Comprehensive analysis of m6A modification in immune infiltration, metabolism and drug resistance in hepatocellular carcinoma.

N6-methyladenosine (m6A) is important in regulating mRNA stability, splicing, and translation, and it also contributes to tumor development. However, there is still limited understanding of the comprehensive effects of m6A modification patterns on the tumor immune microenvironment, metabolism, and drug resistance in hepatocellular carcinoma (HCC). In this study, we utilized unsupervised clustering based on the expression of 23 m6A regulators to identify m6A clusters. We identified differential m6A modification patterns and characterized m6A-gene-cluster A, which exhibited poorer survival rates, a higher abundance of Treg cells, and increased expression of TGFß in the tumor microenvironment (TME). Additionally, m6A-gene-cluster A demonstrated higher levels of glycolysis activity, cholesterol metabolism, and fatty acid biosynthesis. We also found that the m6A score was associated with prognosis and drug resistance. Patients with a low m6A score experienced worse prognoses, which were linked to an abundance of Treg cells, upregulation of TGFß, and increased metabolic activity. HCC patients with a higher m6A score showed improved prognosis following sorafenib treatment and immunotherapy. In conclusion, we reveals the association between m6A modification patterns and the tumor immune microenvironment, metabolism, and drug resistance in HCC. Furthermore, the m6A score holds potential as a predictive factor for the efficacy of targeted therapy and immunotherapy in HCC.

Transformaer-based model for lung adenocarcinoma subtypes.

BACKGROUND: Lung cancer has the highest morbidity and mortality rate among all types of cancer. Histological subtypes serve as crucial markers for the development of lung cancer and possess significant clinical values for cancer diagnosis, prognosis, and prediction of treatment responses. However, existing studies only dichotomize normal and cancerous tissues, failing to capture the unique characteristics of tissue sections and cancer types. PURPOSE: Therefore, we have pioneered the classification of lung adenocarcinoma (LAD) cancer tissues into five subtypes (acinar, lepidic, micropapillary, papillary, and solid) based on section data in whole-slide image sections. In addition, a novel model called HybridNet was designed to improve the classification performance. METHODS: HybridNet primarily consists of two interactive streams: a Transformer and a convolutional neural network (CNN). The Transformer stream captures rich global representations using a self-attention mechanism, while the CNN stream extracts local semantic features to optimize image details. Specifically, during the dual-stream parallelism, the feature maps of the Transformer stream as weights are weighted and summed with those of the CNN stream backbone; at the end of the parallelism, the respective final features are concatenated to obtain more discriminative semantic information. RESULTS: Experimental results on a private dataset of LAD showed that HybridNet achieved 95.12% classification accuracy, and the accuracy of five histological subtypes (acinar, lepidic, micropapillary, papillary, and solid) reached 94.5%, 97.1%, 94%, 91%, and 99% respectively; the experimental results on the public BreakHis dataset show that HybridNet achieves the best results in three evaluation metrics: accuracy, recall and F1-score, with 92.40%, 90.63%, and 91.43%, respectively. CONCLUSIONS: The process of classifying LAD into five subtypes assists pathologists in selecting appropriate treatments and enables them to predict tumor mutation burden (TMB) and analyze the spatial distribution of immune checkpoint proteins based on this and other clinical data. In addition, the proposed HybridNet fuses CNN and Transformer information several times and is able to improve the accuracy of subtype classification, and also shows satisfactory performance on public datasets with some generalization ability.

An Efficient Group Federated Learning Framework for Large-Scale EEG-Based Driver Drowsiness Detection.

To avoid traffic accidents, monitoring the driver's electroencephalogram (EEG) signals to assess drowsiness is an effective solution. However, aggregating the personal data of these drivers may lead to insufficient data usage and pose a risk of privacy breaches. To address these issues, a framework called Group Federated Learning (Group-FL) for large-scale driver drowsiness detection is proposed, which can efficiently utilize diverse client data while protecting privacy. First, by arranging the clients into different levels of groups and gradually aggregating their model parameters from low-level groups to high-level groups, communication and time costs are reduced. In addition, to solve the problem of notable variations in EEG signals among different clients, a global-personalized deep neural network is designed. The global model extracts shared features from various clients, while the personalized model extracts fine-grained features from each client and outputs classification results. Finally, to address special issues such as scale/category imbalance and data pollution, three checking modules are designed for adjusting grouping, evaluating client data, and effectively applying personalized models. Through extensive experimentation, the effectiveness of each component within the framework was validated, and a mean accuracy, F1-score, and Area Under Curve (AUC) of 81.0%, 82.0%, and 87.9% was achieved, respectively, on a publicly available dataset comprising 11 subjects.

