Establishment and identification of bladder cancer cell sheet.

Cell sheet technology (CST) has primarily been applied in tissue engineering for repair purposes. Our preliminary research indicates that an in vivo prostate cancer model established using CST outperforms traditional cell suspension methods. However, the potential for CST to be used with bladder cancer cells has not yet been explored. In this study, we investigated the ability of two bladder cancer cell lines, T24 and 5637, to form cell sheets. We found that T24 cells successfully formed cell sheets. We then performed staining to evaluate the integrity, specific markers, and proliferation characteristics of the T24 cell sheets. Our findings demonstrate that bladder cancer cell sheets can be established, providing a valuable tool for both in vivo and in vitro bladder cancer studies and for personalized drug selection for patients.

The O-Defective g-ZnO Sensor for VOC Gases: The Adsorption-Desorption, Electronic, and Sensitivity Properties.

Adsorption-desorption performance, electronic properties, and sensitivity of O-defective g-ZnO (ODZO) gas sensors for volatile organic compounds (VOCs) are calculated using density functional theory and nonequilibrium Green's formalism. The VOCs are CH2O, CH4, C2H4O, CH4O, and C2H6. The intrinsic g-ZnO (IZO) and ODZO exhibit strong adsorption capabilities for C2H4O and CH4O. The IZO (0.118 e) and ODZO (0.059 e), which act as electron donors, exhibit the highest charge transfer to CH2O, indicating a strong interaction. The VOCs adsorption on the IZO and ODZO systems maintain nonmagnetic semiconductor characteristics. Additionally, the introduction of an O-defect causes the adsorption energy and charge transfer amount of ODZO to show an overall decrease, indicating better desorption ability. Notably, the sensitivity results show that the ODZO gas sensors exhibit high sensitivity to CH2O (39.3%), C2H4O (29.0%), and CH4O (19.6%) at a voltage of 2.6 V, consistent with the adsorption-desorption performance and electronic properties.

Fe-Doped SrCoOx FET Sensors for Extreme Alkaline pH Sensing.

The accurate measurement of pH in highly alkaline environments is critical for various industrial applications but remains a complex task. This paper discusses the development of novel Fe-doped SrCoOx-based FET sensors for the detection of extreme alkaline pH levels. Through a comprehensive investigation of the effects of Fe doping on the structure, electrical properties, and sensing performance of SrCoOx, we have identified the optimal doping level that significantly enhances the sensor's performance in highly alkaline conditions. With a Fe doping level of 5 mol %, the sensitivity of the sensor improves to 0.86 lg(Ω)/pH while maintaining the response rate. Further increasing the Fe doping to 10 mol % results in a sensor that demonstrates favorable response time, a suitable pH range, and a linear correlation between lg(R) and pH. The combination of X-ray photoelectron spectroscopy and X-ray diffraction analysis provides insight into the regulation mechanisms of Fe doping on the crystal structure, electronic structure, and oxygen vacancy concentration of SrCoOx. Our findings indicate that Fe doping leads to an increase in oxygen vacancy concentration and a decrease in the energy barrier for oxygen ion migration, which contributes to the improved sensing performance of the Fe-doped SrCoOx sensors. Additionally, the study highlights the influence of oxygen vacancy concentration on the electrical properties of SrCoOx. Precise control over the concentration of oxygen vacancies is crucial for optimizing the sensitivity and response speed of SrCoOx FET sensors under extreme alkalinity conditions.

g-ZnO/Si9C15: a S-scheme heterojunction with high carrier mobility for photo-electro catalysis of water splitting.

The g-ZnO/Si9C15 heterojunction is designed, and its stability, electronic properties and photo-electro catalytic properties, and the impact of biaxial strain on the electronic and photocatalytic properties are investigated. The g-ZnO/Si9C15 heterojunction has a staggered (type-II) band structure (band gap is 1.770 eV), following the S-scheme mechanism. A high electron mobility of 5.113 × 103 cm2 V-1 s-1 and hole mobility of 3.324 × 104 cm2 V-1 s-1 are obtained in the zigzag and armchair directions, respectively. Suitable oxidation and reduction potentials are obtained such that photocatalytic water decomposition can occur at pH = 0-14, and the corrected solar to hydrogen (STH) efficiency is up to 35.4%. The absorption of visible light is enhanced, and the power conversion efficiency (PCE) is 15.1%. The electro-catalytic hydrogen evolution reaction (HER) is more likely to occur at the Si9C15 interface with a low over-voltage of 0.190 V. Under biaxial strain, due to the controllable band structure, the corrected STH efficiency and PCE increase to 42.7% and 16.7%, respectively. The heterojunction shows potential value in the field of high-efficiency solar devices and catalytic materials for water splitting.

