m6A-mediated lnc-OXAR promotes oxaliplatin resistance by enhancing Ku70 stability in non-alcoholic steatohepatitis-related hepatocellular carcinoma.

BACKGROUND: The escalating prevalence of metabolic diseases has led to a rapid increase in non-alcoholic steatohepatitis (NASH)-related hepatocellular carcinoma (NASH-HCC). While oxaliplatin (OXA)-based hepatic arterial infusion chemotherapy (HAIC) has shown promise in advanced-stage HCC patients, its efficacy in NASH-HCC remains uncertain. This study aims to assess the effectiveness of OXA-based HAIC and elucidate the mechanisms underlying OXA resistance in NASH-HCC. METHODS: The key lncRNAs were screened through RNA-seq analysis of NASH/non-NASH and OXA-sensitive/OXA-resistant (OXA-S/R) HCC tissues. The biological functions of the lnc-OXAR (OXA resistance-related lncRNA in NASH-HCC) in NASH-HCC were verified through a series of in vitro and in vivo experiments. The molecular mechanism of lnc-OXAR was elucidated by fluorescence in situ hybridization, immunoprecipitation-mass spectrometry (FISH), Immunoprecipitation-Mass Spectrometry (IP-MS), RNA pulldown, RNA immunoprecipitation (RIP), methylated RNA immunoprecipitation sequencing (MeRIP-Seq) and a dual-luciferase reporter assay. RESULTS: NASH-HCC exhibited reduced responsiveness to OXA-based HAIC compared to non-NASH HCC. We identified and validated a novel transcript namedlnc-OXAR, which played a crucial role in conferring OXA resistance to NASH-HCC. Inhibition of lnc-OXAR suppressed HCC cell growth and restored OXA sensitivity both in NASH-HCC mouse models and in vitro. Mechanistically, lnc-OXAR recruited Ku70 and cystatin A (CSTA), preventing Ku70 degradation and facilitating DNA double-strand break (DSB) repair, thereby promoting OXA resistance in NASH-HCC. Additionally, WTAP-mediated m6A modification enhanced the stability of lnc-OXAR in an IGF2BP2-dependent manner. Notably, silencing lnc-OXAR significantly enhanced the response to OXA in patient-derived xenograft (PDX) models derived from NASH-HCC. CONCLUSIONS: The reduced responsiveness of NASH-HCC to OXA treatment can be attributed to the upregulation of lnc-OXAR. Our findings provide a rationale for stratifying HCC patients undergoing OXA-based HAIC based on etiology. Lnc-OXAR holds promise as a novel target for overcoming OXA resistance in NASH-HCC and improving prognosis.

Monoacylglycerol acyltransferase-2 inhibits colorectal carcinogenesis in APCmin+/- mice.

Monoacylglycerol acyltransferase-2 (MOGAT2), encodes MOGAT enzyme in the re-synthesis of triacylglycerol and protects from metabolism disorders. While, its precise involvement in colorectal cancer (CRC) progression remains inadequately understood. Our study demonstrated that knockout of Mogat2 in Apcmin/+ mice expedited intestinal tumor growth and progression, indicating that Mogat2 plays a tumor-suppressing role in CRC. Mechanically, Mogat2 deletion resulted in a significant alter the gut microbiota, while Fecal Microbiota Transplantation (FMT) experiments demonstrated that the gut microbiota in Mogat2 deleted mice promoted tumor growth. Furthermore, we identified Mogat2 as a functional regulator suppressing CRC cell proliferation and tumor growth by inhibiting the NF-κB signaling pathway in vivo. Collectively, these results provide novel insights into the protective double roles of Mogat2, inhibiting of NF-κB pathway and keeping gut microbiota homeostasis in colorectal cancer, which may help the development of novel cancer treatments for CRC.

KLF4 Suppresses the Progression of Hepatocellular Carcinoma by Reducing Tumor ATP Synthesis through Targeting the Mir-206/RICTOR Axis.

To address the increased energy demand, tumor cells undergo metabolic reprogramming, including oxidative phosphorylation (OXPHOS) and aerobic glycolysis. This study investigates the role of Kruppel-like factor 4 (KLF4), a transcription factor, as a tumor suppressor in hepatocellular carcinoma (HCC) by regulating ATP synthesis. Immunohistochemistry was performed to assess KLF4 expression in HCC tissues. Functional assays, such as CCK-8, EdU, and colony formation, as well as in vivo assays, including subcutaneous tumor formation and liver orthotopic xenograft mouse models, were conducted to determine the impact of KLF4 on HCC proliferation. Luciferase reporter assay and chromatin immunoprecipitation assay were utilized to evaluate the interaction between KLF4, miR-206, and RICTOR. The findings reveal low KLF4 expression in HCC, which is associated with poor prognosis. Both in vitro and in vivo functional assays demonstrate that KLF4 inhibits HCC cell proliferation. Mechanistically, it was demonstrated that KLF4 reduces ATP synthesis in HCC by suppressing the expression of RICTOR, a core component of mTORC2. This suppression promotes glutaminolysis to replenish the TCA cycle and increase ATP levels, facilitated by the promotion of miR-206 transcription. In conclusion, this study enhances the understanding of KLF4's role in HCC ATP synthesis and suggests that targeting the KLF4/miR-206/RICTOR axis could be a promising therapeutic approach for anti-HCC therapeutics.

