Genetically predicted gut microbiome and risk of oral cancer.

PURPOSE: Mounting evidence suggests a possible link between gut microbiome and oral cancer, pointing to some potential modifiable targets for disease prevention. In the present study, Mendelian randomization (MR) was used to explore whether there was a causal link between gut microbiome and oral cancer. METHODS: The single nucleotide polymorphisms (SNPs) significantly associated with gut microbiome were served as instrumental variables. MR analyses were performed using genetic approaches such as inverse variance weighting (IVW), MR Egger and weighted median, with IVW as the primary approach, supplemented by MR Egger and weighted median. Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) and MR-Egger regression were used to detect the presence of horizontal pleiotropy and identify outlier SNPs. RESULTS: Causal effect estimates indicated that genetically predicted abundance of Prevotellaceae was associated with higher risk of oral cancer (odds ratio (OR) 1.80, 95% confidence interval (CI) 1.16-2.81, p = 0.009). There was no evidence of notable heterogeneity and horizontal pleiotropy. CONCLUSION: Genetically derived estimates suggest that Prevotellaceae may be associated with the risk of oral cancer. Such robust evidence should be given priority in future studies and explore the underlying mechanisms.

Gastroesophageal reflux disease increases the risk of essential hypertension: results from the Nationwide Readmission Database and Mendelian randomization analysis.

BACKGROUND: The link between gastroesophageal reflux disease (GERD) and essential hypertension (EH) and its causal nature remains controversial. Our study examined the connection between GERD and the risk of hypertension and assessed further whether this correlation has a causal relationship. METHODS: First, we utilized the National Readmission Database including 14 422 183 participants to conduct an observational study. Dividing the population into GERD and non-GERD groups, we investigated the correlation between GERD and EH using multivariate logistic regression. Next, bidirectional two-sample Mendelian randomization was adopted. The summary statistics for GERD were obtained from a published genome-wide association study including 78 707 cases and 288 734 controls. We collected summary statistics for hypertension containing 70 651 cases and 223 663 controls from the FinnGen consortium. We assessed causality primarily by the inverse-variance weighted method with validation by four other Mendelian randomization approaches as well as an array of sensitivity analyses. RESULTS: In the unadjusted model, GERD patients had a higher risk of EH than the non-GERD group, regardless of gender (odds ratio, 1.43; 95% confidence interval: 1.42-1.43; P < .001). Further adjusting for critical confounders did not change this association. For Mendelian randomization, we found that genetically predicted GERD was causally linked to an enhanced risk of EH in inverse-variance weighted technique (odds ratio, 1.52; 95% confidence interval: 1.39-1.67; P = 3.51 × 10-18); conversely, EH did not raise the risk of GERD causally. CONCLUSIONS: GERD is a causal risk factor for EH. Further research is required to probe the mechanism underlying this causal connection.

Analysis of intestinal flora and cognitive function in maintenance hemodialysis patients using combined 16S ribosome DNA and shotgun metagenome sequencing.

BACKGROUND: Cognitive impairment is widely prevalent in maintenance hemodialysis (MHD) patients, and seriously affects their quality of life. The intestinal flora likely regulates cognitive function, but studies on cognitive impairment and intestinal flora in MHD patients are lacking. METHODS: MHD patients (36) and healthy volunteers (18) were evaluated using the Montreal Cognitive Function Scale, basic clinical data, and 16S ribosome DNA (rDNA) sequencing. Twenty MHD patients and ten healthy volunteers were randomly selected for shotgun metagenomic analysis to explore potential metabolic pathways of intestinal flora. Both16S rDNA sequencing and shotgun metagenomic sequencing were conducted on fecal samples. RESULTS: Roseburia were significantly reduced in the MHD group based on both 16S rDNA and shotgun metagenomic sequencing analyses. Faecalibacterium, Megamonas, Bifidobacterium, Parabacteroides, Collinsella, Tyzzerella, and Phascolarctobacterium were positively correlated with cognitive function or cognitive domains. Enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways included oxidative phosphorylation, photosynthesis, retrograde endocannabinoid signaling, flagellar assembly, and riboflavin metabolism. CONCLUSION: Among the microbiota, Roseburia may be important in MHD patients. We demonstrated a correlation between bacterial genera and cognitive function, and propose possible mechanisms.