Manipulation of Giant Multipole Resonances via Vortex γ Photons.

Traditional photonuclear reactions primarily excite giant dipole resonances, making the measurement of isovector giant resonances with higher multipolarities a great challenge. In this Letter, the manipulation of collective excitations of different multipole transitions in even-even nuclei via vortex γ photons is investigated. We develop the calculation method for photonuclear cross sections induced by the vortex γ photon beam using the fully self-consistent random-phase approximation plus particle-vibration coupling (RPA+PVC) model based on Skyrme density functional. We find that the electromagnetic transitions with multipolarity J<|m_{γ}| are forbidden for vortex γ photons due to the angular momentum conservation, with m_{γ} being the projection of total angular momentum of γ photon on its propagation direction. For instance, this allows for probing the isovector giant quadrupole resonance without interference from dipole transitions using vortex γ photons with m_{γ}=2. Furthermore, the electromagnetic transition with J=|m_{γ}|+1 vanishes at a specific polar angle. Therefore, the giant resonances with specific multipolarity can be extracted via vortex γ photons. Moreover, the vortex properties of γ photons can be meticulously diagnosed by measuring the nuclear photon-absorption cross section. Our method opens new avenues for photonuclear excitations, generation of coherent γ photon laser and precise detection of vortex particles, and consequently, has significant impact on nuclear physics, nuclear astrophysics and strong laser physics.

RFX6 facilitates aerobic glycolysis-mediated growth and metastasis of hepatocellular carcinoma through targeting PGAM1.

BACKGROUND: Hepatocellular carcinoma (HCC) cells undergo reprogramming of glucose metabolism to support uncontrolled proliferation, of which the intrinsic mechanism still merits further investigation. Although regulatory factor X6 (RFX6) is aberrantly expressed in different cancers, its precise role in cancer development remains ambiguous. METHODS: Microarrays of HCC tissues were employed to investigate the expression of RFX6 in tumour and adjacent non-neoplastic tissues. Functional assays were employed to explore the role of RFX6 in HCC development. Chromatin immunoprecipitation, untargeted metabolome profiling and sequencing were performed to identify potential downstream genes and pathways regulated by RFX6. Metabolic assays were employed to investigate the effect of RFX6 on glycolysis in HCC cells. Bioinformatics databases were used to validate the above findings. RESULTS: HCC tissues exhibited elevated expression of RFX6. High RFX6 expression represented as an independent hazard factor correlated to poor prognosis in patients with HCC. RFX6 deficiency inhibited HCC development in vitro and in vivo, while its overexpression exerted opposite functions. Mechanistically, RFX6 bound to the promoter area of phosphoglycerate mutase 1 (PGAM1) and upregulated its expression. The increased PGAM1 protein levels enhanced glycolysis and further promoted the development of HCC. CONCLUSIONS: RFX6 acted as a novel driver for HCC development by promoting aerobic glycolysis, disclosing the potential of the RFX6-PGAM1 axis for therapeutic targeting.

A straightforward spectral emissivity estimating method based on constructing random rough surfaces.

Spectral emissivity is an essential and sensitive parameter to characterize the radiative capacity of the solid surface in scientific and engineering applications, which would be non-negligibly affected by surface morphology. However, there is a lack of assessment of the effect of roughness on emissivity and a straightforward method for estimating the emissivity of rough surfaces. This paper established an estimating method based on constructing random rough surfaces to predict rough surface (Geometric region) emissivity for metal solids. Based on this method, the emissivity of ideal gray and non-gray body surfaces was calculated and analyzed. The calculated and measured spectral emissivities of GH3044, K465, DD6, and TC4 alloys with different roughness were compared. The results show that the emissivity increases with the roughness degree, and the enhancement effect weakens with the increase of roughness or emissivity due to the existing limit (emissivity ε = 1.0). At the same time, the roughness would not change the overall spectral distribution characteristics but may attenuate the local features of the spectral emissivity. The estimated results are in good agreement with the experimental data for the above alloys' rough surfaces. This study provides a new reliable approach to obtaining the spectral emissivity of rough surfaces. This approach is especially beneficial for measuring objects in extreme environments where emissivity is difficult to obtain. Meanwhile, this study promotes an understanding of surface morphology's effect mechanism on emissivity.

