Search

We elucidate grapevine evolution and domestication histories with 3525 cultivated and wild accessions worldwide. In the Pleistocene, harsh climate drove the separation of wild grape ecotypes caused by continuous habitat fragmentation. Then, domestication occurred concurrently about 11,000 years ago in Western Asia and the Caucasus to yield table and wine grapevines. The Western Asia domesticates dispersed into Europe with early farmers, introgressed with ancient wild western ecotypes, and subsequently diversified along human migration trails into muscat and unique western wine grape ancestries by the late Neolithic. Analyses of domestication traits also reveal new insights into selection for berry palatability, hermaphroditism, muscat flavor, and berry skin color. These data demonstrate the role of the grapevines in the early inception of agriculture across Eurasia.

Inflammation induced by gut microbiota disorder plays an important role in promoting obesity. Inulin has beneficial effects on gut microflora and metabolic endotoxaemia. However, the chain length of inulin determines its different physiological effects. This study aimed to investigate the effect of low polymerization inulin (LPI) and high polymerization inulin (HPI) on inflammation in dogs with obesity induced by a high-fat diet and its potential mechanism. HPI, relative to LPI, significantly reduced the concentrations of LPS, IL-6 and TNF-α in serum and downregulated both the mRNA and protein expression of TLR4, NF-κB, TNF-α and IL-6 in adipose tissue. HPI and LPI intervention reduced adipose tissue fatty accumulation, which improved obesity. Supplementation with LPI and HPI increased gut microbiota diversity and altered specific bacterial populations at both the phylum and genus levels. The relative abundances of Prevotella, Fusobacterium and Enterobacter, which were positively correlated with the serum concentrations of LPS, IL-6 and TNF-α, were reduced. Our results demonstrate that both LPI and HPI can be used as an effective strategy for reducing inflammation and regulating gut microbiota, which can ameliorate obesity in dogs. Moreover, HPI exerts more positive regulation of the inflammatory response and gut microbiota dysfunction than LPI.

Expression of the VaRPP13 in Arabidopsis and tobacco enhanced resistance to oomycete pathogens, and this enhancement is closely related to the activation of salicylic acid (SA) signaling pathway. Resistance (R) genes, which usually contain a nucleotide-binding site and a leucine-rich repeat (NBS-LRR) domain, play crucial roles in disease resistance. In this study, we cloned a CC-NBS-LRR gene VaRPP13 from Vitis amurensis 'Shuang Hong' grapevine, and investigated its function on disease resistance. VaRPP13 expression was induced by Plasmopara viticola, an oomycetes pathogen causing downy mildew disease in grapevine. Heterologous expression VaRPP13 could also enhance resistance to Hyaloperonospora arabidopsidis in Arabidopsis thaliana and Phytophthora capsici in Nicotiana benthamiana, both oomycete pathogens. Further study indicated that VaRPP13 could enhance the expression of genes in SA signal pathway, while exogenous SA could also induce the expression of VaRPP13. In conclusion, our studies demonstrated that VaRPP13 contributes to a broad-spectrum resistance to oomycetes via activating SA signaling pathway.

PurposeSome economic theories have influenced the reform of the socialist open economy with Chinese characteristics. As a new practice of socialism, an open economy is not only driven by China’s productivity level and people’s living standards but also regulated by the law of commodity production and value.Design/methodology/approachIt was popular to participate in economic globalization for most countries in the second half of the 20th century, but not all of them could benefit from it.FindingsThe key to the success of the open-economy reform with Chinese characteristics lies in learning from and innovating the comparative advantage theory, thus forming an organic whole of the open economy, including the core of correctly handling the relationship between the government and the market, the method of gradual reform, the breakthrough point of transforming the mode of economic development, and serving people all the time.Originality/valueAchieving internal and external coordination through the combination of opening-up and independence is a critical principle of China’s economic opening-up, which not only effectively safeguards national interests but also actively promotes the construction of a new global order.

Marine hydrates mainly occur in clayey silt sediments, and their occurrence environment has the characteristics of a high clay content and low permeability, which seriously inhibit an increase in the gas production rate. This study presents a new method, the high-pressure jet breaking and sand filling method, to transform the natural gas hydrate (NGH) reservoir near the production well, whereby a water jet is used to form an area of sediment with large particle diameters and high permeability. Based on indoor experiments, we report the characteristics of hydrate formation, decomposition, and phase equilibrium in the transition area formed by this method under different sand particle sizes and mass fractions. The addition of sand at a high mass fraction with a large particle diameter significantly shortened the time required for rapid hydrate formation, prolonged slow hydrate formation, and reduced the increase in temperature. With an increase in the mass fraction of large-diameter sand, the free water content of pores increased, which made it easier to form hydrates with large particles, thus delaying the hydrate decomposition rate. The phase equilibrium curves of hydrates in clayey silt sediments with sand added at mass fractions of 30% and 50% were close to that of bulk hydrate in pure water at lower temperatures. As the temperature increased, the phase equilibrium curves gradually approached those of hydrates in clayey silt sediments.

