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Background TNBC is the most aggressive breast cancer with higher recurrence and mortality rate than other types of breast cancer. There is an urgent need for identification of therapeutic agents with unique mode of action for overcoming current challenges in TNBC treatment. Methods Different inhibitors were used to study the cell death manner of DMOCPTL . RNA silencing was used to evaluate the functions of GPX4 in ferroptosis and apoptosis of TNBC cells and functions of EGR1 in apoptosis. Immunohistochemical assay of tissue microarray were used for investigating correlation of GPX4 and EGR1 with TNBC. Computer-aided docking and small molecule probe were used for study the binding of DMOCPTL with GPX4. Results DMOCPTL , a derivative of natural product parthenolide, exhibited about 15-fold improvement comparing to that of the parent compound PTL for TNBC cells. The cell death manner assay showed that the anti-TNBC effect of DMOCPTL mainly by inducing ferroptosis and apoptosis through ubiquitination of GPX4. The probe of DMOCPTL assay indicated that DMOCPTL induced GPX4 ubiquitination by directly binding to GPX4 protein. To the best of our knowledge, this is the first report of inducing ferroptosis through ubiquitination of GPX4. Moreover, the mechanism of GPX4 regulation of apoptosis is still obscure. Here, we firstly reveal that GPX4 regulated mitochondria-mediated apoptosis through regulation of EGR1 in TNBC cells. Compound 13 , the prodrug of DMOCPTL , effectively inhibited the growth of breast tumor and prolonged the lifespan of mice in vivo, and no obvious toxicity was observed. Conclusions These findings firstly revealed novel manner to induce ferroptosis through ubiquitination of GPX4 and provided mechanism for GPX4 inducing mitochondria-mediated apoptosis through up-regulation of EGR1 in TNBC cells. Moreover, compound 13 deserves further studies as a lead compound with novel mode of action for ultimate discovery of effective anti-TNBC drug.

In recent decades, with the continuous development of high‐throughput sequencing technology, data volume in medical research has increased, at the same time, almost all clinical researchers have their own independent omics data, which provided a better condition for data mining and a deeper understanding of gene functions. However, for these large amounts of data, many common and cutting‐edge effective bioinformatics research methods still cannot be widely used. This has encouraged the establishment of many analytical platforms, a portion of databases or platforms were designed to solve the special analysis needs of users, for instance, MG RAST, IMG/M, Qiita, BIGSdb, and TRAPR were developed for specific omics research, and some databases or servers provide solutions for special problems solutions. Metascape was designed to only provide functional annotations of genes as well as function enrichment analysis; BioNumerics and RidomSeqSphere+ perform multilocus sequence typing; CARD provides only antimicrobial resistance annotations. Additionally, some web services are outdated, and inefficient interaction often fails to meet the needs of researchers, such as our previous versions of the platform. Therefore, the demand to complete massive data processing tasks urgently requires a comprehensive bioinformatics analysis platform. Hence, we have developed a website platform, Sangerbox 3.0 (http://vip.sangerbox.com/), a web‐based tool platform. On a user‐friendly interface that also supports differential analysis, the platform provides interactive customizable analysis tools, including various kinds of correlation analyses, pathway enrichment analysis, weighted correlation network analysis, and other common tools and functions, users only need to upload their own corresponding data into Sangerbox 3.0, select required parameters, submit, and wait for the results after the task has been completed. We have also established a new interactive plotting system that allows users to adjust the parameters in the image; moreover, optimized plotting performance enables users to adjust large‐capacity vector maps on the web site. At the same time, we have integrated GEO, TCGA, ICGC, and other databases and processed data in batches, greatly reducing the difficulty to obtain data and improving the efficiency of bioimformatics study for users. Finally, we also provide users with rich sources of bioinformatics analysis courses, offering a platform for researchers to share and exchange knowledge. Sangerbox with a user‐friendly interface supports differential analysis, correlation analyses, pathway enrichment analysis, weighted correlation network analysis, and so on. A new interactive plotting system that allows users to adjust the parameters in the image. It has organized GEO, TCGA, ICGC, and other databases; a rapid batch processing reduces the difficulty in data acquirement, greatly improving the efficiency.