Functional validation of AaCaM3 response to high temperature stress in Amorphophallus albus.

Amorphophallus is a perennial monocotyledonous herbaceous plant native to the southwestern region of China, widely used in various fields such as food processing, biomedicine and chemical agriculture. However, Amorphophallus is a typical thermolabile plant, and the continuous high temperature in summer have seriously affected the growth, development and economic yield of Amorphophallus in recent years. Calmodulin (CaM), a Ca2+ sensor ubiquitous in eukaryotes, is the most important multifunctional receptor protein in plant cells, which affects plant stress resistance by participating in the activities of a variety of signaling molecules. In this study, the key gene AaCaM3 for the Ca2+-CaM regulatory pathway was obtained from A. albus, the sequence analysis confirmed that it is a typical calmodulin. The qRT-PCR results demonstrated that with the passage of heat treatment time, the expression of AaCaM3 was significantly upregulated in A. albus leaves. Subcellular localization analysis revealed that AaCaM3 localized on the cytoplasm and nucleus. Meanwhile, heterologous transformation experiments have shown that AaCaM3 can significantly improve the heat tolerance of Arabidopsis under heat stress. The promoter region of AaCaM3 was sequenced 1,338 bp by FPNI-PCR and GUS staining assay showed that the promoter of AaCaM3 was a high-temperature inducible promoter. Yeast one-hybrid analysis and Luciferase activity reporting system analysis showed that the AaCaM3 promoter may interact with AaHSFA1, AaHSFA2c, AaHSP70, AaDREB2a and AaDREB2b. In conclusion, this study provides new ideas for further improving the signal transduction network of high-temperature stress in Amorphophallus.

Circulation pattern and genetic variation of rhinovirus infection among hospitalized children on Hainan Island, before and after the dynamic zero-COVID policy, from 2021 to 2023.

Throughout the COVID-19 pandemic, rhinovirus (RV) remained notable persistence, maintaining its presence while other seasonal respiratory viruses were largely suppressed by pandemic restrictions during national lockdowns. This research explores the epidemiological dynamics of RV infections among pediatric populations on Hainan Island, China, specifically focusing on the impact before and after the zero-COVID policy was lifted. From January 2021 to December 2023, 19 680 samples were collected from pediatric patients hospitalized with acute lower respiratory tract infections (ARTIs) at the Hainan Maternal and Child Health Hospital. The infection of RV was detected by tNGS. RV species and subtypes were identified in 32 RV-positive samples representing diverse time points by analyzing the VP4/VP2 partial regions. Among the 19 680 pediatric inpatients with ARTIs analyzed, 21.55% were found to be positive for RV infection, with notable peaks observed in April 2021 and November 2022. A gradual annual decline in RV infections was observed, alongside a seasonal pattern of higher prevalence during the colder months. The highest proportion of RV infections was observed in the 0-1-year age group. Phylogenetic analysis on 32 samples indicated a trend from RV-A to RV-C in 2022. This observation suggests potential evolving dynamics within the RV species although further studies are needed due to the limited sample size. The research emphasizes the necessity for ongoing surveillance and targeted management, particularly for populations highly susceptible to severe illnesses caused by RV infections.

Expression pattern of the poplar GSTU family members in response to Alternaria alternate and PdbGSTU10 confers A. alternate resistance to Populus davidiana × P. bolleana.

Plant tau glutathione S-transferase (GSTU) is a kind of multiple functions enzyme, but its specific roles in poplar disease resistance remain uncertain. In this study, 27 PdbGSTU-encoding genes from Populus davidiana × P. bollena were cloned and their protein architectures and phylogenetic relationships were subsequently analyzed. Expression analysis revealed that PdbGSTUs were differentially expressed under Alternaria alternate infection. Then, the PdbGSTU10 was further induced by phytohormones and H2O2, especially salicylic acid (SA), indicating its potential role in the pathogen defense of poplar. Subsequently, gain- and loss-of-function assays showed that overexpressed PdbGSTU10 activated antioxidant enzymes and significantly decreased reactive oxygen species (ROS) content, ultimately improving the resistance to A. alternate in poplar. Conversely, silencing PdbGSTU10 had the opposite effect. Moreover, overexpressed PdbGSTU10 also increased the content of SA and induced the expression of SA signal-related genes. These results showed that PdbGSTU10 may enhance disease resistance in poplar by scavenging ROS and affecting the SA signaling pathway. Our findings contribute to the understanding of the functions of GSTU in woody plants, particularly in disease resistance.

