EHMT2 Suppresses ARRB1 Transcription and Activates the Hedgehog Signaling to Promote Malignant Phenotype and Stem Cell Property in Oral Squamous Cell Carcinoma

Oral squamous cell carcinoma (OSCC) represents the primary subtype of head and neck squamous cell carcinoma (HNSCC), characterized by a high morbidity and mortality rate. Although previous studies have established specific correlations between euchromatic histone lysine methyltransferase 2 (EHMT2), a histone lysine methyltransferase, and the malignant phenotype of OSCC cells, its biological functions in OSCC remain largely unknown. This study, grounded in bioinformatics predictions, aims to clarify the influence of EHMT2 on the malignant behavior of OSCC cells and delve into the underlying mechanisms. EHMT2 exhibited high expression in OSCC tissues and demonstrated an association with poor patient outcomes. Artificial EHMT2 silencing in OSCC cells, achieved through lentiviral vector infection, significantly inhibited colony formation, migration, invasion, and cell survival. Regarding the mechanism, EHMT2 was found to bind the promoter of arrestin beta 1 (ARRB1), thereby suppressing its transcription through H3K9me2 modification. ARRB1, in turn, was identified as a negative regulator of the Hedgehog pathway, leading to a reduction in the proteins GLI1 and PTCH1. Cancer stem cells (CSCs) were enriched through repeated sphere formation assays in two OSCC cell lines. EHMT2 was found to activate the Hedgehog pathway, thus promoting sphere formation, migration and invasion, survival, and tumorigenic activity of the OSCC-CSCs. Notably, these effects were counteracted by the additional overexpression of ARRB1. In conclusion, this study provides novel evidence suggesting that EHMT2 plays specific roles in enhancing stem cell properties in OSCC by modulating the ARRB1-Hedgehog signaling cascade.

Multi-Level Structural Enhancement Mechanism of the Excellent Mechanical Properties of Dung Beetle Leg Joint

The multi-level structure is a strategy to enhance the mechanical properties of dung beetle leg joints. Under external loads, the microstructure facilitates energy dissipation and prevents crack extension. The macrostructure aids in transferring the load to more reliable parts. The connection established by the two hemispheres is present in the dung beetle leg joint. The micron-layered and nanoscale crystal structures further constitute the leg joint with excellent mechanical properties. The maximum compression fracture force is ≈101000 times the weight of the leg. Here, the structural design within the dung beetle leg joints and reveal the resulting mechanical response and enhancement mechanisms is determined. A series of beetle leg joints where the macrostructure and microstructure of the dung beetle leg provide mechanical strength at critical strains while avoiding catastrophic failure by transferring the load from the joint to the exoskeleton of the femur is highlighted. Nanocrystalline structures and fiber layers contribute to crack propagation of the exoskeleton. Based on this, the bionic joint with multi-level structures using resin and conducted a series of tests to verify their effectiveness is prepared. This study provides a new idea for designing and optimizing high-load joints in engineering.

Improved RRT* Algorithm for Disinfecting Robot Path Planning

In this paper, an improved APF-GFARRT* (artificial potential field-guided fuzzy adaptive rapidly exploring random trees) algorithm based on APF (artificial potential field) guided sampling and fuzzy adaptive expansion is proposed to solve the problems of weak orientation and low search success rate when randomly expanding nodes using the RRT (rapidly exploring random trees) algorithm for disinfecting robots in the dense environment of disinfection operation. Considering the inherent randomness of tree growth in the RRT* algorithm, a combination of APF with RRT* is introduced to enhance the purposefulness of the sampling process. In addition, in the context of RRT* facing dense and restricted environments such as narrow passages, adaptive step-size adjustment is implemented using fuzzy control. It accelerates the algorithm's convergence and improves search efficiency in a specific area. The proposed algorithm is validated and analyzed in a specialized environment designed in MATLAB, and comparisons are made with existing path planning algorithms, including RRT, RRT*, and APF-RRT*. Experimental results show the excellent exploration speed of the improved algorithm, reducing the average initial path search time by about 46.52% compared to the other three algorithms. In addition, the improved algorithm exhibits faster convergence, significantly reducing the average iteration count and the average final path cost by about 10.01%. The algorithm's enhanced adaptability in unique environments is particularly noteworthy, increasing the chances of successfully finding paths and generating more rational and smoother paths than other algorithms. Experimental results validate the proposed algorithm as a practical and feasible solution for similar problems.

The role of the mitochondrial ribosomal protein family in detecting hepatocellular carcinoma and predicting prognosis, immune features, and drug sensitivity

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most common types of malignant tumors, with a slow onset, rapid progression, and frequent recurrence. Previous research has implicated mitochondrial ribosomal genes in the development, metastasis, and prognosis of various cancers. However, further research is necessary to establish a link between mitochondrial ribosomal protein (MRP) family expression and HCC diagnosis, prognosis, ferroptosis-related gene (FRG) expression, m6A modification-related gene expression, tumor immunity, and drug sensitivity.

METHODS

Bioinformatics resources were used to analyze data from patients with HCC retrieved from the TCGA, ICGC, and GTEx databases (GEPIA, UALCAN, Xiantao tool, cBioPortal, STRING, Cytoscape, TISIDB, and GSCALite).

