Potential role of epithelial-mesenchymal transition induced by periodontal pathogens in oral cancer.

With the increasing incidence of oral cancer in the world, it has become a hotspot to explore the pathogenesis and prevention of oral cancer. It has been proved there is a strong link between periodontal pathogens and oral cancer. However, the specific molecular and cellular pathogenic mechanisms remain to be further elucidated. Emerging evidence suggests that periodontal pathogens-induced epithelial-mesenchymal transition (EMT) is closely related to the progression of oral cancer. Cells undergoing EMT showed increased motility, aggressiveness and stemness, which provide a pro-tumour environment and promote malignant metastasis of oral cancer. Plenty of studies proposed periodontal pathogens promote carcinogenesis via EMT. In the current review, we discussed the association between the development of oral cancer and periodontal pathogens, and summarized various mechanisms of EMT caused by periodontal pathogens, which are supposed to play an important role in oral cancer, to provide targets for future research in the fight against oral cancer.

Synthesis of LaCN3, TbCN3, CeCN5, and TbCN5 Polycarbonitrides at Megabar Pressures.

Inorganic ternary metal-C-N compounds with covalently bonded C-N anions encompass important classes of solids such as cyanides and carbodiimides, well known at ambient conditions and composed of [CN]- and [CN2]2- anions, as well as the high-pressure formed guanidinates featuring [CN3]5- anion. At still higher pressures, carbon is expected to be 4-fold coordinated by nitrogen atoms, but hitherto, such CN4-built anions are missing. In this study, four polycarbonitride compounds (LaCN3, TbCN3, CeCN5, and TbCN5) are synthesized in laser-heated diamond anvil cells at pressures between 90 and 111 GPa. Synchrotron single-crystal X-ray diffraction (SCXRD) reveals that their crystal structures are built of a previously unobserved anionic single-bonded carbon-nitrogen three-dimensional (3D) framework consisting of CN4 tetrahedra connected via di- or oligo-nitrogen linkers. A crystal-chemical analysis demonstrates that these polycarbonitride compounds have similarities to lanthanide silicon phosphides. Decompression experiments reveal the existence of LaCN3 and CeCN5 compounds over a very large pressure range. Density functional theory (DFT) supports these discoveries and provides further insight into the stability and physical properties of the synthesized compounds.

High-Pressure oC16-YBr3 Polymorph Recoverable to Ambient Conditions: From 3D Framework to Layered Material.

Exfoliation of graphite and the discovery of the unique properties of graphene─graphite's single layer─have raised significant attention to layered compounds as potential precursors to 2D materials with applications in optoelectronics, spintronics, sensors, and solar cells. In this work, a new orthorhombic polymorph of yttrium bromide, oC16-YBr3 was synthesized from yttrium and CBr4 in a laser-heated diamond anvil cell at 45 GPa and 3000 K. The structure of oC16-YBr3 was solved and refined using in situ synchrotron single-crystal X-ray diffraction. At high pressure, it can be described as a 3D framework of YBr9 polyhedra, but upon decompression below 15 GPa, the structure motif changes to layered, with layers comprising edge-sharing YBr8 polyhedra weakly bonded by van der Waals interactions. The layered oC16-YBr3 material can be recovered to ambient conditions, and according to Perdew-Burke-Ernzerhof-density functional theory calculations, it exhibits semiconductor properties with a band gap that is highly sensitive to pressure. This polymorph possesses a low exfoliation energy of 0.30 J/m2. Our results expand the list of layered trivalent rare-earth metal halides and provide insights into how high pressure alters their structural motifs and physical properties.

RhoA/ROCK1 regulates the mitochondrial dysfunction through Drp1 induced by Porphyromonas gingivalis in endothelial cells.

Porphyromonas gingivalis (P. gingivalis) is a pivotal pathogen of periodontitis. Our previous studies have confirmed that mitochondrial dysfunction in the endothelial cells caused by P. gingivalis was dependent on Drp1, which may be the mechanism of P. gingivalis causing endothelial dysfunction. Nevertheless, the signalling pathway induced the mitochondrial dysfunction remains unclear. The purpose of this study was to investigate the role of the RhoA/ROCK1 pathway in regulating mitochondrial dysfunction caused by P. gingivalis. P. gingivalis was used to infect EA.hy926 cells (endothelial cells). The expression and activation of RhoA and ROCK1 were assessed by western blotting and pull-down assay. The morphology of mitochondria was observed by mitochondrial staining and transmission electron microscopy. Mitochondrial function was measured by ATP content, mitochondrial DNA and mitochondrial permeability transition pore openness. The phosphorylation and translocation of Drp1 were evaluated using western blotting and immunofluorescence. The role of the RhoA/ROCK1 pathway in mitochondrial dysfunction was investigated using RhoA and ROCK1 inhibitors. The activation of RhoA/ROCK1 pathway and mitochondrial dysfunction were observed in P. gingivalis-infected endothelial cells. Furthermore, RhoA or ROCK1 inhibitors partly prevented mitochondrial dysfunction caused by P. gingivalis. The increased phosphorylation and mitochondrial translocation of Drp1 induced by P. gingivalis were both blocked by RhoA and ROCK1 inhibitors. In conclusion, we demonstrate that the RhoA/ROCK1 pathway was involved in mitochondrial dysfunction caused by P. gingivalis by regulating the phosphorylation and mitochondrial translocation of Drp1. Our research illuminated a possible new mechanism by which P. gingivalis promotes endothelial dysfunction.