METTL9-SLC7A11 axis promotes hepatocellular carcinoma progression through ferroptosis inhibition.

Methytransferase-like proteins 9 (METTL9) has been characterized as an oncogene in several cancers, however, its role in hepatocellular carcinoma (HCC) remains unknown. Here, we investigated the function and molecular mechanism of METTL9 in HCC. We showed that METTL9 expression was elevated in HCC, and its high expression was associated with poor survival outcomes. Knockdown of METTL9 observed a significant inhibition of HCC cell viability, migration, and invasion both in vitro and in vivo. By contrast, METTL9 overexpression HCC cells obtained stronger abilities in cell proliferation and migration. Mechanistically, we discovered that METTL9 knockdown led to a reduction in the expression level of SLC7A11, a key suppressor of ferroptosis, in turn, promoted ferroptosis in HCC cells, impeding the progression of HCC. Moreover, we have proved that targeting METTL9 could significantly restrain the growth of HCC patient-derived xenograft (PDX). Our study established METTL9 as a critical role in promoting HCC development and provides a foundation for further investigation and potential therapeutic interventions targeting ferroptosis in HCC.

Dysregulation of PLOD2 Promotes Tumor Metastasis and Invasion in Hepatocellular Carcinoma.

Background and Aims: Metastasis is a major factor associated with high recurrence and mortality in hepatocellular carcinoma (HCC) patients while the underlying mechanism of metastasis remains elusive. In our study, procollagen-lysine, 2-oxoglutarate 5-dioxygenase 2 (PLOD2) was shown to be involved in the process of metastasis in HCC. Methods: The Cancer Genome Atlas (TCGA) database and HCC tissue microarrays were used to evaluate the expression of genes. In vitro migration, invasion, in vivo subcutaneous tumor model and in vivo lung metastasis assays were used to determine the role of PLOD2 in tumor growth and metastasis in HCC. RNA sequencing and gene set enrichment analysis were performed to uncover the downstream factor of PLOD2 in HCC cells. A luciferase reporter assay was performed to evaluate the interaction between PLOD2 and interferon regulatory factor 5 (IRF5). Results: The expression of PLOD2 in HCC tissues was higher than that in adjacent tissues, and increased PLOD2 expression was often found in advanced tumors and was correlated with poor prognosis in HCC patients. In vitro experiments, knockdown of PLOD2 reduced the migration and invasion of human HCC cells. Loss of PLOD2 suppressed human HCC growth and metastasis in a subcutaneous tumor model and a lung metastasis model. Baculoviral IAP repeat containing 3 (BIRC3) was proven to be the downstream factor of PLOD2 in human HCC cells. In addition, PLOD2 was transcriptionally regulated by IRF5 in HCC cells. Conclusions: High expression of PLOD2 was regulated by IRF5, which was correlated with the poor survival of HCC patients. PLOD2 enhanced HCC metastasis via BIRC3, suggesting that PLOD2 might be a valuable prognostic biomarker for HCC treatment.

In vitro oogenesis from murine premeiotic germ cells using a new three-dimensional culture system.

A faithful reconstitution of the complete process of oogenesis in vitro is helpful for understanding the molecular mechanisms, genetics, and epigenetic changes related to gametogenesis; it can also be useful for clinical drug screening, disease research, and regenerative medicine. To this end, given the consensus that murine female germ cells initiate meiosis at E13.5, substantial works have reported the successful generation of fertile oocytes using E12.5 female gonads as starting materials. Nevertheless, our data demonstrated that murine germ cells at E12.5 have heterogeneously initiated a meiotic transcriptional program based on a measurement of pre-mRNAs (unspliced) and mature mRNAs (spliced) at a single-cell level. Therefore, to establish a platform that faithfully recapitulates the entire process in vitro (from premeiotic murine germ cells to fully developed oocytes), we here report a novel three-dimensional organoid culture (3-DOC) system, which successfully induced fully developed oocytes from E11.5 premeiotic female germ cells (oogonia). Compared with 2D culture and other 3D culture methods, this new culture system is more cost-effective and can create high-quality oocytes similar to in vivo oocytes. In summary, our new culture platform provides an experimental model for future research in regenerative medicine and reproductive biology.

Hybrid Attention Network for Epileptic EEG Classification.

