Early Detection of the Emerging SARS-CoV-2 BA.2.86 Lineage Through Wastewater Surveillance Using a Mediator Probe PCR Assay - Shenzhen City, Guangdong Province, China, 2023.

Introduction: The emergence of the new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron sublineage, BA.2.86, has sparked global public health concerns for its potential heightened transmissibility and immune evasion. Utilizing data from Shenzhen's city-wide wastewater surveillance system, we highlight the presence of the BA.2.86 lineage in Shenzhen. Methods: A mediator probe polymerase chain reaction (PCR) assay was developed to detect the BA.2.86 lineage in wastewater by targeting a specific mutation (Spike: A264D). Between September 19 and December 10, 2023, 781 wastewater samples from 38 wastewater treatment plants (WWTPs) and 9 pump stations in ten districts of Shenzhen were examined. Through multiple short-amplicon sequencing, three positive samples were identified. Results: The BA.2.86 lineage was identified in the wastewater of Futian and Nanshan districts in Shenzhen on December 2, 2023. From December 2 to 10, a total of 21 BA.2.86-positive wastewater samples were found across 6 districts (Futian, Nanshan, Longhua, Baoan, Longgang, and Luohu) in Shenzhen. The weighted average viral load of the BA.2.86 lineage in Shenzhen's wastewater was 43.5 copies/L on December 2, increased to 219.8 copies/L on December 4, and then decreased to approximately 100 copies/L on December 6, 8, and 10. Conclusions: The mediator probe PCR assay, designed for swift detection of low viral concentrations of the BA.2.86 lineage in wastewater samples, shows promise for detecting different SARS-CoV-2 variants. Wastewater surveillance could serve as an early detection system for promptly identifying specific SARS-CoV-2 variants as they emerge.

SMYD2-Methylated PPARγ Facilitates Hypoxia-Induced Pulmonary Hypertension by Activating Mitophagy.

BACKGROUND: Hyperproliferation of pulmonary arterial smooth muscle cells (PASMCs) and consequent pulmonary vascular remodeling are the crucial pathological features of pulmonary hypertension (PH). Protein methylation has been shown to be critically involved in PASMC proliferation and PH, but the underlying mechanism remains largely unknown. METHODS: PH animal models were generated by treating mice/rats with chronic hypoxia for 4 weeks. SMYD2-vTg mice (vascular smooth muscle cell-specific suppressor of variegation, enhancer of zeste, trithorax and myeloid Nervy DEAF-1 domain-containing protein 2 transgenic) or wild-type rats and mice treated with LLY-507 were used to investigate the function of SMYD2 (suppressor of variegation, enhancer of zeste, trithorax and myeloid Nervy DEAF-1 domain-containing protein 2) on PH development in vivo. Primary cultured rat PASMCs with SMYD2 knockdown or overexpression were used to explore the effects of SMYD2 on proliferation and to decipher the underlying mechanism. RESULTS: We demonstrated that the expression of the lysine methyltransferase SMYD2 was upregulated in the smooth muscle cells of pulmonary arteries from patients with PH and hypoxia-exposed rats/mice and in the cytoplasm of hypoxia-induced rat PASMCs. More importantly, targeted inhibition of SMYD2 by LLY-507 significantly attenuated hypoxia-induced pulmonary vascular remodeling and PH development in both male and female rats in vivo and reduced rat PASMC hyperproliferation in vitro. In contrast, SMYD2-vTg mice exhibited more severe PH phenotypes and related pathological changes than nontransgenic mice after 4 weeks of chronic hypoxia treatment. Furthermore, SMYD2 overexpression promoted, while SMYD2 knockdown suppressed, the proliferation of rat PASMCs by affecting the cell cycle checkpoint between S and G2 phases. Mechanistically, we revealed that SMYD2 directly interacted with and monomethylated PPARγ (peroxisome proliferator-activated receptor gamma) to inhibit the nuclear translocation and transcriptional activity of PPARγ, which further promoted mitophagy to facilitate PASMC proliferation and PH development. Furthermore, rosiglitazone, a PPARγ agonist, largely abolished the detrimental effects of SMYD2 overexpression on PASMC proliferation and PH. CONCLUSIONS: Our results demonstrated that SMYD2 monomethylates nonhistone PPARγ and inhibits its nuclear translocation and activation to accelerate PASMC proliferation and PH by triggering mitophagy, indicating that targeting SMYD2 or activating PPARγ are potential strategies for the prevention of PH.

