in hematological disorders. The majority of previous studies in cancer cells demonstrated that DAC inhibits cell proliferation and the motility of the cells. However, since demethylation across the entire genome alters the expression of a large number of genes, the effects of DAC in different tumor cell types are difficult to accurately predict. Neural precursor cell­expressed, developmentally downregulated (NEDD)4­1, a member of the NEDD4 family, which belongs to the E3­ubiquitin ligase family, was reported to be highly expressed in a wide range of tumor types, and it activates the phosphoinositide 3­kinase/Akt pathway by degrading phosphatase and tensin homolog. NEDD4­1 promotes the migration and invasion of glioma cells via the ubiquitination and subsequent degradation of cyclic nucleotide­Ras guanine nucleotide exchange factors (CNrasGEFs). In gastric cardia adenocarcinoma, NEDD4­1 acts as an exceptional prognostic biomarker. In the present study, DAC was revealed to promote the invasive properties of MGC803 gastric cancer cells. NEDD4­1 targeted the CNrasGEF­mediated DAC invasion­promoting activity in MGC803 cells, and CGI methylation in neither the NEDD4 promoter nor the first intron was demonstrated to be associated with this effect. The results of the present study revealed that DAC exerts variable effects in different gastric cancer cell lines and may provide a reference for DAC administration in the clinic.

OCT4B modulates OCT4A expression as ceRNA in tumor cells.

OCT4 is an essential transcription factor for maintaining the self-renewal and the pluripotency of embryonic stem cells (ESCs). The human OCT4 gene can generate three mRNA isoforms (OCT4A, OCT4B and OCT4B1) by alternative splicing. OCT4A protein is a transcription factor for the stemness of ESCs, while the function of OCT4B isoforms remains unclear. Most types of cancer express a relatively low level of OCT4 protein, particularly the OCT4B isoforms. In the present study, we found that OCT4A and OCT4B mRNA were co-expressed in several types of tumor cell lines and tumor samples, and we demonstrated that OCT4B functioned as a non-coding RNA, modulating OCT4A expression in an miRNA-dependent manner [competing endogenous RNA (ceRNA) regulation] at the post-transcription level in the tumor cell lines. This is the first time that ceRNA regulation was observed among spliced isoforms of one gene, and may pave the way for identification of new targets for cancer treatment.