Automatic seizure detection from electroencephalography (EEG) based on deep learning has been significantly improved. However, existing works have not adequately excavate the spatial-temporal information between EEG channels. Besides, most works mainly focus on patient-specific scenarios while cross-patient seizure detection is more challenging and meaningful. Regarding the above problems, we propose a hybrid attention network (HAN) for automatic seizure detection. Specifically, the graph attention network (GAT) extracts spatial features at the front end, and Transformer gets time features as the back end. HAN leverages the attention mechanism and fully extracts the spatial-temporal correlation of EEG signals. The focal loss function is introduced to HAN to deal with the imbalance of the dataset accompanied by seizure detection based on EEG. Both patient-specific and patient-independent experiments are carried out on the public CHB-MIT database. Experimental results demonstrate the efficacy of HAN in both experimental settings.

Improving marginal hazard ratio estimation using quadratic inference functions.

Clustered and multivariate failure time data are commonly encountered in biomedical studies and a marginal regression approach is often employed to identify the potential risk factors of a failure. We consider a semiparametric marginal Cox proportional hazards model for right-censored survival data with potential correlation. We propose to use a quadratic inference function method based on the generalized method of moments to obtain the optimal hazard ratio estimators. The inverse of the working correlation matrix is represented by the linear combination of basis matrices in the context of the estimating equation. We investigate the asymptotic properties of the regression estimators from the proposed method. The optimality of the hazard ratio estimators is discussed. Our simulation study shows that the estimator from the quadratic inference approach is more efficient than those from existing estimating equation methods whether the working correlation structure is correctly specified or not. Finally, we apply the model and the proposed estimation method to analyze a study of tooth loss and have uncovered new insights that were previously inaccessible using existing methods.

PRMT3-mediated arginine methylation of IGF2BP1 promotes oxaliplatin resistance in liver cancer.

Although oxaliplatin-based chemotherapy has been effective in the treatment of hepatocellular carcinoma (HCC), primary or acquired resistance to oxaliplatin remains a major challenge in the clinic. Through functional screening using CRISPR/Cas9 activation library, transcriptomic profiling of clinical samples, and functional validation in vitro and in vivo, we identify PRMT3 as a key driver of oxaliplatin resistance. Mechanistically, PRMT3-mediated oxaliplatin-resistance is in part dependent on the methylation of IGF2BP1 at R452, which is critical for the function of IGF2BP1 in stabilizing the mRNA of HEG1, an effector of PRMT3-IGF2BP1 axis. Also, PRMT3 overexpression may serve as a biomarker for oxaliplatin resistance in HCC patients. Collectively, our study defines the PRTM3-IGF2BP1-HEG1 axis as important regulators and therapeutic targets in oxaliplatin-resistance and suggests the potential to use PRMT3 expression level in pretreatment biopsy as a biomarker for oxaliplatin-resistance in HCC patients.

A novel NHEJ gene signature based model for risk stratification and prognosis prediction in hepatocellular carcinoma.

BACKGROUND: Non-homologous DNA end joining (NHEJ) is the predominant DNA double-strand break (DSB) repair pathway in human. However, the relationship between NHEJ pathway and hepatocellular carcinoma (HCC) is unclear. We aimed to explore the potential prognostic role of NHEJ genes and to develop an NHEJ-based prognosis signature for HCC. METHODS: Two cohorts from public database were incorporated into this study. The Kaplan-Meier curve, the Least absolute shrinkage and selection operator (LASSO) regression analysis, and Cox analyses were implemented to determine the prognostic genes. A NHEJ-related risk model was created and verified by independent cohorts. We derived enriched pathways between the high- and low-risk groups using Gene Set Enrichment Analysis (GSEA). CIBERSORT and microenvironment cell populations-counter algorithm were used to perform immune infiltration analysis. XRCC6 is a core NHEJ gene and immunohistochemistry (IHC) was further performed to elucidate the prognostic impact. In vitro proliferation assays were conducted to investigate the specific effect of XRCC6. RESULTS: A novel NHEJ-related risk model was developed based on 6 NHEJ genes and patients were divided into distinct risk groups according to the risk score. The high-risk group had a poorer survival than those in the low-risk group (P < 0.001). Meanwhile, an obvious discrepancy in the landscape of the immune microenvironment also indicated that distinct immune status might be a potential determinant affecting prognosis as well as immunotherapy reactiveness. High XRCC6 expression level associates with poor outcome in HCC. Moreover, XRCC6 could promote HCC cell proliferation in vitro. CONCLUSIONS: In brief, this work reveals a novel NHEJ-related risk signature for prognostic evaluation of HCC patients, which may be a potential biomarker of HCC immunotherapy.

