Generation and Application of Inducible Chimeric RNA ASTN2-PAPPA(as) Knockin Mouse Model

Chimeric RNAs (chiRNAs) play many previously unrecognized roles in different diseases including cancer. They can not only be used as biomarkers for diagnosis and prognosis of various diseases but also serve as potential therapeutic targets. In order to better understand the roles of chiRNAs in pathogenesis, we inserted human sequences into mouse genome and established a knockin mouse model of the tamoxifen-inducible expression of ASTN2-PAPPA antisense chimeric RNA (A-P(as)chiRNA). Mice carrying the A-P(as)chiRNA knockin gene do not display any apparent abnormalities in growth, fertility, histological, hematopoietic, and biochemical indices. Using this model, we dissected the role of A-P(as)chiRNA in chemical carcinogen 4-nitroquinoline 1-oxide (4NQO)-induced carcinogenesis of esophageal squamous cell carcinoma (ESCC). To our knowledge, we are the first to generate a chiRNA knockin mouse model using the Cre-loxP system. The model could be used to explore the roles of chiRNA in pathogenesis and potential targeted therapies

Targeting PELP1 Attenuates Angiogenesis and Enhances Chemotherapy Efficiency in Colorectal Cancer

SIMPLE SUMMARY: Excessive angiogenesis is a distinct feature of colorectal cancer (CRC) and plays a pivotal role in tumor development and metastasis. Therefore, it is essential to clarify the underlying mechanism of angiogenesis. In this study, we found that the level of proline-, glutamic acid, and leucine-rich protein 1 (PELP1) was positively correlated with microvessel density (MVD). In vitro and in vivo assays further showed PELP1 regulated angiogenesis via the Signal transducer and activator of transcription 3 (STAT3)/Vascular endothelial growth factor (VEGFA). Notably, we found that inhibition of PELP1 enhanced the efficacy of chemotherapy due to vascular normalization. Thus, targeting of PELP1 may be a potentially therapeutic strategy for CRC. ABSTRACT: Abnormal angiogenesis is one of the important hallmarks of colorectal cancer as well as other solid tumors. Optimally, anti-angiogenesis therapy could restrain malignant angiogenesis to control tumor expansion. PELP1 is as a scaffolding oncogenic protein in a variety of cancer types, but its involvement in angiogenesis is unknown. In this study, PELP1 was found to be abnormally upregulated and highly coincidental with increased MVD in CRC. Further, treatment with conditioned medium (CM) from PELP1 knockdown CRC cells remarkably arrested the function of human umbilical vein endothelial cells (HUVECs) compared to those treated with CM from wildtype cells. Mechanistically, the STAT3/VEGFA axis was found to mediate PELP1-induced angiogenetic phenotypes of HUVECs. Moreover, suppression of PELP1 reduced tumor growth and angiogenesis in vivo accompanied by inactivation of STAT3/VEGFA pathway. Notably, in vivo, PELP1 suppression could enhance the efficacy of chemotherapy, which is caused by the normalization of vessels. Collectively, our findings provide a preclinical proof of concept that targeting PELP1 to decrease STAT3/VEGFA-mediated angiogenesis and improve responses to chemotherapy due to normalization of vessels. Given the newly defined contribution to angiogenesis of PELP1, targeting PELP1 may be a potentially ideal therapeutic strategy for CRC as well as other solid tumors

Neoantigen-based cancer vaccination using chimeric RNA-loaded dendritic cell-derived extracellular vesicles

Cancer vaccines critically rely on the availability of targetable immunogenic cancer-specific neoepitopes. However, mutation-based immunogenic neoantigens are rare or even non-existent in subgroups of cancer types. To address this issue, we exploited a cancer-specific aberrant transcription-induced chimeric RNA, designated A-Pas chiRNA, as a possible source of clinically relevant and targetable neoantigens. A-Pas chiRNA encodes a recently discovered cancer-specific chimeric protein that comprises full-length astrotactin-2 (ASTN2) C-terminally fused in-frame to the antisense sequence of the 18th intron of pregnancy-associated plasma protein-A (PAPPA). We used extracellular vesicles (EVs) from A-Pas chiRNA-transfected dendritic cells (DCs) to produce the cell-free anticancer vaccine DEXA-P . Treatment of immunocompetent cancer-bearing mice with DEXA-P inhibited tumour growth and prolonged animal survival. In summary, we demonstrate for the first time that cancer-specific transcription-induced chimeric RNAs can be exploited to produce a cell-free cancer vaccine that induces potent CD8+ T cell-mediated anticancer immunity. Our novel approach may be particularly useful for developing cancer vaccines to treat malignancies with low mutational burden or without mutation-based antigens. Moreover, this cell-free anticancer vaccine approach may offer several practical advantages over cell-based vaccines, such as ease of scalability and genetic modifiability as well as enhanced shelf life

