Generation and Characterization of Novel Human IRAS Monoclonal Antibodies

Imidazoline receptors were first proposed by Bousquet et al., when they studied antihypertensive effect of clonidine. A strong candidate for I1R, known as imidazoline receptor antisera-selected protein (IRAS), has been cloned from human hippocampus. We reported that IRAS mediated agmatine-induced inhibition of opioid dependence in morphine-dependent cells. To elucidate the functional and structure properties of I1R, we developed the newly monoclonal antibody against the N-terminal hIRAS region including the PX domain (10–120aa) through immunization of BALB/c mice with the NusA-IRAS fusion protein containing an IRAS N-terminal (10–120aa). Stable hybridoma cell lines were established and monoclonal antibodies specifically recognized full-length IRAS proteins in their native state by immunoblotting and immunoprecipitation. Monoclonal antibodies stained in a predominantly punctate cytoplasmic pattern when applied to IRAS-transfected HEK293 cells by indirect immunofluorescence assays and demonstrated excellent reactivity in flow immunocytometry. These monoclonal antibodies will provide powerful reagents for the further investigation of hIRAS protein functions

Interference in Autophagosome Fusion by Rare Earth Nanoparticles Disrupts Autophagic Flux and Regulation of an Interleukin-1β Producing Inflammasome

Engineered nanomaterials (ENMs) including multiwall carbon nanotubes (MWCNTs) and rare earth oxide (REO) nanoparticles, which are capable of activating the NLRP3 inflammasome and inducing IL-1β production, have the potential to cause chronic lung toxicity. Although it is known that lysosome damage is an upstream trigger in initiating this pro-inflammatory response, the same organelle is also an important homeostatic regulator of activated NLRP3 inflammasome complexes, which are engulfed by autophagosomes and then destroyed in lysosomes after fusion. Although a number of ENMs have been shown to induce autophagy, no definitive research has been done on the homeostatic regulation of the NLRP3 inflammasome during autophagic flux. We used a myeloid cell line (THP-1) and bone marrow derived macrophages (BMDM) to compare the role of autophagy in regulating inflammasome activation and IL-1β production by MWCNTs and REO nanoparticles. THP-1 cells express a constitutively active autophagy pathway and are also known to mimic NLRP3 activation in pulmonary macrophages. We demonstrate that, while activated NLRP3 complexes could be effectively removed by autophagosome fusion in cells exposed to MWCNTs, REO nanoparticles interfered in autophagosome fusion with lysosomes. This leads to the accumulation of the REO-activated inflammasomes, resulting in robust and sustained IL-1β production. The mechanism of REO nanoparticle interference in autophagic flux was clarified by showing that they disrupt lysosomal phosphoprotein function and interfere in the acidification that is necessary for lysosome fusion with autophagosomes. Binding of LaPO4 to the REO nanoparticle surfaces leads to urchin-shaped nanoparticles collecting in the lysosomes. All considered, these data demonstrate that in contradistinction to autophagy induction by some ENMs, specific materials such as REOs interfere in autophagic flux, thereby disrupting homeostatic regulation of activated NLRP3 complexes

AnyGPT: Unified Multimodal LLM with Discrete Sequence Modeling

We introduce AnyGPT, an any-to-any multimodal language model that utilizes discrete representations for the unified processing of various modalities, including speech, text, images, and music. AnyGPT can be trained stably without any alterations to the current large language model (LLM) architecture or training paradigms. Instead, it relies exclusively on data-level preprocessing, facilitating the seamless integration of new modalities into LLMs, akin to the incorporation of new languages. We build a multimodal text-centric dataset for multimodal alignment pre-training. Utilizing generative models, we synthesize the first large-scale any-to-any multimodal instruction dataset. It consists of 108k samples of multi-turn conversations that intricately interweave various modalities, thus equipping the model to handle arbitrary combinations of multimodal inputs and outputs. Experimental results demonstrate that AnyGPT is capable of facilitating any-to-any multimodal conversation while achieving performance comparable to specialized models across all modalities, proving that discrete representations can effectively and conveniently unify multiple modalities within a language model. Demos are shown in https://junzhan2000.github.io/AnyGPT.github.io/Comment: 28 pages, 16 figures, under review, work in progres

Supercapacitors (electrochemical capacitors)