Stabilization Of The CN3 5- Anion In Recoverable High-pressure Ln3 O2 (CN3 ) (Ln=La, Eu, Gd, Tb, Ho, Yb) Oxoguanidinates.

A series of isostructural Ln3 O2 (CN3 ) (Ln=La, Eu, Gd, Tb, Ho, Yb) oxoguanidinates was synthesized under high-pressure (25-54 GPa) high-temperature (2000-3000 K) conditions in laser-heated diamond anvil cells. The crystal structure of this novel class of compounds was determined via synchrotron single-crystal X-ray diffraction (SCXRD) as well as corroborated by X-ray absorption near edge structure (XANES) measurements and density functional theory (DFT) calculations. The Ln3 O2 (CN3 ) solids are composed of the hitherto unknown CN3 5- guanidinate anion-deprotonated guanidine. Changes in unit cell volumes and compressibility of Ln3 O2 (CN3 ) (Ln=La, Eu, Gd, Tb, Ho, Yb) compounds are found to be dictated by the lanthanide contraction phenomenon. Decompression experiments show that Ln3 O2 (CN3 ) compounds are recoverable to ambient conditions. The stabilization of the CN3 5- guanidinate anion at ambient conditions provides new opportunities in inorganic and organic synthetic chemistry.

Revealing Phosphorus Nitrides up to the Megabar Regime: Synthesis of α'-P3 N5, δ-P3 N5 and PN2.

Invited for the cover of this issue are Dominique Laniel (University of Edinburgh), Florian Trybel (University of Linköping), and their colleagues. The image depicts a bridge built of the newly discovered δ-P3 N5 solid with the structure featuring PN6 units, a previously missing connection between the carbon group elements nitrides and chalcogens nitrides. Read the full text of the article at 10.1002/chem.202201998.

Revealing Phosphorus Nitrides up to the Megabar Regime: Synthesis of α'-P3 N5, δ-P3 N5 and PN2.

Non-metal nitrides are an exciting field of chemistry, featuring a significant number of compounds that can possess outstanding material properties. These properties mainly rely on maximizing the number of strong covalent bonds, with crosslinked XN6 octahedra frameworks being particularly attractive. In this study, the phosphorus-nitrogen system was studied up to 137 GPa in laser-heated diamond anvil cells, and three previously unobserved phases were synthesized and characterized by single-crystal X-ray diffraction, Raman spectroscopy measurements and density functional theory calculations. δ-P3 N5 and PN2 were found to form at 72 and 134 GPa, respectively, and both feature dense 3D networks of the so far elusive PN6 units. The two compounds are ultra-incompressible, having a bulk modulus of K0 =322 GPa for δ-P3 N5 and 339 GPa for PN2 . Upon decompression below 7 GPa, δ-P3 N5 undergoes a transformation into a novel α'-P3 N5 solid, stable at ambient conditions, that has a unique structure type based on PN4 tetrahedra. The formation of α'-P3 N5 underlines that a phase space otherwise inaccessible can be explored through materials formed under high pressure.

A potent synthetic nanobody with broad-spectrum activity neutralizes SARS-CoV-2 virus and the Omicron variant BA.1 through a unique binding mode.