Association between social capital and utilization of essential public health services among elderly migrants: a multilevel logistic study based on the 2017 China migrant dynamic survey (CMDS).

BACKGROUND: As the number of elderly migrants in China continues to grow, it is necessary to pay closer attention to their health and health services. Some studies have confirmed that social capital plays a significant role in the utilization of health services. Therefore, an in-depth exploration of the relationship between social capital and the utilization of essential public health services (EPHS) by elderly migrants will not only contribute to improving their overall health but also facilitate a more balanced development of public health service system in China. METHODS: Based on the cross-sectional data from the 2017 China Migrants Dynamic Survey (CMDS), this study examined the impact of social capital on the utilization of EPHS among elderly migrants. We evaluated social capital at two distinct levels: the individual and the community, and considered two dimensions of social capital: structural social capital (SSC) and cognitive social capital (CSC). The study aimed to delve into the impact of these forms of social capital on the utilization of EPHS among elderly migrants, and whether the migration range moderates this impact by multilevel logistic regression analysis. RESULTS: A total of 5,728 migrant elderly individuals were selected. The health records establishment rate and health education acceptance rate were approximately 33.0% and 58.6%, respectively. Social capital influenceed the utilization of EPHS among elderly migrants. Specifically, individual-level SSC and CSC have impacts on both the establishment of health records (OR = 1.598, 95%CI 1.366-1.869; OR = 1.705, 95%CI 1.433-2.028) and the acceptance of health education (OR = 1.345, 95%CI 1.154-1.567; OR = 2.297, 95%CI 1.906-2.768) among elderly migrants, while community-level SSC only affected the acceptance of health education (OR = 3.838, 95%CI 1.328-11.097). There were significant differences in individual-level SSC, health records, and health education among different migration range subgroups among elderly migrants. Migration range moderated the effect of social capital on the utilization of EPHS, crossing provinces could weaken the relationship between SSC and health education. CONCLUSIONS: Social capital is associated with a higher utilization rate of EPHS among elderly migrants. It is necessary to encourage them to actively participate in social activities, strengthen public services and infrastructure construction in the area, and improve their sense of belonging and identity.

RD-OpenMax: Rethinking OpenMax for Robust Realistic Open-Set Recognition.

Open-set recognition (OSR) toward a practical open-world setting has attracted increasing research attention in recent years. However, existing OSR settings are either too idealized or focus on specific scenes such as long-tailed distribution and few-shot samples, which fail to capture the complexity of real-world scenarios. In this article, we propose a realistic OSR (ROSR) setting that covers a diverse range of challenging and real-world scenarios, including fine-grained cases with strong semantic correlation and a large number of species, few-shot samples, long-tailed sample distribution, dynamic inputs (e.g., images, spatio-temporal, and multimodal signals) and cross-domain adaptation. In particular, we rethink the simple and basic OpenMax for the ROSR setting and introduce a novel method, regularized discriminative OpenMax (RD-OpenMax), to handle the challenges in the ROSR setting. RD-OpenMax improves upon the basic OpenMax approach by introducing a covariance attention-based covariance pooling (CACP) module as a global aggregation step before the deep architecture's classifier. This module explores rich statistical information on features and provides discriminative distance scores for OpenMax. To address the instability of extreme value theory (EVT) estimation due to insufficient training samples under few-shot and long-tailed scenarios, we propose a regularized EVT (REVT) method based on Monte Carlo sampling to recalibrate the distribution of distance scores. As such, our RD-OpenMax performs a REVT model of distance scores generated by discriminative CACP representations to distinguish known classes and recognize unknown ones effectively and robustly. Extensive experiments are conducted on more than ten visual benchmarks across several scenarios, and the empirical comparisons show that the ROSR setting challenges existing state-of-the-art OSR approaches. Moreover, our RD-OpenMax clearly outperforms its counterparts under the ROSR setting while performing favorably against state-of-the-arts under the traditional OSR setting.

