Gibberellic acid targeting ZBTB16 reduces NF-κB dependent inflammatory stress in sepsis-induced neuroinflammation.

OBJECTIVE: Sepsis is frequently complicated by neuroinflammation. Gibberellic acid (GA3) is recognized for its anti-inflammatory properties. In this study, our objective was to investigate whether GA3 could alleviate Nuclear factor-kappa B (NF-κB) -dependent inflammatory stress in sepsis-induced neuroinflammation. METHODS: C57BL/6 J mice were administered 10 mg/kg lipopolysaccharide (LPS) to induce sepsis. BV2 cells were pre-incubated with GA3 and subjected lipopolysaccharide stimulation to replicate the inflammatory microglia during sepsis. Subsequently, we assessed the release of IL-6, TNF-α, and IL-1ß, along with the expression of Zbtb16, NF-κB, and IκB. To investigate whether any observed anti-inflammatory effects of GA3 were mediated through a Zbtb16-dependent mechanism, Zbtb16 was silenced using siRNA. RESULTS: GA3 improved the survival of sepsis mice and alleviated post-sepsis cognitive impairment. Additionally, GA3 attenuated microglial M1 activation (pro-inflammatory phenotype), inflammation, and neuronal damage in the brain. Moreover, GA3 inhibited the release of TNF-α, IL-6, and IL-1ß in microglia stimulated with LPS. The NF-κB signaling pathway emerged as one of the key molecular pathways associated with the impact of GA3 on LPS-stimulated microglia. Lastly, GA3 upregulated Zbtb16 expression in microglia that had been downregulated by LPS. The inhibitory effects of GA3 on microglial M1 activation were partially reversed through siRNA knockdown of Zbtb16. CONCLUSIONS: Pre-incubation of microglia with GA3 led to the upregulation of the NF-κB regulator, Zbtb16. This process counteracted LPS-induced microglial M1 activation, resulting in an anti-inflammatory effect upon subsequent LPS stimulation.

Prediction of miRNA-disease associations based on strengthened hypergraph convolutional autoencoder.

Most existing graph neural network-based methods for predicting miRNA-disease associations rely on initial association matrices to pass messages, but the sparsity of these matrices greatly limits performance. To address this issue and predict potential associations between miRNAs and diseases, we propose a method called strengthened hypergraph convolutional autoencoder (SHGAE). SHGAE leverages multiple layers of strengthened hypergraph neural networks (SHGNN) to obtain robust node embeddings. Within SHGNN, we design a strengthened hypergraph convolutional network module (SHGCN) that enhances original graph associations and reduces matrix sparsity. Additionally, SHGCN expands node receptive fields by utilizing hyperedge features as intermediaries to obtain high-order neighbor embeddings. To improve performance, we also incorporate attention-based fusion of self-embeddings and SHGCN embeddings. SHGAE predicts potential miRNA-disease associations using a multilayer perceptron as the decoder. Across multiple metrics, SHGAE outperforms other state-of-the-art methods in five-fold cross-validation. Furthermore, we evaluate SHGAE on colon and lung neoplasms cases to demonstrate its ability to predict potential associations. Notably, SHGAE also performs well in the analysis of gastric neoplasms without miRNA associations.

LUNCRW: Prediction of potential lncRNA-disease associations based on unbalanced neighborhood constraint random walk.

Accumulating evidence suggests that long non-coding RNAs (lncRNAs) are associated with various complex human diseases. They can serve as disease biomarkers and hold considerable promise for the prevention and treatment of various diseases. The traditional random walk algorithms generally exclude the effect of non-neighboring nodes on random walking. In order to overcome the issue, the neighborhood constraint (NC) approach is proposed in this study for regulating the direction of the random walk by computing the effects of both neighboring nodes and non-neighboring nodes. Then the association matrix is updated by matrix multiplication for minimizing the effect of the false negative data. The heterogeneous lncRNA-disease network is finally analyzed using an unbalanced random walk method for predicting the potential lncRNA-disease associations. The LUNCRW model is therefore developed for predicting potential lncRNA-disease associations. The area under the curve (AUC) values of the LUNCRW model in leave-one-out cross-validation and five-fold cross-validation were 0.951 and 0.9486 ± 0.0011, respectively. Data from published case studies on three diseases, including squamous cell carcinoma, hepatocellular carcinoma, and renal cell carcinoma, confirmed the predictive potential of the LUNCRW model. Altogether, the findings indicated that the performance of the LUNCRW method is superior to that of existing methods in predicting potential lncRNA-disease associations.