The major challenge to controlling the COVID pandemic is the rapid mutation rate of the SARS-CoV-2 virus, leading to the escape of the protection of vaccines and most of the neutralizing antibodies to date. Thus, it is essential to develop neutralizing antibodies with broad-spectrum activity targeting multiple SARS-CoV-2 variants. Here, we report a synthetic nanobody (named C5G2) obtained by phage display and subsequent antibody engineering. C5G2 has a single-digit nanomolar binding affinity to the RBD domain and inhibits its binding to ACE2 with an IC50 of 3.7 nM. Pseudovirus assays indicated that monovalent C5G2 could protect the cells from infection with SARS-CoV-2 wild-type virus and most of the viruses of concern, i.e., Alpha, Beta, Gamma and Omicron variants. Strikingly, C5G2 has the highest potency against Omicron BA.1 among all the variants, with an IC50 of 4.9 ng/mL. The cryo-EM structure of C5G2 in complex with the spike trimer showed that C5G2 binds to RBD mainly through its CDR3 at a conserved region that does not overlap with the ACE2 binding surface. Additionally, C5G2 binds simultaneously to the neighboring NTD domain of the spike trimer through the same CDR3 loop, which may further increase its potency against viral infection. Third, the steric hindrance caused by FR2 of C5G2 could inhibit the binding of ACE2 to RBD as well. Thus, this triple-function nanobody may serve as an effective drug for prophylaxis and therapy against Omicron as well as future variants.

MineBL: A Battery-Free Localization Scheme with Binocular Camera for Coal Mine.

Accurate localization in underground coal mining is a challenging technology in coal mine safety production. This paper proposes a low-cost battery-free localization scheme based on depth images, called MineBL. The main idea is to utilize the battery-free low-cost reflective balls as position nodes and realize underground target localization with a series of algorithms. In particular, the paper designs a data enhancement strategy based on small-target reorganization to increase the identification accuracy of tiny position nodes. Moreover, a novel ranging algorithm based on multi-filter cooperative denoising has been proposed, and an optimized weighted centroid location algorithm based on multilateral location errors has been designed to minimize underground localization errors. Many experiments in the indoor laboratories and the underground coal mine laboratories have been conducted, and the experimental results have verified that MineBL has good localization performances, with localization errors less than 30 cm in 95% of cases. Therefore, MineBL has great potential to provide a low-cost and effective solution for precise target localization in complex underground environments.

Toward COVID-19 Contact Tracing though Wi-Fi Probes.

COVID-19 is currently the biggest threat that challenges all of humankind's health and property. One promising and effective way to control the rapid spreading of this infection is searching for primary close contacts of the confirmed cases. In response, we propose COVID-19 Tracer, a low-cost passive searching system to find COVID-19 patients' close contacts. The main idea is utilizing ubiquitous WiFi probe requests to describe the location similarity, which is then achieved by two designed range-free judgment indicators: location similarity coefficient and close contact distance. We have carried out extensive experiments in a school office building, and the experimental results show an average accuracy of more than 98%, demonstrating our system's effectiveness in judging close contacts. Last but not least, we have developed a prototype system for a school building to find potential close contacts.

Localization with Transfer Learning Based on Fine-Grained Subcarrier Information for Dynamic Indoor Environments.

Indoor localization provides robust solutions in many applications, and Wi-Fi-based methods are considered some of the most promising means for optimizing indoor fingerprinting localization accuracy. However, Wi-Fi signals are vulnerable to environmental variations, resulting in data across different times being subjected to different distributions. To solve this problem, this paper proposes an across-time indoor localization solution based on channel state information (CSI) fingerprinting via multi-domain representations and transfer component analysis (TCA). We represent the format of CSI readings in multiple domains, extending the characterization of fine-grained information. TCA, a domain adaptation method in transfer learning, is applied to shorten the distribution distances among several CSI readings, which overcomes various CSI distribution problems at different time periods. Finally, we present a modified Bayesian model averaging approach to integrate the multi-domain outcomes and give the estimated positions. We conducted test-bed experiments in three scenarios on both personal computer (PC) and smartphone platforms in which the source and target fingerprinting data were collected across different days. The experimental results showed that our method outperforms state-of-the-art methods in localization accuracy.

ARS: Adaptive Robust Synchronization for Underground Coal Wireless Internet of Things.

Clock synchronization is still a vital and challenging task for underground coal wireless internet of things (IoT) due to the uncertainty of underground environment and unreliability of communication links. Instead of considering on-demand driven clock synchronization, this paper proposes a novel Adaptive Robust Synchronization (ARS) scheme with packets loss for mine wireless environment. A clock synchronization framework that is based on Kalman filtering is first proposed, which can adaptively adjust the sampling period of each clock and reduce the communication overhead in single-hop networks. The proposed scheme also solves the problem of outliers in data packets with time-stamps. In addition, this paper extends the ARS algorithm to multi-hop networks. Additionally, the upper and lower bounds of error covariance expectation are analyzed in the case of incomplete measurement. Extensive simulations are conducted in order to evaluate the performance. In the simulation environment, the clock accuracy of ARS algorithm is improved by 7.85% when compared with previous studies for single-hop networks. For multi-hop networks, the proposed scheme improves the accuracy by 12.56%. The results show that the proposed algorithm has high scalability, robustness, and accuracy, and can quickly adapt to different clock accuracy requirements.