DeepAIR: A deep learning framework for effective integration of sequence and 3D structure to enable adaptive immune receptor analysis

Structural docking between the adaptive immune receptors (AIRs), including T cell receptors (TCRs) and B cell receptors (BCRs), and their cognate antigens are one of the most fundamental processes in adaptive immunity. However, current methods for predicting AIR-antigen binding largely rely on sequence-derived features of AIRs, omitting the structure features that are essential for binding affinity. In this study, we present a deep learning framework, termed DeepAIR, for the accurate prediction of AIR-antigen binding by integrating both sequence and structure features of AIRs. DeepAIR achieves a Pearson’s correlation of 0.813 in predicting the binding affinity of TCR, and a median area under the receiver-operating characteristic curve (AUC) of 0.904 and 0.942 in predicting the binding reactivity of TCR and BCR, respectively. Meanwhile, using TCR and BCR repertoire, DeepAIR correctly identifies every patient with nasopharyngeal carcinoma and inflammatory bowel disease in test data. Thus, DeepAIR improves the AIR-antigen binding prediction that facilitates the study of adaptive immunity

Design and optimization of an advanced time-of-flight neutron spectrometer for deuterium plasmas of the large helical device

A time-of-flight neutron spectrometer based on the Time-Of-Flight Enhanced Diagnostic (TOFED) concept has been designed and is under development for the Large Helical Device (LHD). It will be the first advanced neutron spectrometer to measure the 2.45 MeV D–D neutrons (DDNs) from helical/stellarator plasmas. The main mission of the new TOFED is to study the supra-thermal deuterons generated from the auxiliary heating systems in helical plasmas by measuring the time-of-flight spectra of DDN. It will also measure the triton burnup neutrons (TBNs) from the d+t reactions, unlike the original TOFED in the EAST tokamak. Its capability of diagnosing the TBN ratios is evaluated in this work. This new TOFED is expected to be installed in the basement under the LHD hall and shares the collimator with one channel of the vertical neutron camera to define its line of sight. The distance from its primary scintillators to the equatorial plane of LHD plasmas is about 15.5 m. Based on Monte Carlo simulation by a GEANT4 model, the resolution of the DDN energy spectra is 6.6%. When projected onto the neutron rates that are typically obtained in LHD deuterium plasmas (an order of 1015 n/s with neutral beam injection), we expect to obtain the DDN and TBN counting rates of about 2.5 · 105 counts/s and 250 counts/s, respectively. This will allow us to analyze the DDN time-of-flight spectra on time scales of 0.1 s and diagnose the TBN emission rates in several seconds with one instrument, for the first time in helical/stellarator plasmas

DINet: Deformation Inpainting Network for Realistic Face Visually Dubbing on High Resolution Video

For few-shot learning, it is still a critical challenge to realize photo-realistic face visually dubbing on high-resolution videos. Previous works fail to generate high-fidelity dubbing results. To address the above problem, this paper proposes a Deformation Inpainting Network (DINet) for high-resolution face visually dubbing. Different from previous works relying on multiple up-sample layers to directly generate pixels from latent embeddings, DINet performs spatial deformation on feature maps of reference images to better preserve high-frequency textural details. Specifically, DINet consists of one deformation part and one inpainting part. In the first part, five reference facial images adaptively perform spatial deformation to create deformed feature maps encoding mouth shapes at each frame, in order to align with input driving audio and also the head poses of input source images. In the second part, to produce face visually dubbing, a feature decoder is responsible for adaptively incorporating mouth movements from the deformed feature maps and other attributes (i.e., head pose and upper facial expression) from the source feature maps together. Finally, DINet achieves face visually dubbing with rich textural details. We conduct qualitative and quantitative comparisons to validate our DINet on high-resolution videos. The experimental results show that our method outperforms state-of-the-art works

