Enhancing rutin accumulation in Tartary buckwheat through a novel flavonoid transporter protein FtABCC2.

Tartary buckwheat (Fagopyrum tataricum) is an annual coarse cereal from the Polygonaceae family, known for its high content of flavonoid compounds, particularly rutin. But so far, the mechanisms of the flavonoid transport and storage in Tartary buckwheat (TB) remain largely unexplored. This study focuses on ATP-binding cassette transporters subfamily C (ABCC) members, which are crucial for the biosynthesis and transport of flavonoids in plants. The evolutionary and expression pattern analyses of the ABCC genes in TB identified an ABCC protein gene, FtABCC2, that is highly correlated with rutin synthesis. Subcellular localization analysis revealed that FtABCC2 protein is specifically localized to the vacuole membrane. Heterologous expression of FtABCC2 in Saccharomyces cerevisiae confirmed that its transport ability of flavonoid glycosides such as rutin and isoquercetin, but not the aglycones such as quercetin and dihydroquercetin. Overexpression of FtABCC2 in TB hairy root lines resulted in a significant increase in total flavonoid and rutin content (P < 0.01). Analysis of the FtABCC2 promoter revealed potential cis-acting elements responsive to hormones, cold stress, mechanical injury and light stress. Overall, this study demonstrates that FtABCC2 can efficiently facilitate the transport of rutin into vacuoles, thereby enhancing flavonoids accumulation. These findings suggest that FtABCC2 is a promising candidate for molecular-assisted breeding aimed at developing high-flavonoid TB varieties.

Chemo-, Regio- and Stereoselective Preparation of (Z)-2-Butene-1,4-Diol Monoesters via Pd-Catalyzed Decarboxylative Acyloxylation.

(Z)-alkenes are useful synthons but thermodynamically less stable than their (E)-isomers and typically more difficult to prepare. The synthesis of 1,4-hetero-bifunctionalized (Z)-alkenes is particularly challenging due to the inherent regio- and stereoselectivity issues. Herein we demonstrate a general, chemoselective and direct synthesis of (Z)-2-butene-1,4-diol monoesters. The protocol operates within a Pd-catalyzed decarboxylative acyloxylation regime involving vinyl ethylene carbonates (VECs) and various carboxylic acids as the reaction partners under mild and operationally attractive conditions. The newly developed process allows access to a structurally diverse pool of (Z)-2-butene-1,4-diol monoesters in good yields and with excellent regio- and stereoselectivity. Various synthetic transformations of the obtained (Z)-2-butene-1,4-diol monoesters demonstrate how these synthons are of great use to rapidly diversify the portfolio of these formal desymmetrized (Z)-alkenes.

Series of Viologen-Based Metal-Organic Polyhedra with Photo/Electrochromic Behavior for Inkless Printing and UV Detection.

The fabrication of molecular crystalline materials with fast, multistimuli-responsive behavior and the construction of the corresponding structure-activity relationship are of extraordinary significance for the development of smart materials. In this context, three multistimuli-responsive functional metal-organic polyhedra (MOP), {[Dy2(bcbp)3(NO3)1.5(H2O)7]·Cl4.2·(NO3)0.3·H2O}n (1), {[Dy2(bcbp)4(H2O)8]Cl6}n (2), and {[Eu2(bcbp)4(H2O)10]Cl6·H2O}n (3; bcbp = 1,1'-bis(4-carboxyphenyl)-4,4'-bipyridinium), were successfully prepared and characterized. All of the compounds exhibit rapid and reversible photochromic and electrochromic dual-responsive behaviors. Furthermore, benefiting from the well-defined crystal structure and different responsive behaviors, the photoinduced electron transfer (PIET) process and structure-activity relationship were explored. In addition, considering the excellent photochromic performance, function filter paper and smart organic glass were successfully prepared and used for ink-free printing and UV light detection.

A GAN-BO-XGBoost model for high-quality patents identification.

