Oct4 redox sensitivity potentiates reprogramming and differentiation.

The transcription factor Oct4/Pou5f1 is a component of the regulatory circuitry governing pluripotency and is widely used to induce pluripotency from somatic cells. Here we used domain swapping and mutagenesis to study Oct4's reprogramming ability, identifying a redox-sensitive DNA binding domain, cysteine residue (Cys48), as a key determinant of reprogramming and differentiation. Oct4 Cys48 sensitizes the protein to oxidative inhibition of DNA binding activity and promotes oxidation-mediated protein ubiquitylation. Pou5f1 C48S point mutation has little effect on undifferentiated embryonic stem cells (ESCs) but upon retinoic acid (RA) treatment causes retention of Oct4 expression, deregulated gene expression, and aberrant differentiation. Pou5f1 C48S ESCs also form less differentiated teratomas and contribute poorly to adult somatic tissues. Finally, we describe Pou5f1 C48S (Janky) mice, which in the homozygous condition are severely developmentally restricted after E4.5. Rare animals bypassing this restriction appear normal at birth but are sterile. Collectively, these findings uncover a novel Oct4 redox mechanism involved in both entry into and exit from pluripotency.

Candida albicans elicits protective allergic responses via platelet mediated T helper 2 and T helper 17 cell polarization.

Fungal airway infection (airway mycosis) is an important cause of allergic airway diseases such as asthma, but the mechanisms by which fungi trigger asthmatic reactions are poorly understood. Here, we leverage wild-type and mutant Candida albicans to determine how this common fungus elicits characteristic Th2 and Th17 cell-dependent allergic airway disease in mice. We demonstrate that rather than proteinases that are essential virulence factors for molds, C. albicans instead promoted allergic airway disease through the peptide toxin candidalysin. Candidalysin activated platelets through the Von Willebrand factor (VWF) receptor GP1bα to release the Wnt antagonist Dickkopf-1 (Dkk-1) to drive Th2 and Th17 cell responses that correlated with reduced lung fungal burdens. Platelets simultaneously precluded lethal pulmonary hemorrhage resulting from fungal lung invasion. Thus, in addition to hemostasis, platelets promoted protection against C. albicans airway mycosis through an antifungal pathway involving candidalysin, GP1bα, and Dkk-1 that promotes Th2 and Th17 responses.

A membrane-based seawater electrolyser for hydrogen generation.

Electrochemical saline water electrolysis using renewable energy as input is a highly desirable and sustainable method for the mass production of green hydrogen1-7; however, its practical viability is seriously challenged by insufficient durability because of the electrode side reactions and corrosion issues arising from the complex components of seawater. Although catalyst engineering using polyanion coatings to suppress corrosion by chloride ions or creating highly selective electrocatalysts has been extensively exploited with modest success, it is still far from satisfactory for practical applications8-14. Indirect seawater splitting by using a pre-desalination process can avoid side-reaction and corrosion problems15-21, but it requires additional energy input, making it economically less attractive. In addition, the independent bulky desalination system makes seawater electrolysis systems less flexible in terms of size. Here we propose a direct seawater electrolysis method for hydrogen production that radically addresses the side-reaction and corrosion problems. A demonstration system was stably operated at a current density of 250 milliamperes per square centimetre for over 3,200 hours under practical application conditions without failure. This strategy realizes efficient, size-flexible and scalable direct seawater electrolysis in a way similar to freshwater splitting without a notable increase in operation cost, and has high potential for practical application. Importantly, this configuration and mechanism promises further applications in simultaneous water-based effluent treatment and resource recovery and hydrogen generation in one step.

The AAA-ATPase Yta4/ATAD1 interacts with the mitochondrial divisome to inhibit mitochondrial fission.

