Isoquercitrin promotes ferroptosis and oxidative stress in nasopharyngeal carcinoma via the AMPK/NF-κB pathway.

Isoquercitrin has been discovered with various biological properties, including anticancer, anti-inflammation, antioxidation, and neuroprotection. The aim of this study is to explore the efficacy of isoquercitrin in nasopharyngeal carcinoma (NPC) and to disclose its potential regulating mechanisms. CNE1 and HNE1 cells were treated with various concentrations of isoquercitrin. Ferrostatin-1 (Fer-1, a ferroptosis inhibitor) and alpha-lipoic acid (ALA, an activator of the AMP-activated protein kinase [AMPK] pathway) treatments were conducted to verify the effects of isoquercitrin, respectively. Cell viability, proliferation, reactive oxygen species (ROS) generation, and lipid peroxidation were determined, respectively. GPX4 expression and ferroptosis- and pathway-related protein expression were measured. A xenograft tumor model was constructed by subcutaneously inoculating CNE1 cells into the middle groin of each mouse. We found that the IC50 values of CNE1 and HNE1 cells were 392.45 and 411.38 µM, respectively. CNE1 and HNE1 viability and proliferation were both markedly reduced with the increasing concentration of isoquercitrin. ROS generation and lipid peroxidation were both enhanced with declined ferroptosis-related markers under isoquercitrin treatment. The nuclear factor kappa B (NF-κB) pathway, the AMPK pathway, and the interleukin (IL)-1ß expression were all markedly suppressed by isoquercitrin. Moreover, isoquercitrin restrained the tumor growth and enhanced lipid peroxidation and ferroptosis in vivo. Interestingly, both Fer-1 and ALA treatments distinctly offset isoquercitrin-induced effects in vitro and in vivo. These findings indicated that isoquercitrin might enhance oxidative stress and ferroptosis in NPC via AMPK/NF-κB p65 inhibition.

EIF4A3-induced circFIP1L1 represses miR-1253 and promotes radiosensitivity of nasopharyngeal carcinoma.

BACKGROUND: Radiation is currently used to be a mainstay of salvage therapy for nasopharyngeal carcinoma (NPC), however, development of radioresistance largely limits the radiation efficacy. Circular RNAs (circRNAs) have been shown to affect NPC progression, but its role in radioresistance remain unclear. METHODS: The circular structure of circFIP1L1(circ_0069740) was verified by RNA-sequencing, RT-PCR based on gDNA or cDNA, RNase R treatment, and actinomycin D treatment. Cellular localization of circFIP1L1 and miR-1253 was detected by nucleoplasmic separation and/or fluorescence in situ hybridization. Expression of non-coding RNAs and mRNAs was detected by qRT-PCR, protein expression was detected by Western blot. Functionally, EdU, CCK-8, and colony formation experiments were employed to assess cell proliferation, flow cytometry was adopted to estimate cell cycle and apoptosis. Xenograft tumor growth was performed to detect the role of circFIP1L1 in vivo. Mechanistically, we examined the interplay between miR-1253 and circFIP1L1 or EIF4A3 through dual-luciferase reporter assay. The potential regulatory impacts of EIF4A3 on circFIP1L1 or PTEN was examined by RNA immunoprecipitation and RNA pull-down assays. RESULTS: CircFIP1L1 overexpression and miR-1253 knockdown repressed NPC cell proliferation, facilitated NPC cell apoptosis, and enhanced NPC radiosensitivity. Mechanistically, circFIP1L1 was revealed to repress miR-1253 by binding to it, and EIF4A3 is a target gene of miR-1253. CircFIP1L1 regulated NPC proliferation, apoptosis, and radiosensitivity through miR-1253/EIF4A3. Moreover, we found that EIF4A3 bound to FIP1L1 mRNA transcript and induced circFIP1L1 formation, and thus stabilizing PTEN mRNA. CONCLUSION: Our findings suggested that EIF4A3-induced circFIP1L1 repressed NPC cell proliferation, facilitated NPC cell apoptosis, and enhanced NPC radiosensitivity by miR-1253.

Role of CD23 Activated ERK Signaling Pathway in the Pathogenesis of Eosinophilic Chronic Sinusitis with Nasal Polyps.