Influence of maximum diameter on fine-needle aspiration biopsy outcomes in ACR TI-RADS 5 thyroid nodules.

Introduction: Fine needle aspiration (FNA) biopsy is a widely accepted method for diagnosing thyroid nodules. However, the influence of maximum diameter (MD) of ACR TIRADS 5 (TR5) thyroid nodules on the FNA outcomes remains debated. This study examined the influence of MD on the FNA outcomes and investigated the optimal MD threshold for FNA in TR5 nodules. Methods: We conducted a retrospective analysis of 280 TR5 thyroid nodules from 226 patients who underwent FNA from January to June 2022 in our department. Probably malignant (PM) group was defined as Bethesda V in cytopathology with confirmed BRAF V600E mutation or Bethesda VI, the other cytopathology outcomes were defined as probably benign (PB) group. We examined factors influencing malignant cytopathology outcomes and determined the optimal MD threshold for FNA in TR5 nodules using logistic regression and restricted cubic spline (RCS) analysis. Results: Among these nodules, 58.2% (163/280) had PM outcomes. The PM group had a significantly larger MD than the PB group [6.5mm (range 5.0-8.4) vs. 5.3mm (range 4.0-7.0), p < 0.001]. In multivariate logistic regression fully adjusted for confounders, MD was significantly associated with PM outcomes [odds ratio 1.16, 95%CI 1.05-1.31; p = 0.042]. The highest quartile of MD had a greater likelihood of PM outcomes compared to the lowest quartile [odds ratio 4.71, 95% CI 1.97-11.69, p = 0.001]. The RCS analysis identified 6.2 mm as the optimal MD threshold for FNA in TR5 nodules. Conclusion: MD significantly affects the probability of malignant outcomes in FNA of TR5 thyroid nodules. A MD threshold of ≥6.2mm is suggested for FNA in these nodules.

Melatonin promotes hair regeneration by modulating the Wnt/ß-catenin signalling pathway.

Melatonin (MLT) is a circadian hormone that reportedly influences the development and cyclic growth of secondary hair follicles; however, the mechanism of regulation remains unknown. Here, we systematically investigated the role of MLT in hair regeneration using a hair depilation mouse model. We found that MLT supplementation significantly promoted hair regeneration in the hair depilation mouse model, whereas supplementation of MLT receptor antagonist luzindole significantly suppressed hair regeneration. By analysing gene expression dynamics between the MLT group and luzindole-treated groups, we revealed that MLT supplementation significantly up-regulated Wnt/ß-catenin signalling pathway-related genes. In-depth analysis of the expression of key molecules in the Wnt/ß-catenin signalling pathway revealed that MLT up-regulated the Wnt/ß-catenin signalling pathway in dermal papillae (DP), whereas these effects were facilitated through mediating Wnt ligand expression levels in the hair follicle stem cells (HFSCs). Using a DP-HFSCs co-culture system, we verified that MLT activated Wnt/ß-catenin signalling in DPs when co-cultured with HFSCs, whereas supplementation of DP cells with MLT alone failed to activate Wnt/ß-catenin signalling. In summary, our work identified a critical role for MLT in promoting hair regeneration and will have potential implications for future hair loss treatment in humans.

Semantic image sorting method for RSVP presentation.

Objective.The rapid serial visual presentation (RSVP) paradigm, which is based on the electroencephalogram (EEG) technology, is an effective approach for object detection. It aims to detect the event-related potentials (ERP) components evoked by target images for rapid identification. However, the object detection performance within this paradigm is affected by the visual disparity between adjacent images in a sequence. Currently, there is no objective metric to quantify this visual difference. Consequently, a reliable image sorting method is required to ensure the generation of a smooth sequence for effective presentation.Approach. In this paper, we propose a novel semantic image sorting method for sorting RSVP sequences, which aims at generating sequences that are perceptually smoother in terms of the human visual experience.Main results. We conducted a comparative analysis between our method and two existing methods for generating RSVP sequences using both qualitative and quantitative assessments. A qualitative evaluation revealed that the sequences generated by our method were smoother in subjective vision and were more effective in evoking stronger ERP components than those generated by the other two methods. Quantitatively, our method generated semantically smoother sequences than the other two methods. Furthermore, we employed four advanced approaches to classify single-trial EEG signals evoked by each of the three methods. The classification results of the EEG signals evoked by our method were superior to those of the other two methods.Significance. In summary, the results indicate that the proposed method can significantly enhance the object detection performance in RSVP-based sequences.

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.

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.

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.

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.