USP31 serves as a potential biomarker for predicting prognosis and immune responses for clear cell renal cell carcinoma via single-cell and bulk RNA-sequencing.

BACKGROUND: Currently, there is no research available on the prognosis, potential effect and therapeutic value of USP31 in clear cell renal cell carcinoma (ccRCC). To address this gap, the present study aimed to shed light on its potential roles and possible mechanisms in ccRCC. METHODS: R software was utilized to conduct bioinformatics analyses with the data derived from The Cancer Genome Atlas (i.e. KIRC) and Gene Expression Omnibus datasets. The expression of USP31 in ccRCC was validated by a PCR. The independent prognostic ability of USP31 was evaluated by Cox regression analysis. We conducted gene set enrichment analysis (GSEA) to explore the potential USP31-related pathways. We also discussed the relationships between USP31 and immunity, by predicting its possible upstream transcription factors (TFs) by ChEA3. RESULTS: In ccRCC, USP31 demonstrated a high level of expression and this increased expression was correlated with a poor prognosis (p < 0.05). Through univariate and multivariate Cox regression analysis, USP31 was identified as an independent prognostic factor for ccRCC (p < 0.05). Furthermore, eight USP31-related pathways were identified by GSEA (p < 0.05). Moreover, USP31 was found to be associated with microsatellite instability, tumor microenvironment, a variety of immune cells and immune checkpoints and immune infiltration (p < 0.05). Additionally, Patients with high USP31 expression in ccRCC were shown to have better curative effects after immunotherapy (p < 0.05). Finally, we found that AR, USF1, MXI1 and CLOCK could be the potential upstream TFs of USP31. CONCLUSIONS: USP31 could serve as a potential biomarker for predicting both prognosis and immune responses, revealing its potential mechanisms of TF-USP31 mRNA networks in ccRCC.

KDM4B: A promising oncology therapeutic target.

Epigenetic modifications are significant in tumor pathogenesis, wherein the process of histone demethylation is indispensable for regulating gene transcription, apoptosis, DNA replication, and repair of damaged DNA. The lysine demethylases (KDMs) serve an essential role in the aforementioned processes, with particular emphasis on the KDM4 family, also referred to as JMJD2. Multiple studies have underscored the significance of the KDM4 family in the regulation of various biological processes including, but not limited to, the cell cycle, DNA repair mechanisms, signaling pathways, and the progression of tumor formation. Nevertheless, it is imperative to elucidate the underlying mechanism of KDM4B, which belongs to the KDM4 gene family. This review presents a comprehensive examination of the structure, mechanism, and function of KDM4B, as well as a critical analysis of the current body of research pertaining to its involvement in tumorigenesis and development. Furthermore, this review explores the potential therapeutic strategies that specifically target KDM4B.

Comprehensive Visual Question Answering on Point Clouds through Compositional Scene Manipulation.

Visual Question Answering on 3D Point Cloud (VQA-3D) is an emerging yet challenging field that aims at answering various types of textual questions given an entire point cloud scene. To tackle this problem, we propose the CLEVR3D, a large-scale VQA-3D dataset consisting of 171K questions from 8,771 3D scenes. Specifically, we develop a question engine leveraging 3D scene graph structures to generate diverse reasoning questions, covering the questions of objects' attributes (i.e., size, color, and material) and their spatial relationships. Through such a manner, we initially generated 44K questions from 1,333 real-world scenes. Moreover, a more challenging setup is proposed to remove the confounding bias and adjust the context from a common-sense layout. Such a setup requires the network to achieve comprehensive visual understanding when the 3D scene is different from the general co-occurrence context (e.g., chairs always exist with tables). To this end, we further introduce the compositional scene manipulation strategy and generate 127K questions from 7,438 augmented 3D scenes, which can improve VQA-3D models for real-world comprehension. Built upon the proposed dataset, we baseline several VQA-3D models, where experimental results verify that the CLEVR3D can significantly boost other 3D scene understanding tasks. Our code and dataset are publicly available at https://github.com/yanx27/CLEVR3D.

A Long-Life and Excellent Rate-Capability Aqueous Zn-Benzoquinone Battery Enabled by Iodine-Catalyzed Cathode.