Objective: In the context of the rising prevalence of eosinophilic chronic sinusitis accompanied by nasal polyps, this study aims toinvestigate the role of CD23 in the pathogenesis of eosinophilic chronic sinusitis with nasal polyps. Methods: The cross-sectional study was conducted, 75 patients with chronic sinusitis and nasal polyps treated in our hospital from January 2019 to May 2021 were selected, including 40 cases of eosinophilic patients with the average age of 29.92 years and 35 cases of non-eosinophilic patients with the average age of 30.05 years and 30 patients with the average age of 30.14 years who underwent skull base benign tumor resection in our hospital were selected as the control group, the expression of CD23 in polyp tissue was detected by immunohistochemistry, and the expression of CD23, p-ERK and CCL20 in polyp tissue were detected by Western blot. Specifically, tissue samples were processed and subjected to staining using specific antibodies targeting CD23. The stained sections were then visualized under a microscope to determine the expression levels of CD23. CD23, p-ERK, and CCL20 expressions in polyp tissue were evaluated via Western blot. Total protein was extracted, separated on a gel, transferred to a membrane, and probed with specific antibodies. Chemiluminescence allowed visualization and quantification of protein expressions. Results: Immunohistochemistry showed that CD23 expression was high in the eosinophilic group but low in the non-eosinophilic and control groups. The relative expression levels of CD23 protein, p-ERK protein, and CCL20 protein in polyp tissue s of the eosinophilic group were (0.892 ± 0.092), (0.733 ± 0.101) and (0.813 ± 0.106), respectively, which were significantly higher than those in non-eosinophilic group and control group (P < .05). The relative expression levels of CD23 protein, p-ERK protein, and CCL20 protein in the non-eosinophilic group were (0.461 ± 0.087), 0.412 ± 0.096) and (0.424 ± 0.098), which were significantly higher than those in the control group (P < .05). The relative expression level of CD23 protein in the eosinophilic group was positively correlated with the relative expression levels of p-ERK protein and CCL20 protein (P < .05). The Lund-Kennedy score in the eosinophilic group was (6.10 ± 1.01), which was significantly higher than that in the non-eosinophilic group (P < .05). The relative expression level of CD23 protein in the eosinophilic group was positively correlated with Lund-Kennedy score (P < .05). Conclusion: Eosinophilic chronic sinusitis with nasal polyp mucosal tissue CD23 expression is up-regulated, which is positively correlated with the ERK signaling pathway and disease severity. This study provides valuable insights into potential therapeutic targets that could be explored to develop future treatment modalities. The potential clinical significance of the study is to reveal the important role of CD23 in the pathogenesis of chronic sinusitis with nasal polyps. The upward adjustment of CD23 is positively related to the severity of the disease, which provides valuable guidance for future treatment strategies. This discovery may provide new ways for the development of CD23 treatment methods, so as to better control the progress of the disease of eosinophilic chronic sinusitis with nasal polyps. Further research can explore the molecular mechanism of CD23 regulation, further verify the feasibility of CD23 as the treatment target, and evaluate the potential value of CD23 as a prognostic logo.

A Micro-Topography Measurement and Compensation Method for the Key Component Surface Based on White-Light Interferometry.

The grinding grooves of material removal machining and the residues of a machining tool on the key component surface cause surface stress concentration. Thus, it is critical to carry out precise measurements on the key component surface to evaluate the stress concentration. Based on white-light interferometry (WLI), we studied the measurement distortion caused by the reflected light from the steep side of the grinding groove being unable to return to the optical system for imaging. A threshold value was set to eliminate the distorted measurement points, and the cubic spline algorithm was used to interpolate the eliminated points for compensation. The compensation result agrees well with the atomic force microscope (AFM) measurement result. However, for residues on the surface, a practical method was established to obtain a microscopic 3D micro-topography point cloud and a super-depth-of-field fusion image simultaneously. Afterward, the semantic segmentation network U-net was adopted to identify the residues in the super-depth-of-field fusion image and achieved a recognition accuracy of 91.06% for residual identification. Residual feature information, including height, position, and size, was obtained by integrating the information from point clouds and super-depth-of-field fusion images. This work can provide foundational data to study surface stress concentration.