Bacillus species as fungal antagonistic agents have been widely used in the agriculture and considered as safe products for the management of plant pathogens. In this study, we reported the whole genome sequence of strain LJBV19 isolated from grapevine rhizosphere soil. Strain LJBV19 was identified as Bacillus velezensis through morphological, physicochemical, molecular analysis and genome comparison. Bacillus velezensis LJBV19 had a significant inhibitory effect on the growth of Magnaporthe oryzae with an inhibition ratio up to 75.55% and showed broad spectrum of activity against fungal phytopathogens. The 3,973,013-bp circular chromosome with an average GC content of 46.5% consisted of 3993 open reading frames (ORFs), and 3308 ORFs were classified into 19 cluster of orthologous groups of proteins (COG) categories. Genes related to cell wall degrading enzymes were predicted by Carbohydrate-Active enZYmes (CAZy) database and validated at the metabolic level, producing 0.53 ± 0.00 U/mL cellulose, 0.14 ± 0.01 U/mL chitinase, and 0.11 ± 0.01 U/mL chitosanase. Genome comparison confirmed the taxonomic position of LJBV19, conserved genomic structure, and genetic homogeneity. Moreover, 13 gene clusters for biosynthesis of secondary metabolites in LJBV19 genome were identified and two unique clusters (clusters 2 and 12) shown to direct an unknown compound were only present in strain LJBV19. In general, our results will provide insights into the antifungal mechanisms of Bacillus velezensis LJBV19 and further application of the strain.

We evaluate existing foundation models video understanding capabilities using a carefully designed experiment protocol consisting of three hallmark tasks (action recognition, temporal localization, and spatiotemporal localization), eight datasets well received by the community, and four adaptation methods tailoring a foundation model (FM) for a downstream task. Moreover, we propose a scalar VideoGLUE score (VGS) to measure an FMs efficacy and efficiency when adapting to general video understanding tasks. Our main findings are as follows. First, task-specialized models significantly outperform the six FMs studied in this work, in sharp contrast to what FMs have achieved in natural language and image understanding. Second,video-native FMs, whose pretraining data contains the video modality, are generally better than image-native FMs in classifying motion-rich videos, localizing actions in time, and understanding a video of more than one action. Third, the video-native FMs can perform well on video tasks under light adaptations to downstream tasks(e.g., freezing the FM backbones), while image-native FMs win in full end-to-end finetuning. The first two observations reveal the need and tremendous opportunities to conduct research on video-focused FMs, and the last confirms that both tasks and adaptation methods matter when it comes to the evaluation of FMs.

In this work, we introduce Semantic Pyramid AutoEncoder (SPAE) for enabling frozen LLMs to perform both understanding and generation tasks involving non-linguistic modalities such as images or videos. SPAE converts between raw pixels and interpretable lexical tokens (or words) extracted from the LLM's vocabulary. The resulting tokens capture both the semantic meaning and the fine-grained details needed for visual reconstruction, effectively translating the visual content into a language comprehensible to the LLM, and empowering it to perform a wide array of multimodal tasks. Our approach is validated through in-context learning experiments with frozen PaLM 2 and GPT 3.5 on a diverse set of image understanding and generation tasks. Our method marks the first successful attempt to enable a frozen LLM to generate image content while surpassing state-of-the-art performance in image understanding tasks, under the same setting, by over 25%.

To meet the growing global demand for gluconic acid as a cement and concrete retarder, inexpensive and abundant lignocellulosic materials are regarded as the most suitable alternatives to starchy materials. However, their enzymatic hydrolysate contains not only glucose but also xylose, which negatively affects the performance of gluconic acid as a retarder. Notably, glucose is preferentially bio-oxidized into gluconic acid by Gluconobacter oxydans, but gluconic acid cannot be metabolized by Candida tropicalis. Given this, an artificially designed biological cascade process, respectively employing Gluconobacter oxydans and Candida tropicalis, was established to successfully carry out glucose conversion into gluconic acid, and xylose into a single-cell protein, using the enzymatic hydrolysate of corncobs as a feedstock. This sequential fermentation process produced 95.8 g/L gluconic acid and 9.0 g/L single-cell protein from one liter of the enzymatic hydrolysate that initially contained 98.1 g/L of glucose and 25.4 g/L of xylose. The mass-balance calculation showed that approximately 280 grams of gluconic acid and 27 grams of the single-cell protein could be harvested from 1000 grams of the corncob feedstock. The results suggest that the above-mentioned two-step bioconversion method is efficient in utilizing glucose and xylose from lignocellulosic hydrolysates.

We study domain-adaptive image synthesis, the problem of teaching pretrained image generative models a new style or concept from as few as one image to synthesize novel images, to better understand the compositional image synthesis. We present a framework that leverages a pretrained class-conditional generation model and visual prompt tuning. Specifically, we propose a novel source class distilled visual prompt that learns disentangled prompts of semantic (e.g., class) and domain (e.g., style) from a few images. Learned domain prompt is then used to synthesize images of any classes in the style of target domain. We conduct studies on various target domains with the number of images ranging from one to a few to many, and show qualitative results which show the compositional generalization of our method. Moreover, we show that our method can help improve zero-shot domain adaptation classification accuracy., tech report

Introduction: Complete androgen insensitivity syndrome (CAIS) is a rare sex development disorder that results from X-linked androgen receptor gene mutations. Malignant transformation of the gonads is the most feared complication in postpubertal patients.Methods: In the current report, primary amenorrhea, infertility, and groin mass were symptoms described by a 58-year-old woman and his younger sister. Their two aunts, who shared the same clinical traits, passed away for an unknown reason.Results: After gonadectomy, both patients were diagnosed with seminoma and an extratesticular benign tumor, and the elder sister suffered from breast cancer about a year after the operation. The diagnosis of CAIS was verified by whole-exome sequencing (WES), in which an uncommon mutation (c.2197G>A) in the AR gene was identified.Discussion: This is the first family report of CAIS with germ cell tumors. The identified AR gene mutation based on WES can expand the understanding of CAIS.