Transcriptome analysis and functional validation reveal the novel role of LhCYCL in axillary bud development in hybrid Liriodendron.

Shoot branching significantly influences yield and timber quality in woody plants, with hybrid Liriodendron being particularly valuable due to its rapid growth. However, understanding of the mechanisms governing shoot branching in hybrid Liriodendron remains limited. In this study, we systematically examined axillary bud development using morphological and anatomical approaches and selected four distinct developmental stages for an extensive transcriptome analysis. A total of 9,449 differentially expressed genes have been identified, many of which are involved in plant hormone signal transduction pathways. Additionally, we identified several transcription factors downregulated during early axillary bud development, including a noteworthy gene annotated as CYC-like from the TCP TF family, which emerged as a strong candidate for modulating axillary bud development. Quantitative real-time polymerase chain reaction results confirmed the highest expression levels of LhCYCL in hybrid Liriodendron axillary buds, while histochemical ß-glucuronidase staining suggested its potential role in Arabidopsis thaliana leaf axil development. Ectopic expression of LhCYCL in A. thaliana led to an increase of branches and a decrease of plant height, accompanied by altered expression of genes involved in the plant hormone signaling pathways. This indicates the involvement of LhCYCL in regulating shoot branching through plant hormone signaling pathways. In summary, our results emphasize the pivotal role played by LhCYCL in shoot branching, offering insights into the function of the CYC-like gene and establishing a robust foundation for further investigations into the molecular mechanisms governing axillary bud development in hybrid Liriodendron.

Design, Synthesis, and Biological Evaluation of a Novel NIK Inhibitor with Anti-Inflammatory and Hepatoprotective Effects for Sepsis Treatment.

NIK plays a crucial role in the noncanonical NF-κB signaling pathway associated with diverse inflammatory and autoimmune diseases. Our study presents compound 54, a novel NIK inhibitor, designed through a structure-based scaffold-hopping approach from the previously identified B022. Compound 54 demonstrates remarkable selectivity and potency against NIK both in vitro and in vivo, effectively suppressing pro-inflammatory cytokines and nitric oxide production. In mouse models, compound 54 protected against LPS-induced systemic sepsis, reducing AST, ALT, and AKP liver injury markers. Additionally, it also attenuates sepsis-induced lung and kidney damage. Mechanistically, compound 54 blocks the noncanonical NF-κB signaling pathway by targeting NIK, preventing p100 to p52 processing. This work reveals a novel class of NIK inhibitors with significant potential for sepsis therapy.

Comprehensive insights into potential roles of purinergic P2 receptors on diseases: Signaling pathways involved and potential therapeutics.

BACKGROUND: Purinergic P2 receptors, which can be divided into ionotropic P2X receptors and metabotropic P2Y receptors, mediate cellular signal transduction of purine or pyrimidine nucleoside triphosphates and diphosphate. Based on the wide expression of purinergic P2 receptors in tissues and organs, their significance in homeostatic maintenance, metabolism, nociceptive transmission, and other physiological processes is becoming increasingly evident, suggesting that targeting purinergic P2 receptors to regulate biological functions and signal transmission holds significant promise for disease treatment. AIM OF REVIEW: This review highlights the detailed mechanisms by which purinergic P2 receptors engage in physiological and pathological progress, as well as providing prospective strategies for discovering clinical drug candidates. KEY SCIENTIFIC CONCEPTS OF REVIEW: The purinergic P2 receptors regulate complex signaling and molecular mechanisms in nervous system, digestive system, immune system and as a result, controlling physical health states and disease progression. There has been a significant rise in research and development focused on purinergic P2 receptors, contributing to an increased number of drug candidates in clinical trials. A few influential pioneers have laid the foundation for advancements in the evaluation, development, and of novel purinergic P2 receptors modulators, including agonists, antagonists, pharmaceutical compositions and combination strategies, despite the different scaffolds of these drug candidates. These advancements hold great potential for improving therapeutic outcomes by specifically targeting purinergic P2 receptors.