METTL3-mediated m6A modification promotes processing and maturation of pri-miRNA-19a to facilitate nasopharyngeal carcinoma cell proliferation and invasion.

The interplay between N6-methyladenosine (m6A) modification and microRNAs (miRs) participates in cancer progression. This study is conducted to explore the role of miR-19a-3p in nasopharyngeal carcinoma (NPC) cell proliferation and invasion. Reverse transcription quantitative polymerase chain reaction and Western blot showed that miR-19a-3p was upregulated in NPC tissues and cells and related to poor prognosis, methyltransferase-like 3 (METTL3) was highly expressed, whereas BMP and activin membrane-bound inhibitor (BAMBI) was weakly expressed in NPC tissues and cells. miR-19a-3p downregulation inhibited cell proliferation and invasion, whereas miR-19a-3p overexpression played the opposite role. m6A quantification and m6A RNA immunoprecipitation assays showed that METTL3-mediated m6A modification promoted the processing and maturation of pri-miR-19a via DiGeorge syndrome critical region gene 8 (DGCR8). Dual-luciferase assay showed that BAMBI was a target of miR-19a-3p. The rescue experiments showed that BAMBI downregulation reversed the role of miR-19a-3p inhibition in NPC cells. A xenograft tumor model showed that METTL3 downregulation inhibited tumor growth via the miR-19a-3p/BAMBI in vivo. Overall, our findings elicited that METTL3-mediated m6A modification facilitated the processing and maturation of pri-miR-19a via DGCR8 to upregulate miR-19a-3p, and miR-19a-3p inhibited BAMBI expression to promote NPC cell proliferation and invasion, thus driving NPC progression.

Structural basis of dimerization and dual W-box DNA recognition by rice WRKY domain.

In rice, the critical regulator of the salicylic acid signalling pathway is OsWRKY45, a transcription factor (TF) of the WRKY TF family that functions by binding to the W-box of gene promoters, but the structural basis of OsWRKY45/W-box DNA recognition is unknown. Here, we show the crystal structure of the DNA binding domain of OsWRKY45 (OsWRKY45-DBD, i.e. the WRKY and zinc finger domain) in complex with a W-box DNA. Surprisingly, two OsWRKY45-DBD molecules exchange ß4-ß5 strands to form a dimer. The domain swapping occurs at the hinge region between the ß3 and ß4 strands, and is bridged and stabilized by zinc ion via coordinating residues from different chains. The dimer contains two identical DNA binding domains that interact with the major groove of W-box DNA. In addition to hydrophobic and direct hydrogen bonds, water mediated hydrogen bonds are also involved in base-specific interaction between protein and DNA. Finally, we discussed the cause and consequence of domain swapping of OsWRKY45-DBD, and based on our work and that of previous studies present a detailed mechanism of W-box recognition by WRKY TFs. This work reveals a novel dimerization and DNA-binding mode of WRKY TFs, and an intricate picture of the WRKY/W-box DNA recognition.

PFBNet: a priori-fused boosting method for gene regulatory network inference.

BACKGROUND: Inferring gene regulatory networks (GRNs) from gene expression data remains a challenge in system biology. In past decade, numerous methods have been developed for the inference of GRNs. It remains a challenge due to the fact that the data is noisy and high dimensional, and there exists a large number of potential interactions. RESULTS: We present a novel method, namely priori-fused boosting network inference method (PFBNet), to infer GRNs from time-series expression data by using the non-linear model of Boosting and the prior information (e.g., the knockout data) fusion scheme. Specifically, PFBNet first calculates the confidences of the regulation relationships using the boosting-based model, where the information about the accumulation impact of the gene expressions at previous time points is taken into account. Then, a newly defined strategy is applied to fuse the information from the prior data by elevating the confidences of the regulation relationships from the corresponding regulators. CONCLUSIONS: The experiments on the benchmark datasets from DREAM challenge as well as the E.coli datasets show that PFBNet achieves significantly better performance than other state-of-the-art methods (Jump3, GEINE3-lag, HiDi, iRafNet and BiXGBoost).

Hybrid Fiber Optic Sensor, Based on the Fabry⁻Perot Interference, Assisted with Fluorescent Material for the Simultaneous Measurement of Temperature and Pressure.