The peroxisome proliferator-activated receptor gamma (PPARγ) are nuclear receptors with distinct roles in energy metabolism and immunity. Although extensively studied in mammals, immunomodulatory roles of this molecule in teleost fish remain to be investigated. In this study, large yellow croaker (Larimichthys crocea) PPARγ (LcPPARγ) sequence was cloned, which encodes a polypeptide of 541 amino acids that include signature domains belonging to the nuclear receptor superfamily. Phylogenetically, LcPPARγ was most closely related to PPARγ derived from European sea bass (Dicentrarchus labrax). Quantitative analysis shown a ubiquitous expression of this molecule, with highest expression level detected in the intestine. The expression of LcPPARγ was decreased in the intestine, muscle, body kidney, spleen and head kidney-derived monocytes/macrophages (MO/MФs) over the course of Vibrio alginolyticus (V. alginolyticus) infection. In contrast, an up-regulation of LcPPARγ was observed in head kidney-derived MO/MФs following docosahexaenoic acid (DHA) treatment. This increase in LcPPARγ leads to an up-regulation of LcCD11b and LcCD18 and an enhancement of complement-mediated phagocytosis. Furthermore, cytokine secretions of V. alginolyticus-stimulated MO/MФs were modulated following LcPPARγ activations that up-regulated the expression of LcIL-10, while decreased the expression of LcIL-1β, LcTNF-α and LcTGF-β1. Overall, our results indicated that LcPPARγ plays a role in regulating functions of MO/MФs and likely contribute to MO/MФs polarization.

CXC chemokine receptor 4 (CXCR4), a member of the G-protein-coupled receptor family, plays an important role in host immune responses. Within the teleost lineage, there are two paralogs of CXCR4; however, the role of CXCR4 in teleost B cells is poorly understood. In this study, we determined the cDNA sequences of the two CXCR4 paralogs from the Japanese sea bass (Lateolabrax japonica; LjCXCR4a and LjCXCR4b). Sequence and phylogenetic tree analyses revealed that LjCXCR4a and LjCXCR4b are most closely related to CXCR4a and CXCR4b, respectively, in the large yellow croaker (Larimichthys crocea). CXCR4 transcripts were mainly expressed in the gills, and their expression in different tissues was altered upon infection with Vibrio harveyi. LjCXCR4a and LjCXCR4b protein levels were upregulated in infected B cells. Knockdown of LjCXCR4a and LjCXCR4b in B cells by RNA interference, the phagocytic activity of B cells was not affected. Furthermore, knockdown of LjCXCR4a, not of LjCXCR4b, was observed to inhibit LjIgM expression in lipopolysaccharide-stimulated B cells. In addition, knockdown of LjCXCR4a, not of LjCXCR4b, was found to reduce reactive oxygen species levels in B cells. Our results indicate that LjCXCR4a and LjCXCR4b modulate the immune response of Japanese sea bass B cells against bacterial infection, albeit via different pathways.

The rapid development of global transportation network and information communication technology has an important impact on regional economy and social spatial structure, and promotes the transformation of regional research paradigm. The coordinated development of urban agglomeration and regional functional linkage from the perspective of flow space has become an important issue in urban regional research. Different from the traditional central place theory that emphasizes the differences in scale and level of cities within the region, the flow space perspective helps to understand how the regional factor flow organizes cities of all scales and levels in the form of network with the background of space-time compression, and promotes the functional linkage and coordinated development within the region on the basis of reshaping the urban spatial relationship. Based on the literature review of relevant research at home and abroad, this paper constructs an analytical framework for the relationship between regional spatial factor flow and function collaboration, and discusses the regional function collaborative mechanism of urban agglomeration from three aspects: "how to reshape the regional spatial network by factor flow", "how to restructure the urban hierarchy by infrastructure connectivity" and "how to strengthen the regional functional linkage by functional complementarity". On this basis, taking the urban agglomeration of San Francisco Bay Area as an example, this paper discusses the evolution progress of San Francisco Bay Area from "single center agglomeration development" to "double-core symbiotic evolution", "polycentric development" and "generic network functional linkage development" from three aspects of liquidity, connectivity and complementarity. The study found that: 1) In the first stage (before the 1930s), fact flow strengthened the connection between San Francisco and Oakland, connectivity improved the status of Oakland, and functional complementarity promoted the symbiosis of the two cities. 2) In the second stage (1940s-1980s), the flow and converge of factors towards the south bay promoted the tripartite growth of San Francisco, Oakland and San Jose, transport connectivity strengthened the core-peripheral connection, and factor convection and functional reciprocity promoted the multi-center linkage development. 3) In the third stage (since 1980s), factor distribution and transportation network connectivity contributed to the generic network spatial structure, dislocation and complementary development strengthened the regional circulation and realized the functional linkage of the Bay Area. Based on the perspective of flow space, this paper reviews the basic situation of the development of world-class bay area urban agglomerations and excavates the internal mechanism of regional functional coordinated development driven by factor flow, which has reference significance for guiding China's cities from competition to competition and cooperation and establishing a new mechanism of regional coordinated development. The research shows that to promote the development of China's bay area in the future, we should: 1) Comply with the law of factor flow, innovate the mechanism and remove barriers to factor mobility, and promote the free flow of factors inside and outside the region; 2) Give play to the guiding role of the government and non-governmental organizations to improve the connectivity of software and hardware infrastructure within the region; 3) Explore the regional consultation mechanism, break through the regional administrative barriers, and formulate the regional development strategy of functional complementation and linkage with the help of multiple subject forces.