CCP-GNN: Competitive Covariance Pooling for Improving Graph Neural Networks.

Graph neural networks (GNNs) have advanced graph classification tasks, where a global pooling to generate graph representations by summarizing node features plays a critical role in the final performance. Most of the existing GNNs are built with a global average pooling (GAP) or its variants, which however, take no full consideration of node specificity while neglecting rich statistics inherent in node features, limiting classification performance of GNNs. Therefore, this article proposes a novel competitive covariance pooling (CCP) based on observation of graph structures, i.e., graphs generally can be identified by a (small) key part of nodes. To this end, our CCP generates node-level second-order representations to explore rich statistics inherent in node features, which are fed to a competitive-based attention module for effectively discovering key nodes through learning node weights. Subsequently, our CCP aggregates node-level second-order representations in conjunction with node weights by summation to produce a covariance representation for each graph, while an iterative matrix normalization is introduced to consider geometry of covariances. Note that our CCP can be flexibly integrated with various GNNs (namely CCP-GNN) to improve the performance of graph classification with little computational cost. The experimental results on seven graph-level benchmarks show that our CCP-GNN is superior or competitive to state-of-the-arts. Our code is available at https://github.com/Jillian555/CCP-GNN.

[Genetic characterization and drug resistance analysis of Salmonella Kentucky ST314 in Shenzhen in 2010-2021].

OBJECTIVE: To understand the prevalence, genetic characteristics and drug resistance features of Salmonella Kentucky ST314 in Shenzhen. METHODS: Whole genome sequencing of 14 strains of Salmonella Kentucky ST314 collected from 2010-2021 by the Foodborne Disease Surveillance Network of Shenzhen Center for Disease Control and Prevention for phylogenetic evolutionary analysis, drug resistance gene and plasmid detection; drug susceptibility experiments were performed by micro-broth dilution method. RESULTS: A total of 57 strains of Salmonella Kentucky were collected from the foodborne disease surveillance network, 14 of which were ST314. The Shenzhen isolates were clustered with isolates from Southeast Asian countries such as Vietnam and Thailand on clade 314.2, and the single nucleotide polymorphism distance between local strains in Shenzhen was large, indicating dissemination. In this study, a total of 17 drug resistance genes/mutations in 9 categories were detected in the genome of Salmonella Kentucky ST314, carrying 3 extended spectrum beta-lactamases(ESBLs), including bla_(CTX-M-24)(14.3%, 2/14), bla_(CTX-M-55)(7.1%, 1/14), and bla_(CTX-M-130)(14.3%, 2/14), all located on plasmids. Regarding quinolone resistance factors, two plasmid-mediated quinolone resistance(PMQR) genes were identified in the genome: qnrB6(71.4%, 10/14) and aac(6')Ib-cr(78.6%, 11/14), a quinolone resistance quinolone resistance-determining regions(QRDR) mutation T57 S(100%, 14/14). The multi-drug resistance rate of Salmonella Kentucky ST314 in Shenzhen was 92.86%(13/14)with the highest rate of resistance to tetracycline and cotrimoxazole(100%, 14/14), followed by chloramphenicol(92.86%, 13/14), cefotaxime and ampicillin(78.57%, 11/14), ciprofloxacin and nalidixic acid(71.43%, 10/14), and ampicillin-sulbactam had the lowest resistance rate(21.43%, 3/14). CONCLUSION: ST314 is the second most prevalent ST type among Salmonella Kentucky in Shenzhen, mainly isolated from food, especially poultry; phylogenetic analysis suggests that ST314 is a disseminated infection and the genome shows a highly genetically conserved phenotype. Drug resistance of Salmonella Kentucky ST314 is very serious, especially QRDR mutation, PMQR gene co-mediated quinolone resistance and plasmid-mediated cephalosporin resistance are prominent and deserve extensive attention.