Herein we design a fiber sensor able to simultaneously measure the temperature and the pressure under harsh conditions, such as strong electromagnetic interference and high pressure. It is built on the basis of the fiber-optic Fabry⁻Perot (F⁻P) interference and the temperature sensitive mechanism of fluorescent materials. Both halogen lamps and light-emitting diodes (LED) are employed as the excitation light source. The reflected light from the sensor contains the low coherent information of interference cavity and the fluorescent lifetime. This information is independent due to the separate optical path and the different demodulation device. It delivers the messages of pressure and temperature, respectively. It is demonstrated that the sensor achieved pressure measurement at the range of 120⁻400 KPa at room temperature with a sensitivity of 1.5 nm/KPa. Moreover, the linearity of pressure against the cavity length variation was over 99.9%. In the meantime, a temperature measurement in the range of 25⁻80 °C, with a sensitivity of 0.0048 ms/°C, was obtained. These experimental results evince that this kind of sensor has a simple configuration, low-cost, and easy fabrication. As such, it can be particularly applied to many fields.

Gene regulatory network inference using PLS-based methods.

BACKGROUND: Inferring the topology of gene regulatory networks (GRNs) from microarray gene expression data has many potential applications, such as identifying candidate drug targets and providing valuable insights into the biological processes. It remains a challenge due to the fact that the data is noisy and high dimensional, and there exists a large number of potential interactions. RESULTS: We introduce an ensemble gene regulatory network inference method PLSNET, which decomposes the GRN inference problem with p genes into p subproblems and solves each of the subproblems by using Partial least squares (PLS) based feature selection algorithm. Then, a statistical technique is used to refine the predictions in our method. The proposed method was evaluated on the DREAM4 and DREAM5 benchmark datasets and achieved higher accuracy than the winners of those competitions and other state-of-the-art GRN inference methods. CONCLUSIONS: Superior accuracy achieved on different benchmark datasets, including both in silico and in vivo networks, shows that PLSNET reaches state-of-the-art performance.

A centroid-based gene selection method for microarray data classification.

For classification problems based on microarray data, the data typically contains a large number of irrelevant and redundant features. In this paper, a new gene selection method is proposed to choose the best subset of features for microarray data with the irrelevant and redundant features removed. We formulate the selection problem as a L1-regularized optimization problem, based on a newly defined linear discriminant analysis criterion. Instead of calculating the mean of the samples, a kernel-based approach is used to estimate the class centroid to define both the between-class separability and the within-class compactness for the criterion. Theoretical analysis indicates that the global optimal solution of the L1-regularized criterion can be reached with a general condition, on which an efficient algorithm is derived to the feature selection problem in a linear time complexity with respect to the number of features and the number of samples. The experimental results on ten publicly available microarray datasets demonstrate that the proposed method performs effectively and competitively compared with state-of-the-art methods.

Measurement system with high accuracy for laser beam quality.

Presently, most of the laser beam quality measurement system collimates the optical path manually with low efficiency and low repeatability. To solve these problems, this paper proposed a new collimated method to improve the reliability and accuracy of the measurement results. The system accuracy controlled the position of the mirror to change laser beam propagation direction, which can realize the beam perpendicularly incident to the photosurface of camera. The experiment results show that the proposed system has good repeatability and the measuring deviation of M2 factor is less than 0.6%.

Multi-Objective Process Parameter Optimization of Ultrasonic Rolling Combining Machine Learning and Non-Dominated Sorting Genetic Algorithm-II.

Ultrasonic rolling is an effective technique for enhancing surface integrity, and surface integrity is closely related to fatigue performance. The process parameters of ultrasonic rolling critically affect the improvement of surface integrity. This study proposes an optimization method for process parameters by combining machine learning (ML) with the NSGA-II. Five ML models were trained to establish relationships between process parameters and surface residual stress, hardness, and surface roughness by incorporating feature augmentation and physical information. The best-performing model was selected and integrated with NSGA-II for multi-objective optimization. Ultrasonic rolling tests based on a uniform design were performed, and a dataset was established. The objective was to maximize surface residual stress and hardness while minimizing surface roughness. For test specimens with an initial surface roughness of 0.54 µm, the optimized process parameters were a static pressure of 900 N, a spindle speed of 75 rpm, a feed rate of 0.19 mm/r, and rolling once. Using optimized parameters, the surface residual stress reached -920.60 MPa, surface hardness achieved 958.23 HV, surface roughness reduced to 0.32 µm, and contact fatigue life extended to 3.02 × 107 cycles, representing a 52.5% improvement compared to untreated specimens and an even more significant improvement over without parameter optimization.