Recent advances in aggregation-induced emission-active type I photosensitizers with near-infrared fluorescence: From materials design to therapeutic platform fabrication.

Near-infrared (NIR) fluorescence imaging-guided photodynamic therapy (PDT) technology plays an important role in treating various diseases and still attracts increasing research interests for developing novel photosensitizers (PSs) with outstanding performances. Conventional PSs such as porphyrin and rhodamine derivatives have easy self-aggregation properties in the physiological environment due to their inherent hydrophobic nature caused by their rigid molecular structure that induces strong intermolecular stacking π-π interaction, leading to serious fluorescence quenching and cytotoxic reactive oxygen species (ROS) reduction. Meanwhile, hypoxia is an inherent barrier in the microenvironment of solid tumors, seriously restricting the therapeutic outcome of conventional PDT. Aforementioned disadvantages should be overcome urgently to enhance the therapeutic effect of PSs. Novel NIR fluorescence-guided type I PSs with aggregation-induced emission (AIE), which features the advantages of improving fluorescent intensity and ROS generation efficiency at aggregation as well as outstanding oxygen tolerance, bring hope for resolving aforementioned problems simultaneously. At present, plenty of research works fully demonstrates the advancement of AIE-active PDT based on type I PSs. In this review, cutting-edge advances focusing on AIE-active NIR type I PSs that include the aspects of the photochemical mechanism of type I ROS generation, various molecular structures of reported type I PSs with NIR fluorescence and their design strategies, and typical anticancer applications are summarized. Finally, a brief conclusion is obtained, and the underlying challenges and prospects of AIE-active type I PSs are proposed.

Aggregation Effect on Multiperformance Improvement in Aryl-Armed Phenazine-Based Emitters.

The concept of aggregate science was proposed to explain changes in materials performance that accompany the generation of aggregates, but aggregation-triggered multifunction improvements in a class of materials have rarely been reported. Herein, we present the first report of a new class of multifunctional aggregation-induced emission (AIE) luminogens (AIEgens) based on 5,10-diarylphenazine (DPZ) derivates with full-wavelength emission. Intriguingly, multiple properties, such as fluorescence intensity and free radical and type I reactive oxygen species (ROS) efficiencies, could be simultaneously activated from the unimolecular level to the aggregate state. The mechanisms of this multiple performance improvement are discussed in detail based on sufficient performance characterization, and some of the newly prepared AIEgens exhibited toxicity to cancer cells during photodynamic therapy. This work systematically demonstrates the positive effect of aggregation on improving multiple functions of materials, which is expected to promote the development of aggregate science theory for the design of multifunctional materials.

Echinacoside, a promising sortase A inhibitor, combined with vancomycin against murine models of MRSA-induced pneumonia.

Methicillin-resistant Staphylococcus aureus (MRSA) is a pathogenic bacterium responsible for a range of severe infections, such as skin infections, bacteremia, and pneumonia. Due to its antibiotic-resistant nature, current research focuses on targeting its virulence factors. Sortase A (SrtA) is a transpeptidase that anchors surface proteins to the bacterial cell wall and is involved in adhesion and invasion to host cells. Through fluorescence resonance energy transfer (FRET), we identified echinacoside (ECH), a natural polyphenol, as a potential SrtA inhibitor with an IC50 of 38.42 µM in vitro. It was demonstrated that ECH inhibited SrtA-mediated S. aureus fibrinogen binding, surface protein A anchoring, and biofilm formation. The fluorescence quenching assay determined the binding mode of ECH to SrtA and calculated the KA-binding constant of 3.09 × 105 L/mol, demonstrating the direct interaction between the two molecules. Molecular dynamics simulations revealed that ECH-SrtA interactions occurred primarily at the binding sites of A92G, A104G, V168A, G192A, and R197A. Importantly, the combination of ECH and vancomycin offered protection against murine models of MRSA-induced pneumonia. Therefore, ECH may serve as a potential antivirulence agent against S. aureus infections, either alone or in combination with vancomycin.

Inhibitory effect of bilobalide on Staphylococcus aureus von Willebrand factor-binding protein and its therapeutic effect in mice with pneumonia.