Evaluation and prediction of ecological carrying capacity in the Qilian Mountain National Park, China.

With increasing human impacts on the ecosystem in natural protected areas, there is an urgent need to undertake an assessment of ecological carrying capacity taken as a benchmark for assessing regional sustainability. Based on satellite remote sensing and socio-economic statistical data from 2000 to 2019, this study distinguished the controlling factors for the spatial and temporal patterns of ecological carrying capacity in the Qilian Mountain National Park, one of the 10 pilot national parks in China. The ecological carrying capacity index (ECCI) was developed by using the Driver-Pressure-State-Impact-Response framework and a comprehensive weight method. The results showed that the multiyear averaged ECCI was low in the south and west but was high in central and eastern regions. The spatial distribution of the ECCI was constrained by soil resources, ecosystem quality, land use/cover and water environment. At the regional scale, the ECCI decreased from 2000 to 2014, especially in Tianzhu, where farmland expansion and severe droughts reduced habitat quality and ecosystem function. However, the ECCI increased significantly from 2014 to 2019, which was attributed to a warm moist climate and the implementation of eco-environmental protection policies. Forest and grassland coverage, soil and water conservation, waste water treatment amount and terrestrial water reserves accounted for 35%, 26%, 20% and 8%, respectively, of the temporal variability in the ECCI. Concurrent with national park development, the ECCI is predicted to increase in most areas from 2020 to 2029 by back-propagation artificial neural networks, except for Sunan, Shandan and Menyuan, possibly owing to increasing conflicts between humans and the environment. The findings of this study provide evidence about the effectiveness of government policies in promoting regional sustainability by altering ecosystem composition and function. In addition, the dominant drivers for the temporal variability of ecological carrying capacity varied in space according to stepwise regression analysis, calling for region-specific management strategies in mountain protected areas and their surroundings.

Vocal cord lesions in representative autoimmune diseases.

OBJECTIVE: The aim of this study was to describe the clinical features of vocal cord lesions in patients with representative autoimmune diseases including systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA). METHOD: A total of 31 SLE/RA patients (14 SLE and 17 RA) complicated with vocal cord lesions (SLE/RA-VC group) who had been admitted to Peking Union Medical College Hospital were retrieved from the electronic registration system. Ninety-three age and sex-matched SLE/RA patients (42 SLE and 51 RA) without vocal cord lesions (SLE/RA-nVC group) admitted during the same period were chosen randomly as controls. Medical files were reviewed and clinical data collected for comparisons. RESULTS: Vocal cord paralysis (n = 12, 38.7%) and vocal cord mass (n = 14, 45.2%) were the most common types of vocal cord lesions in this cohort. Unilateral lesions were more common than bilateral lesions (67.8% vs 32.3%) and the two sides were affected equally. Two cases of vocal cord bamboo node lesion were observed in SLE-VC group even as an initial manifestation and SLE-VC group had a slightly higher disease activity index (SLEDAI-2K) than their control counterparts (18.56 ± 8.23 vs 13.63 ± 5.89, p = 0.041). The RA-VC group had less pulmonary interstitial disease (29.4% vs 63%, p = 0.017) and lower CRP levels (p = 0.006) than their controls. As for the treatment, 71% of SLE/RA-VC patients had received glucocorticoids and immunosuppressants and 30% had undergone surgery. 45.2% of SLE/RA-VC patients got improvement at the time of discharge. CONCLUSIONS: The association of vocal cord lesions with disease activity can be observed in SLE patients but not in RA patients. Vocal cord lesions in SLE/RA patients should be considered as a part of the systemic involvement and should be treated accordingly. Key Points • Vocal cord paralysis and vocal cord mass were the main types of vocal cord lesions in patients with SLE/RA. • Vocal cord lesions in SLE patients may associate with disease activity and vocal cord bamboo node lesions could be an initial manifestation. • Glucocorticoid and immunosuppressants could be effective for vocal cord lesions in SLE/RA patients.

[Fecal Microbiota Transplantation:Traditional Chinese Medicine Meets Western Medicine].