An Effective DNA-Based File Storage System for Practical Archiving and Retrieval of Medical MRI Data.

DNA-based data storage is a new technology in computational and synthetic biology, that offers a solution for long-term, high-density data archiving. Given the critical importance of medical data in advancing human health, there is a growing interest in developing an effective medical data storage system based on DNA. Data integrity, accuracy, reliability, and efficient retrieval are all significant concerns. Therefore, this study proposes an Effective DNA Storage (EDS) approach for archiving medical MRI data. The EDS approach incorporates three key components (i) a novel fraction strategy to address the critical issue of rotating encoding, which often leads to data loss due to single base error propagation; (ii) a novel rule-based quaternary transcoding method that satisfies bio-constraints and ensure reliable mapping; and (iii) an indexing technique designed to simplify random search and access. The effectiveness of this approach is validated through computer simulations and biological experiments, confirming its practicality. The EDS approach outperforms existing methods, providing superior control over bio-constraints and reducing computational time. The results and code provided in this study open new avenues for practical DNA storage of medical MRI data, offering promising prospects for the future of medical data archiving and retrieval.

BO-DNA: Biologically optimized encoding model for a highly-reliable DNA data storage.

DNA data storage is a promising technology that utilizes computer simulation, and synthetic biology, offering high-density and reliable digital information storage. It is challenging to store massive data in a small amount of DNA without losing the original data since nonspecific hybridization errors occur frequently and severely affect the reliability of stored data. This study proposes a novel biologically optimized encoding model for DNA data storage (BO-DNA) to overcome the reliability problem. BO-DNA model is developed by a new rule-based mapping method to avoid data drop during the transcoding of binary data to premier nucleotides. A customized optimization algorithm based on a tent chaotic map is applied to maximize the lower bounds that help to minimize the nonspecific hybridization errors. The robustness of BO-DNA is computed by four bio-constraints to confirm the reliability of newly generated DNA sequences. Experimentally, different medical images are encoded and decoded successfully with 12%-59% improved lower bounds and optimally constrained-based DNA sequences reported with 1.77bit/nt average density. BO-DNA's results demonstrate substantial advantages in constructing reliable DNA data storage.

Evolutionary approach to construct robust codes for DNA-based data storage.

DNA is a practical storage medium with high density, durability, and capacity to accommodate exponentially growing data volumes. A DNA sequence structure is a biocomputing problem that requires satisfying bioconstraints to design robust sequences. Existing evolutionary approaches to DNA sequences result in errors during the encoding process that reduces the lower bounds of DNA coding sets used for molecular hybridization. Additionally, the disordered DNA strand forms a secondary structure, which is susceptible to errors during decoding. This paper proposes a computational evolutionary approach based on a synergistic moth-flame optimizer by Levy flight and opposition-based learning mutation strategies to optimize these problems by constructing reverse-complement constraints. The MFOS aims to attain optimal global solutions with robust convergence and balanced search capabilities to improve DNA code lower bounds and coding rates for DNA storage. The ability of the MFOS to construct DNA coding sets is demonstrated through various experiments that use 19 state-of-the-art functions. Compared with the existing studies, the proposed approach with three different bioconstraints substantially improves the lower bounds of the DNA codes by 12-28% and significantly reduces errors.

Intracellular FGF1 promotes invasion and migration in thyroid carcinoma via HMGA1 independent of FGF receptors.