AIMS: Disabling bacterial virulence with small molecules has been proposed as a potential strategy to prevent bacterial pathogenicity. The von Willebrand factor-binding protein of Staphylococcus aureus was identified previously as a key virulence determinant. Our objective was to discover a von Willebrand-factor binding protein (vWbp) inhibitor distinct from the antibiotics used to prevent infections resulting from S. aureus. METHODS AND RESULTS: Using coagulation assays, we found that the sesquiterpene trilactone bilobalide blocks coagulation mediated by vWbp, but has no impact on the growth of S. aureus at a concentration of 128 µg ml-1. Moreover, a mouse model of pneumonia caused by S. aureus indicated that bilobalide could attenuate S. aureus virulence in vivo. This effect is achieved not by interfering with the expression of vWbp but by binding to vWbp, as demonstrated by western blotting, thermal shift assays, and fluorescence quenching assays. Using molecular dynamic simulations and point mutagenesis analysis, we identified that the Q17A and R453A residues are key residues for the binding of bilobalide to vWbp. CONCLUSIONS: Overall, we tested the ability of bilobalide to inhibit S. aureus infections by targeting vWbp and explored the potential mechanism of this activity.

Empagliflozin activates JAK2/STAT3 signaling and protects cardiomyocytes from hypoxia/reoxygenation injury under high glucose conditions.

The morbidity and mortality rates of cardiovascular disease are markedly higher in patients with diabetes than in non-diabetic patients, including patients with ischemia-reperfusion injury (IRI). However, the cardiovascular protective effects of Empagliflozin (EMPA) on IRI in diabetes mellitus have rarely been studied. In this study, we established a cardiomyocyte hypoxia/reoxygenation (H/R) injury model to mimic myocardial I/R injuries that occur in vivo. H9C2 cells were subjected to high glucose (HG) treatment plus H/R injury to mimic myocardial I/R injuries that occur in diabetes mellitus. Next, different concentrations of EMPA were added to the H9C2 cells and its protective effect was detected. STAT3 knockdown with recombinant plasmids was used to determine its roles. Our results showed that H/R injury-induced cell apoptosis, necroptosis, oxidative stress, and endoplasmic reticulum stress were further promoted by HG conditions, and HG treatment plus an H/R injury inhibited the activation of JAK2/STAT3 signaling. EMPA was found to protect against H/R-induced cardiomyocyte injury under HG conditions and activate JAK2/STAT3 signaling, while down-regulation of STAT3 reversed the protective effect of EMPA. When taken together, these findings indicate that EMPA protects against I/R-induced cardiomyocyte injury by activating JAK2/STAT3 signaling under HG conditions. Our results clarified the mechanisms that underlie the cardiovascular protective effects of EMPA in diabetes mellitus and provide new therapeutic targets for IRI in diabetes mellitus.

The effect of air pollution exposure on the risk of outpatient visits for periodontitis: a time-series study.

This study aimed to determine if air pollution affected the risk of periodontitis outpatient visits. We collected the records of 56,456 periodontitis outpatient visits in Hefei, China, from January 1，2014 to December 31，2021. The relationship between air pollution and periodontitis outpatient visits was evaluated using distributed lag nonlinear and generalized linear models. Additional analyses were performed, stratifying the data by age, season, and sex. Subgroup analyses showed a significantly higher risk of periodontitis outpatient visits due to NO2 exposure during the warm season compared with the cold season. Moreover, O3 exposure was associated with a lower risk of periodontitis outpatient visits in the cold season. The findings suggest that NO2 exposure is associated with an increased risk of periodontitis outpatient visits, whereas O3 exposure is associated with a decreased risk of periodontitis outpatient visits. Season is found to be an effect modifier in these associations.

Remote Enantioselective [4 + 1] Annulation with Copper-Vinylvinylidene Intermediates.

The first copper-catalyzed enantioselective [4 + 1] annulation of yne-allylic esters with 1,3-dicarbonyl compounds was realized through an elegant remote stereocontrol strategy. The very remote ε regioselective nucleophilic substitution was developed by employing a novel chiral copper-vinylvinylidene species from the new C4 synthon yne-allylic esters. Thus, greatly diverse spirocycles were obtained with ample scope and excellent levels of chemo-, regio-, and enantioselectivities. Moreover, detailed mechanistic studies suggest an yne-allylic substitution and Conia-ene cascade pathway on the remote stereochemical induction progress.