Fecal microbiota transplantation (FMT) is a therapy of transplanting the functional flora from the feces of a healthy donor into the gastrointestinal tract of a patient to reconstruct the normal flora.The application of FMT in western medicine dates from the 1950s.After decades of development,the efficacy of FMT has been proven in a variety of diseases.The record of FMT in traditional Chinese medicine (TCM) dates early from the 3rd century A.D.,and relevant theories have been recorded in many TCM works in the past dynasties.FMT as a therapy that has been written into guidelines has been accepted by some countries and regions such as the United States and the United Kingdom in the treatment of Clostridium difficile infection,and its clinical indications are expanding.TCM and western medicine,with different medical thoughts,meet in the application of FMT.Exploring a normative and effective FMT procedure reflects not only the patient-centered principle but also the mutual promotion of TCM and western medicine.

High expression of YKT6 associated with progression and poor prognosis of hepatocellular carcinoma.

BACKGROUND AND OBJECTIVE: The N-ethylmaleimide-sensitive fusion protein attachment protein receptor YKT6 is a key protein that controls the release of exosomes, was reported to play important roles in multiple cancers. However, the role of YKT6 in hepatocellular carcinoma (HCC) is still unknown. METHODS: Here we first used bioinformatics tools to analyze the YKT6 mRNA expression in HCC. In addition, we retrospectively collected 330 cancer tissue specimens from HCC patients and 180 para-cancerous tissue specimens, and detected YKT6 expression using immunohistochemical staining. Then the relationship between YKT6 expression and the clinical characteristics of HCC was analyzed, Kaplan-Meier analysis and Cox regression model were also performed to evaluate the impact of YKT6 expression on prognosis of HCC. Protein-protein interaction network of YKT6, and the gene enrichment analysis (GSEA) database were used to predict possible signal pathways regulated by YKT6 in HCC. RESULTS: The high expression rate of YKT6 in HCC (72.40%, 239/330) was higher than that in adjacent tissues (17.80%, 32/180, p < .001), and high expression of YKT6 was correlated with tumor size (p = 0.002), Edmondson Grade (p < .001), metastasis (p < .001), microvascular invasion (p = .005), AFP level (p = .002). Kaplan-Meier survival analysis showed that HCC patients with high YKT6 expression level had poorer prognosis. Meanwhile, multivariate Cox regression analysis showed that Edmondson grade (p = .009), metastasis (p = .049), YKT6 expression (p = .037) are independent risk factors for poor prognosis of HCC. Conclusions: Our results suggested that the upregulated expression of YKT6 is closely related to the progression HCC, which may be used as a potential biomarker for poor prognosis in HCC.

Identification of hub genes correlated with sleep deprivation using co-expression analysis.

BACKGROUND: Sleep deprivation (SD) has become a serious concern worldwide. This study aimed to identify key modules and candidate hub genes correlated with diseases caused by SD, using co-expression analysis. METHODS: The weighted gene co-expression network analysis was performed to construct a co-expression network of hub genes correlated with SD. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed to search for signaling pathways. The protein-protein interaction network analysis of central genes was performed to recognize the interactions among central genes. Molecular Complex Detection, a plugin in Cytoscape, was used to discover the hub gene clusters involved in SD. RESULTS: A total of 564 genes in the yellow module were identified based on the results of topological overlap measure-based clustering. The yellow module showed a pivotal correlation with SD. Six hub gene clusters prominently associated with SD were identified. Heat shock protein family and circadian clock genes among them may be the hub genes involved in SD. CONCLUSIONS: These genes and pathways might become therapeutic targets with clinical usefulness in the future.

Probing the Neutron Skin with Ultrarelativistic Isobaric Collisions.

Particle production in ultrarelativistic heavy ion collisions depends on the details of the nucleon density distributions in the colliding nuclei. We demonstrate that the charged hadron multiplicity distributions in isobaric collisions at ultrarelativistic energies provide a novel approach to determine the poorly known neutron density distributions and thus the neutron skin thickness in finite nuclei, which can in turn put stringent constraints on the nuclear symmetry energy.

BRD4 and PIN1 gene polymorphisms are associated with high pulse pressure risk in a southeastern Chinese population.