Empirical research on household consumption carbon emissions and key impact factors in urban and rural China.

The analysis of household consumption carbon emissions (HCCEs), a significant source of CO2 emissions, is essential to achieving China's carbon peak before 2030 and carbon neutrality before 2060. Based on the calculation of urban and rural HCCEs during 2005-2019, the differences between urban and rural areas, spatial-temporal pattern and agglomeration characteristics of HCCEs were analyzed, and the panel quantile STIRPAT model was constructed to empirically test the influence of socioeconomic factors on urban and rural HCCEs at different quantile levels. The results indicate that, first, China's HCCEs are generally growing, indirect HCCEs are more than direct HCCEs, urban HCCEs are far more than rural, and the gap has a growing trend. Second, the urban and rural HCCEs have significant disequilibrium and agglomeration characteristics in space, and high-high and low-low agglomerations dominated the local region. Third, household size and the number of patent application authorizations increase the urban and rural HCCEs, while the consumption capacity and consumption structure inhibit the urban and rural HCCEs. In addition, the level of education also has an inhibitory effect on the rural HCCEs, while the aging degree of the population has a significant positive impact on the rural HCCEs when it is only at the 90th percentile. Finally, it is suggested to formulate differentiated emission reduction policies.

[Analysis of chest imaging features of novel coronavirus pneumonia, bacterial pneumonia and viral pneumonia].

OBJECTIVE: To investigate and summarize the chest CT imaging features of patients with novel coronavirus pneumonia (COVID-19), bacterial pneumonia and other viral pneumonia. METHODS: Chest CT data of 102 patients with pulmonary infection due to different etiologies were retrospectively analyzed, including 36 patients with COVID-19 admitted to Hainan Provincial People's Hospital and the Second Affiliated Hospital of Hainan Medical University from December 2019 to March 2020, 16 patients with other viral pneumonia admitted to Hainan Provincial People's Hospital from January 2018 to February 2020, and 50 patients with bacterial pneumonia admitted to Haikou Affiliated Hospital of Central South University Xiangya School of Medicine from April 2018 to May 2020. Two senior radiologists and two senior intensive care physicians were participated to evaluated the extent of lesions involvement and imaging features of the first chest CT after the onset of the disease. RESULTS: Bilateral pulmonary lesions were more common in patients with COVID-19 and other viral pneumonia, and the incidence was significantly higher than that of bacterial pneumonia (91.6%, 75.0% vs. 26.0%, P < 0.05). Compared with other viral pneumonia and COVID-19, bacterial pneumonia was mainly characterized by single-lung and multi-lobed lesion (62.0% vs. 18.8%, 5.6%, P < 0.05), accompanied by pleural effusion and lymph node enlargement. The proportion of ground-glass opacity in the lung tissues of patients with COVID-19 was 97.2%, that of patients with other viral pneumonia was 56.2%, and that of patients with bacterial pneumonia was only 2.0% (P < 0.05). The incidence rate of lung tissue consolidation (25.0%, 12.5%), air bronchial sign (13.9%, 6.2%) and pleural effusion (16.7%, 37.5%) in patients with COVID-19 and other viral pneumonia were significantly lower than those in patients with bacterial pneumonia (62.0%, 32.0%, 60.0%, all P < 0.05), paving stone sign (22.2%, 37.5%), fine mesh sign (38.9%, 31.2%), halo sign (11.1%, 25.0%), ground-glass opacity with interlobular septal thickening (30.6%, 37.5%), bilateral patchy pattern/rope shadow (80.6%, 50.0%) etc. were significantly higher than those of bacterial pneumonia (2.0%, 4.0%, 2.0%, 0%, 22.0%, all P < 0.05). The incidence of local patchy shadow in patients with COVID-19 was only 8.3%, significantly lower than that in patients with other viral pneumonia and bacterial pneumonia (8.3% vs. 68.8%, 50.0%, P < 0.05). There was no significant difference in the incidence of peripheral vascular shadow thickening in patients with COVID-19, other viral pneumonia and bacterial pneumonia (27.8%, 12.5%, 30.0%, P > 0.05). CONCLUSIONS: The probability of ground-glass opacity, paving stone and grid shadow in chest CT of patients with COVID-19 was significantly higher than those of bacterial pneumonia, and it was more common in the lower lungs and lateral dorsal segment. In other patients with viral pneumonia, ground-glass opacity was distributed in both upper and lower lungs. Bacterial pneumonia is usually characterized by single lung consolidation, distributed in lobules or large lobes and accompanied by pleural effusion.