Benzoquinone (BQ) is considered to be a desirable cathode material for aqueous zinc-based batteries. The major limitations of BQ electrode are the severe sublimation and poor electrical conductivity, which results in serious mass loss during electrode preparation and inferior rate performance. In this study, iodine (I2 ) species are utilized as an efficient catalyst for the highly reversible conversion of BQ/BQ2- couple in the Zn-BQ battery system, wherein N-doped porous carbon is employed as a host material for anchoring the BQ molecule. In the combination electrode (denoted as BQ-I@NPC) with 1wt% I2 additive where I2 can serve as a carrier to accelerates the Zn2+ transmission, and reduce the voltage hysteresis of the electrode. As a result, the BQ-I@NPC cathode delivers a high specific capacity of ≈482 mAh g-1 at 0.25 A g-1 , realizing a high energy density of 545 Wh kg-1 (based on BQ), which is the highest values among reported organic cathode materials for aqueous Zn-based batteries. Also, a high BQ loading (8 mg cm-2 ) can be attained, and achieving a superior cycling stability with a capacity retention of ≈80% after 20,000 times at 10 C. The work proposes an effective approach toward high performance organic electrode materials.

Acetaminophen impairs ferroptosis in the hippocampus of septic mice by regulating glutathione peroxidase 4 and ferroptosis suppressor protein 1 pathways.

BACKGROUND: Neuronal ferroptosis is a major cause of cognitive impairment and mortality in patients with sepsis-associated encephalopathy (SAE). A low dose of acetaminophen (APAP) in septic mice can prevent ferroptosis in the hippocampal tissue; however, the underlying mechanism is unknown. This study aimed to investigate the mechanism by which APAP reduces ferroptosis in the hippocampal tissues of septic mice. METHODS: A mouse model of SAE was established, and the ferroptosis pathway inhibitors RSL3 and iFSP1+RSL3 were used in addition to APAP for the interventions, respectively. The 7-day survival rate of the mice was recorded, and cognitive function was examined using the Morris water maze test. Hematoxylin and eosin staining was performed to observe hippocampal tissue damage. Hippocampal iron and malondialdehyde (MDA) were measured using chemical colorimetric methods. Immunofluorescence was used to detect the reactive oxygen species (ROS) content in hippocampal tissues. RESULTS: RSL3 reversed the efficacy of APAP on improving cognitive dysfunction in septic mice but did not obviously reverse the survival rate of mice enhanced by APAP. RSL3 aggravated APAP-induced hippocampal tissue damage in mice attenuated by APAP. RSL3 inhibited glutathione peroxidase 4 (GPX4) expression and increased ferroptosis suppressor protein 1 (FSP1) and 4-hydroxy-2-nonenal (4-HNE) expression. RSL3 also reversed the effects of APAP in reducing iron, MDA, and ROS levels in the hippocampal tissues of septic mice. iFSP1+RSL3 further reversed the effect of APAP on ameliorating cognitive dysfunction in septic mice and successfully reversed the survival rate of mice enhanced by APAP. iFSP1+RSL3 aggravated APAP-induced cerebral hippocampal damage. iFSP1+RSL3 inhibited both GPX4 and FSP1, further reversing the effect of APAP on the reduction in iron, 4-HNE, ROS, and MDA levels in the cerebral hippocampus of mice with sepsis. CONCLUSION: These data suggest that APAP inhibits ferroptosis in the cerebral hippocampus of septic mice through the GPX4 and FSP1 pathways.

A machine learning model based on MRI for the preoperative prediction of bladder cancer invasion depth.

OBJECTIVES: To construct and validate a prediction model based on full-sequence MRI for preoperatively evaluating the invasion depth of bladder cancer. METHODS: A total of 445 patients with bladder cancer were divided into a seven-to-three training set and test set for each group. The radiomic features of lesions were extracted automatically from the preoperative MRI images. Two feature selection methods were performed and compared, the key of which are the Least Absolute Shrinkage and Selection Operator (LASSO) and the Max Relevance Min Redundancy (mRMR). The classifier of the prediction model was selected from six advanced machine-learning techniques. The receiver operating characteristic (ROC) curves and the area under the curve (AUC) were applied to assess the efficiency of the models. RESULTS: The models with the best performance for pathological invasion prediction and muscular invasion prediction consisted of LASSO as the feature selection method and random forest as the classifier. In the training set, the AUC of the pathological invasion model and muscular invasion model were 0.808 and 0.828. Furthermore, with the mRMR as the feature selection method, the external invasion model based on random forest achieved excellent discrimination (AUC, 0.857). CONCLUSIONS: The full-sequence models demonstrated excellent accuracy for preoperatively predicting the bladder cancer invasion status. CLINICAL RELEVANCE STATEMENT: This study introduces a full-sequence MRI model for preoperative prediction of the depth of bladder cancer infiltration, which could help clinicians to recognise pathological features associated with tumour infiltration prior to invasive procedures. KEY POINTS: • Full-sequence MRI prediction model performed better than Vesicle Imaging-Reporting and Data System (VI-RADS) for preoperatively evaluating the invasion status of bladder cancer. • Machine learning methods can extract information from T1-weighted image (T1WI) sequences and benefit bladder cancer invasion prediction.