Multiview Deep Subspace Clustering Networks.

Multiview subspace clustering aims to discover the inherent structure of data by fusing multiple views of complementary information. Most existing methods first extract multiple types of handcrafted features and then learn a joint affinity matrix for clustering. The disadvantage of this approach lies in two aspects: 1) multiview relations are not embedded into feature learning and 2) the end-to-end learning manner of deep learning is not suitable for multiview clustering. Even when deep features have been extracted, it is a nontrivial problem to choose a proper backbone for clustering on different datasets. To address these issues, we propose the multiview deep subspace clustering networks (MvDSCNs), which learns a multiview self-representation matrix in an end-to-end manner. The MvDSCN consists of two subnetworks, i.e., a diversity network (Dnet) and a universality network (Unet). A latent space is built using deep convolutional autoencoders, and a self-representation matrix is learned in the latent space using a fully connected layer. Dnet learns view-specific self-representation matrices, whereas Unet learns a common self-representation matrix for all views. To exploit the complementarity of multiview representations, the Hilbert-Schmidt independence criterion (HSIC) is introduced as a diversity regularizer that captures the nonlinear, high-order interview relations. Because different views share the same label space, the self-representation matrices of each view are aligned to the common one by universality regularization. The MvDSCN also unifies multiple backbones to boost clustering performance and avoid the need for model selection. Experiments demonstrate the superiority of the MvDSCN.

A hybrid denoising approach for PPG signals utilizing variational mode decomposition and improved wavelet thresholding.

BACKGROUND: Photoplethysmography (PPG) signals are sensitive to motion-induced interference, leading to the emergence of motion artifacts (MA) and baseline drift, which significantly affect the accuracy of PPG measurements. OBJECTIVE: The objective of our study is to effectively eliminate baseline drift and high-frequency noise from PPG signals, ensuring that the signal's critical frequency components remain within the range of 1 ∼ 10 Hz. METHODS: This paper introduces a novel hybrid denoising method for PPG signals, integrating Variational Mode Decomposition (VMD) with an improved wavelet threshold function. The method initially employs VMD to decompose PPG signals into a set of narrowband intrinsic mode function (IMF) components, effectively removing low-frequency baseline drift. Subsequently, an improved wavelet thresholding algorithm is applied to eliminate high-frequency noise, resulting in denoised PPG signals. The effectiveness of the denoising method was rigorously assessed through a comprehensive validation process. It was tested on real-world PPG measurements, PPG signals generated by the Fluke ProSim™ 8 Vital Signs Simulator with synthesized noise, and extended to the MIMIC-III waveform database. RESULTS: The application of the improved threshold function let to a substantial 11.47% increase in signal-to-noise ratio (SNR) and an impressive 26.75% reduction in root mean square error (RMSE) compared to the soft threshold function. Furthermore, the hybrid denoising method improved SNR by 15.54% and reduced RMSE by 37.43% compared to the improved threshold function. CONCLUSION: This study proposes an effective PPG denoising algorithm based on VMD and an improved wavelet threshold function, capable of simultaneously eliminating low-frequency baseline drift and high-frequency noise in PPG signals while faithfully preserving their morphological characteristics. This advancement establishes the foundation for time-domain feature extraction and model development in the domain of PPG signal analysis.

Genome-wide investigation of SQUAMOSA promoter binding protein-like genes in Liriodendron and functional characterization of LcSPL2.