Write-a-speaker: Text-based Emotional and Rhythmic Talking-head Generation

In this paper, we propose a novel text-based talking-head video generation framework that synthesizes high-fidelity facial expressions and head motions in accordance with contextual sentiments as well as speech rhythm and pauses. To be specific, our framework consists of a speaker-independent stage and a speaker-specific stage. In the speaker-independent stage, we design three parallel networks to generate animation parameters of the mouth, upper face, and head from texts, separately. In the speaker-specific stage, we present a 3D face model guided attention network to synthesize videos tailored for different individuals. It takes the animation parameters as input and exploits an attention mask to manipulate facial expression changes for the input individuals. Furthermore, to better establish authentic correspondences between visual motions (i.e., facial expression changes and head movements) and audios, we leverage a high-accuracy motion capture dataset instead of relying on long videos of specific individuals. After attaining the visual and audio correspondences, we can effectively train our network in an end-to-end fashion. Extensive experiments on qualitative and quantitative results demonstrate that our algorithm achieves high-quality photo-realistic talking-head videos including various facial expressions and head motions according to speech rhythms and outperforms the state-of-the-art

<it>De novo</it> sequencing and analysis of the <it>Ulva linza</it> transcriptome to discover putative mechanisms associated with its successful colonization of coastal ecosystems

Abstract Background The green algal genus Ulva Linnaeus (Ulvaceae, Ulvales, Chlorophyta) is well known for its wide distribution in marine, freshwater, and brackish environments throughout the world. The Ulva species are also highly tolerant of variations in salinity, temperature, and irradiance and are the main cause of green tides, which can have deleterious ecological effects. However, limited genomic information is currently available in this non-model and ecologically important species. Ulva linza is a species that inhabits bedrock in the mid to low intertidal zone, and it is a major contributor to biofouling. Here, we presented the global characterization of the U. linza transcriptome using the Roche GS FLX Titanium platform, with the aim of uncovering the genomic mechanisms underlying rapid and successful colonization of the coastal ecosystems. Results De novo assembly of 382,884 reads generated 13,426 contigs with an average length of 1,000 bases. Contiguous sequences were further assembled into 10,784 isotigs with an average length of 1,515 bases. A total of 304,101 reads were nominally identified by BLAST; 4,368 isotigs were functionally annotated with 13,550 GO terms, and 2,404 isotigs having enzyme commission (EC) numbers were assigned to 262 KEGG pathways. When compared with four other full sequenced green algae, 3,457 unique isotigs were found in U. linza and 18 conserved in land plants. In addition, a specific photoprotective mechanism based on both LhcSR and PsbS proteins and a C4-like carbon-concentrating mechanism were found, which may help U. linza survive stress conditions. At least 19 transporters for essential inorganic nutrients (i.e., nitrogen, phosphorus, and sulphur) were responsible for its ability to take up inorganic nutrients, and at least 25 eukaryotic cytochrome P450s, which is a higher number than that found in other algae, may be related to their strong allelopathy. Multi-origination of the stress related proteins, such as glutamate dehydrogenase, superoxide dismutases, ascorbate peroxidase, catalase and heat-shock proteins, may also contribute to colonization of U. linza under stress conditions. Conclusions The transcriptome of U. linza uncovers some potential genomic mechanisms that might explain its ability to rapidly and successfully colonize coastal ecosystems, including the land-specific genes; special photoprotective mechanism based on both LhcSR and PsbS; development of C4-like carbon-concentrating mechanisms; muti-origin transporters for essential inorganic nutrients; multiple and complex P450s; and glutamate dehydrogenase, superoxide dismutases, ascorbate peroxidase, catalase, and heat-shock proteins that are related to stress resistance.</p

Observation of Wavelength Tuning in a Mode-Locked Figure-9 Fiber Laser

We demonstrate an all-PM Er-doped soliton mode-locked fiber oscillator based on the figure-9 configuration with a compact adjustable reflection-type non-reciprocal phase shifter. An analytical model based on the Jones matrix is established to simulate the wavelength tuning phenomenon. Experimentally, it is observed that the increase in pump power results in a significant redshift in the spectrum of output pulses. When the angle of the half-wave plate is rotated in one direction, the output spectrum is redshifted and then blueshifted successively. Good qualitative agreement is presented between the simulations and the experimental results. It is shown that the increase in pump power changes the nonlinear phase shift, which causes the redshift of the transmittance curves at the laser output port. In contrast, the rotation of wave plates not only changes the nonlinear phase shift difference, but also causes variations in linear phase bias and modulation depth. The changes in these parameters lead to the redshift and blueshift of the transmission curves, which enables wavelength tuning