Mitochondria are in a constant balance of fusion and fission. Excessive fission or deficient fusion leads to mitochondrial fragmentation, causing mitochondrial dysfunction and physiological disorders. How the cell prevents excessive fission of mitochondria is not well understood. Here, we report that the fission yeast AAA-ATPase Yta4, which is the homolog of budding yeast Msp1 responsible for clearing mistargeted tail-anchored (TA) proteins on mitochondria, plays a critical role in preventing excessive mitochondrial fission. The absence of Yta4 leads to mild mitochondrial fragmentation in a Dnm1-dependent manner but severe mitochondrial fragmentation upon induction of mitochondrial depolarization. Overexpression of Yta4 delocalizes the receptor proteins of Dnm1, i.e., Fis1 (a TA protein) and Mdv1 (the bridging protein between Fis1 and Dnm1), from mitochondria and reduces the localization of Dnm1 to mitochondria. The effect of Yta4 overexpression on Fis1 and Mdv1, but not Dnm1, depends on the ATPase and translocase activities of Yta4. Moreover, Yta4 interacts with Dnm1, Mdv1, and Fis1. In addition, Yta4 competes with Dnm1 for binding Mdv1 and decreases the affinity of Dnm1 for GTP and inhibits Dnm1 assembly in vitro. These findings suggest a model, in which Yta4 inhibits mitochondrial fission by inhibiting the function of the mitochondrial divisome composed of Fis1, Mdv1, and Dnm1. Therefore, the present work reveals an uncharacterized molecular mechanism underlying the inhibition of mitochondrial fission.

A KDELR-mediated ER-retrieval system modulates mitochondrial functions via the unfolded protein response in fission yeast.

KDELR (Erd2 [ER retention defective 2] in yeasts) is a receptor protein that retrieves endoplasmic reticulum (ER)-resident proteins from the Golgi apparatus. However, the role of the KDELR-mediated ER-retrieval system in regulating cellular homeostasis remains elusive. Here, we show that the absence of Erd2 triggers the unfolded protein response (UPR) and enhances mitochondrial respiration and reactive oxygen species in an UPR-dependent manner in the fission yeast Schizosaccharomyces pombe. Moreover, we perform transcriptomic analysis and find that the expression of genes related to mitochondrial respiration and the tricarboxylic acid cycle is upregulated in a UPR-dependent manner in cells lacking Erd2. The increased mitochondrial respiration and reactive oxygen species production is required for cell survival in the absence of Erd2. Therefore, our findings reveal a novel role of the KDELR-Erd2-mediated ER-retrieval system in modulating mitochondrial functions and highlight its importance for cellular homeostasis in the fission yeast.

RLBind: a deep learning method to predict RNA-ligand binding sites.

Identification of RNA-small molecule binding sites plays an essential role in RNA-targeted drug discovery and development. These small molecules are expected to be leading compounds to guide the development of new types of RNA-targeted therapeutics compared with regular therapeutics targeting proteins. RNAs can provide many potential drug targets with diverse structures and functions. However, up to now, only a few methods have been proposed. Predicting RNA-small molecule binding sites still remains a big challenge. New computational model is required to better extract the features and predict RNA-small molecule binding sites more accurately. In this paper, a deep learning model, RLBind, was proposed to predict RNA-small molecule binding sites from sequence-dependent and structure-dependent properties by combining global RNA sequence channel and local neighbor nucleotides channel. To our best knowledge, this research was the first to develop a convolutional neural network for RNA-small molecule binding sites prediction. Furthermore, RLBind also can be used as a potential tool when the RNA experimental tertiary structure is not available. The experimental results show that RLBind outperforms other state-of-the-art methods in predicting binding sites. Therefore, our study demonstrates that the combination of global information for full-length sequences and local information for limited local neighbor nucleotides in RNAs can improve the model's predictive performance for binding sites prediction. All datasets and resource codes are available at https://github.com/KailiWang1/RLBind.

VIGA: a one-stop tool for eukaryotic virus identification and genome assembly from next-generation-sequencing data.