A robust method for the preparation of a bottlebrush polymer under physiological buffer conditions was developed via the combination of a grafting onto strategy and an o-phthalaldehyde-amine coupling reaction.

ObjectiveOral potentially malignant disorders (OPMDs) are a spectrum of diseases that harbor the potential of malignant transformation and developing into oral squamous cell carcinoma (OSCC). Narrow band imaging (NBI) has been clinically utilized for the adjuvant diagnosis of OPMD and OSCC. This study aimed to comprehensively evaluate the diagnostic accuracy of NBI for malignant transformations of OPMD by applying the intraepithelial papillary capillary loop (IPCL) classification approach.MethodsStudies reporting the diagnostic validity of NBI in the detection of OPMD/OSCC were selected. Four databases were searched and 11 articles were included in the meta-analysis. We performed four subgroup analyses by defining IPCL I/II as negative diagnostic results and no/mild dysplasia as negative pathological outcome. Pooled data were analyzed using random-effects models. Meta-regression analysis was performed to explore heterogeneity.ResultsAfter pooled analysis of the four subgroups, we found that subgroup 1, defining IPCL II and above as a clinically positive result, demonstrated the most optimal overall diagnostic accuracy for the malignant transformation of OPMDs, with a sensitivity and specificity of NBI of 0.87 (95% confidence interval (CI) [0.67, 0.96], p p ConclusionsNBI is a promising and non-invasive adjunctive tool for identifying malignant transformations of OPMDs. The IPCL grading is currently a sound criterion for the clinical application of NBI. After excluding potentially false positive results, these oral lesions classified as IPCL II or above are suggested to undergo biopsy for early and accurate diagnosis as well as management.

Responsible innovation has been widely concerned by the public sector and actively explored by scholars for its great role in supporting eco-innovation and sustainable development. However, as the main body of innovation, enterprises have not been fully recognized. Moreover, the research on the driving factors of responsible innovation is mostly the direct influence of a single factor, lacking the overall consideration of the internal and external environment. To bridge this research gap, this study, by deeply interviewing 13 entrepreneurs in environmental protection enterprises, clarified the concept of corporate responsible innovation and its four-dimensional framework (inclusion, anticipation, reflexivity, responsiveness), and then proposed the MPN-MSE driving factor model of corporate responsible innovation from the internal and external perspectives. The external factors include market pressure (M), policy pressure (P), and normative pressure (N), while the internal factors include responsible innovation motivation (M), responsible innovation system (S), and responsible innovation elements (E). The research findings provide an important theoretical contribution to the research of corporate responsible innovation.

We present Muse, a text-to-image Transformer model that achieves state-of-the-art image generation performance while being significantly more efficient than diffusion or autoregressive models. Muse is trained on a masked modeling task in discrete token space: given the text embedding extracted from a pre-trained large language model (LLM), Muse is trained to predict randomly masked image tokens. Compared to pixel-space diffusion models, such as Imagen and DALL-E 2, Muse is significantly more efficient due to the use of discrete tokens and requiring fewer sampling iterations; compared to autoregressive models, such as Parti, Muse is more efficient due to the use of parallel decoding. The use of a pre-trained LLM enables fine-grained language understanding, translating to high-fidelity image generation and the understanding of visual concepts such as objects, their spatial relationships, pose, cardinality etc. Our 900M parameter model achieves a new SOTA on CC3M, with an FID score of 6.06. The Muse 3B parameter model achieves an FID of 7.88 on zero-shot COCO evaluation, along with a CLIP score of 0.32. Muse also directly enables a number of image editing applications without the need to fine-tune or invert the model: inpainting, outpainting, and mask-free editing. More results are available at https://muse-model.github.io

In this paper, we study the problem of MOOC quality evaluation which is essential for improving the course materials, promoting students' learning efficiency, and benefiting user services. While achieving promising performances, current works still suffer from the complicated interactions and relationships of entities in MOOC platforms. To tackle the challenges, we formulate the problem as a course representation learning task-based and develop an Information-aware Graph Representation Learning(IaGRL) for multi-view MOOC quality evaluation. Specifically, We first build a MOOC Heterogeneous Network (HIN) to represent the interactions and relationships among entities in MOOC platforms. And then we decompose the MOOC HIN into multiple single-relation graphs based on meta-paths to depict the multi-view semantics of courses. The course representation learning can be further converted to a multi-view graph representation task. Different from traditional graph representation learning, the learned course representations are expected to match the following three types of validity: (1) the agreement on expressiveness between the raw course portfolio and the learned course representations; (2) the consistency between the representations in each view and the unified representations; (3) the alignment between the course and MOOC platform representations. Therefore, we propose to exploit mutual information for preserving the validity of course representations. We conduct extensive experiments over real-world MOOC datasets to demonstrate the effectiveness of our proposed method.