Circular RNA circFBXO7 attenuates non-small cell lung cancer tumorigenesis by sponging miR-296-3p to facilitate KLF15-mediated transcriptional activation of CDKN1A.

BACKGROUND: Accumulating evidence indicates that circular RNAs (circRNAs) play important roles in various cancers. Hsa_circ_0008832 (circFBXO7) is a circRNA generated from the second exon of the human F-box only protein 7 (FBXO7). Mouse circFbxo7 is a circRNA generated from the second exon of mouse F-box only protein 7 (Fbxo7). The role of human circFBXO7 and mouse circFbxo7 in non-small cell lung cancer (NSCLC) has not been reported. METHODS: The expression of circFBXO7 was measured by quantitative real-time PCR. Survival analysis was performed to explore the association between the expression of circFBXO7 and the prognosis of patients with NSCLC. Lung cancer cell lines were transfected with plasmids. Cell proliferation, cell cycle, and tumorigenesis were evaluated to assess the effects of circFBXO7. Fluorescence in situ hybridization assay was used to identify the location of circFBXO7 and circFbxo7 in human and mouse lung cancer cells. Luciferase reporter assay was conducted to confirm the relationship between circFBXO7 and microRNA. RESULTS: In this study, we found that circFBXO7 was downregulated in NSCLC tissues and cell lines. NSCLC patients with high circFBXO7 expression had prolonged overall survival. Overexpression of circFBXO7 inhibited cell proliferation both in vitro and in vivo. Mechanistically, we demonstrated that circFBXO7 upregulated the expression of miR-296-3p target gene Krüppel-like factor 15 (KLF15) and KLF15 transactivated the expression of CDKN1A. CONCLUSIONS: CircFBXO7 acts as a tumor suppressor by a novel circFBXO7/miR-296-3p/KLF15/CDKN1A axis, which may serve as a potential biomarker and therapeutic target for NSCLC.

Circ_0001721 knockdown relieves IL-1ß-induced chondrocyte injury via regulating miR-373-3p/CXCR4 in osteoarthritis.

BACKGROUND: Circular RNA (circRNA) plays an important role in osteoarthritis (OA) progression. Circ_0001721 has been noted to be significantly overexpressed in OA patients, but its function in OA progression remain unclear. The purpose of this study was to investigate the role and mechanism of circ_0001721 in OA progression. METHODS: Interleukin-1ß (IL-1ß)-induced chondrocytes were used to mimic OA cell model in vitro. The expression of circ_0001721, microRNA (miR)-373-3p and CXC chemokine receptor 4 (CXCR4) was examined by quantitative real-time PCR. The concentrations of inflammatory factors were assessed by ELISA assay. Cell proliferation and apoptosis were determined by MTT assay, EdU assay and flow cytometry. Protein levels were detected by western blot analysis. The interaction between miR-373-3p and circ_0001721 or CXCR4 was confirmed by dual-luciferase reporter assay, RIP assay and RNA pull-down assay. RESULTS: Our results showed that circ_0001721 was highly expressed in OA patients and IL-1ß-induced chondrocytes. IL-1ß treatment could suppress the proliferation, while promote the apoptosis, extracellular matrix (ECM) degradation and inflammation of chondrocytes. Knockdown of circ_0001721 alleviated IL-1ß-induced chondrocyte injury. MiR-373-3p could be sponged by circ_0001721, and its inhibitor reversed the regulation of circ_0001721 knockdown on IL-1ß-induced chondrocyte injury. CXCR4 was a target of miR-373-3p, and circ_0001721 could sponge miR-373-3p to regulate CXCR4. Furthermore, miR-373-3p overexpression inhibited IL-1ß-induced chondrocyte injury, and these effects could be overturned by CXCR4 upregulation. CONCLUSION: Our data confirmed that circ_0001721 knockdown alleviated IL-1ß-induced chondrocyte injury by miR-373-3p/CXCR4 axis, which suggested that circ_0001721 might be a potential therapeutic target for OA.

Driver Drowsiness EEG Detection Based on Tree Federated Learning and Interpretable Network.