Disruption of C/EBPß-Clec7a axis exacerbates neuroinflammatory injury via NLRP3 inflammasome-mediated pyroptosis in experimental neuropathic pain.

BACKGROUND: Growing evidence shows that C-Type Lectin Domain Containing 7A (Clec7a) may be involved into neuroinflammatory injury of various neurological diseases. However, its roles in neuropathic pain remain unclear. METHODS: A chronic constriction injury (CCI) rat model was constructed, and gene expression profilings in spinal cord tissues of CCI-insulted rats were detected by both microarray and RNA-seq studies. A series of bioinformatics analyses identified C/EBPß-Clec7a to be a candidate axis involved into neuropathic pain. Then, its roles in mechanical allodynia, and pathological and molecular changes during CCI progression were determined by various gain-of-function and loss-of-function experiments in vivo and in vitro. RESULTS: Significant upregulation of Clec7a at both mRNA and protein levels were verified in spinal cord tissues of CCI-insulted rats. Clec7a knockdown markedly attenuated CCI-induced mechanical allodynia, obstructed Syk, ERK and JNK phosphorylation, inhibited NLRP3 inflammasome and caspase-1 activation, GSDMD cleavage, and consequently reduced the release of pro-inflammatory cytokines (all P < 0.05). Mechanically, the rat Clec7a promoter was predicted to bind with transcription factor C/EBPß, confirmed by Luciferase assay and ChIP-qPCR. Both in vivo and in vitro assays demonstrated that C/EBPß knockdown significantly suppressed CCI- or LPS/ATP-induced Clec7a upregulation, and subsequently reduced Syk, ERK and JNK phosphorylation, NLRP3 oligomerization, caspase-1 activation, GSDMD expression and pyroptosis, which were markedly reversed by the co-transfection of Clec7a expression vector. CONCLUSIONS: This pre-clinical investigation reveals that C/EBPß-Clec7a axis may be a potential target for relieving neuropathic pain through alleviating neuroinflammation, paving its way for clinical translation as a promising approach for neuropathic pain therapy.

CBGRU: A Detection Method of Smart Contract Vulnerability Based on a Hybrid Model.

In the context of the rapid development of blockchain technology, smart contracts have also been widely used in the Internet of Things, finance, healthcare, and other fields. There has been an explosion in the number of smart contracts, and at the same time, the security of smart contracts has received widespread attention because of the financial losses caused by smart contract vulnerabilities. Existing analysis tools can detect many smart contract security vulnerabilities, but because they rely too heavily on hard rules defined by experts when detecting smart contract vulnerabilities, the time to perform the detection increases significantly as the complexity of the smart contract increases. In the present study, we propose a novel hybrid deep learning model named CBGRU that strategically combines different word embedding (Word2Vec, FastText) with different deep learning methods (LSTM, GRU, BiLSTM, CNN, BiGRU). The model extracts features through different deep learning models and combine these features for smart contract vulnerability detection. On the currently publicly available dataset SmartBugs Dataset-Wild, we demonstrate that the CBGRU hybrid model has great smart contract vulnerability detection performance through a series of experiments. By comparing the performance of the proposed model with that of past studies, the CBGRU model has better smart contract vulnerability detection performance.

A Novel Smart Contract Vulnerability Detection Method Based on Information Graph and Ensemble Learning.

Blockchain presents a chance to address the security and privacy issues of the Internet of Things; however, blockchain itself has certain security issues. How to accurately identify smart contract vulnerabilities is one of the key issues at hand. Most existing methods require large-scale data support to avoid overfitting; machine learning (ML) models trained on small-scale vulnerability data are often difficult to produce satisfactory results in smart contract vulnerability prediction. However, in the real world, collecting contractual vulnerability data requires huge human and time costs. To alleviate these problems, this paper proposed an ensemble learning (EL)-based contract vulnerability prediction method, which is based on seven different neural networks using contract vulnerability data for contract-level vulnerability detection. Seven neural network (NN) models were first pretrained using an information graph (IG) consisting of source datasets, which then were integrated into an ensemble model called Smart Contract Vulnerability Detection method based on Information Graph and Ensemble Learning (SCVDIE). The effectiveness of the SCVDIE model was verified using a target dataset composed of IG, and then its performances were compared with static tools and seven independent data-driven methods. The verification and comparison results show that the proposed SCVDIE method has higher accuracy and robustness than other data-driven methods in the target task of predicting smart contract vulnerabilities.