Text-to-image models, which can generate high-quality images based on textual input, have recently enabled various content-creation tools. Despite significantly affecting a wide range of downstream applications, the distributions of these generated images are still not fully understood, especially when it comes to the potential stereotypical attributes of different genders. In this work, we propose a paradigm (Gender Presentation Differences) that utilizes fine-grained self-presentation attributes to study how gender is presented differently in text-to-image models. By probing gender indicators in the input text (e.g., "a woman" or "a man"), we quantify the frequency differences of presentation-centric attributes (e.g., "a shirt" and "a dress") through human annotation and introduce a novel metric: GEP. Furthermore, we propose an automatic method to estimate such differences. The automatic GEP metric based on our approach yields a higher correlation with human annotations than that based on existing CLIP scores, consistently across three state-of-the-art text-to-image models. Finally, we demonstrate the generalization ability of our metrics in the context of gender stereotypes related to occupations., Comment: Preprint, 23 pages, 14 figures. Project page at https://salt-nlp.github.io/GEP/

Pre-trained large text-to-image models synthesize impressive images with an appropriate use of text prompts. However, ambiguities inherent in natural language and out-of-distribution effects make it hard to synthesize image styles, that leverage a specific design pattern, texture or material. In this paper, we introduce StyleDrop, a method that enables the synthesis of images that faithfully follow a specific style using a text-to-image model. The proposed method is extremely versatile and captures nuances and details of a user-provided style, such as color schemes, shading, design patterns, and local and global effects. It efficiently learns a new style by fine-tuning very few trainable parameters (less than $1\%$ of total model parameters) and improving the quality via iterative training with either human or automated feedback. Better yet, StyleDrop is able to deliver impressive results even when the user supplies only a single image that specifies the desired style. An extensive study shows that, for the task of style tuning text-to-image models, StyleDrop implemented on Muse convincingly outperforms other methods, including DreamBooth and textual inversion on Imagen or Stable Diffusion. More results are available at our project website: https://styledrop.github.io, Comment: Preprint. Project page at https://styledrop.github.io

In order to investigate the seismic behavior of the hybrid coupled partially encased composite (PEC) wall system, two 2/3-scale three-story specimens with different elastic coupling ratios (CRelastic) were tested under cyclic loading. The results showed that the hysteretic curves of the two specimens were full and stable, indicating their robust cyclic performance and excellent energy dissipation capacity. Under reversed cyclic lateral loading, the specimens exhibited a two-stage yielding energy dissipation mechanism, in accordance with theoretical expectations. Both specimens dissipated a large amount of energy during loading, with the equivalent viscous damping ξeq reaching 0.32 and 0.35 at the maximum displacement level, respectively. Based on the experimental results, the refined finite element model for the hybrid coupled PEC wall was established in ABAQUS and validated. A parametric analysis demonstrated that the CRelastic and the design axial compression ratio (n) had significant influences on the seismic behavior of the hybrid coupled PEC wall. With increasing CRelastic, the lateral stiffness, strength, and yield displacement of the hybrid coupled PEC wall gradually increased, while its ductility deteriorated. Moreover, the ductility of the hybrid coupled PEC wall decreased with increasing n owing to the strong coupling action of the steel coupling beams. In order to ensure the good seismic performance and form a reasonable failure mode, the CRelastic and n in the hybrid coupled PEC wall should not exceed 65% and 0.5, respectively.

In this work, Sentaurus TCAD was used to study the transient surge current mechanism of the 4H-SiC merged pin and schottky (MPS) diode. For the first time, a structure combining multicells with transition region was used to analyze the transient surge current mechanism of the MPS diode. The electrothermal simulation analysis of the surge characteristics of the MPS diode is carried out. Internal carrier distribution and lattice temperature in the surge current transient process of the device are mainly studied. The simulation results show that the hole current distribution and the electron current distribution in the MPS diode are not uniform. In the transient process of surge current, the transition region first enters the bipolar conduction mode, and then, the cells in the active region enter the bipolar conduction mode in the order from outside (close to transition region) to inside. The voltage-time (V-t), maximum temperature-time ( $T_{max}$ -t), and I-V curves of MPS diode in surge current events are obtained by simulation. Combined with the current density distribution diagram, the device behavior of multiple critical time nodes is analyzed in detail, and a reasonable explanation is given. In addition, the influence of different transition region contact types on the internal current distribution of the MPS diode is studied, and the simulation results are reasonably explained.

Electroacupuncture (EA) is considered to have potential antidiabetic effects; however, the role of the pancreatic intrinsic nervous system (PINS) in EA-induced amelioration of type 2 diabetes (T2DM) remains unclear. Therefore, we investigated whether EA at ST25 exerts any beneficial effects on insulin resistance (IR), inflammation severity, and pancreatic β cell function via the PINS in a rat model of a high-fat diet-streptozotocin (HFD/STZ)-induced diabetes. To this end, Sprague Dawley rats were fed with HFD to induce IR, followed by STZ (35 mg/kg, i.p.) injection to establish the T2DM model. After hyperglycemia was confirmed as fasting glucose level > 16.7 mmol/L, the rats were treated with EA (2 mA, 2/15 Hz) for the next 28 days. Model rats showed increased serum glucose, insulin, IR, and TNF-α levels with a concomitant decrease in β cell function. Microscopy examination of the pancreas revealed pathological changes in islets, which reverted to near-normal levels after EA at ST25. EA improved islet cell morphology by increasing islet area and reducing vacuolation. EA at ST25 decreased transient receptor potential vanilloid 1 (TRPV1) and increased substance P (SP) and calcitonin gene-related peptide (CGRP) expression. Subsequently, insulin secretion decreased and impaired pancreatic endocrine function was restored through the TRPV1 channel (SP/CGRP)-insulin circuit. EA increased choline acetyltransferase and neuropeptide Y expression and controlled inflammation. It also enhanced the cocaine and amphetamine-regulated transcript prepropeptide expression and promoted glucagon-like peptide-1 secretion. Additionally, the electrophysiological activity of PINS during acupuncture (2.71 ± 1.72 Hz) was significantly increased compared to the pre-acupuncture frequency (0.32 ± 0.37 Hz, P < 0.05). Thus, our study demonstrated the beneficial effect of EA on β cell dysfunction via the PINS in rat models of HFD-STZ-induced T2DM.