The number of patents increases quickly, while more and more low-quality patents are emerging. It's important to identify high-quality patents from massive data quickly and accurately for organizational R&D decision-making and patent layout. However, due to low percentage of high-quality patents, it is challenging to identify them efficiently. In order to solve above problem, we reconstruct the existing index system for identifying high-quality patents by adding 4 features from technological strength of patentees. Furthermore, we propose an improved model by integrating resampling technique and ensemble learning algorithm. First, generative adversarial networks (GAN) are used to expand minority samples. Second, Extreme Gradient Boosting algorithm (XGBoost) with Bayesian optimization (BO) is used to identify high-quality patents. For clarity, this model is called a GAN-BO-XGBoost model. To test the effectiveness of above model, we use patent data in field of lithography technology. Tenfold cross-validation is carried out to evaluate the performance between our proposed model and other models. The results show that GAN-BO-XGBoost model performs better and it's more stable than other models.

Tartary buckwheat rutin: Accumulation, metabolic pathways, regulation mechanisms, and biofortification strategies.

Rutin is a significant flavonoid with strong antioxidant property and various therapeutic effects. It plays a crucial role in disease prevention and human health maintenance, especially in anti-inflammatory, antidiabetic, hepatoprotective and cardiovascular effects. While many plants can synthesize and accumulate rutin, tartary buckwheat is the only food crop possessing high levels of rutin. At present, the rutin content (RC) is regarded as the key index for evaluating the nutritional quality of tartary buckwheat. Consequently, rutin has become the focus for tartary buckwheat breeders and has made considerable progress. Here, we summarize research on the rutin in tartary buckwheat in the past two decades, including its accumulation, biosynthesis and breakdown pathways, and regulatory mechanisms. Furthermore, we propose several strategies to increase the RC in tartary buckwheat seeds based on current knowledge. This review aims to provide valuable references for elevating the quality of tartary buckwheat in the future.

[Spatial-temporal Evolution and Driving Factors Analysis of Ecological Environment Quality in Daihai Basin based on AWRSEI].

Watersheds are an important ecological security barrier and social and economic development area. In order to evaluate the ecological environment quality of arid and semi-arid watersheds more objectively and accurately, based on the remote sensing ecological index (RSEI), the salinity index was introduced to construct a remote sensing ecological index (AWRSEI) suitable for arid and semi-arid watersheds, and the Daihai watershed was taken as an example to analyze its applicability. Based on the AWRSEI model, four phases of Landsat TM/OLI composite images were used to quantitatively evaluate the ecological and environmental quality of the Daihai Basin from 2001 to 2020. The spatio-temporal evolution of the ecological and environmental quality of the Daihai Basin was analyzed using the coefficient of variation and spatial autocorrelation, and the cause analysis and driving factor explanation power analysis were carried out using geographic detectors. The results showed that:① the average correlation coefficient between AWRSEI and various ecological factors was 0.860, which was more representative than that of a single index component. The load positive and negative values and ranking of the first principal component were consistent with those of RSEI, the contribution rate of eigenvalues was 3.69% higher than those of RSEI, and the evaluation results were closer to the real surface conditions, which is suitable for the ecological environment quality assessment of arid watersheds. ② The annual average of the AWRSEI index in the Daihai Basin from 2001 to 2020 was 0.427, which indicated a poor ecological environment quality basis. During the study period, the average of AWRSEI showed a fluctuating trend and reached the highest value of 0.502 in 2020. The overall ecological environment quality improved significantly, the deterioration area decreased by 20.51%, and the improvement area increased by 12.71%. In terms of spatial distribution, the ecological environment quality of forest land in the southern and northwestern high-altitude areas of the Daihai Basin was good, whereas that in the northern and southern mid-altitude areas was poor, and that in the northern area was better than that in the southern area. ③ The average variation coefficient of AWRSEI in the Daihai Basin was 0.280, the ecological environment quality was stable, and the overall change fluctuation was small; the high fluctuation was mainly concentrated in the southern part of the lake and the residential area. There was a significant spatial autocorrelation in the ecological environment quality of the Daihai Basin, and the high-high agglomeration area was mainly distributed in the forest area at high altitude and the cultivated land area at low altitude. Low-low concentration areas were scattered in the middle altitude area. ④ The improvement of the ecological environment in Daihai Basin from 2001 to 2020 was mainly due to the increase in NDVI and the decrease in NDBSI and NDSI. NDVI and NDBSI were the combination with the strongest interaction and the strongest interpretation of the ecological environment. Land use was the dominant factor of AWRSEI and had the strongest explanatory power. The combination of land use and meteorological factors was the strongest interaction, and the relationship between each driving factor was enhanced.