The plant-specific SQUAMOSA promoter-binding protein-like (SPL) transcription factors play a pivotal role in various developmental processes, including leaf morphogenesis and vegetative to reproductive phase transition. Liriodendron chinense and Liriodendron tulipifera are widely used in landscaping due to their tulip-like flowers and peculiar leaves. However, the SPL gene family in Liriodendron has not been identified and systematically characterized. We systematically identified and characterized the SPL family members in Liriodendron, including phylogeny, gene structure and syntenic analyses. Subsequently, we quantified the expression patterns of LcSPLs across various tissue sites through transcription-quantitative polymerase chain reaction (RT-qPCR) assays and identified the target gene, LcSPL2. Finally, we characterized the functions of LcSPL2 via ectopic transformation. Altogether, 17 LcSPL and 18 LtSPL genes were genome-widely identified in L. chinense and L. tulipifera, respectively. All the 35 SPLs were grouped into 9 clades. Both species had three SPL gene pairs arising from segmental duplication events, and the LcSPLs displayed high collinearity with the L. tulipifera genome. RT-qPCR assays showed that SPL genes were differentially expressed in different tissues, especially. Because LcSPL2 is highly expressed in pistils and leaves, it was selected to describe the SPL gene family of L. chinense by ectopic expression. We showed that overexpression of LcSPL2 in Arabidopsis thaliana resulted in earlier flowering and fewer rosette leaves. Moreover, we observed that overexpression of LcSPL2 in A. thaliana up-regulated the expression levels of four genes related to flower development. This study identified SPL genes in Liriodendron and characterized the function of LcSPL2 in advancing flower development.

Layer-Specific Knowledge Distillation for Class Incremental Semantic Segmentation.

Recently, class incremental semantic segmentation (CISS) towards the practical open-world setting has attracted increasing research interest, which is mainly challenged by the well-known issue of catastrophic forgetting. Particularly, knowledge distillation (KD) techniques have been widely studied to alleviate catastrophic forgetting. Despite the promising performance, existing KD-based methods generally use the same distillation schemes for different intermediate layers to transfer old knowledge, while employing manually tuned and fixed trade-off weights to control the effect of KD. These KD-based methods take no consideration of feature characteristics from different intermediate layers, limiting the effectiveness of KD for CISS. In this paper, we propose a layer-specific knowledge distillation (LSKD) method to assign appropriate knowledge schemes and weights for various intermediate layers by considering feature characteristics, aiming to further explore the potential of KD in improving the performance of CISS. Specifically, we present a mask-guided distillation (MD) to alleviate the background shift on semantic features, which performs distillation by masking the features affected by the background. Furthermore, a mask-guided context distillation (MCD) is presented to explore global context information lying in high-level semantic features. Based on them, our LSKD assigns different distillation schemes according to feature characteristics. To adjust the effect of layer-specific distillation adaptively, LSKD introduces a regularized gradient equilibrium method to learn dynamic trade-off weights. Additionally, our LSKD makes an attempt to simultaneously learn distillation schemes and trade-off weights of different layers by developing a bi-level optimization method. Extensive experiments on widely used Pascal VOC 12 and ADE20K show our LSKD clearly outperforms its counterparts while achieving state-of-the-art results.

Targeting P2Y14R protects against necroptosis of intestinal epithelial cells through PKA/CREB/RIPK1 axis in ulcerative colitis.

Purinergic signaling plays a causal role in the pathogenesis of inflammatory bowel disease. Among purinoceptors, only P2Y14R is positively correlated with inflammatory score in mucosal biopsies of ulcerative colitis patients, nevertheless, the role of P2Y14R in ulcerative colitis remains unclear. Here, based on the over-expressions of P2Y14R in the intestinal epithelium of mice with experimental colitis, we find that male mice lacking P2Y14R in intestinal epithelial cells exhibit less intestinal injury induced by dextran sulfate sodium. Mechanistically, P2Y14R deletion limits the transcriptional activity of cAMP-response element binding protein through cAMP/PKA axis, which binds to the promoter of Ripk1, inhibiting necroptosis of intestinal epithelial cells. Furthermore, we design a hierarchical strategy combining virtual screening and chemical optimization to develop a P2Y14R antagonist HDL-16, which exhibits remarkable anti-colitis effects. Summarily, our study elucidates a previously unknown mechanism whereby P2Y14R participates in ulcerative colitis, providing a promising therapeutic target for inflammatory bowel disease.

Rationally designed nanotrap structures for efficient separation of rare earth elements over a single step.