Clinical success of adoptive cell therapy with chimeric antigen receptor (CAR) T cells for treating hematological malignancies has revolutionized the field of cellular immunotherapy. However, due to the nature of utilizing autologous T cells, affordability and availability are major hurdles, in addition to scientific challenges relating to CAR‐T therapy optimization. Natural killer (NK) cell is a specialized immune effector cell type that recognizes and kills targets without human leukocyte antigen (HLA) restriction and prior sensitization. CAR‐NK cells do not cause graft vs host disease and can be obtained from unrelated donors as well as pluripotent stem cells (PSC), representing an ideal off‐the‐shelf therapeutics readily available for patients. Furthermore, unlike cytotoxic T cells, NK cells specifically target and eliminate cancer stem cells, which are the cells causing relapse and metastasis. PSCs can be genetically manipulated and engineered with CARs at the pluripotent stage, which allows the establishment of permanent, stable, and clonal PSC‐CAR lines for the manufacture of unlimited homogenous CAR‐NK cells. Multiple master PSC‐CAR cell banks targeting a variety of antigens for cancer, viral infection, and autoimmune diseases provide inexhaustible cell sources for all patients. Development of a next‐generation 3D bioreactor platform for PSC expansion and NK cell production overcomes major barriers related to cost and scalability for CAR‐NK product., The establishment of a master pluripotent stem cell (PSC)‐CAR cell bank targeting a variety of specific antigens will provide inexhaustible cell sources for the manufacture of truly off‐the‐shelf CAR‐NK cells for all patients of cancer, infectious, and autoimmune diseases.

We introduce the MAsked Generative VIdeo Transformer, MAGVIT, to tackle various video synthesis tasks with a single model. We introduce a 3D tokenizer to quantize a video into spatial-temporal visual tokens and propose an embedding method for masked video token modeling to facilitate multi-task learning. We conduct extensive experiments to demonstrate the quality, efficiency, and flexibility of MAGVIT. Our experiments show that (i) MAGVIT performs favorably against state-of-the-art approaches and establishes the best-published FVD on three video generation benchmarks, including the challenging Kinetics-600. (ii) MAGVIT outperforms existing methods in inference time by two orders of magnitude against diffusion models and by 60x against autoregressive models. (iii) A single MAGVIT model supports ten diverse generation tasks and generalizes across videos from different visual domains. The source code and trained models will be released to the public at https://magvit.cs.cmu.edu., CVPR 2023 highlight

In this paper, a novel silicon carbide (SiC) insulated gate bipolar transistor (IGBT) with a 4H-SiC/Si heterojunction in buffer layer (HBL) is proposed to improve the turn-off characteristic. Compared with the conventional 4H-SiC IGBT, the polysilicon region is integrated in the buffer layer to form a natural potential well, which can help to store excessive carriers at the turn-off process. Simulation results indicate that the turn-off time (toff) is reduced from 325 ns to 232 ns and the turn-off loss (Eoff) is decreased from 2.619 mJ to 1.375 mJ, while a similar on-state ability is maintained. That means the reduction of 28.6% toff and 47.5% Eoff can be achieved. Based on the structure benefits, a better trade-off between Eoff-VF is also achieved for the proposed HBL-IGBT. Moreover, the heterojunction of HBL-IGBT can be formed with the plasma active direct bonding technology, which is compatible with the conventional fabrication process.

Intrahepatic cholangiocarcinoma (ICC) develops rapidly with a high malignancy. SOX9 expression is increased in several tumors. However, its expression and role in intrahepatic cholangiocarcinoma have not yet been elucidated. Real time PCR and Western blot were done to assess SOX9 expression in tumor tissues and adjacent tissues of ICC. ICC cell line QBC939 cells were separated into control group, SOX9 overexpression group and SOX9 siRNA group followed by analysis of cell survival by MTT assay, cell migration by cell scratch assay, cell invasion by transwell chamber, E-cadherin and Vimentin level by western blot, TGFβ/Smad signaling protein level by real time PCR. SOX9 level in tumor tissues was significantly increased compared to adjacent tissues (P < 0.05) and it was associated with TNM stage, tissue type and metastasis, and survival time (P < 0.05). Transfection of pcDNA3.1-SOX9 upregulated SOX9, promoted cell proliferation, migration and invasion, downregulated E-cadherin, upregulated Vimentin, TGF-β1 and Smad4 (P < 0.05). SOX9 siRNA transfection into QBC939 cells could significantly reverse the above mentioned changes (P < 0.05). SOX9 level is increased in intrahepatic cholangiocarcinoma and targeting SOX9 can inhibit cell migration and invasion, and EMT via regulating TGFβ/Smad signaling.

The ${I}$ – ${V}$ characteristics of 4H-SiC N/P-channel MOSFETs have been carried out at high temperatures up to 300 °C. Different scattering mechanisms of surface mobility for 4H-SiC N-channel MOSFETs have been studied in this article. Moreover, the temperature dependencies of various scattering mobilities for P-channel MOSFETs are given for the first time. Their temperature dependencies were simulated and analyzed at a temperature ranging from 27 °C to 300 °C. Furthermore, an improved method of extracting trapped charge from transfer characteristic is proposed, such that the density of occupied interface traps in a strong inversion can be extracted. The analysis of experimental results shows that sacrificial oxidation can decrease the occupied interface traps at high temperatures but not much effective at room temperature, and the Coulomb scattering in 4H-SiC P-channel MOSFETs has always been the main mechanism from 27 °C to 300 °C, which is different from 4H-SiC N-channel MOSFETs.