A CSI-Based Indoor Fingerprinting Localization with Model Integration Approach.

Convenient indoor positioning has become an urgent need due to the improvement it offers to quality of life, which inspires researchers to focus on device-free indoor location. In areas covered with Wi-Fi, people in different locations will to varying degrees have an impact on the transmission of channel state information (CSI) of Wi-Fi signals. Because space is divided into several small regions, the idea of classification is used to locate. Therefore, a novel localization algorithm is put forward in this paper based on Deep Neural Networks (DNN) and a multi-model integration strategy. The approach consists of three stages. First, the local outlier factor (LOF), the anomaly detection algorithm, is used to correct the abnormal data. Second, in the training phase, 3 DNN models are trained to classify the region fingerprints by taking advantage of the processed CSI data from 3 antennas. Third, in the testing phase, a model fusion method named group method of data handling (GMDH) is adopted to integrate 3 predicted results of multiple models and give the final position result. The test-bed experiment was conducted in an empty corridor, and final positioning accuracy reached at least 97%.

IPL: Image-Assisted Person Localization for Underground Coal Mines.

Underground personnel localization is highly important in the operations of coal mines. Considering the special underground environment, this paper introduces a novel localization scheme based on step detection and image recognition technologies, which makes use of unique characteristics of the underground environment like the dark environment and the miner's lamp. Since the underground topology is relatively simple, the miner can be located only by step information. However, the localization with step information always causes the problem of cumulative error. To solve this problem, we rebuild a special base station with a camera in a dark underground environment. A miner's lamp, which every miner carries, can simply transform to irradiate unique shapes (such as triangles, rectangles, and circles) and every coal miner at the base station can identify these shapes based on image recognition technologies. Thus, we can obtain the miner's precise position when he/she is passing by a base station. In that way, we can correct the localization results to solve cumulative error. We implemented our algorithm in indoor and underground environments. The experimental results show that 96% of spatial errors were 2.5 m or less.

Localization with Graph Diffusion Property.

Node localization is an essential issue in wireless sensor networks (WSNs). Many range-free localization methods have been proposed to satisfy the requirement of low-system cost. However, some range-free methods only depend on network connectivity, and others only utilize the proximity information attached in neighborhood ordering. To employ the strength of the above two aspects, this paper introduces a new metric system called Combined and Weighted Diffusion Distance (CWDD). CWDD is designed to obtain the relative distance among nodes based on both graph diffusion property and neighbor information. We implement our design by embedding CWDD into two well-known localization algorithms and evaluate it by extensive simulations. Results show that our design improves the localization performance in large scale and non-uniform sensor networks, which reduces positioning errors by as much as 26%.

Sensitive determination of positional isomers of benzenediols in human urine by boronate affinity capillary electrophoresis with chemiluminescence detection.

A boronate ACE coupled with chemiluminescence (CL) detection was developed for sensitive determination of three isomeric benzenediols, which was based on the principle of an inhibited effect of borate complexation on the CL reaction between luminol and potassium hexacyanoferrate (K3 Fe(CN)6 ) in alkaline solution. The effects of some important factors on CE separation and CL intensity were systemically investigated. Baseline separation of isomeric benzenediols including o-benzenediol, m-benzenediol, and p-benzenediol was achieved by using a mobile phase of 40 mmol/L glycine-NaOH buffer at pH 9.4 containing 0.8 mmol/L luminol and 0.4 mol/L 4-iodophenylboronic acid. The calibration curves of the analytes by plotting the peak height against corresponding concentration were linear over the range of 4.5 × 10(-8) ∼ 4.5 × 10(-5) mol/L for p-benzenediol, 6.8 × 10(-8) ∼ 2.7 × 10(-5) mol/L for m-benzenediol, and 9.0 × 10(-8) ∼ 4.5 × 10(-5) mol/L for o-benzenediol. The corresponding detection limits for p-, m-, and o-benzenediols were 2.8 × 10(-8) mol/L (68 amol), 3.2 × 10(-8) mol/L (108.4 amol), and 3.7 × 10(-8) mol/L (125.8 amol; S/N = 3), respectively. The proposed method has been successfully applied to the analysis of trace benzenediols in spiked human urine sample and the recoveries were >97.2%. Our primary result demonstrated the proposed CE-CL method has great potential for biomarker determination in clinical diagnosis.

Onion cryptochrome 1 (AcCRY1) regulates photomorphogenesis and photoperiod flowering in Arabidopsis and exploration of its functional mechanisms under blue light.