Extracting rare earth elements (REEs) from wastewater is essential for the growth and an eco-friendly sustainable economy. However, it is a daunting challenge to separate individual rare earth elements by their subtle differences. To overcome this difficulty, we report a unique REE nanotrap that features dense uncoordinated carboxyl groups and triazole N atoms in a two-fold interpenetrated metal-organic framework (named NCU-1). Notably, the synergistic effect of suitable pore sizes and REE nanotraps in NCU-1 is highly responsive to the size variation of rare-earth ions and shows high selectivity toward light REE. As a proof of concept, Pr/Lu and Nd/Er are used as binary models, which give a high separation factor of SFPr/Lu = 796 and SFNd/Er = 273, demonstrating highly efficient separation over a single step. This ability achieves efficient and selective extraction and separation of REEs from mine tailings, establishing this platform as an important advance for sustainable obtaining high-purity REEs.

Calcium sensing receptor: A promising therapeutic target in pulmonary hypertension.

Pulmonary hypertension (PH) is characterized by elevation of pulmonary arterial pressure and pulmonary vascular resistance. The increased pulmonary arterial pressure and pulmonary vascular resistance due to sustained pulmonary vasoconstriction and pulmonary vascular remodeling can lead to right heart failure and eventual death. A rise in intracellular Ca2+ concentration ([Ca2+]i) and enhanced pulmonary arterial smooth muscle cells (PASMCs) proliferation contribute to pulmonary vasoconstriction and pulmonary vascular remodeling. Recent studies demonstrated that extracellular calcium sensing receptor (CaSR) as a G-protein coupled receptor participates in [Ca2+]i increase induced by hypoxia in the experimental animals of PH and in PH patients. Pharmacological blockade or gene knockout of CaSR significantly attenuates the development of PH. This review will aim to discuss and update the pathogenicity of CaSR attributed to onset and progression in PH.

TRIM14 suppressed the progression of NSCLC via hexosamine biosynthesis pathway.

Tripartite Motif 14 (TRIM14) is an oncoprotein that belongs to the E3 ligase TRIM family, which is involved in the progression of various tumors except for non-small cell lung carcinoma (NSCLC). However, little is currently known regarding the function and related mechanisms of TRIM14 in NSCLC. Here, we found that the TRIM14 protein was downregulated in lung adenocarcinoma tissues compared with the adjacent tissues, which can suppress tumor cell proliferation and migration both in vitro and in vivo. Moreover, TRIM14 can directly bind to glutamine fructose-6-phosphate amidotransferase 1 (GFAT1), which in turn results in the degradation of GFAT1 and reduced O-glycosylation levels. GFAT1 is a key enzyme in the rate-limiting step of the hexosamine biosynthetic pathway (HBP). Replenishment of N-acetyl-d-glucosamine can successfully reverse the inhibitory effect of TRIM14 on the NSCLC cell growth and migration as expected. Collectively, our data revealed that TRIM14 suppressed NSCLC cell proliferation and migration through ubiquitination and degradation of GFAT1, providing a new regulatory role for TRIM14 on HBP.

The identification and functional characterization of the LcMCT gene from Liriodendron chinense reveals its potenatial role in carotenoids biosyanthesis.

Terpenoids are not only important component of plant floral scent, but also indispensable elements in the formation of floral color. The petals of Liriodendron chinense are rich in tetraterpene carotenoids and release large amounts of volatile monoterpene and sesquiterpene compounds during full blooming stage. However, the mechanism of terpenoid synthesis is not clear in L. chinense. In this study, we identified a LcMCT gene and characterized its potential function in carotenoids biosynthesis. A total of 2947 up-regulated differentially expressed genes (DEGs) were discerned from the transcriptomic data of L. chinense petals, with a significant enrichment of DEGs related to plant hormone signal transduction and terpenoid backbone biosynthesis. After comprehensive analysis on these DEGs, the LcMCT gene was selected for subsequent function characterization. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) results showed that LcMCT was expressed at the highest level in the petals during full blooming stage, suggesting a possible role in carotenoids biosynthesis and volatile terpenoid biosynthesis. Subcellular localization showed that the LcMCT protein was localized in the chloroplast. Overexpression of LcMCT in Arabidopsis thaliana affected the expression levels of MEP pathway genes. Moreover, the MCT enzyme activity and carotenoids contents in transgenic A. thaliana were increased by 69.27% and 15.57%, respectively. These results suggest that LcMCT promotes the biosynthesis of terpenoid precursors via the MEP pathway. Our work lays a foundation for exploring the mechanism of terpenoid synthesis in L. chinense.