SPCBIG-EC: A Robust Serial Hybrid Model for Smart Contract Vulnerability Detection.

With countless devices connected to the Internet of Things, trust mechanisms are especially important. IoT devices are more deeply embedded in the privacy of people's lives, and their security issues cannot be ignored. Smart contracts backed by blockchain technology have the potential to solve these problems. Therefore, the security of smart contracts cannot be ignored. We propose a flexible and systematic hybrid model, which we call the Serial-Parallel Convolutional Bidirectional Gated Recurrent Network Model incorporating Ensemble Classifiers (SPCBIG-EC). The model showed excellent performance benefits in smart contract vulnerability detection. In addition, we propose a serial-parallel convolution (SPCNN) suitable for our hybrid model. It can extract features from the input sequence for multivariate combinations while retaining temporal structure and location information. The Ensemble Classifier is used in the classification phase of the model to enhance its robustness. In addition, we focused on six typical smart contract vulnerabilities and constructed two datasets, CESC and UCESC, for multi-task vulnerability detection in our experiments. Numerous experiments showed that SPCBIG-EC is better than most existing methods. It is worth mentioning that SPCBIG-EC can achieve F1-scores of 96.74%, 91.62%, and 95.00% for reentrancy, timestamp dependency, and infinite loop vulnerability detection.

A mis-regulated cyclic nucleotide-gated channel mediates cytosolic calcium elevation and activates immunity in Arabidopsis.

Calcium (Ca2+ ) is a second messenger for plant cell surface and intracellular receptors mediating pattern-triggered and effector-triggered immunity (respectively, PTI and ETI). Several CYCLIC NUCLEOTIDE-GATED CHANNELS (CNGCs) were shown to control transient cytosolic Ca2+ influx upon PTI activation. The contributions of specific CNGC members to PTI and ETI remain unclear. ENHANCED DISEASE SUSCEPTIBLITY1 (EDS1) regulates ETI signaling. In an Arabidopsis genetic screen for suppressors of eds1, we identify a recessive gain-of-function mutation in CNGC20, denoted cngc20-4, which partially restores disease resistance in eds1. cngc20-4 enhances PTI responses and ETI hypersensitive cell death. A cngc20-4 single mutant exhibits autoimmunity, which is dependent on genetically parallel EDS1 and salicylic acid (SA) pathways. CNGC20 self-associates, forms heteromeric complexes with CNGC19, and is phosphorylated and stabilized by BOTRYTIS INDUCED KINASE1 (BIK1). The cngc20-4 L371F exchange on a predicted transmembrane channel inward surface does not disrupt these interactions but leads to increased cytosolic Ca2+ accumulation, consistent with mis-regulation of CNGC20 Ca2+ -permeable channel activity. Our data show that ectopic Ca2+ influx caused by a mutant form of CNGC20 in cngc20-4 affects both PTI and ETI responses. We conclude that tight control of the CNGC20 Ca2+ ion channel is important for regulated immunity.

The Novel Synthetic Triterpene Methyl 3ß-O-[4-(2-Aminoethylamino)-4-oxo-butyryl]olean-12-ene-28-oate Inhibits Breast Tumor Cell Growth in Vitro and in Vivo.