Competition between p53 and YY1 determines PHGDH expression and malignancy in bladder cancer.

PURPOSE: Serine metabolism is frequently dysregulated in many types of cancers and the tumor suppressor p53 is recently emerging as a key regulator of serine metabolism. However, the detailed mechanism remains unknown. Here, we investigate the role and underlying mechanisms of how p53 regulates the serine synthesis pathway (SSP) in bladder cancer (BLCA). METHODS: Two BLCA cell lines RT-4 (WT p53) and RT-112 (p53 R248Q) were manipulated by applying CRISPR/Cas9 to examine metabolic differences under WT and mutant p53 status. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) and non-targeted metabolomics analysis were adopted to identify metabolomes changes between WT and p53 mutant BLCA cells. Bioinformatics analysis using the cancer genome atlas and Gene Expression Omnibus datasets and immunohistochemistry (IHC) staining was used to investigate PHGDH expression. Loss-of-function of PHGDH and subcutaneous xenograft model was adopted to investigate the function of PHGDH in mice BLCA. Chromatin immunoprecipitation (Ch-IP) assay was performed to analyze the relationships between YY1, p53, SIRT1 and PHGDH expression. RESULTS: SSP is one of the most prominent dysregulated metabolic pathways by comparing the metabolomes changes between wild-type (WT) p53 and mutant p53 of BLCA cells. TP53 gene mutation shows a positive correlation with PHGDH expression in TCGA-BLCA database. PHGDH depletion disturbs the reactive oxygen species homeostasis and attenuates the xenograft growth in the mouse model. Further, we demonstrate WT p53 inhibits PHGDH expression by recruiting SIRT1 to the PHGDH promoter. Interestingly, the DNA binding motifs of YY1 and p53 in the PHGDH promoter are partially overlapped which causes competition between the two transcription factors. This competitive regulation of PHGDH is functionally linked to the xenograft growth in mice. CONCLUSION: YY1 drives PHGDH expression in the context of mutant p53 and promotes bladder tumorigenesis, which preliminarily explains the relationship between high-frequency mutations of p53 and dysfunctional serine metabolism in bladder cancer.

Molecular characterization of a novel amalgavirus infecting lilium spp. in China.

A novel plant virus with a double-stranded (ds) RNA genome was detected in Lilium spp. in China by high-throughput sequencing and tentatively named "lily amalgavirus 2" (LAV2). The genomic RNA of LAV2 is 3432 nucleotides (nt) in length and contains two open reading frames (ORFs) that putatively encode a '1 + 2' fusion protein of 1053 amino acids (aa), generated by a '+1' programmed ribosomal frameshift (PRF). ORF1 encodes a putative 386-aa protein of unknown function, and ORF2 overlaps ORF1 by 350 nt and encodes a putative 783-aa protein with conserved RNA-dependent RNA polymerase (RdRp) motifs. The '+1' ribosomal frameshifting motif, UUU_CGN, which is highly conserved among amalgaviruses, is also found in LAV2. Sequence analysis showed that the complete genome shared 46.04%-51.59% nucleotide sequence identity with those of members of the genus Amalgavirus and had the most similarity (51.59% sequence identity) to lily amalgavirus 1 (accession no. OM782323). Phylogenetic analysis based on RdRp amino acid sequences showed that LAV2 clustered with members of the genus Amalgavirus. Overall, our data suggest that LAV2 is a new member of the genus Amalgavirus.

Iodine doping induced activation of covalent organic framework cathodes for Li-ion batteries.