Accumulation of the bitter substance quercetin mediated by the overexpression of a novel seed-specific gene FtRDE2 in Tartary buckwheat.

Tartary buckwheat (Fagopyrum tataricum) is frequently employed as a resource to develop health foods, owing to its abundant flavonoids such as rutin. However, the consumption of Tartary buckwheat (TB) is limited in food products due to the strong bitterness induced by the hydrolysis of rutin into quercetin. This transformation is facilitated by the degrading enzyme (RDE). While multiple RDE isoenzymes exist in TB, the superior coding gene of FtRDEs has not been fully explored, which hinders the breeding of TB varieties with minimal bitterness. Here, we found that FtRDE2 is the most abundant enzyme in RDE crude extracts, and its corresponding gene is specifically expressed in TB seeds. Results showed that FtRDE2 has strong rutin hydrolysis activity. Overexpression of FtRDE2 not only significantly promoted rutin hydrolysis and quercetin accumulation but also dramatically upregulated genes involved in the early phase of flavonoid synthesis (FtPAL1、FtC4H1、Ft4CL1, FtCHI1) and anthocyanin metabolism (FtDFR1). These findings elucidate the role of FtRDE2, emphasizing it as an endogenous factor contributing to the bitterness in TB and its involvement in the metabolic regulatory network. Moreover, correlation analysis revealed a positive relationship between the catalytic activity of RDE extracts and the expression level of FtRDE2 during seed germination. In summary, our results suggest that FtRDE2 can serve as a promising candidate for the molecular breeding of a TB variety with minimal bitterness.

Beyond genome: Advanced omics progress of Panax ginseng.

Ginseng is a perennial herb of the genus Panax in the family Araliaceae as one of the most important traditional medicine. Genomic studies of ginseng assist in the systematic discovery of genes related to bioactive ginsenosides biosynthesis and resistance to stress, which are of great significance in the conservation of genetic resources and variety improvement. The transcriptome reflects the difference and consistency of gene expression, and transcriptomics studies of ginseng assist in screening ginseng differentially expressed genes to further explore the powerful gene source of ginseng. Protein is the ultimate bearer of ginseng life activities, and proteomic studies of ginseng assist in exploring the biosynthesis and regulation of secondary metabolites like ginsenosides and the molecular mechanism of ginseng adversity adaptation at the overall level. In this review, we summarize the current status of ginseng research in genomics, transcriptomics and proteomics, respectively. We also discuss and look forward to the development of ginseng genome allele mapping, ginseng spatiotemporal, single-cell transcriptome, as well as ginseng post-translational modification proteome. We hope that this review will contribute to the in-depth study of ginseng and provide a reference for future analysis of ginseng from a systems biology perspective.

Bilateral diffuse metastases in advanced lung adenocarcinoma harboring EGFR mutations was associated with a favorable prognosis to EGFR-TKIs.

Bilateral diffuse metastatic lung adenocarcinoma (BLDM-LUAD) is a special imaging pattern of lung adenocarcinoma (LUAD). We retrospectively assessed survival outcomes and co-mutation characteristics of BLDM-LUAD patients harboring epidermal growth factor receptor (EGFR) mutations who were treated with EGFR-yrosine kinase inhibitors (TKIs). From May 2016 to May 2021, among 458 patients who submitted samples for next generation sequencing (NGS) detection in 1125 patients with non-small-cell lung cancer (NSCLC), and 44 patients were diagnosed as BLDM-LUAD. In order to analyze the survival outcomes of BLDM-LUAD patients harboring EGFR mutations who were treated with EGFR-TKIs, the factors age, gender, smoking history, hydrothorax, site of EGFR mutations and EGFR-TKIs treatment were adjusted using propensity score-matching (PSM). The Kaplan-Meier survival curves and log-rank test were used to analyze progression-free survival (PFS) and overall survival (OS). The co-mutation characteristics of BLDM-LUAD patients harboring EGFR mutations were analyzed by NGS panels. 64 patients with advanced lung adenocarcinoma harboring EGFR mutations and first-line treatment of EGFR-TKIs were successfully matched. BLDM-LUAD (n = 32) have significantly longer median PFS than control group (n = 32) (mPFS: 14 vs 6.2 months; p = .002) and insignificantly longer median OS than control group (mOS: 45 vs 25 months; p = .052). The patients with BLDM-LUAD have the higher frequency of EGFR mutation than control group (84.1% vs 62.0%) before PSM. The co-mutation genes kirsten rat sarcoma viral oncogene homolog (KRAS) (9.4%), ataxia telangiectasia-mutated (ATM) (7.4%) and mesenchymal-epithelial transition (MET) (3.1%) only appeared in the control group after PSM. The BLDM-LUAD harboring EGFR mutations was associated with a favorable prognosis to EGFR-TKI.

