Molecular epidemiology and genetic diversity of norovirus among hospitalized patients with acute gastroenteritis in Shandong, China, 2016-2018.

Norovirus (NoV) infection is a leading cause of acute gastroenteritis (AGE) for people of all ages. Here, we reported the molecular epidemiology and genetic diversity of NoVs among hospitalized patients with AGE between 2016 and 2018 in Shandong Province, China. Two thousand sixty-nine AGE patients from sentinel hospitals were enrolled. The stool samples were collected and tested for NoVs by real-time RT-PCR. The RNA-dependent RNA polymerase (RdRp) and capsid gene of 163 strains were amplified and sequenced for genotyping. Phylogenetic analyses and genomic characterization were conducted with the VP1 and RdRp region of the full genome sequences. Four hundred seventy two (21.76%) samples were NoV-positive. The positive rate in 2016 was higher than those of 2017 and 2018. We observed diverse NoV genotypes. GII.2[P16] emerged in January 2017 and became the dominant genotype between May and June 2017. Phylogenetic analyses showed that our GII.2[P16] genomes clustered in the SC1 in VP1 region, while they belonged to the Emerging GⅡ.P16 (2015-2017) clade in RdRp region. Our GⅡ.4 strains displayed two amino acid mutations, positions R297H and D372N, in epitope A of the VP1 region. Our study highlighted that NoV is an important pathogen of viral AGE in Shandong and, therefore, it is necessary to strengthen its surveillance.

Differential effects of climatic and non-climatic factors on the distribution of vegetation phenology trends on the Tibetan plateau.

The study of vegetation phenology changes is important because it is a sensitive indicator of climate change, affecting the exchange of carbon, energy and water fluxes between the land and the atmosphere. Previous studies have focused on the effects of climatic factors among environmental factors on vegetation phenology, thus the effects of non-climatic factors among environmental factors have not been well quantified. This study endeavors to scrutinize the spatiotemporal inconsistency in the start-of-season (SOS) and the end-of-season (EOS) on the Tibetan Plateau (TP) and to quantify the effects of environmental factors on phenology. To this end, the Moderate-resolution Imaging Spectroradiomater (MODIS) Normalized Difference Vegetation Index (NDVI) data from 2001 to 2018 and four common used methods were employed to extract SOS and EOS, and the site data was used to select the most appropriate phenology results. The Geodetector model was used to assess and measure the explanatory power of different environmental factors. The research results indicate that temperature exerts a more substantial impact on phenology than precipitation on TP. non-climatic factors such as longitude, latitude, and elevation are more influential in determining the distribution of phenological trends than climatic factors. Among these non-climatic factors, latitude has the most prominent effect on the trends of SOS. Furthermore, non-climatic factors exhibit a stronger effect on SOS, whereas EOS is more susceptible to climatic factors and less influenced by non-climatic factors. These discoveries bear great significance in comprehending the intricate outcomes of regional changes on vegetation phenology and enhancing phenology models.

Graph MADDPG with RNN for multiagent cooperative environment.

Multiagent systems face numerous challenges due to environmental uncertainty, with scalability being a critical issue. To address this, we propose a novel multi-agent cooperative model based on a graph attention network. Our approach considers the relationship between agents and continuous action spaces, utilizing graph convolution and recurrent neural networks to define these relationships. Graph convolution is used to define the relationship between agents, while recurrent neural networks define continuous action spaces. We optimize and model the multiagent system by encoding the interaction weights among agents using the graph neural network and the weights between continuous action spaces using the recurrent neural network. We evaluate the performance of our proposed model by conducting experimental simulations using a 3D wargame engine that involves several unmanned air vehicles (UAVs) acting as attackers and radar stations acting as defenders, where both sides have the ability to detect each other. The results demonstrate that our proposed model outperforms the current state-of-the-art methods in terms of scalability, robustness, and learning efficiency.

Discovery and Structure-Activity Relationship Studies of Novel Adenosine A1 Receptor-Selective Agonists.

A series of benzyloxy and phenoxy derivatives of the adenosine receptor agonists N6-cyclopentyl adenosine (CPA) and N6-cyclopentyl 5'-N-ethylcarboxamidoadenosine (CP-NECA) were synthesized, and their potency and selectivity were assessed. We observed that the most potent were the compounds with a halogen in the meta position on the aromatic ring of the benzyloxy- or phenoxycyclopentyl substituent. In general, the NECA-based compounds displayed greater A1R selectivity than the adenosine-based compounds, with N6-2-(3-bromobenzyloxy)cyclopentyl-NECA and N6-2-(3-methoxyphenoxy)cyclopentyl-NECA showing ∼1500-fold improved A1R selectivity compared to NECA. In addition, we quantified the compounds' affinity and kinetics of binding at both human and rat A1R using a NanoBRET binding assay and found that the halogen substituent in the benzyloxy- or phenoxycyclopentyl moiety seems to confer high affinity for the A1R. Molecular modeling studies suggested a hydrophobic subpocket as contributing to the A1R selectivity displayed. We believe that the identified selective potent A1R agonists are valuable tool compounds for adenosine receptor research.

Selective activation of Gαob by an adenosine A1 receptor agonist elicits analgesia without cardiorespiratory depression.