Covalent organic frameworks (COFs) are considered as promising candidate organic electrode materials for lithium-ion batteries (LIBs) because of their relatively high capacity, ordered nanopores, and limited solubility in electrolyte. However, the practical capacity of COF materials is mainly affected by their low electronic/ionic conductivity and the deep-buried active sites inside the COFs. Here, we synthesize an iodine doped ß-ketoenamine-linked COF (2,6-diaminoanthraquinone and 1,3,5-triformylphloroglucinol, denoted as COF-I) by a facile one-pot solvothermal reaction. The introduction of iodine can make the COF more lithiophilic inside and exhibit high intrinsic ion/electron transport, ensuring more accessible active sites of the COFs. Consequently, when used as the cathode of LIBs, COF-I demonstrates a high initial discharge capacity of 140 mA h g-1 at 0.2 A g-1, and excellent cycling stability with 92% capacity retention after 1000 cycles. Furthermore, a reversible capacity of 95 mA h g-1 at 1.0 A g-1 is also achieved after 300 cycles. Our study provides a facile way to develop high-performance COF electrode materials for LIB applications.

Integrative analysis of ferroptosis regulators for clinical prognosis based on deep learning and potential chemotherapy sensitivity of prostate cancer.

Exploring useful prognostic markers and developing a robust prognostic model for patients with prostate cancer are crucial for clinical practice. We applied a deep learning algorithm to construct a prognostic model and proposed the deep learning-based ferroptosis score (DLFscore) for the prediction of prognosis and potential chemotherapy sensitivity in prostate cancer. Based on this prognostic model, there was a statistically significant difference in the disease-free survival probability between patients with high and low DLFscore in the The Cancer Genome Atlas (TCGA) cohort (P < 0.0001). In the validation cohort GSE116918, we also observed a consistent conclusion with the training set (P = 0.02). Additionally, functional enrichment analysis showed that DNA repair, RNA splicing signaling, organelle assembly, and regulation of centrosome cycle pathways might regulate prostate cancer through ferroptosis. Meanwhile, the prognostic model we constructed also had application value in predicting drug sensitivity. We predicted some potential drugs for the treatment of prostate cancer through AutoDock, which could potentially be used for prostate cancer treatment.

Histone demethylase KDM4B contributes to advanced clear cell renal carcinoma and association with copy number variations and cell cycle progression.

Advanced renal cell carcinoma (RCC) poses a threat to patient survival. Epigenetic remodelling is the pathogenesis of renal cancer. Histone demethylase 4B (KDM4B) is overexpressed in many cancers through various pathways. However, the role of KDM4B in clear cell renal carcinoma has not yet been elucidated. The differential expression of KDM4B was first verified by analysing public databases. The expression of KDM4B in fresh tissues and pathology slides was further analysed by western blotting and immunohistochemical staining. KDM4B overexpression and knockdown cell lines were also established. Cell Counting Kit-8 (CCK-8) assay was used to detect cell growth. Transwell assays were performed to assess cell migration. Xenografts were used to evaluate tumour growth and metastasis in vivo. Finally, KDM4B expression levels associated with copy number variation (CNV) and cell cycle stage were evaluated based on single-cell RNA sequencing data. KDM4B was expressed at higher levels in tumour tissues than in the adjacent normal tissues. High levels of KDM4B are associated with worse pathological features and poorer prognosis. KDM4B also promotes cell proliferation and migration in vitro, as well as tumour growth and metastasis in vivo. Tumour cells with high KDM4B expression exhibited higher CNV levels and a greater proportion of cells in the G1/S transition phase. Our results confirm that KDM4B promotes the progression of clear cell renal carcinoma, is correlated with poor prognosis, and may be related to high levels of CNV and cell cycle progression.

Cuproptosis-Related Genes Are Associated with Cell Cycle and Serve as the Prognostic Signature for Clear Cell Renal Cell Carcinoma.

Cuproptosis is a newly discovered type of cell death. The role and potential mechanism of Cuproptosis-related genes (CRGs) in the prognosis of cancer patients are not fully understood. In this study, we included two cohorts of clear cell renal cell carcinoma patients, TCGA and E-MTAB-1980. The TCGA cohort is used as a training set to construct a CRG signature using the LASSO-cox regression analysis, and E-MTAB-1980 is used as a cohort for verification. A total of eight genes (FDX1, LIAS, LIPT1, DLAT, PDHA1, MTF1, GLS, CDKN2A) were screened to construct a prognostic model in the TCGA cohort. There is a significant difference in OS (p < 0.0001) between the high and low cuproptosis score group, and a similar difference is also observed in the OS (p = 0.0054) of the E-MTAB-1980 cohort. The area under the ROC curves (AUC) were 0.87, 0.82, and 0.78 at 1, 3, and 5 years in the TCGA cohort, respectively. Finally, gene set enrichment analysis revealed that CRGs were associated with cell cycle and mitotic signaling pathways.