Oleanolic and ursolic acids were used as lead compounds to synthesize a series of pentacyclic triterpenoid derivatives bearing ethylenediamine, butanediamine, or hexanediamine groups at the C-3 position. The potential antiproliferative activity of these compounds was examined in A549 (human non-small cell lung cancer cells), MCF-7 (human breast cancer cells), and HeLa (human cervical carcinoma cells) cells. Methyl 3ß-O-[4-(2-aminoethylamino)-4-oxo-butyryl]olean-12-ene-28-oate (DABO-Me) was identified as a promising antiproliferative agent in vitro and in vivo. DABO-Me strongly suppressed the proliferation of A549, MCF-7, and HeLa cells (IC50 = 4-7 µM). In MCF-7 cells, DABO-Me upregulated the pro-apoptotic protein Bax, downregulated the anti-apoptotic protein Bcl-2, promoted the release of cytochrome c, and activated caspase-3/9. Transwell and flow cytometry assays showed that DABO-Me inhibited MCF-7 cell proliferation, migration, and invasion, and induced apoptosis and S phase arrest. In vitro and in vivo experiments indicated that DABO-Me inhibited MCF-7 cell proliferation and suppressed tumor growth. Taken together, these results indicate that DABO-Me could be developed as an effective antitumor drug.

Changes of serum 25(OH) D3 and IGF-1 levels in patients with thyroid nodules.

BACKGROUND: The present study aimed to study the relationship between serum 25 hydroxyvitamin D3(25(OH)D3) and insulin-like growth factor-1 (IGF-1) and thyroid nodules. METHODS: Two hundred eighty-nine cases with thyroid nodules and 109 health subjects (control group) who admitted to the Hebei General Hospital during June 2016 to December 2016 were included in the study. Basic clinical information (age, sex, thyroid function, liver and kidney function, hypertension history, etc.) of patients were collected. Serum 25(OH) D3 and Serum IGF-1 were detected by electrochemiluminescence and radioimmunoassay methods, respectively. The relationship between the above-mentioned factors and thyroid nodules was statistically analyzed. RESULTS: Serum 25(OH)D3, IGF-1, fasting blood glucose (FBG), total cholesterol (TC), waist circumference (WC), total triiodothyronine (TT3), total thyroxine (TT4), hypertension history, and drinking history were significantly different between the nodules group and the control group (P < 0.05). Logistic regression analysis showed that there was a negative correlation between thyroid nodules and levels of 25(OH)D3, IGF-1, TT3, as well as a positive correlation with FBG, TC, TT4, and hypertension. There was a positive correlation between IGF-1 and serum 25(OH)D3 in thyroid nodules (P < 0.05). After correcting the aforementioned factors, high-level of serum 25(OH)D3 was significantly correlated with the decreased incidence of thyroid nodules. CONCLUSIONS: The incidence of thyroid nodules is relatively lower in a high-level of serum 25(OH)D3, and serum 25(OH)D3 may be a direct protective factor for thyroid nodules. Serum IGF-1 can be one of the indirect protective factors for thyroid nodules as well.

Correction: Yan, Y.; et al. Building Extraction Based on an Optimized Stacked Sparse Autoencoder of Structure and Training Samples Using LIDAR DSM and Optical Images. Sensors 2017, 17, 1957.

The authors wish to make the following corrections to this paper [1]:[...].

A Dynamic Multi-Projection-Contour Approximating Framework for the 3D Reconstruction of Buildings by Super-Generalized Optical Stereo-Pairs.

The authors wish to make the following corrections to this paper [...].

Object-Oriented Hierarchy Radiation Consistency for Different Temporal and Different Sensor Images.

In the paper, we propose a novel object-oriented hierarchy radiation consistency method for dense matching of different temporal and different sensor data in the 3D reconstruction. For different temporal images, our illumination consistency method is proposed to solve both the illumination uniformity for a single image and the relative illumination normalization for image pairs. Especially in the relative illumination normalization step, singular value equalization and linear relationship of the invariant pixels is combined used for the initial global illumination normalization and the object-oriented refined illumination normalization in detail, respectively. For different sensor images, we propose the union group sparse method, which is based on improving the original group sparse model. The different sensor images are set to a similar smoothness level by the same threshold of singular value from the union group matrix. Our method comprehensively considered the influence factors on the dense matching of the different temporal and different sensor stereoscopic image pairs to simultaneously improve the illumination consistency and the smoothness consistency. The radiation consistency experimental results verify the effectiveness and superiority of the proposed method by comparing two other methods. Moreover, in the dense matching experiment of the mixed stereoscopic image pairs, our method has more advantages for objects in the urban area.