Herein, the design for a tunable plasmonic refractive index nanosensor is presented. The sensor is composed of a metal–insulator–metal waveguide with a baffle and a circular split-ring resonator cavity. Analysis of transmission characteristics of the sensor structures was performed using the finite element method, and the influence of the structure parameters on the sensing characteristics of the sensor is studied in detail. The calculation results show that the structure can realize dual Fano resonance, and the structural parameters of the sensor have different effects on Fano resonance. The peak position and the line shape of the resonance can be adjusted by altering the sensitive parameters. The maximum value of structural sensitivity was found to be 1114.3 nm/RIU, with a figure of merit of 55.71. The results indicate that the proposed structure can be applied to optical integrated circuits, particularly in high sensitivity nanosensors.

Uranium (U) is a well-known nephrotoxicant which forms precipitates in the lysosomes of renal proximal tubular epithelial cells (PTECs) after U-exposure at a cytotoxic dose. However, the roles of lysosomes in U decorporation and detoxification remain to be elucidated. Mucolipin transient receptor potential channel 1 (TRPML1) is a major lysosomal Ca 2+ channel regulating lysosomal exocytosis. We herein demonstrate that the delayed administration of the specific TRPML1 agonist ML-SA1 significantly decreases U accumulation in the kidney, mitigates renal proximal tubular injury, increases apical exocytosis of lysosomes and reduces lysosomal membrane permeabilization (LMP) in renal PTECs of male mice with single-dose U poisoning or multiple-dose U exposure. Mechanistic studies reveal that ML-SA1 stimulates intracellular U removal and reduces U-induced LMP and cell death through activating the positive TRPML1-TFEB feedback loop and consequent lysosomal exocytosis and biogenesis in U-loaded PTECs in vitro. Together, our studies demonstrate that TRPML1 activation is an attractive therapeutic strategy for the treatment of U-induced nephrotoxicity. The roles of lysosomes in uranium (U) decorporation and detoxification remain to be elucidated. Here, the authors demonstrate that TRPML1 activation is an attractive therapeutic strategy to induce lysosomal exocytosis and biogenesis for the treatment of U-induced nephrotoxicity.

Light signaling and phytohormones both influence plant growth, development, and stress responses; however, cross talk between these two signaling pathways in response to cold remains underexplored. Here, we report that far-red light (FR) and red light (R) perceived by phytochrome A (phyA) and phyB positively and negatively regulated cold tolerance, respectively, in tomato (Solanum lycopersicum), which were associated with the regulation of levels of phytohormones such as abscisic acid (ABA) and jasmonic acid (JA) and transcript levels of ABA- and JA-related genes and the C-REPEAT BINDING FACTOR (CBF) stress signaling pathway genes. A reduction in the R/FR ratio did not alter cold tolerance, ABA and JA accumulation, and transcript levels of ABA- and JA-related genes and the CBF pathway genes in phyA mutant plants; however, those were significantly increased in wild-type and phyB plants with the reduction in the R/FR ratio. Even though low R/FR treatments did not confer cold tolerance in ABA-deficient (notabilis [not]) and JA-deficient (prosystemin-mediated responses2 [spr2]) mutants, it up-regulated ABA accumulation and signaling in the spr2 mutant, with no effect on JA levels and signaling in the not mutant. Foliar application of ABA and JA further confirmed that JA functioned downstream of ABA to activate the CBF pathway in light quality-mediated cold tolerance. It is concluded that phyA and phyB function antagonistically to regulate cold tolerance that essentially involves FR light-induced activation of phyA to induce ABA signaling and, subsequently, JA signaling, leading to an activation of the CBF pathway and a cold response in tomato plants.