Investigation of rare earth-based magnetic nanocomposites for specific enrichment of exosomes from human plasma.

Exosomes, also known as small extracellular vesicles, are widely present in a variety of body fluids (e.g., blood, urine, and saliva). Exosomes are becoming an alternative promising source of diagnostic markers for disease rich in cargo of metabolites, proteins, and nucleic acids. However, due to the low abundance and structure similarity with protein complex, the efficient isolation of exosomes is one of the most important issues for biomedical applications. With a higher order of f-orbitals in rare earth element, it will have strong adsorption toward the phosphate group on the surface of the phospholipid bilayer of exosomes. In this study, we systematically investigated the ability of various rare earths interacting with phosphate-containing molecules and plasma exosomes. One of the best binding europium was selected and used to synthesize core-shell magnetic nanomaterials (Fe3O4@SiO2@Eu2O3) for the enrichment of exosomes from human plasma. The developed nanomaterials exhibited higher enrichment capacity, less time consumption and more convenient handling compared to commonly used ultracentrifugation method. The nanomaterials were applied to separate exosomes from the plasma of patients with hepatocellular carcinoma and healthy controls for metabolomics study with high-resolution mass spectrometry, where 70 differentially expressed metabolites were identified, involving amino acid and lipid metabolic pathway. We anticipated the rare earth-based materials to be an alternative approach on exosome isolation for disease diagnosis or postoperative clinical monitoring.

lncRNA799/TBL1XR1/ZEB1 Axis Forms a Feedback Loop to Promote the Epithelial-Mesenchymal Transition of Cervical Cancer Cells.

Cervical cancer is a common malignancy among women worldwide. Long non-coding RNAs (lncRNAs) are frequently involved in the pathogenesis of cervical cancer. Therefore, the present study aimed to investigate the potentials of lncRNA799 in cervical cancer. mRNA and protein expression were detected by reverse transcription-quantitative polymerase chain reaction and Western blot analysis, respectively. Cellular functions were assessed using CCK-8, wound healing and transwell analysis. The binding potential of zinc finger E-box-binding homeobox 1 (ZEB1) on the promoter of lncRNA799 was predicted utilizing the JASPAR database, and was then verified by luciferase and chromatin immunoprecipitation (ChIP) assays. Furthermore, the gene interactions were assessed using RNA immunoprecipitation and co-immunoprecipitation assays. The results demonstrated that lncRNA799 was upregulated in cervical cancer cells. However, lncRNA799 deficiency suppressed the proliferation and epithelial-mesenchymal transition of cervical cancer cells. Furthermore, lncRNA799 could interact with eukaryotic translation initiation factor 4A3 to maintain the mRNA stability of transducin (ß)-like 1 X-linked receptor 1 (TBL1XR1) and promote the interaction between ZEB1 and TBL1XR1. Additionally, the results showed that ZEB1 could transcriptionally activate lncRNA799. Taken together, the present study suggested that the lncRNA799/TBL1XR1/ZEB1 axis could form a positive feedback loop in cervical cancer and could be, therefore, considered as a potential therapeutic strategy for cervical cancer.

Cancer-associated fibroblasts induce sorafenib resistance of hepatocellular carcinoma cells through CXCL12/FOLR1.