International audienceRapid development of the technologies based on electric energy in the last decades have stimulated intensive research on efficient power sources. Electrochemical energy conversion and storage systems are based on Faradaic reactions (charge transfer) and electrostatic attraction of ions at the electrode/electrolyte interface. The latter might be an interesting solution for applications requiring moderate energy density, high power rates, and long cycle life. Electrochemical capacitors (ECs) store the charge in a physical manner, hence, their energy density is moderate. At the same time, the lack of electrochemical reactions ensures very high power and long cycle life compared to batteries. Activated carbons with their versatile properties (like specific surface area, well-developed and suitable porosity, heteroatoms in the graphene matrix) are the most popular materials in EC application. This chapter provides a comprehensive overview of the carbon-based materials recently developed, with special attention devoted to those obtained by biomass carbonization and activation. Electrochemical properties demonstrated by such carbons are discussed in respect to their physicochemical characteristic

Comprehensive molecular characterization of gastric adenocarcinoma

Gastric cancer is a leading cause of cancer deaths, but analysis of its molecular and clinical characteristics has been complicated by histological and aetiological heterogeneity. Here we describe a comprehensive molecular evaluation of 295 primary gastric adenocarcinomas as part of The Cancer Genome Atlas (TCGA) project. We propose a molecular classification dividing gastric cancer into four subtypes: tumours positive for Epstein–Barr virus, which display recurrent PIK3CA mutations, extreme DNA hypermethylation, and amplification of JAK2, CD274 (also known as PD-L1) and PDCD1LG2 (also knownasPD-L2); microsatellite unstable tumours, which show elevated mutation rates, including mutations of genes encoding targetable oncogenic signalling proteins; genomically stable tumours, which are enriched for the diffuse histological variant and mutations of RHOA or fusions involving RHO-family GTPase-activating proteins; and tumours with chromosomal instability, which show marked aneuploidy and focal amplification of receptor tyrosine kinases. Identification of these subtypes provides a roadmap for patient stratification and trials of targeted therapies

Multiplatform Analysis of 12 Cancer Types Reveals Molecular Classification within and across Tissues of Origin

Recent genomic analyses of pathologically-defined tumor types identify “within-a-tissue” disease subtypes. However, the extent to which genomic signatures are shared across tissues is still unclear. We performed an integrative analysis using five genome-wide platforms and one proteomic platform on 3,527 specimens from 12 cancer types, revealing a unified classification into 11 major subtypes. Five subtypes were nearly identical to their tissue-of-origin counterparts, but several distinct cancer types were found to converge into common subtypes. Lung squamous, head & neck, and a subset of bladder cancers coalesced into one subtype typified by TP53 alterations, TP63 amplifications, and high expression of immune and proliferation pathway genes. Of note, bladder cancers split into three pan-cancer subtypes. The multi-platform classification, while correlated with tissue-of-origin, provides independent information for predicting clinical outcomes. All datasets are available for data-mining from a unified resource to support further biological discoveries and insights into novel therapeutic strategies

The Impact of Large-scale Media on Online Marketing

This study aims to explore the relationship between large-scale media (referring to individuals or companies with a large number of followers on social media) and marketing, and to utilize the influence of large-scale media to increase product sales and brand exposure. Specifically, the paper first introduces the concept of centrality, including degree centrality, closeness centrality, and betweenness centrality, as well as their applications in social networks. Then, this study regards large-scale media as nodes in the social network and proposes the centrality concept of large-scale media. Next, this study analyzes the influence and propagation effects of large-scale media in the social network, thereby highlighting the importance of large-scale media in marketing activities. Finally, through empirical analysis, the paper verifies the positive impact of the centrality of large-scale media on product sales and brand exposure. The findings of this study suggest that marketing professionals need to pay more attention to the role and value of large-scale media, and strengthen cooperation with large-scale media in marketing strategies. At the same time, this study proposes suggestions for optimizing marketing strategies using centrality methods, such as finding and cooperating with large-scale media with greater influence, and establishing a relationship network with central nodes. These suggestions can help improve product sales and brand exposure, thus bringing better business benefits to enterprises

Genome-Wide Analysis of LRR-RLK Gene Family in Four <i>Gossypium</i> Species and Expression Analysis during Cotton Development and Stress Responses