Accurate identification of driver's drowsiness state through Electroencephalogram (EEG) signals can effectively reduce traffic accidents, but EEG signals are usually stored in various clients in the form of small samples. This study attempts to construct an efficient and accurate privacy-preserving drowsiness monitoring system, and proposes a fusion model based on tree Federated Learning (FL) and Convolutional Neural Network (CNN), which can not only identify and explain the driver's drowsiness state, but also integrate the information of different clients under the premise of privacy protection. Each client uses CNN with the Global Average Pooling (GAP) layer and shares model parameters. The tree FL transforms communication relationships into a graph structure, and model parameters are transmitted in parallel along connected branches of the graph. Moreover, the Class Activation Mapping (CAM) is used to find distinctive EEG features for representing specific classes. On EEG data of 11 subjects, it is found that this method has higher average accuracy, F1-score and AUC than the traditional classification method, reaching 73.56%, 73.26% and 78.23%, respectively. Compared with the traditional FL algorithm, this method better protects the driver's privacy and improves communication efficiency.

N6-methyladenosine demethylase FTO enhances chemo-resistance in colorectal cancer through SIVA1-mediated apoptosis.

N6-methyladenosine (m6A) is the most pervasive RNA modification and is recognized as a novel epigenetic regulation in RNA metabolism. Although the m6A modification involves various physiological processes, its roles in drug resistance in colorectal cancer (CRC) still remain unknown. We analyzed the RNA expression profile of m6A/A (%) with MRM mass spectrometry in human 5-fluorouracil (5-FU)-resistant CRC tissues, and used the m6A RNA immunoprecipitation assay to validate the m6A-regulated target. Our results have shown that the m6A demethylase FTO was up-regulated in human primary and 5-FU-resistant CRC. Depletion of FTO decreased cell growth, colony formation and metastasis in 5-FU-resistant CRC cells in vitro and in vivo. Mechanistically, we identified SIVA1, a critical apoptotic gene, as a key downstream target of the FTO-mediated m6A demethylation. The m6A demethylation of SIVA1 at the CDS region induced its mRNA degradation via a YTHDF2-dependent mechanism. The SIVA1 levels were negatively correlated with the FTO levels in clinical CRC tissues. Notably, inhibition of FTO significantly reduced the tolerance of 5-FU in 5-FU-resistant CRC cells via the FTO-SIVA1 axis, whereas SIVA1-depletion could restore the m6A-dependent 5-FU sensitivity in CRC cells. In summary, our findings demonstrate a critical role of FTO as an m6A demethylase enhancing chemo-resistance in CRC cells, and suggest that FTO inhibition may restore the sensitivity of chemo-resistant CRC cells to 5-FU.

Virulence Variability and Genetic Diversity in Blumeria graminis f. sp. hordei in Southeastern and Southwestern China.

Powdery mildew is a key airborne foliar disease of barley in southeastern and southwestern China. Barley varieties usually partially or wholly lose resistance to the pathogen Blumeria graminis (DC.) f. sp. hordei 3 to 5 years after release due to the frequent acquirements of new virulences in the pathogen population. However, no B. graminis f. sp. hordei virulence detection has been carried out in the recent decade and, thus, no information is available on the present virulence components and major pathotypes in epidemic regions. Twenty-one near-isogenic lines of Pallas were selected to detect B. graminis f. sp. hordei virulence variation, with 97 pathotypes identified from the isolates collected from 2015 to 2019. The virulence complexities ranged from 1 to 12, with 1.5 isolates on average assigned per pathotype, suggesting a natural trait of high pathotype diversity and low virulence complexity in the Chinese B. graminis f. sp. hordei populations. Eleven high-virulence pathotypes were detected in the traditional barley-growing regions in Yunnan and Zhejiang. Six virulent pathotypes to resistance gene mlo-5 were detected only in the two traditional epidemic regions, with a virulence frequency (VF) of 4.8% (7 of 147). Compared with the results from a decade ago, VFs for resistance alleles Mla3, mlo-5, Mla6 + Mla14, Mla7 + Mlk, Mlg + MlCP, and Mla13 + MlRu3 + MlaRu4 increased from 0 to 0.7 to 25.8%. Isolates from Yunnan and Zhejiang had similar virulence profiles, which differed from those identified in Tibet. In addition, genetic diversities differed in the isolate groups collected from Tibet, Yunnan, and Zhejiang.