BACKGROUND: Due to the high drug resistance of hepatocellular carcinoma (HCC), sorafenib has limited efficacy in the treatment of advanced HCC. Cancer-associated fibroblasts (CAFs) play an important regulatory role in the induction of chemoresistance. This study aimed to clarify the mechanism underlying CAF-mediated resistance to sorafenib in HCC. METHODS: Immunohistochemistry and immunofluorescence showed that the activation of CAFs was enhanced in HCC tissues. CAFs and paracancerous normal fibroblasts (NFs) were isolated from the cancer and paracancerous tissues of HCC, respectively. Cell cloning assays, ELISAs, and flow cytometry were used to detect whether CAFs induced sorafenib resistance in HCC cells via CXCL12. Western blotting and qPCR showed that CXCL12 induces sorafenib resistance in HCC cells by upregulating FOLR1. We investigated whether FOLR1 was the target molecule of CAFs regulating sorafenib resistance in HCC cells by querying gene expression data for human HCC specimens from the GEO database. RESULTS: High levels of activated CAFs were present in HCC tissues but not in paracancerous tissues. CAFs decreased the sensitivity of HCC cells to sorafenib. We found that CAFs secrete CXCL12, which upregulates FOLR1 in HCC cells to induce sorafenib resistance. CONCLUSIONS: CAFs induce sorafenib resistance in HCC cells through CXCL12/FOLR1.

Control of chaotic systems through reservoir computing.

Chaos is an important dynamic feature, which generally occurs in deterministic and stochastic nonlinear systems and is an inherent characteristic that is ubiquitous. Many difficulties have been solved and new research perspectives have been provided in many fields. The control of chaos is another problem that has been studied. In recent years, a recurrent neural network has emerged, which is widely used to solve many problems in nonlinear dynamics and has fast and accurate computational speed. In this paper, we employ reservoir computing to control chaos in dynamic systems. The results show that the reservoir calculation algorithm with a control term can control the chaotic phenomenon in a dynamic system. Meanwhile, the method is applicable to dynamic systems with random noise. In addition, we investigate the problem of different values for neurons and leakage rates in the algorithm. The findings indicate that the performance of machine learning techniques can be improved by appropriately constructing neural networks.

Berberine hydrochloride ameliorates PM2.5-induced pulmonary fibrosis in mice through inhibiting oxidative stress and inflammatory.

Elevated levels of respirable particulate matter (PM) have been strongly linked to disease incidence and mortality in population-based epidemiological studies. Berberine hydrochloride (BBR), an isoquinoline alkaloid found in Coptis chinensis, exhibits antipyretic, anti-inflammatory, and antioxidant properties. However, the protective effects and underlying mechanism of BBR against pulmonary fibrosis remain unclear. This study aimed to investigate the protective effect of BBR on lung tissue damage using a mouse model of PM2.5-induced pulmonary fibrosis. SPF grade C57BL/6 mice were randomly assigned to four groups, each consisting of 10 mice. The mice were pretreated with BBR (50 mg/kg) by gavage for 45 consecutive days. A tracheal drip of PM2.5 suspension (8 mg/kg) was administered once every three days for a total of 15 times to induce lung fibrosis. Moreover, the results demonstrated that PM2.5 was found to inhibit the PPARγ signaling pathway, increase ROS expression, upregulate protein levels of IL-6, IL-1ß, TNF-α, as well as regulation of gene expression of STAT3 and SOCS3. Importantly, PM2.5 induced lung fibrosis by promoting collagen deposition, upregulating gene expression of fibrosis markers (TGF-ß1, FN, α-SMA, COL-1, and COL-3), and downregulating E-cadherin expression. Remarkably, our findings suggest that these injuries could be reversed by BBR pretreatment. BBR acts as a PPARγ agonist in PM2.5-induced pulmonary fibrosis, activating the PPARγ signaling pathway to mitigate oxidative and inflammatory factor-mediated lung injury. This study provides valuable insights for the future prevention and treatment of pulmonary fibrosis.

Improving the Mechanical Properties of a Lattice Structure Composed of Struts with a Tri-Directional Elliptical Cylindrical Section via Selective Laser Melting.