Cryptochromes (CRYs), as blue-light photoreceptors, play a crucial role in regulating flowering time and hypocotyl and cotyledon development. Their physiological functions have been extensively studied in various plant species. However, research on onions remains limited. In this study, we identified AcCRY1 and conducted preliminary investigations into its function. Our results demonstrate that AcCRY1 possesses a conserved domain typical of cryptochromes with high homology to those found in monocots. Furthermore, we examined the expression level of AcCRY1 in onion. The green tissues is significantly higher compared to non-green tissues, and it exhibits a significant response to blue-light induction. AcCRY1 demonstrates cytoplasmic localization under blue-light conditions, while it localizes in the nucleus during darkness, indicating a strong dependence on blue-light for its subcellular distribution. In comparison to cry1, overexpression of AcCRY1 leads to a significant shorten in seedling hypocotyl length, notable expansion of cotyledons, and acceleration of flowering time. The yeast two-hybrid experiment demonstrated the in vitro interaction between AcCRY1, AcCOP1, and AcSPA1. Additionally, BIFC analysis confirmed their interaction in Onion epidermis. Notably, under blue-light conditions, a significantly enhanced binding activity was observed compared to dark conditions. These findings establish a functional foundation for the regulatory role of AcCRY1 in important physiological processes of onion and provide initial insights into the underlying molecular mechanisms.

Stabilization of N6 and N8 anionic units and 2D polynitrogen layers in high-pressure scandium polynitrides.

Nitrogen catenation under high pressure leads to the formation of polynitrogen compounds with potentially unique properties. The exploration of the entire spectrum of poly- and oligo-nitrogen moieties is still in its earliest stages. Here, we report on four novel scandium nitrides, Sc2N6, Sc2N8, ScN5, and Sc4N3, synthesized by direct reaction between yttrium and nitrogen at 78-125 GPa and 2500 K in laser-heated diamond anvil cells. High-pressure synchrotron single-crystal X-ray diffraction reveals that in the crystal structures of the nitrogen-rich Sc2N6, Sc2N8, and ScN5 phases nitrogen is catenated forming previously unknown N66- and N86- units and ∞ 2 ( N 5 3 - ) anionic corrugated 2D-polynitrogen layers consisting of fused N12 rings. Density functional theory calculations, confirming the dynamical stability of the synthesized compounds, show that Sc2N6 and Sc2N8 possess an anion-driven metallicity, while ScN5 is an indirect semiconductor. Sc2N6, Sc2N8, and ScN5 solids are promising high-energy-density materials with calculated volumetric energy density, detonation velocity, and detonation pressure higher than those of TNT.

Diverse high-pressure chemistry in Y-NH3BH3 and Y-paraffin oil systems.

The yttrium-hydrogen system has gained attention because of near-ambient temperature superconductivity reports in yttrium hydrides at high pressures. We conducted a study using synchrotron single-crystal x-ray diffraction (SCXRD) at 87 to 171 GPa, resulting in the discovery of known (two YH3 phases) and five previously unknown yttrium hydrides. These were synthesized in diamond anvil cells by laser heating yttrium with hydrogen-rich precursors-ammonia borane or paraffin oil. The arrangements of yttrium atoms in the crystal structures of new phases were determined on the basis of SCXRD, and the hydrogen content estimations based on empirical relations and ab initio calculations revealed the following compounds: Y3H11, Y2H9, Y4H23, Y13H75, and Y4H25. The study also uncovered a carbide (YC2) and two yttrium allotropes. Complex phase diversity, variable hydrogen content in yttrium hydrides, and their metallic nature, as revealed by ab initio calculations, underline the challenges in identifying superconducting phases and understanding electronic transitions in high-pressure synthesized materials.

Synthesis of Ultra-Incompressible and Recoverable Carbon Nitrides Featuring CN4 Tetrahedra.

Carbon nitrides featuring three-dimensional frameworks of CN4 tetrahedra are one of the great aspirations of materials science, expected to have a hardness greater than or comparable to diamond. After more than three decades of efforts to synthesize them, no unambiguous evidence of their existence has been delivered. Here, the high-pressure high-temperature synthesis of three carbon-nitrogen compounds, tI14-C3 N4 , hP126-C3 N4 , and tI24-CN2 , in laser-heated diamond anvil cells, is reported. Their structures are solved and refined using synchrotron single-crystal X-ray diffraction. Physical properties investigations show that these strongly covalently bonded materials, ultra-incompressible and superhard, also possess high energy density, piezoelectric, and photoluminescence properties. The novel carbon nitrides are unique among high-pressure materials, as being produced above 100 GPa they are recoverable in air at ambient conditions.