RESULTS

Among the 82 MRP family members, 14 MRP genes (MRPS21, MRPS23, MRPL9, DAP3, MRPL13, MRPL17, MRPL24, MRPL55, MRPL16, MRPL14, MRPS17, MRPL47, MRPL21, and MRPL15) were significantly upregulated differentially expressed genes (DEGs) in HCC tumor samples in comparison to normal samples. Receiver-operating characteristic curve analysis indicated that all 14 DEGs show good diagnostic performance. Furthermore, TCGA analysis revealed that the mRNA expression of 39 MRPs was associated with overall survival (OS) in HCC. HCC was divided into two molecular subtypes (C1 and C2) with distinct prognoses using clustering analysis. The clusters showed different FRG expression and m6A methylation profiles and immune features, and prognostic models showed that the model integrating 5 MRP genes (MRPS15, MRPL3, MRPL9, MRPL36, and MRPL37) and 2 FRGs (SLC1A5 and SLC5A11) attained a greater clinical net benefit than three other prognostic models. Finally, analysis of the CTRP and GDSC databases revealed several potential drugs that could target prognostic MRP genes.

CONCLUSION

We identified 14 MRP genes as HCC diagnostic markers. We investigated FRG and m6A modification-related gene expression profiles and immune features in patients with HCC, and developed and validated a model incorporating MRP and FRG expression that accurately and reliably predicts HCC prognosis and may predict disease progression and treatment response.

Research on the Preparation and Application of Fixed-Abrasive Tools Based on Solid-Phase Reactions for Sapphire Wafer Lapping and Polishing

Single-crystal sapphire specimen (α-Al2O3) have been widely applied in the semiconductor industry, microelectronics, and so on. In order to shorten the production time and improve the processing efficiency of sapphire processing, an integrated fixed-abrasive tool (FAT) based on solid-phase reactions is proposed in this article. The optimal FAT composition is determined using a preliminary experiment and orthogonal experiments. The mass fraction of the abrasives is chosen as 55 wt%, and the mass ratio of SiO2/Cr2O3 is 2. Surface roughness Ra decreased from 580.4 ± 52.7 nm to 8.1 ± 0.7 nm after 150 min, and the average material removal rate was 14.3 ± 1.2 nm/min using the prepared FAT. Furthermore, FAT processing combined with chemical mechanical polishing (CMP) was shortened by 1.5 h compared to the traditional sapphire production process in obtaining undamaged sapphire surfaces with a roughness of Ra < 0.4 nm, which may have the potential to take the place of the fine lapping and rough polishing process.

Method for Denoising the Vibration Signal of Rotating Machinery through VMD and MODWPT

The vibration signals from rotating machinery are constantly mixed with other noises during the acquisition process, which has a negative impact on the accuracy of signal feature extraction. For vibration signals from rotating machinery, the conventional linear filtering-based denoising method is ineffective. To address this issue, this paper suggests an enhanced signal denoising method based on maximum overlap discrete wavelet packet transform (MODWPT) and variational mode decomposition (VMD). VMD decomposes the vibration signal of rotating machinery to produce a set of intrinsic mode functions (IMFs). By computing the composite weighted entropy (CWE), the phantom IMF component is then removed. In the end, the sensitive component is obtained by computing the value of the degree of difference (DID) after the high-frequency noise component has been decomposed through MODWPT. The denoised signal reconstructs the signal's intrinsic characteristics as well as the denoised high-frequency IMF component. This technique was used to analyze the simulated and real-world signals of gear faults and it was compared to wavelet threshold denoising (WTD), empirical mode decomposition reconstruction denoising (EMD-RD), and ensemble empirical mode decomposition wavelet threshold denoising (EEMD-WTD). The outcomes demonstrate that this method can accurately extract the signal feature information while filtering out the noise components in the signal.

Antimicrobial Mechanisms and Clinical Application Prospects of Antimicrobial Peptides

Antimicrobial peptides are a type of small-molecule peptide that widely exist in nature and are components of the innate immunity of almost all living things. They play an important role in resisting foreign invading microorganisms. Antimicrobial peptides have a wide range of antibacterial activities against bacteria, fungi, viruses and other microorganisms. They are active against traditional antibiotic-resistant strains and do not easily induce the development of drug resistance. Therefore, they have become a hot spot of medical research and are expected to become a new substitute for fighting microbial infection and represent a new method for treating drug-resistant bacteria. This review briefly introduces the source and structural characteristics of antimicrobial peptides and describes those that have been used against common clinical microorganisms (bacteria, fungi, viruses, and especially coronaviruses), focusing on their antimicrobial mechanism of action and clinical application prospects.

Analyzing the Effect of Particle Shape on Deformation Mechanism during Cutting Simulation of SiC P/Al Composites

To analyze the effect of particle shape on deformational behavior in the cutting simulation process for metal matrix composites (MMCs), two 2D mesoscopic-based finite element (FE) models reinforced with randomly distributed circular and irregular polygonal particles were developed. Different material properties (metal matrix phase, particle reinforced phase) and the properties of the particle-matrix interface were comprehensively considered in the proposed FE model. Systematic cutting experiments were conducted to compare the differences between two modeling approaches with respect to particle fracture, chip formation, cutting force and surface integrity. The results show that the irregular polygonal particle model is closer to the microstructure of MMCs, and is better able to reflect the deformation behavior of particles. The simulation model with irregular polygonal particles is even able to capture more details of the impact caused by particles, reflecting variations in the cutting force in the actual cutting process. The initiation and propagation of microcracks is mainly determined on the basis of particle geometry and further affects chip formation. Both models are able to correctly reflect surface defects, but the irregular polygonal particle model provides a more comprehensive prediction for the subsurface damage of MMCs.