To optimize the optimal nozzle structure and multiple nozzle arrangement for hydrate jet crushing and to promote the development of solid fluidization extraction technology for shallow unconformity hydrate in China’s oceans, the submerged jet flow field of six commonly used nozzle structures in the downhole in-situ jet crushing process was analyzed on the basis of the solid fluidization extraction process in double-layer pipes, and the effect of the jet hole arrangement on the overflow performance of hydrate slurry in the outer annulus of double-layer pipes was also investigated. It was demonstrated that tapered straight nozzles were preferably selected as the nozzle type for hydrate solid fluidization mining process based on jet core stage length, jet energy dissipation rate, and jet fluid axial velocity. In the meantime, the optimum arrangement of the nozzles was preferred on the basis of the annular pressure drop and the flow resistance coefficient, with the number of single circle not higher than 3 and the axial spacing of the nozzles not lower than 50 mm. This study can provide a theoretical basis for nozzle selection and tool design for the solid fluidization jet crushing process of marine unconformable hydrates.

Tumor metastasis is the major cause of cancer mortality; therefore, it is imperative to discover effective therapeutic drugs for anti-metastasis therapy. In the current study, we investigated whether ivermectin (IVM), an FDA-approved antiparasitic drug, could prevent cancer metastasis. Colorectal and breast cancer cell lines and a cancer cell-derived xenograft tumor metastasis model were used to investigate the anti-metastasis effect of IVM. Our results showed that IVM significantly inhibited the motility of cancer cells in vitro and tumor metastasis in vivo. Mechanistically, IVM suppressed the expressions of the migration-related proteins via inhibiting the activation of Wnt/β-catenin/integrin β1/FAK and the downstream signaling cascades. Our findings indicated that IVM was capable of suppressing tumor metastasis, which provided the rationale on exploring the potential clinical application of IVM in the prevention and treatment of cancer metastasis.

We report a methodology in which students gain experience in authentic research by developing artificial intelligence (AI) solutions for researchers in natural sciences. While creating education benefits for students, our approach also directly benefits scientists, who get an opportunity to evaluate the usefulness of machine learning for their specific needs. In order to accomplish this, we work with research laboratories that reveal/specify the needs they have, and then our student teams work on the discovery, design, and development of an AI solution for unique problems using a consulting-like arrangement. Our design addresses common barriers which appear in most existing authentic research education approaches and thus is suitable for wide adoption at various schools. To date, our group has been operating at New York University (NYU) for five consecutive semesters and has engaged more than seventy students, ranging from first-year college students to master's candidates, and worked on more than 15 projects with 14 collaborators.

Hypothalamus-pituitary-adrenal (HPA) axis plays critical roles in stress responses under challenging conditions such as hypoxia, via regulating gene expression and integrating activities of hypothalamus-pituitary-targets cells. However, the transcriptional regulatory mechanisms and signaling pathways of hypoxic stress in the pituitary remain to be defined. Here, we report that hypoxia induced dynamic changes in the transcription factors, hormones, and their receptors in the adult rat pituitary. Hypoxia-inducible factors (HIFs), oxidative phosphorylation, and cAMP signaling pathways were all differentially enriched in genes induced by hypoxic stress. In the pituitary gene network, hypoxia activated c-Fos and HIFs with specific pituitary transcription factors (Prop1), targeting the promoters of hormones and their receptors. HIF and its related signaling pathways can be a promising biomarker during acute or constant hypoxia. Hypoxia stimulated the transcription of marker genes for microglia, chemokines, and cytokine receptors of the inflammatory response. Corticotropin-releasing hormone receptor 1 (CRHR1) mediated the transcription of Pomc, Sstr2, and Hif2a, and regulated the function of HPA axis. Together with HIF, c-Fos initiated and modulated dynamic changes in the transcription of hormones and their receptors. The receptors were also implicated in the regulation of functions of target cells in the pituitary network under hypoxic stress. CRHR1 played an integrative role in the hypothalamus-pituitary-target axes. This study provides new evidence for CRHR1 involved changes of hormones, receptors, signaling molecules and pathways in the pituitary induced by hypoxia.

The physiological function of adipose tissue is dominated by the sympathetic nerve system (SNS), but obesity and other diseases may cause the abnormality of the SNS signaling pathway. Acupuncture has been proved to be an effective the-rapy to improve the function of SNS in adipose tissue. Based on the physiological and pathological significance of SNS, this paper reviewed the molecular pathways in which acupuncture directly or indirectly regulated the function of SNS in adipose tissue. As the mechanism of electroacupuncture in regulating autonomic nerves was continuously illuminated, the adjustment of acupuncture mode, such as selection of acupoints in different nerve segments and adjustment of stimulation parameters of electroacupuncture, presumedly induced different content ratios of neurotransmitters released by SNS efferent axons, including noradrenaline and neuropeptide Y, thereby producing different effects on weight loss. Therefore, the specific connections between various acupuncture modes and neurotransmitters released by SNS enriched the intrinsic nerve coding of acupoints, thus optimizing the acupoint selection protocol for the treatment of obesity.脂肪组织的生理功能依赖交感神经系统(SNS)的调控, 而肥胖等疾病会引起SNS信号通路的异常。针刺是改善脂肪组织内SNS功能的有效方法, 本文基于脂肪组织内SNS的生理病理意义梳理了针刺直接或间接调节脂肪组织SNS功能的分子通路。随着电针调控自主神经的机制不断被阐明, 调整针刺作用模式(包括选取不同神经节段的穴位及调整电针刺激参数等)可能导致脂肪组织内SNS传出支释放的去甲肾上腺素及神经肽Y等神经递质的含量比不同, 从而产生不同的减肥疗效。在此基础之上, 建立不同针刺作用模式与SNS神经末梢释放神经递质之间的特异联系可以丰富穴位内在的神经编码, 从而优化肥胖症的选穴治疗方案。.