The development of therapeutic agonists for G protein-coupled receptors (GPCRs) is hampered by the propensity of GPCRs to couple to multiple intracellular signalling pathways. This promiscuous coupling leads to numerous downstream cellular effects, some of which are therapeutically undesirable. This is especially the case for adenosine A1 receptors (A1Rs) whose clinical potential is undermined by the sedation and cardiorespiratory depression caused by conventional agonists. We have discovered that the A1R-selective agonist, benzyloxy-cyclopentyladenosine (BnOCPA), is a potent and powerful analgesic but does not cause sedation, bradycardia, hypotension or respiratory depression. This unprecedented discrimination between native A1Rs arises from BnOCPA's unique and exquisitely selective activation of Gob among the six Gαi/o subtypes, and in the absence of ß-arrestin recruitment. BnOCPA thus demonstrates a highly-specific Gα-selective activation of the native A1R, sheds new light on GPCR signalling, and reveals new possibilities for the development of novel therapeutics based on the far-reaching concept of selective Gα agonism.

Phase separation of OCT4 controls TAD reorganization to promote cell fate transitions.

Topological-associated domains (TADs) are thought to be relatively stable across cell types, although some TAD reorganization has been observed during cellular differentiation. However, little is known about the mechanisms through which TAD reorganization affects cell fate or how master transcription factors affect TAD structures during cell fate transitions. Here, we show extensive TAD reorganization during somatic cell reprogramming, which is correlated with gene transcription and changes in cellular identity. Manipulating TAD reorganization promotes reprogramming, and the dynamics of concentrated chromatin loops in OCT4 phase separated condensates contribute to TAD reorganization. Disrupting OCT4 phase separation attenuates TAD reorganization and reprogramming, which can be rescued by fusing an intrinsically disordered region (IDR) to OCT4. We developed an approach termed TAD reorganization-based multiomics analysis (TADMAN), which identified reprogramming regulators. Together, these findings elucidate a role and mechanism of TAD reorganization, regulated by OCT4 phase separation, in cellular reprogramming.

Hippo-YAP signaling controls lineage differentiation of mouse embryonic stem cells through modulating the formation of super-enhancers.

Hippo-YAP signaling pathway functions in early lineage differentiation of pluripotent stem cells, but the detailed mechanisms remain elusive. We found that knockout (KO) of Mst1 and Mst2, two key components of the Hippo signaling in mouse embryonic stem cells (ESCs), resulted in a disruption of differentiation into mesendoderm lineage. To further uncover the underlying regulatory mechanisms, we performed a series of ChIP-seq experiments with antibodies against YAP, ESC master transcription factors and some characterized histone modification markers as well as RNA-seq assays using wild type and Mst KO samples at ES and day 4 embryoid body stage respectively. We demonstrate that YAP is preferentially co-localized with super-enhancer (SE) markers such as Nanog, Sox2, Oct4 and H3K27ac in ESCs. The hyper-activation of nuclear YAP in Mst KO ESCs facilitates the binding of Nanog, Sox2 and Oct4 as well as H3K27ac modification at the loci where YAP binds. Moreover, Mst depletion results in novel SE formation and enhanced liquid-liquid phase-separated Med1 condensates on lineage associated genes, leading to the upregulation of these genes and the distortion of ESC differentiation. Our study reveals a novel mechanism on how Hippo-YAP signaling pathway dictates ESC lineage differentiation.

Removal of organic herbicides from aqueous solution by ionic liquid modified chitosan/metal-organic framework composite.

The novel ILCS/U-X powder materials were fabricated by depositing UiO-66 on ionic liquid modified chitosan, and different doping ratio materials were used to adsorb 2,4-dichlorophenoxyacetic acid in aqueous solution. The samples were characterized by X-ray powder diffraction, Fourier transform infra-red, X-ray photoelectron spectroscopy, Scanning electron microscopy, Brunauer-Emmett-Teller, Barrette-Joyner-Halenda, Thermal gravimetric analyzer, Energy dispersive spectrometer and Zeta potential. Adsorption experiments revealed that temperature and pH have a great influence on adsorption, and all adsorbents have the highest adsorption at low temperature and weak acid. The dependence of ILCS/U-X on pseudo-second order model and Temkin model was observed. Compared to other ratios, the Micro-doped ILCS/U-10 has the largest adsorption capacity and can quickly complete adsorption within 60 min. ILCS/U-10 also has good stability and can be recycled many times. Hydrogen bonding and electrostatic interaction are the two most important forces that dominate adsorption.

Dynamic Changes of NDVI in the Growing Season of the Tibetan Plateau During the Past 17 Years and Its Response to Climate Change.

The fragile alpine vegetation in the Tibetan Plateau (TP) is very sensitive to environmental changes, making TP one of the hotspots for studying the response of vegetation to climate change. Existing studies lack detailed description of the response of vegetation to different climatic factors using the method of multiple nested time series analysis and the method of grey correlation analysis. In this paper, based on the Normalized Difference Vegetation Index (NDVI) of TP in the growing season calculated from the MOD09A1 data product of Moderate-resolution Imaging Spectroradiometer (MODIS), the method of multiple nested time series analysis is adopted to study the variation trends of NDVI in recent 17 years, and the lag time of NDVI to climate change is analyzed using the method of Grey Relational Analysis (GRA). Finally, the characteristics of temporal and spatial differences of NDVI to different climate factors are summarized. The results indicate that: (1) the spatial distribution of NDVI values in the growing season shows a trend of decreasing from east to west, and from north to south, with a change rate of -0.13/10° E and -0.30/10° N, respectively. (2) From 2001 to 2017, the NDVI in the TP shows a slight trend of increase, with a growth rate of 0.01/10a. (3) The lag time of NDVI to air temperature is not obvious, while the NDVI response lags behind cumulative precipitation by zero to one month, relative humidity by two months, and sunshine duration by three months. (4) The effects of different climatic factors on NDVI are significantly different with the increase of the study period.