In recent years, lattice structures produced via additive manufacturing have been increasingly investigated for their unique mechanical properties and the flexible and diverse approaches available to design them. The design of a strut with variable cross-sections in a lattice structure is required to improve the mechanical properties. In this study, a lattice structure design method based on a strut cross-section composed of a mixture of three ellipses named a tri-directional elliptical cylindrical section (TEC) is proposed. The lattice structures were fabricated via the selective laser melting of 316L alloy. The finite element analysis results show that the TEC strut possessed the high mechanical properties of lattice structures. Compression experiments confirmed that the novel lattice structure with the TEC strut exhibited increases in the elastic modulus, compressive yield strength, and energy absorption capacity of 24.99%, 21.66%, and 20.50%, respectively, compared with the conventional lattice structure at an equal level of porosity.

Granule-bound starch synthase in plants: Towards an understanding of their evolution, regulatory mechanisms, applications, and perspectives.

Amylose content (AC) is a significant quality trait in starchy crops, affecting their processing and application by the food and non-food industries. Therefore, fine-tuning AC in these crops has become a focus for breeders. Granule-bound starch synthase (GBSS) is the core enzyme that directly determines the AC levels. Several excellent reviews have summarized key progress in various aspects of GBSS research in recent years, but they mostly focus on cereals. Herein, we provide an in-depth review of GBSS research in monocots and dicots, focusing on the molecular characteristics, evolutionary relationships, expression patterns, molecular regulation mechanisms, and applications. We also discuss future challenges and directions for controlling AC in starchy crops, and found simultaneously increasing both the PTST and GBSS gene expression levels may be an effective strategy to increase amylose content.

DPAM-PSPNet: ultrasonic image segmentation of thyroid nodule based on dual-path attention mechanism.

Objective.Deep learning has demonstrated its versatility in the medical field, particularly in medical image segmentation, image classification, and other forms of automated diagnostics. The clinical diagnosis of thyroid nodules requires radiologists to locate nodules, diagnose conditions based on nodule boundaries, textures and their experience. This task is labor-intensive and tiring; therefore, an automated system for accurate thyroid nodule segmentation is essential. In this study, a model named DPAM-PSPNet was proposed, which automatically segments nodules in thyroid ultrasound images and enables to segment malignant nodules precisely.Approach.In this paper, accurate segmentation of nodule edges is achieved by introducing the dual path attention mechanism (DPAM) in PSPNet. In one channel, it captures global information with a lightweight cross-channel interaction mechanism. In other channel, it focus on nodal margins and surrounding information through the residual bridge network. We also updated the integrated loss function to accommodate the DPAM-PSPNet.Main results.The DPAM-PSPNet was tested against the classical segmentation model. Ablation experiments were designed for the two-path attention mechanism and the new loss function, and generalization experiments were designed on the public dataset. Our experimental results demonstrate that DPAM-PSPNet outperforms other existing methods in various evaluation metrics. In the model comparison experiments, it achieved performance with an mIOU of 0.8675, mPA of 0.9357, mPrecision of 0.9202, and Dice coefficient of 0.9213.Significance.The DPAM-PSPNet model can segment thyroid nodules in ultrasound images with little training data and generate accurate boundary regions for these nodules.

Multi-Biomarkers Panel in Identifying Benign and Malignant Lung Diseases and Pathological Types of Lung Cancer.

With the discovery of many tumor markers, there are new strategies for the early diagnosis and treatment of lung cancer and the prediction of prognosis. We examined the multi-protein markers panel (4MP, consisting of Pro-SFTPB, CA125, Cyfra21-1, and CEA) diagnosis performance in differentiating benign and malignant lung diseases and identifying pathological types of lung cancer. Meantime, the complementary performance of three conventional tumor markers (NSE, SCC, and Pro-GRP) for 4MP was assessed. A total of 294 patients with lung cancer or benign lung disease are contained in this study. The AUCs of 4MP and 7MP (NSE, SCC, Pro-GRP, and 4MP) in distinguishing benign lung disease and lung cancer were 0.808 and 0.832, respectively. In distinguishing SQCLC and SCLC, the AUCs were 0.716 and 0.985, respectively. In distinguishing LADC and SCLC, the AUCs were 0.849 and 0.998, respectively. This study demonstrated that 4MP can distinguish lung cancer from benign disease. Traditional biomarkers NSE, SCC, and Pro-GRP can significantly improve the performance of 4MP in the differentiation of LADC, SQCLC, and SCLC, which is expected to contribute to the accurate diagnosis and personalized treatment of patients.