Identification of viruses and further assembly of viral genomes from the next-generation-sequencing data are essential steps in virome studies. This study presented a one-stop tool named VIGA (available at https://github.com/viralInformatics/VIGA) for eukaryotic virus identification and genome assembly from NGS data. It was composed of four modules, namely, identification, taxonomic annotation, assembly and novel virus discovery, which integrated several third-party tools such as BLAST, Trinity, MetaCompass and RagTag. Evaluation on multiple simulated and real virome datasets showed that VIGA assembled more complete virus genomes than its competitors on both the metatranscriptomic and metagenomic data and performed well in assembling virus genomes at the strain level. Finally, VIGA was used to investigate the virome in metatranscriptomic data from the Human Microbiome Project and revealed different composition and positive rate of viromes in diseases of prediabetes, Crohn's disease and ulcerative colitis. Overall, VIGA would help much in identification and characterization of viromes, especially the known viruses, in future studies.

The protective effect and bioactive compounds of Astragalus membranaceus against neurodegenerative disorders via alleviating oxidative stress in Drosophila.

Oxidative stress is proposed as a regulatory element in various neurological disorders, which is involved in the progress of several neurodegenerative diseases such as Alzheimer's disease (AD) and Parkinson's disease (PD). Antioxidant drugs are widely used to alleviate neurodegenerative disorders. Astragalus membranaceus (Huangqi, AM) is a commonly used medicinal herb with a wide range of pharmacological effects. Here, the protective effect and mechanism of AM extract (AME) and its bioactive compounds against neurodegenerative disorders via alleviating oxidative stress were detected using adult Drosophila melanogaster. The drug safety was measured by development analysis; oxidative stress resistance ability was detected by survival rate under H2O2 environment; ROS level was detected by DHE staining and gstD1-GFP fluoresence assay; antioxidative abilitiy was represent by measuring antioxidant enzyme activity, antioxidative-related gene expression, and ATP and MFN2 levels. The neuroprotective effect was evaluated by lifespan and locomotion analysis in Aß42 transgenic and Pink1B9 mutants. AME dramatically increased the survival rates, improved the CAT activity, restored the decreased mRNA expressions of Sod1, Cat, and CncC under H2O2 stimulation, and ameliorated the neurobehavioral defects of the AD and PD. Thirteen small molecules in AM had antioxidant function, in which vanillic acid and daidzein had the most potent antioxidant effect. Vanillic acid and daidzein could increase the activities of SOD and CAT, GSH level, and the expressions of antioxidant genes. Vanillic acid could improve the levels of ATP and MFN2, and mRNA expressions of ND42 and SDHC to rescue mitochondrial dysfunction. Furthermore, vanillic acid ameliorated neurobehavioral defects of PD. Daidzein ameliorated neurobehavioral defect of Aß-induced AD mode. Taken together, AM plays a protective role in oxidative damage, thereby as a potential natural drug to treat neurodegenerative disorders.

Excitonic Quantum Coherence in Light Emission from CsPbBr3 Metal-Halide Perovskite Nanocrystals.

The decay of excited states via radiative and nonradiative paths is well understood in molecules and bulk semiconductors but less so in nanocrystals. Here, we perform time-resolved photoluminescence (t-PL) experiments on CsPbBr3 metal-halide perovskite nanocrystals, with a time resolution of 3 ps, sufficient to observe the decay of both excitons and biexcitons as a function of temperature. The striking result is that the radiative rate constant of the single exciton increases at low temperatures with an exponential functional form, suggesting quantum coherent effects with dephasing at high temperatures. The opposing directions of the radiative and nonradiative decay rate constants enable enhanced brightening of PL from excitons to biexcitons due to quantum effects, promoting a faster approach to the quantum theoretical limits of light emission. Ab initio quantum dynamics simulations reproduce the experimental observations of radiation controlled by quantum spatial coherence enhanced at low temperatures.

Precise Distance Control and Functionality Adjustment of Frustrated Lewis Pairs in Metal-Organic Frameworks.

We report the construction of frustrated Lewis pairs (FLPs) in a metal-organic framework (MOF), where both Lewis acid (LA) and Lewis base (LB) are fixed to the backbone. The anchoring of a tritopic organoboron linker as LA and a monotopic linker as LB to separate metal oxide clusters in a tetrahedron geometry allows for the precise control of distance between them. As the type of monotopic LB linker varies, pyridine, phenol, aniline, and benzyl alcohol, a series of 11 FLPs were constructed to give fixed distances of 7.1, 5.5, 5.4, and 4.8 Å, respectively, revealed by 11B-1H solid-state nuclear magnetic resonance spectroscopy. Keeping LA and LB apart by a fixed distance makes it possible to investigate the electrostatic effect by changing the functional groups in the monotopic LB linker, while the LA counterpart remains unaffected. This approach offers new chemical environments of the active site for FLP-induced catalysis.