Urban mining is essential for continued natural resource extraction. The recovery of rare and precious metals （RPMs） from urban mines has attracted increasing attention from both academic and industrial sectors, because of the broad application and high price of RPMs, and their low content in natural ores. This study summarizes the distribution characteristics of various RPMs in urban mines, and the advantages and shortcomings of various technologies for RPM recovery from urban mines, including both conventional （pyrometallurgical, hydrometallurgical, and biometallurgical processing）, and emerging （electrochemical, supereritieal fluid, mechanochemical, and ionic liquids processing） technologies. Mechanical/physical technologies are commonly employed to separate RPMs from nonmetallic components in a pre-treatment process. A pyrometallurgical process is often used tbr RPM recovery, although the expensive equipment required has limited its use in small and medium-sized enterprises. Hydrometallurgical processing is effective and easy to operate, with high selectivity of target metals and high recovery efficiency of RPMs, compared to pyrometallurgy. Biometallurgy, though, has shown the most promise for leaching RPMs from urban mines, because of its low cost and environmental friendliness. Newly developed technologies electrochemical, supercritical fluid, ionic liquid, and mechanochemical have offered new choices and achieved some success in laboratory experiments, especially as efficient and environmentally friendly methods of recycling RPMs. With continuing advances in science and technology, more technologies will no doubt be developed in this field, and be able to contribute to the sustainability of RPM mining.

In the recycling of retired lithium‐ion batteries (LIBs), the cathode materials containing valuable metals should be first separated from the current collector aluminum foil to decrease the difficulty and complexity in the subsequent metal extraction. However, strong the binding force of organic binder polyvinylidene fluoride (PVDF) prevents effective separation of cathode materials and Al foil, thus affecting metal recycling. This paper reviews the composition, property, function, and binding mechanism of PVDF, and elaborates on the separation technologies of cathode material and Al foil (e.g., physical separation, solid‐phase thermochemistry, solution chemistry, and solvent chemistry) as well as the corresponding reaction behavior and transformation mechanisms of PVDF. Due to the characteristic variation of the reaction systems, the dissolution, swelling, melting, and degradation processes and mechanisms of PVDF exhibit considerable differences, posing new challenges to efficient recycling of spent LIBs worldwide. It is critical to separate cathode materials and Al foil and recycle PVDF to reduce environmental risks from the recovery of retired LIBs resources. Developing fluorine‐free alternative materials and solid‐state electrolytes is a potential way to mitigate PVDF pollution in the recycling of spent LIBs in the EV era. The state‐of‐the‐art separation technologies are evaluated for cathode materials and Al foil of spent lithium‐ion batteries, including physical separation, solid‐phase thermochemistry, solution chemistry, and solvent chemistry, as well as the corresponding reaction behavior and transformation mechanisms of the organic binder polyvinylidene fluoride.

During the COVID-19 pandemic, digital technology has been used in all aspects of the agricultural field. How to seize the opportunity to achieve the production-marketing connection is increasingly becoming a top concern for green agri-food enterprises. Based on the theory of a task–technology fit, this study analyzes the fitness between livestreaming e-commerce and green agri-food. More specifically, the task characteristics cover the seasonality, locality, and eco-friendliness of green agri-food, and the technology characteristics cover the responsiveness, interactivity, and entertainment of livestreaming e-commerce. Using data of a sample of 574 green agri-food entrepreneurial firms collected through a web-based questionnaire, we preform structural equation modeling (SEM) analysis and find that the locality and eco-friendliness of green agri-food, the responsiveness, interactivity, and entertainment of livestreaming e-commerce have a positive effect on the fit of green agri-food livestreaming e-commerce. Moreover, the fit of green agri-food livestreaming has a positive effect on firm performance and the intention to adopt livestreaming e-commerce. This study also demonstrates that perceived corporate social responsibility has a moderating effect on the relationship between the fit of livestreaming of green agri-food and the intention to adopt livestreaming e-commerce. This study extends prior research on the task–technology fit into livestreaming e-commerce companies and provides insights into our understanding of successful adoption of livestreaming e-commerce.