Oleanolic acid inhibits mercury chloride induced-liver ferroptosis by regulating ROS/iron overload.

Mercury chloride can cause severe liver injury, which involves multiple mechanisms. Ferroptosis plays an important role in regulating the development and progression of liver pathology. Oleanolic acid (OA), a triterpenoid compound widely exists in fruits, has liver protective properties. In this study, we investigated the role of ferroptosis in mercury chloride-induced liver injury and the intervention effect of OA, and clarified the potential mechanism. We found that mercury chloride-induced oxidative stress in liver tissues and cells, leading to lipid peroxidation and iron overload, thereby reducing the expression levels of GPX4 and SLC7A11, and increasing the expression level of TRF1, OA pretreatment improved the changes of GPX4, SLC7A11 and TRF1 induced by mercury chloride, which were related to its inhibition of oxidative stress. Furthermore, We pretreated cells with OA, VC, and Fer-1, respectively and found that VC pretreatment reduced oxidative stress and significantly reversed the gene and protein expressions of GPX4, SLC7A11, and TRF1 in mercury chloride-exposed cells (P < 0.05, vs. HgCl2 group), however, the protein expression level of GPX4 in OA pre-treatment group was lower than that in VC pre-treatment group (P < 0.05). Fer-1 pretreatment decreased the level of iron ions in cells, increased the gene and protein expression levels of GPX4 and SLC7A11, and decreased the gene and protein expression levels of TRF1 (P < 0.05, vs. HgCl2 group), however, the protein expression levels of GPX4 and SLC7A11 in OA pre-treatment group were lower than those in Fer-1 pre-treatment group (P < 0.05). Moreover, vivo experiments also demonstrated that pre-treatment with OA, VC, and Fer-1 reversed the changes in gene expression levels of Nrf2 and SOD1, and protein expression of GPX4 induced by mercury chloride (P < 0.05, vs. HgCl2 group), meanwhile, the difference was not statistically significant among OA, VC, and Fer-1 pretreatment. The improvement effect of OA pretreatment on the change in TFR1 protein expression caused by mercury chloride was similar to that of Fer-1 and VC, however, the intervention effect of OA on SLC7A11 protein expression was not as good as Fer-1 and VC pre-treatment. To sum up, all these results suggest that ferroptosis is involved in mercury chloride-induced liver injury, OA pretreatment alleviated mercury chloride-induced ferroptosis by inhibiting ROS production and iron ion overload, and then alleviate the liver injury.

An effective convolutional neural network for classification of benign and malignant breast and thyroid tumors from ultrasound images.

Breast and thyroid cancers are the two most common cancers among women worldwide. The early clinical diagnosis of breast and thyroid cancers often utilizes ultrasonography. Most of the ultrasound images of breast and thyroid cancer lack specificity, which reduces the accuracy of ultrasound clinical diagnosis. This study attempts to develop an effective convolutional neural network (E-CNN) for the classification of benign and malignant breast and thyroid tumors from ultrasound images. The 2-Dimension (2D) ultrasound images of 1052 breast tumors were collected, and 8245 2D tumor images were obtained from 76 thyroid cases. We performed tenfold cross-validation on breast and thyroid data, with a mean classification accuracy of 0.932 and 0.902, respectively. In addition, the proposed E-CNN was applied to classify and evaluate 9297 mixed images (breast and thyroid images). The mean classification accuracy was 0.875, and the mean area under the curve (AUC) was 0.955. Based on data in the same modality, we transferred the breast model to classify typical tumor images of 76 patients. The finetuning model achieved a mean classification accuracy of 0.945, and a mean AUC of 0.958. Meanwhile, the transfer thyroid model realized a mean classification accuracy of 0.932, and a mean AUC of 0.959, on 1052 breast tumor images. The experimental results demonstrate the ability of the E-CNN to learn the features and classify breast and thyroid tumors. Besides, it is promising to classify benign and malignant tumors from ultrasound images with the transfer model under the same modality.