Excessive androgen production and obesity are key to Polycystic ovary syndrome (PCOS) pathogenesis. PCOS-like mouse models induced by androgen exposure include the prenatal androgenized (PNA), peripubertal androgenized, and overexpression of nerve growth factor in theca cells (17NF), as well as the effect of diet-induced maternal obesity model on offspring. To reveal the molecular features of these models, we performed transcriptomic profiling of the hypothalamus, adipose tissue, ovary, and MII oocytes. The largest number of differentially expressed genes (DEGs) were found in the ovaries of 17NF and in the adipose tissues of peripubertal androgenized models. In contrast, the hypothalamus is most affected in PNA and maternal obesity models suggesting fetal programming effects. The Ms4a6e gene, membrane-spanning 4-domains subfamily A member 6E, a DEG identified in the adipose tissue in all PCOS-like mouse models is also differently expressed in adipose tissue of women with PCOS women, highlighting a conservative disease mechanism. Our comprehensive transcriptomic mapping of key target tissues of the PCOS pathology provides a unique resource when investigating molecular mechanisms induced by androgen exposure and highlights that there are critical windows for androgen administration and maternal obesity.

Few sample learning (FSL) is significant and challenging in the field of machine learning. The capability of learning and generalizing from very few samples successfully is a noticeable demarcation separating artificial intelligence and human intelligence since humans can readily establish their cognition to novelty from just a single or a handful of examples whereas machine learning algorithms typically entail hundreds or thousands of supervised samples to guarantee generalization ability. Despite the long history dated back to the early 2000s and the widespread attention in recent years with booming deep learning technologies, little surveys or reviews for FSL are available until now. In this context, we extensively review 300+ papers of FSL spanning from the 2000s to 2019 and provide a timely and comprehensive survey for FSL. In this survey, we review the evolution history as well as the current progress on FSL, categorize FSL approaches into the generative model based and discriminative model based kinds in principle, and emphasize particularly on the meta learning based FSL approaches. We also summarize several recently emerging extensional topics of FSL and review the latest advances on these topics. Furthermore, we highlight the important FSL applications covering many research hotspots in computer vision, natural language processing, audio and speech, reinforcement learning and robotic, data analysis, etc. Finally, we conclude the survey with a discussion on promising trends in the hope of providing guidance and insights to follow-up researches., Comment: 30 pages, Accepted by Pattern Recognition, 2023

Exposure to air pollution will pose a serious threat to human health. Accurate air pollution forecasting can help people to reduce exposure risks and promote environmental pollution control, and it is also an extremely important part of smart city management. However, the current deep-learning-based models for air pollution forecasting usually focus on prediction accuracy improvement without considering the model interpretability. These models usually fail to explain the complex relationships between prediction targets and external factors (e.g., ozone concentration (O3), wind speed, temperature variation, etc.) The relationships between variables in air pollution time series prediction problems are very complex, with intricate relationships between different types of variables, often with nonlinear multivariate dependencies. To address these problems mentioned above, we proposed a hybrid autoformer network with a genetic algorithm optimization to predict air pollution temporal variation as well as establish interpretable relationships between pollutants and external variables. Furthermore, an elite variable voting operator was designed to better filter out more important external factors such as elite variables, so as to perform a more refined search for elite variables. Moreover, we designed an archive storage operator to reduce the effect of neural network model initialization on the search for external variables. Finally, we conducted comprehensive experiments on the Ma’anshan air pollution dataset to verify the proposed model, where the prediction accuracy was improved by 2–8%, and the selection of model influencing factors was more interpretable.

The heavy ion radiation response and degradation of SiC junction barrier Schottky (JBS) diodes with different P+ implantation intervals (S) are studied in detail. The experimental results show that the larger the S, the faster the reverse leakage current increases, and the more serious the degradation after the experiment. TCAD simulation shows that the electric field of sensitive points directly affects the degradation rate of devices with different structures. The large transient energy introduced by the heavy ion impact can induce a local temperature increase in the device resulting in lattice damage and the introduction of defects. The reverse leakage current of the degraded device is the same at low voltage as before the experiment, and is gradually dominated by space-charge-limited-conduction (SCLC) as the voltage rises, finally showing ballistic transport characteristics at high voltage.

Mg-air batteries are explored as the next-generation power systems for wearable and implantable electronics as they could work stably in neutral electrolytes and are also biocompatible. However, high corrosion rate and low utilization of Mg anode largely impair the performance of Mg-air battery with low discharge voltage, poor specific capacity and low energy density. Here, to the best of our knowledge, we first report a dual-layer gel electrolyte to simultaneously solve the above two problems by preventing the corrosion of Mg anode and the production of dense passive layer, respectively. The resulting Mg-air batteries produced an average specific capacity of 2190 mAh g-1 based on the total Mg anode (99.3 % utilization rate of Mg anode) and energy density of 2282 Wh kg-1 based on the total anode and air electrode, both of which are the highest among the reported Mg-air batteries. Besides, our Mg-air batteries could be made into a fiber shape, and they were flexible to work stably under various deformations such as bending and twisting.