Objective This study aimed to examine the factors that affect treatment delay in early childhood caries (ECC), guided by a modern medical model. This study attempted to analyze the pathways influenced by these factors and provide a theoretical foundation for designing targeted intervention programs. Methods Data were collected from young children who visited the department of stomatology at a tertiary hospital from January to December 2023. Data were collected via a general information survey questionnaire, the Scale of Oral Health Outcomes for 5-year-old Children (SOHO-5), the Children’s Fear Survey Schedule-Dental Subscale-Chinese (CFSS-DS-C), the Parental Caregiver Perceptions Questionnaire-8 (P-CPQ-8), the Family Impact Scale (FIS-8), and the Perceived Barriers to Health Care-Seeking Decision-Chinese (PBHSD-C). The data in this study were analyzed using a variety of statistical tests, including the Kruskal-Wallis and Mann-Whitney tests, correlation analysis, multiple stepwise regression analysis, and structural equation modeling (SEM). Results The treatment delay score of early childhood caries was 36.77 ± 10.11, indicating that the state of early childhood caries was currently at a moderate level of delay. The SOHO-5 score was 6.41 ± 1.78, the CFSS-DS-C score was 23.60 ± 6.91, the P-CPQ-8 score was 18.43 ± 4.33, and the FIS-8 score was 18.66 ± 4.28. Multi-factor analysis revealed key factors affecting treatment delay, including permanent residence, medical insurance type, oral health habits, reasons for visit, first symptoms, the time of first discovery of oral problems, brushing teeth before bedtime every day, a genetic history of dental caries and the staging of dental caries. A positive correlation existed between oral health, children’s dental fear and treatment delay, whereas social support was negatively correlated with treatment delay. The SEM, which is based on the modern medical model, revealed that children’s dental fear plays a mediating role in the relationships among social support, oral health, and treatment delay. Conclusion The present study developed a novel model to study the ECC treatment delay, elucidated the causal links between the identified variables, and proposed potential intervention strategies to enhance oral health awareness, knowledge, and skills among young children and their parents. These strategies can help improve children’s dental visiting behavior and reduce treatment delay.

Current irrigation water use (IWU) estimation methods confront uncertainties warranting further attention, primarily stemming from constraints within model structure and data quality. This study proposes a hybrid framework that integrates multiple machine learning (ML) methods with theory‐guided strategies to calculate IWU for three principal cereal crops within the Chinese agricultural landscape. We generated high resolution time series data sets of evapotranspiration and surface soil moisture (SM) using remote sensing resources. ML techniques, along with the Bayesian three‐cornered hat ensemble, were employed to drive multiple remote sensing‐derived data sets in IWU calculation. We applied two theory‐guided mechanisms to quantify irrigation signals: first, converting original SM values into logarithmic terms, and second, extracting process‐based SM residuals. Proposed framework has been validated at 12 field stations across China, yielding coefficient of determination (R2) ranging from 0.54 to 0.70, and root mean square error (RMSE) spanning 278–335 mm/yr. Our framework demonstrates considerable strength in IWU estimation when compared to reported IWU values form 341 cities across China. Specifically, for rice, wheat, and maize, the R2 values range from 0.78 to 0.83, 0.68 to 0.76, and 0.53 to 0.64, respectively, with corresponding RMSE measuring 0.22–0.25, 0.10–0.12, and 0.11–0.13 km3/yr, respectively. These findings highlight the effectiveness of theory‐guided strategies in discerning irrigation‐related information, thereby improving overall model performance. Attention should be directed toward the uncertainties in evapotranspiration and precipitation products on model performance, which remained modest, with a relative change of less than 5%. Key Points Hybrid framework is developed to estimate irrigation water use (IWU) for three staple cereal crops in China Machine learning is employed to drive multiple remote sensing‐derived products for precise IWU estimation Proposed framework accurately estimates IWU and incorporates theory‐guided module to reveal implicit irrigation signal