Background: Fibroblast growth factor 1 (FGF1) is extensively amplified in many tumors and accelerates tumor invasion and metastasis. However, the role and precise molecular mechanism by which FGF1 participates in thyroid cancer (TC) are still unclear. Methods: Quantitative real-time polymerase chain reaction- and western blotting were used to detect the mRNA and protein levels of FGF1, high mobility group A (HMGA1), epithelial-to-mesenchymal transition (EMT)-related factors, and FGFs in both TC tissues and cell lines. Immunohistochemistry was conducted to examine the expression of FGF1 and HMGA1. Immunofluorescence staining was used to detect the coexpression of FGF1 and HMGA1. Transwell and wound healing assays were conducted to evaluate the effects of FGF1 on the capacity of invasion and migration in cells. Results: FGF1 was upregulated in papillary thyroid carcinoma (PTC) tissues and cell lines and was relatively higher in PTC tissues with cervical lymph node metastasis. Furthermore, FGF1 promotes invasion and metastasis through the EMT pathway. Mechanistically, FGF1 promotes EMT through intracellular function independent of FGF receptors. Interestingly, we demonstrated that FGF1 could upregulate HMGA1 in TC cells, and the correlation of FGF1 and HMGA1 was positive in PTC tissues. FGF1 and HMGA1 had obvious colocalization in the nucleus. We further revealed that FGF1 promotes the invasion and migration of TC cells through the upregulation of HMGA1. Conclusion: Intracellular FGF1 could promote invasion and migration in TC by mediating the expression of HMGA1 independent of FGF receptors, and FGF1 may be an effective therapeutic target in TC.

FTH1 indicates poor prognosis and promotes metastasis in head and neck squamous cell carcinoma.

Background: Currently, ferritin heavy chain (FTH1) has been increasingly found to play a crucial role in cancer as a core regulator of ferroptosis, while its role of non-ferroptosis in head and neck squamous cell carcinoma (HNSCC) is still unclear. Methods: Herein, we analyzed the expression level of FTH1 in HNSCC using TCGA database, and FTH1 protein in HNSCC tissues and cell lines was determined by immunohistochemistry (IHC) and western blotting, respectively. Then, its prognostic value and relationship with clinical parameters were investigated in HNSCC patients. Additionally, the biological function of FTH1 in HNSCC was explored. Results: The current study showed that FTH1 is significantly overexpressed in HNSCC tissues and related to poor prognosis and lymph node metastasis of HNSCC. FTH1 knockdown could suppress the metastasis and epithelial-mesenchymal transition (EMT) process of HNSCC. Conclusion: Our findings indicate that FTH1 plays a critical role in the progression and metastasis of HNSCC and can serve as a promising prognostic factor and therapeutic target in HNSCC.

A novel hierarchical clustering algorithm for gene sequences.

BACKGROUND: Clustering DNA sequences into functional groups is an important problem in bioinformatics. We propose a new alignment-free algorithm, mBKM, based on a new distance measure, DMk, for clustering gene sequences. This method transforms DNA sequences into the feature vectors which contain the occurrence, location and order relation of k-tuples in DNA sequence. Afterwards, a hierarchical procedure is applied to clustering DNA sequences based on the feature vectors. RESULTS: The proposed distance measure and clustering method are evaluated by clustering functionally related genes and by phylogenetic analysis. This method is also compared with BlastClust, CD-HIT-EST and some others. The experimental results show our method is effective in classifying DNA sequences with similar biological characteristics and in discovering the underlying relationship among the sequences. CONCLUSIONS: We introduced a novel clustering algorithm which is based on a new sequence similarity measure. It is effective in classifying DNA sequences with similar biological characteristics and in discovering the relationship among the sequences.

A neural network-based framework to understand the type 2 diabetes-related alteration of the human gut microbiome.

The identification of microbial markers adequate to delineate the disease-related microbiome alterations from the complex human gut microbiota is of great interest. Here, we develop a framework combining neural network (NN) and random forest, resulting in 40 marker species and 90 marker genes identified from the metagenomic data set (185 healthy and 183 type 2 diabetes [T2D] samples), respectively. In terms of these markers, the NN model obtained higher accuracy in classifying the T2D-related samples than other methods; the interaction network analyses identified the key species and functional modules; the regression analysis determined that fasting blood glucose is the most significant factor (p < 0.05) in the T2D-related alteration of the human gut microbiome. We also observed that those marker species varied little across the case and control samples greatly shift in the different stages of the T2D development, suggestive of their important roles in the T2D-related microbiome alteration. Our study provides a new way of identifying the disease-related biomarkers and analyzing the role they may play in the development of the disease.