Th2-skewed peripheral T-helper cells drive B-cells in allergic bronchopulmonary aspergillosis.

INTRODUCTION: Patients with allergic bronchopulmonary aspergillosis (ABPA) suffer from repeated exacerbations. The involvement of T-cell subsets remains unclear. METHODS: We enrolled ABPA patients, asthma patients and healthy controls. T-helper type 1 (Th1), 2 (Th2) and 17 (Th17) cells, regulatory T-cells (Treg) and interleukin (IL)-21+CD4+T-cells in total or sorted subsets of peripheral blood mononuclear cells and ABPA bronchoalveolar lavage fluid (BALF) were analysed using flow cytometry. RNA sequencing of subsets of CD4+T-cells was done in exacerbated ABPA patients and healthy controls. Antibodies of T-/B-cell co-cultures in vitro were measured. RESULTS: ABPA patients had increased Th2 cells, similar numbers of Treg cells and decreased circulating Th1 and Th17 cells. IL-5+IL-13+IL-21+CD4+T-cells were rarely detected in healthy controls, but significantly elevated in the blood of ABPA patients, especially the exacerbated ones. We found that IL-5+IL-13+IL-21+CD4+T-cells were mainly peripheral T-helper (Tph) cells (PD-1+CXCR5-), which also presented in the BALF of ABPA patients. The proportions of circulating Tph cells were similar among ABPA patients, asthma patients and healthy controls, while IL-5+IL-13+IL-21+ Tph cells significantly increased in ABPA patients. Transcriptome data showed that Tph cells of ABPA patients were Th2-skewed and exhibited signatures of follicular T-helper cells. When co-cultured in vitro, Tph cells of ABPA patients induced the differentiation of autologous B-cells into plasmablasts and significantly enhanced the production of IgE. CONCLUSION: We identified a distinctly elevated population of circulating Th2-skewed Tph cells that induced the production of IgE in ABPA patients. It may be a biomarker and therapeutic target for ABPA.

Multidimensional Applications and Challenges of Riboswitches in Biosensing and Biotherapy.

Riboswitches have received significant attention over the last two decades for their multiple functionalities and great potential for applications in various fields. This article highlights and reviews the recent advances in biosensing and biotherapy. These fields involve a wide range of applications, such as food safety detection, environmental monitoring, metabolic engineering, live cell imaging, wearable biosensors, antibacterial drug targets, and gene therapy. The discovery, origin, and optimization of riboswitches are summarized to help readers better understand their multidimensional applications. Finally, this review discusses the multidimensional challenges and development of riboswitches in order to further expand their potential for novel applications.

Aptamer and Thiol Co-Regulated Color-Shifting Fluorophores via Dynamic Through-Bond/Space Conjugation for Constructing Ratiometric RNA Sensor.

Fluorophores with color-shifting characteristics have attracted enormous research interest in the quantitative application of RNA sensors. It reports here a simple synthesis, luminescent properties, and co-transcription ability of de-conjugated triphenylmethane leucomalachite green (LMG). This novel clusteroluminescence fluorophore is rapidly synthesized from malachite green (MG) in reductive transcription system containing dithiothreitol, emitting fluorescence in the UV region through space conjugation. The co-transcribed MG RNA aptamer (MGA) bound to the ligand, resulting in red fluorescence from the through-bond conjugation. Given the equilibrated color-shifting fluorophores, they are rationally employed in a 3WJ-based rolling circle transcription switch, with the target-aptamer acting as an activator to achieve steric allosterism. This one-pot system allows the target to compete continuously for allosteric sites, and the activated transcription switches continue to amplify MGA forward, achieving accurate Aflatoxin 1 quantification at the picomolar level in 1 h. Due to the programmability of this RNA sensor, the design method of target-competitive aptamers is standardized, making it universally applicable.