Genome-wide identification of GROWTH-REGULATING FACTORs in Liriodendron chinense and functional characterization of LcGRF2 in leaf size regulation.

GROWTH-REGULATING FACTORs (GRFs) play a pivotal role in the regulation of leaf size in plants and have been widely reported in plants. However, their specific functions in leaf size regulation in Liriodendron chinense remains unclear. Therefore, in this study, we identified GRF genes on a genome-wide scale in L. chinense to characterize the roles of LcGRFs in regulating leaf size. A total of nine LcGRF genes were identified, and these genes exhibited weak expression in mature leaves but strong expression in shoot apex. Notably, LcGRF2 exhibited the highest expression level in the shoot apex of L. chinense. Further RT-qPCR assay revealed that the expression level of LcGRF2 gradually decreased along with the leaf development process, and also displayed a gradient along the leaf proximo-distal and medio-lateral axes. Furthermore, overexpression of LcGRF2 in Arabidopsis thaliana resulted in increased leaf size, and significantly up-regulated the expression of genes involved in cell division like AtCYCD3;1, AtKNOLLE, and AtCYCB1;1, indicating that LcGRF2 may influence leaf size by promoting cell proliferation. This work contributes to a better understanding of the roles and molecular mechanisms of LcGRFs in the regulation of leaf size in L. chinense.

Macrophage P2Y6 receptor deletion attenuates atherosclerosis by limiting foam cell formation through phospholipase Cß/store-operated calcium entry/calreticulin/scavenger receptor A pathways.

BACKGROUND AND AIMS: Macrophage-derived foam cells play a causal role during the pathogenesis of atherosclerosis. P2Y6 receptor (P2Y6R) highly expressed has been considered as a disease-causing factor in atherogenesis, but the detailed mechanism remains unknown. This study aims to explore P2Y6R in regulation of macrophage foaming, atherogenesis, and its downstream pathways. Furthermore, the present study sought to find a potent P2Y6R antagonist and investigate the feasibility of P2Y6R-targeting therapy for atherosclerosis. METHODS: The P2Y6R expression was examined in human atherosclerotic plaques and mouse artery. Atherosclerosis animal models were established in whole-body P2Y6R or macrophage-specific P2Y6R knockout mice to evaluate the role of P2Y6R. RNA sequencing, DNA pull-down experiments, and proteomic approaches were performed to investigate the downstream mechanisms. High-throughput Glide docking pipeline from repurposing drug library was performed to find potent P2Y6R antagonists. RESULTS: The P2Y6R deficiency alleviated atherogenesis characterized by decreasing plaque formation and lipid deposition of the aorta. Mechanically, deletion of macrophage P2Y6R significantly inhibited uptake of oxidized low-density lipoprotein through decreasing scavenger receptor A expression mediated by phospholipase Cß/store-operated calcium entry pathways. More importantly, P2Y6R deficiency reduced the binding of scavenger receptor A to CALR, accompanied by dissociation of calreticulin and STIM1. Interestingly, thiamine pyrophosphate was found as a potent P2Y6R antagonist with excellent P2Y6R antagonistic activity and binding affinity, of which the pharmacodynamic effect and mechanism on atherosclerosis were verified. CONCLUSIONS: Macrophage P2Y6R regulates phospholipase Cß/store-operated calcium entry/calreticulin signalling pathway to increase scavenger receptor A protein level, thereby improving foam cell formation and atherosclerosis, indicating that the P2Y6R may be a potential therapeutic target for intervention of atherosclerotic diseases using P2Y6R antagonists including thiamine pyrophosphate.