Leucine-rich repeat receptor-like kinases (LRR-RLKs) have been reported to play important roles in plant growth, development, and stress responses. However, no comprehensive analysis of this family has been performed in cotton (Gossypium spp.), which is an important economic crop that suffers various stresses in growth and development. Here we conducted a comprehensive analysis of LRR-RLK family in four Gossypium species (Gossypium arboreum, Gossypium barbadense, Gossypium hirsutum, and Gossypium raimondii). A total of 1641 LRR-RLK genes were identified in the four Gossypium species involved in our study. The maximum-likelihood phylogenetic tree revealed that all the LRR-RLK genes were divided into 21 subgroups. Exon-intron organization structure of LRR-RLK genes kept relatively conserved within subfamilies and between Arabidopsis and Gossypium genomes. Notably, subfamilies XI and XII were found dramatically expanded in Gossypium species. Tandem duplication acted as an important mechanism in expansion of the Gossypium LRR-RLK gene family. Functional analysis suggested that Gossypium LRR-RLK genes were enriched for plant hormone signaling and plant-pathogen interaction pathways. Promoter analysis revealed that Gossypium LRR-RLK genes were extensively regulated by transcription factors (TFs), phytohormonal, and various environmental stimuli. Expression profiling showed that Gossypium LRR-RLK genes were widely involved in stress defense and diverse developmental processes including cotton fiber development and provides insight into potential functional divergence within and among subfamilies. Our study provided valuable information for further functional study of Gossypium LRR-RLK genes

Genome-Wide Analysis of Cotton Auxin Early Response Gene Families and Their Roles in Somatic Embryogenesis

Auxin is well known to regulate growth and development processes. Auxin early response genes serve as a critical component of auxin signaling and mediate auxin regulation of diverse physiological processes. In the present study, a genome-wide identification and comprehensive analysis of auxin early response genes were conducted in upland cotton. A total of 71 auxin response factor (ARF), 86 Auxin/Indole-3-Acetic Acid (Aux/IAA), 63 Gretchen Hagen3 (GH3), and 194 small auxin upregulated RNA (SAUR) genes were identified in upland cotton, respectively. Phylogenetic analysis revealed that the ARF, GH3, and SAUR families were likely subject to extensive evolutionary divergence between Arabidopsis and upland cotton, while the Aux/IAA family was evolutionary conserved. Expression profiles showed that the ARF, Aux/IAA, GH3, and SAUR family genes were extensively involved in embryogenic competence acquisition of upland cotton callus. The Aux/IAA family genes generally showed a higher expression level in the non-embryogenic callus (NEC) of highly embryogenic cultivar CCRI24 than that of recalcitrant cultivar CCRI12, which may be conducive to initializing the embryogenic transformation. Auxin early response genes were tightly co-expressed with most of the known somatic embryogenesis (SE) related genes, indicating that these genes may regulate upland cotton SE by interacting with auxin early response genes

Detectability of Repeated Airborne Laser Scanning for Mountain Landslide Monitoring

Multi-temporal airborne laser scanning (ALS) surveys have become a prime consideration for detecting landslide movements and evaluating landslide risk in mountain areas. The minimum elevation change (or detectability) that can be detected by repeated ALS surveys has become a critical threshold for landslide researchers and engineers to decide if ALS is a capable tool for detecting targeted landslides and arranging the minimum time span between two scans if ALS is a choice. The National Center for Airborne Laser Mapping (NCALM) at the University of Houston conducted three repeated ALS surveys at the Slumgullion landslide site in Colorado, U.S. over one week in July of 2015. These repeated ALS surveys provide valuable datasets for evaluating the vertical detectability of multi-temporal ALS surveys in a typical mountain area. According to this study, the difference of digital elevation models (DDEM) derived from ALS has the ability of detecting a minimum elevation change of 5 cm over flatter and moderately rugged terrain areas (slope &lt; 20 degrees) and a minimum of a 10-cm elevation change over rugged terrain areas (20 degrees &lt; slope &lt; 40 degrees). However, the DDEM values over highly rugged terrain areas (slope &gt; 40 degrees), such as cliff and landslide scarps, should be interpolated with caution. Global Navigation Satellite Systems (GNSS) and Terrestrial Laser Scanning (TLS) surveys were also performed at the middle portion of the landslide area for assessing the accuracy of ALS datasets. The accuracy of ALS varies from approximately one decimeter (~10 cm) to one foot (~30 cm) depending on the roughness of terrain surface and vegetation coverage (point density). The detectability and accuracy estimates of ALS measurements obtained from the case study could be used as a reference for estimating the performance of modern ALS in mountain areas with similar topography and vegetation coverage