DeepLncLoc: a deep learning framework for long non-coding RNA subcellular localization prediction based on subsequence embedding.

Long non-coding RNAs (lncRNAs) are a class of RNA molecules with more than 200 nucleotides. A growing amount of evidence reveals that subcellular localization of lncRNAs can provide valuable insights into their biological functions. Existing computational methods for predicting lncRNA subcellular localization use k-mer features to encode lncRNA sequences. However, the sequence order information is lost by using only k-mer features. We proposed a deep learning framework, DeepLncLoc, to predict lncRNA subcellular localization. In DeepLncLoc, we introduced a new subsequence embedding method that keeps the order information of lncRNA sequences. The subsequence embedding method first divides a sequence into some consecutive subsequences and then extracts the patterns of each subsequence, last combines these patterns to obtain a complete representation of the lncRNA sequence. After that, a text convolutional neural network is employed to learn high-level features and perform the prediction task. Compared with traditional machine learning models, popular representation methods and existing predictors, DeepLncLoc achieved better performance, which shows that DeepLncLoc could effectively predict lncRNA subcellular localization. Our study not only presented a novel computational model for predicting lncRNA subcellular localization but also introduced a new subsequence embedding method which is expected to be applied in other sequence-based prediction tasks. The DeepLncLoc web server is freely accessible at http://bioinformatics.csu.edu.cn/DeepLncLoc/, and source code and datasets can be downloaded from https://github.com/CSUBioGroup/DeepLncLoc.

LncLocFormer: a Transformer-based deep learning model for multi-label lncRNA subcellular localization prediction by using localization-specific attention mechanism.

MOTIVATION: There is mounting evidence that the subcellular localization of lncRNAs can provide valuable insights into their biological functions. In the real world of transcriptomes, lncRNAs are usually localized in multiple subcellular localizations. Furthermore, lncRNAs have specific localization patterns for different subcellular localizations. Although several computational methods have been developed to predict the subcellular localization of lncRNAs, few of them are designed for lncRNAs that have multiple subcellular localizations, and none of them take motif specificity into consideration. RESULTS: In this study, we proposed a novel deep learning model, called LncLocFormer, which uses only lncRNA sequences to predict multi-label lncRNA subcellular localization. LncLocFormer utilizes eight Transformer blocks to model long-range dependencies within the lncRNA sequence and shares information across the lncRNA sequence. To exploit the relationship between different subcellular localizations and find distinct localization patterns for different subcellular localizations, LncLocFormer employs a localization-specific attention mechanism. The results demonstrate that LncLocFormer outperforms existing state-of-the-art predictors on the hold-out test set. Furthermore, we conducted a motif analysis and found LncLocFormer can capture known motifs. Ablation studies confirmed the contribution of the localization-specific attention mechanism in improving the prediction performance. AVAILABILITY AND IMPLEMENTATION: The LncLocFormer web server is available at http://csuligroup.com:9000/LncLocFormer. The source code can be obtained from https://github.com/CSUBioGroup/LncLocFormer.

Fractional exhaled nitric oxide, a potential biomarker for evaluating glucocorticoids treatment and prognosis in allergic bronchopulmonary aspergillosis.

BACKGROUND: Allergic bronchopulmonary aspergillosis (ABPA) is characterized by enhanced TH2 inflammatory response. Fractional exhaled nitric oxide (FeNO) measurement has been used as a valuable tool in predicting the development and management of asthma, another typical TH2 inflammation. However, the clinical significance of FeNO in ABPA remains unclear. OBJECTIVE: To investigate the association between FeNO and the prognosis of patients with ABPA to provide a basis for the use of FeNO in evaluating the efficacy of glucocorticoids in ABPA treatment. METHODS: This study comprised 2 parts; 58 patients were enrolled in the retrospective study. Clinical indexes in patients with different prognoses were compared, and receiver operating characteristic curve analysis was used to determine the threshold value. The prospective observational study involved 61 patients who were regularly followed up at 4 to 6 weeks and 6 months since the initial treatment. Patients were grouped on the basis of baseline FeNO values; correlation analysis was performed in the clinical data. RESULTS: Different prognoses were observed between patients with high and low baseline FeNO values, with a threshold value of 57 parts per billion. The percentage of Aspergillus fumigatus-specific IgE, percentage of positive A fumigatus-specific IgG, and relapse/exacerbation rate differed significantly between the high and low FeNO groups. Patients with higher FeNO needed longer treatment duration and showed shorter interval between glucocorticoid withdrawal and the next relapse/exacerbation. CONCLUSION: Our findings indicate that the level of FeNO is associated with the prognosis of ABPA. It can serve as an independent and valuable biomarker for evaluating the effectiveness of glucocorticoid treatment.