BACKGROUND: BRD4 and PIN1 have been described to be involved in inflammation and vascular endothelial cell dysfunction, which in turn may increase pulse pressure. HYPOTHESIS: Genetic mutations within the BRD4 and PIN1 genes could affect the risk of high pulse pressure. METHODS: A total of four single nucleotide polymorphisms (SNPs) (BRD4: rs4808278; PIN1: rs2233678, rs2287838, and rs2233682) were genotyped in a cohort of 666 hypertensive patients and 232 normotensive controls with Chinese Han origin. Generalized multifactor dimensionality reduction (GMDR) was used to screen the best interaction combination among the four SNPs within the BRD4 and PIN1 genes and diabetes. Logistic regression analysis was performed to calculate the odds ratio (ORs) (95% confidence interval (CI)) for the association between the four SNPs. RESULTS: Adjusted for age, weight, waist circumference, drinking, smoking, hypertension, and diabetes, high pulse pressure risk was significantly higher for carriers with the rs4808278-TT genotype in BRD4 than those with wild genotypes (OR: 0.400, 95% CI: 0.217-0.737, P* < 0.05). However, we did not find any significant association of rs2233678, rs2287838, and rs2233682 in PIN1 with high pulse pressure susceptibility after covariate adjustment. GMDR analysis indicated a significant three-locus model (P = 0.0107) involving rs4808278, rs2233678, and diabetes, the cross-validation consistency of the three-locus models was 9/10, and the testing accuracy was 57.47%. CONCLUSIONS: Genetic mutations within BRD4 (rs4808278) could affect the susceptibility to high pulse pressure in a southeastern Chinese population.

Importance of Isobar Density Distributions on the Chiral Magnetic Effect Search.

Under the approximate chiral symmetry restoration, quark interactions with topological gluon fields in quantum chromodynamics can induce a chirality imbalance and parity violation in local domains. An electric charge separation (CS) could be generated along the direction of a strong magnetic field (B), a phenomenon called the chiral magnetic effect (CME). CS measurements by azimuthal correlators are contaminated by major backgrounds from elliptic flow anisotropy (v_{2}). Isobaric _{44}^{96}Ru+_{44}^{96}Ru and _{40}^{96}Zr+_{40}^{96}Zr collisions have been proposed to identify the CME (expected to differ between the two systems) out of the backgrounds (to be almost the same). We show, by using the density functional theory calculations of the proton and neutron distributions, that these expectations may not hold as originally anticipated because the two systems may have sizable differences in eccentricity and v_{2}.

Trend shifts in satellite-derived vegetation growth in Central Eurasia, 1982-2013.

Central Eurasian vegetation is critical for the regional ecological security and the global carbon cycle. However, climatic impacts on vegetation growth in Central Eurasia are uncertain. The reason for this uncertainty lies in the fact that the response of vegetation to climate change showed nonlinearity, seasonality and differences among plant functional types. Based on remotely sensed vegetation index and in-situ meteorological data for the years 1982-2013, in conjunction with the latest land cover type product, we analyzed how vegetation growth trend varied across different seasons and evaluated vegetation response to climate variables at regional, biome and pixel scales. We found a persistent increase in the growing season NDVI over Central Eurasia during 1982-1994, whereas this greening trend has stalled since the mid-1990s in response to increased water deficit. The stalled trend in the growing season NDVI was largely attributed by summer and autumn NDVI changes. Enhanced spring vegetation growth after 2002 was caused by rapid spring warming. The response of vegetation to climatic factors varied in different seasons. Precipitation was the main climate driver for the growing season and summer vegetation growth. Changes in temperature and precipitation during winter and spring controlled the spring vegetation growth. Autumn vegetation growth was mainly dependent on the vegetation growth in summer. We found diverse responses of different vegetation types to climate drivers in Central Eurasia. Forests were more responsive to temperature than to precipitation. Grassland and desert vegetation responded more strongly to precipitation than to temperature in summer but more strongly to temperature than to precipitation in spring. In addition, the growth of desert vegetation was more dependent on winter precipitation than that of grasslands. This study has important implications for improving the performance of terrestrial ecosystem models to predict future vegetation response to climate change.

1H-2,3-dihydroperimidine derivatives: a new class of potent protein tyrosine phosphatase 1B inhibitors.

A series of 1H-2,3-dihydroperimidine derivatives was designed, synthesized, and evaluated as a new class of inhibitors of protein tyrosine phosphatase 1B (PTP1B) with IC50 values in the micromolar range. Compounds 46 and 49 showed submicromolar inhibitory activity against PTP1B, and good selectivity (3.48-fold and 2.10-fold respectively) over T-cell protein tyrosine phosphatases (TCPTP). These results have provided novel lead compounds for the design of inhibitors of PTP1B as well as other PTPs.