Preparation and characterization of ZnO/graphene/graphene oxide/multi-walled carbon nanotube composite aerogels.

ZnO/Graphene (G)/Graphene Oxide (GO)/Multi-walled Carbon Nanotube (MCNT) composite aerogels with a three-dimensional porous structure were prepared by the sol-gel method under average temperature and alkaline conditions, combined with freeze-drying process and heat treatment process. The photocatalytic degradation of Rhodamine B (RhB) was mainly studied. The scanning electron microscope (SEM) test results showed that the morphology uniformity of the ZnO/G/GO/MCNT composite aerogel was significantly enhanced, which effectively solving the agglomeration problem of MCNT and ZnO. The photocatalytic degradation test results of RhB show that due to the synergistic effect of physical adsorption and photocatalytic degradation, the total degradation efficiency of RhB by ZnO/G/GO/MCNT could reach 86.8%, which is 3.3 times higher than that of ZnO. In addition, the synergistic effect of ZnO and G effectively hinders the recombination of photo-generated electron-hole pairs and enhances photocatalytic activity. The ZnO/G/GO/MCNT composite aerogel can be applied in the visible light catalytic degradation of water pollution.

Electronic, Magnetic, and Optical Properties of Metal Adsorbed g-ZnO Systems.

2D ZnO is one of the most attractive materials for potential applications in photocatalysis, gas and light detection, ultraviolet light-emitting diodes, resistive memory, and pressure-sensitive devices. The electronic structures, magnetic properties, and optical properties of M (Li, Na, Mg, Ca, or Ga) and TM (Cr, Co, Cu, Ag, or Au) adsorbed g-ZnO were investigated with density functional theory (DFT). It is found that the band structure, charge density difference, electron spin density, work function, and absorption spectrum of g-ZnO can be tuned by adsorbing M or TM atoms. More specifically, the specific charge transfer occurs between g-ZnO and adsorbed atom, indicating the formation of a covalent bond. The work functions of M adsorbed g-ZnO systems are obviously smaller than that of intrinsic g-ZnO, implying great potential in high-efficiency field emission devices. The Li, Na, Mg, Ca, Ga, Ag, or Au adsorbed g-ZnO systems, the Cr adsorbed g-ZnO system, and the Co or Cu adsorbed g-ZnO systems exhibit non-magnetic semiconductor proprieties, magnetic semiconductor proprieties, and magnetic metal proprieties, respectively. In addition, the magnetic moments of Cr, Co, or Cu adsorbed g-ZnO systems are 4 µ B, 3 µ B, or 1 µ B, respectively, which are mainly derived from adsorbed atoms, suggesting potential applications in nano-scale spintronics devices. Compared with the TM absorbed g-ZnO systems, the M adsorbed g-ZnO systems have more obvious absorption peaks for visible light, particularly for Mg or Ca adsorbed g-ZnO systems. Their absorption peaks appear in the near-infrared region, suggesting great potential in solar photocatalysis. Our work contributes to the design and fabrication of high-efficiency field emission devices, nano-scale spintronics devices, and visible-light responsive photocatalytic materials.

Hybrid Triboelectric-Electromagnetic Magnetic Energy Harvester-Based Sensing for Wireless Monitoring of Transmission Lines.

Magnetic energy is an abundant and persistent form of energy radiating from various sources. Here, a hybrid triboelectric-electromagnetic magnetic energy harvester (HMEH) system consisting of a modified pendulum unit is proposed, interacting mechanically with two multilayered TENGs and remotely with Cu coils. Systematic studies are conducted on magneto-mechano-energy conversion from power transmission lines. The pendulum is made out of a thin PET plate, with two permanent magnets stuck at each side of the free end of the PET plate. Two multilayered TENGs (each of which has one layer fixed at the same angle while other layers are set free) are located at both sides of the pendulum unit. The coils and the magnets make up the electromagnetic generator (EMG). Multilayered TENGs are connected in parallel with the EMG (each unit is connected to an independent rectifying bridge), and it is possible to charge a 100 µF capacitor to 4.78 V within 55 s. The HMEH system is used to power up a thermometer continuously via a 47 µF capacitor. Furthermore, a design for a wireless early warning system for potential fire hazards due to overheating is realized, revealing potential applications for self-powered wireless monitoring of transmission lines.