Feasibility of a clinical-radiomics combined model to predict the occurrence of stroke-associated pneumonia.

PURPOSE: To explore the predictive value of radiomics in predicting stroke-associated pneumonia (SAP) in acute ischemic stroke (AIS) patients and construct a prediction model based on clinical features and DWI-MRI radiomics features. METHODS: Univariate and multivariate logistic regression analyses were used to identify the independent clinical predictors for SAP. Pearson correlation analysis and the least absolute shrinkage and selection operator with ten-fold cross-validation were used to calculate the radiomics score for each feature and identify the predictive radiomics features for SAP. Multivariate logistic regression was used to combine the predictive radiomics features with the independent clinical predictors. The prediction performance of the SAP models was evaluated using receiver operating characteristics (ROC), calibration curves, decision curve analysis, and subgroup analyses. RESULTS: Triglycerides, the neutrophil-to-lymphocyte ratio, dysphagia, the National Institutes of Health Stroke Scale (NIHSS) score, and internal carotid artery stenosis were identified as clinically independent risk factors for SAP. The radiomics scores in patients with SAP were generally higher than in patients without SAP (P < 0. 05). There was a linear positive correlation between radiomics scores and NIHSS scores, as well as between radiomics scores and infarct volume. Infarct volume showed moderate performance in predicting the occurrence of SAP, with an AUC of 0.635. When compared with the other models, the combined prediction model achieved the best area under the ROC (AUC) in both training (AUC = 0.859, 95% CI 0.759-0.936) and validation (AUC = 0.830, 95% CI 0.758-0.896) cohorts (P < 0.05). The calibration curves and decision curve analysis further confirmed the clinical value of the nomogram. Subgroup analysis showed that this nomogram had potential generalization ability. CONCLUSION: The addition of the radiomics features to the clinical model improved the prediction of SAP in AIS patients, which verified its feasibility.

Discovery of a first-in-class protein degrader for the c-ros oncogene 1 (ROS1).

The c-ros oncogene 1 (ROS1), an oncogenic driver, is known to induce non-small cell lung cancer (NSCLC) when overactivated, particularly through the formation of fusion proteins. Traditional targeted therapies focus on inhibiting ROS1 activity with ROS 1 inhibitors to manage cancer progression. However, a new strategy involving the design of protein degraders offers a more potent approach by completely degrading ROS1 fusion oncoproteins, thereby effectively blocking their kinase activity and enhancing anti-tumour potential. Utilizing PROteolysis-TArgeting Chimera (PROTAC) technology and informed by molecular docking and rational design, we report the first ROS1-specific PROTAC, SIAIS039. This degrader effectively targets multiple ROS1 fusion oncoproteins (CD74-ROS1, SDC4-ROS1 and SLC34A2-ROS1) in engineered Ba/F3 cells and HCC78 cells, demonstrating anti-tumour effects against ROS1 fusion-driven cancer cells. It suppresses cell proliferation, induces cell cycle arrest, and apoptosis, and inhibits clonogenicity. The anti-tumour efficacy of SIAIS039 surpasses two approved drugs, crizotinib and entrectinib, and matches that of the top inhibitors, including lorlatinib and taletrectinib. Mechanistic studies confirm that the degradation induced by 039 requires the participation of ROS1 ligands and E3 ubiquitin ligases, and involves the proteasome and ubiquitination. In addition, 039 exhibited excellent oral bioavailability in a mouse xenograft model, highlighting its potential for clinical application. In conclusion, our study presents a promising and novel therapeutic strategy for ROS1 fusion-positive NSCLC by targeting ROS1 fusion oncoproteins for degradation, laying the foundation for the development of further PROTAC and offering hope for patients with ROS1 fusion-positive NSCLC.

Functional and structural alterations in different durations of untreated illness in the frontal and parietal lobe in major depressive disorder.

Major depressive disorder (MDD) is one of the most disabling illnesses that profoundly restricts psychosocial functions and impairs quality of life. However, the treatment rate of MDD is surprisingly low because the availability and acceptability of appropriate treatments are limited. Therefore, identifying whether and how treatment delay affects the brain and the initial time point of the alterations is imperative, but these changes have not been thoroughly explored. We investigated the functional and structural alterations of MDD for different durations of untreated illness (DUI) using regional homogeneity (ReHo) and voxel-based morphometry (VBM) with a sample of 125 treatment-naïve MDD patients and 100 healthy controls (HCs). The MDD patients were subgrouped based on the DUI, namely, DUI ≤ 1 M, 1 < DUI ≤ 6 M, 6 < DUI ≤ 12 M, and 12 < DUI ≤ 48 M. Subgroup comparison (MDD with different DUIs) was applied to compare ReHo and grey matter volume (GMV) extracted from clusters of regions with significant differences (the pooled MDD patients relative to HCs). Correlations and mediation effects were analysed to estimate the relationships between the functional and structural neuroimaging changes and clinical characteristics. MDD patients exhibited decreased ReHo in the left postcentral gyrus and precentral gyrus and reduced GMV in the left middle frontal gyrus and superior frontal gyrus relative to HCs. The initial functional abnormalities were detected after being untreated for 1 month, whereas this duration was 3 months for GMV reduction. Nevertheless, a transient increase in ReHo was observed after being untreated for 3 months. No significant differences were discovered between HCs and MDD patients with a DUI less than 1 month or among MDD patients with different DUIs in either ReHo or GMV. Longer DUI was related to reduced ReHo with GMV as mediator in MDD patients. We identified disassociated functional and anatomical alterations in treatment-naïve MDD patients at different time points in distinct brain regions at the early stage of the disease. Additionally, we also discovered that GMV mediated the relationship between a longer DUI and diminished ReHo in MDD patients, disclosing the latent deleterious and neuro-progressive implications of DUI on both the structure and function of the brain and indicating the necessity of early treatment of MDD.

Targeting N7-methylguanosine tRNA modification blocks hepatocellular carcinoma metastasis after insufficient radiofrequency ablation.

Radiofrequency heat ablation is an ideal radical treatment for hepatocellular carcinoma (HCC). However, insufficient radiofrequency ablation (IRFA) could lead to high recurrence of HCC. N7-methylguanosine (m7G) on tRNAs, an evolutionally conservative modification in mammals and yeast, modulates heat stress responses and tumor progression, while its function in HCC recurrence after IRFA remains unknown. Here, we found that IRFA significantly upregulates the level of m7G tRNA modification and its methyltransferase complex components METTL1/WDR4 in multiple systems including HCC patient-derived xenograft (PDX) mouse, patients' HCC tissues, sublethal-heat-treated models of HCC cell lines, and organoids. Functionally, gain-/loss-of-function assays showed that METTL1-mediated m7G tRNA modification promotes HCC metastasis under sublethal heat exposure both in vitro and in vivo. Mechanistically, we found that METTL1 and m7G tRNA modification enhance the translation of SLUG/SNAIL in a codon frequency-dependent manner under sublethal heat stress. Overexpression of SLUG/SNAIL rescued the malignant potency of METTL1 knockdown HCC cells after sublethal heat exposure. Our study uncovers the key functions of m7G tRNA modification in heat stress responses and HCC recurrence after IRFA, providing molecular basis for targeting METTL1-m7G-SLUG/SNAIL axis to prevent HCC metastasis after radiofrequency heat ablation treatment.