Blood culture quality and turnaround time of clinical microbiology laboratories in Chinese Teaching Hospitals: A multicenter study.

PURPOSE: Blood culture (BC) remains the gold standard for the diagnosis of bloodstream infections. Improving the quality of clinical BC samples, optimizing BC performance, and accelerating antimicrobial susceptibility test (AST) results are essential for the early detection of bloodstream infections and specific treatments. METHODS: We conducted a retrospective multicenter study using 450,845 BC specimens from clinical laboratories obtained from 19 teaching hospitals between 1 January 2021 and 31 December 2021. We evaluated key performance indicators (KPIs), turnaround times (TATs), and frequency distributions of processing in BC specimens. We also evaluated the AST results of clinically significant isolates for four different laboratory workflow styles. RESULTS: Across the 10 common bacterial isolates (n = 16,865) and yeast isolates (n = 1011), the overall median (interquartile range) TATs of AST results were 2.67 (2.05-3.31) and 3.73 (2.98-4.64) days, respectively. The specimen collections mainly occurred between 06:00 and 24:00, and specimen reception and loadings mainly between 08:00 and 24:00. Based on the laboratory workflows of the BCs, 16 of the 19 hospitals were divided into four groups. Time to results (TTRs) from specimen collection to the AST reports were 2.35 (1.95-3.06), 2.61 (1.98-3.32), 2.99 (2.60-3.87), and 3.25 (2.80-3.98) days for groups I, II, III, and IV, respectively. CONCLUSION: This study shows the related BC KPIs and workflows in different Chinese hospitals, suggesting that laboratory workflow optimization can play important roles in shortening time to AST reports and initiation of appropriate timely treatment.

Palmarumycin P3 Reverses Mrr1-Mediated Azole Resistance by Blocking the Efflux Pump Mdr1.

Palmarumycin P3 (PP3) reduces fluconazole-induced MDR1 transcription to reverse azole resistance in clinical Candida strains. Here, we demonstrated that PP3 restores the susceptibility to several antifungal drugs for Candida albicans strains with gain-of-function mutations in the transcription factor Mrr1. In addition, PP3 inhibits the efflux of Mdr1 substrates by C. albicans strains harboring hyperactive MRR1 alleles. Molecular docking revealed that PP3 is a potential Mdr1 blocker that binds to the substrate binding pocket of Mdr1.

Flavaspidic acid BB combined with mupirocin improves its anti-bacterial and anti-biofilm activities against Staphylococcus epidermidis.

BACKGROUND: The increase in drug-resistant opportunistic pathogenic bacteria, especially of antibiotic-resistant Staphylococcus epidermidis (S. epidermidis), has led to difficulties in the treatment of skin and soft tissue infections (SSTI). The major reason for bacterial resistance is the formation of bacterial biofilm. Here, we report a promising combination therapy of flavaspidic acid BB (BB) and mupirocin, which can effectively eradicate the biofilm of S. epidermidis and eliminate its drug resistance. RESULT: The susceptibility test showed that the combination of BB and mupirocin has good antibacterial and antibiofilm activities, and the fractional inhibitory concentration index (FICI) of BB combined with mupirocin was 0.51 ± 0.00 ~ 0.75 ± 0.05, showing synergistic effect. Moreover, the time-kill curve assay results indicated that the combination of drugs can effectively inhibit the planktonic S. epidermidis. After drugs treatment, the drug-combination showed significantly inhibitory effects on the metabolic activity and total biomass in each stage of biofilm formation. The synergistic effect is likely related to the adhesion between bacteria, which is confirmed by field emission scanning electron microscope. And the expression level of aap, sarA and agrA genes were detected by real-time quantitative PCR (qRT-PCR). CONCLUSION: Our study provides the experimental data for the use of BB for the clinical treatment of skin infections and further demonstrate the potential of BB as a novel biofilm inhibitor.

ZHX2 inhibits thyroid cancer metastasis through transcriptional inhibition of S100A14.

BACKGROUND: Thyroid cancer is the most common malignant endocrine tumour, and metastasis has become the main reason for treatment failure. However, the underlying molecular mechanism of thyroid cancer metastasis remains poorly understood. We investigated the role of the tumour suppressor zinc fingers and homeoboxes 2 (ZHX2) in the metastasis of thyroid cancer. METHODS: To study the role of ZHX2 in thyroid cancer metastasis, we evaluated the EMT process using cell migration, wound healing and lung metastatic tumour formation in vitro and in vivo models. RESULTS: ZHX2 expression was significantly decreased in thyroid cancer tissues, which correlated with poor prognosis of thyroid cancer patients. ZHX2 knockdown significantly promoted the migration of thyroid cancer cells. Mechanistically, ZHX2 associated with the S100 calcium binding protein A14 (S100A14) promoter to decrease the transcription of S100A14. Moreover, S100A14 was highly expressed in human thyroid cancer samples, and its expression negatively correlated with ZHX2 expression. CONCLUSIONS: Inhibition of S100A14 attenuated the ZHX2 knockdown-induced enhanced metastasis of thyroid cancer cells both in vitro and in vivo. The evidence presented here suggests that ZHX2 inhibits the progression of thyroid cancer by blocking S100A14-mediated metastasis.

Rimonabant potentiates the antifungal activity of amphotericin B by increasing cellular oxidative stress and cell membrane permeability.

Amphotericin B (AmB) is a very effective antifungal agent, and resistance in clinical isolates is rare. However, clinical treatment with AmB is often associated with severe side effects. Reducing the administration dose of AmB by combining it with other agents is a promising strategy to minimize this toxicity. In this study, we screened a small compound library and observed that the anti-obesity drug rimonabant exhibited synergistic antifungal action with AmB against Candida species and Cryptococcus neoformans. Moreover, the combination of AmB and rimonabant exhibited synergistic or additive effects against Candida albicans biofilm formation and cell viability in preformed biofilms. The effects of this combination were further confirmed in vivo using a murine systemic infection model. Exploration of the mechanism of synergy revealed that rimonabant enhances the fungicidal activity of AmB by increasing cellular oxidative stress and cell membrane permeability. These findings provide a foundation for the possible development of AmB-rimonabant polytherapies for fungal infections.

First Chinese case report of Helcococcus kunzii in a patient with diabetic foot.

BACKGROUND: Infection of Helcococcus kunzii(H. kunzii) from diabetic foot wound is rarely reported. This case report describes the infection of H.kunzii and highlights the therapeutic effect on H.kunzii from a diabetic foot wound. CASE PRESENTATION: In this study, one H. kunzii strain was isolated from a patient with diabetic foot, which was confirmed by 16S rRNA gene analysis and MALDI-TOF-MS. It is the first Chinese case of H. kunzii in a patient with diabetic foot. As a result of the lack of antibiotic sensitivity data and multiple comorbidities, antibiotics were used cautiously, and those administered during the first 3 months were ineffective. Then, vacuum sealing drainage (VSD) was applied during hospitalization; no antibiotics were used and the wound healed well. CONCLUSIONS: VSD alone may be more effective in treating diabetic feet infected with H. kunzii, which may provide reference for clinical treatment of H. kunzii infection from diabetic foot.

Predicting the response to neoadjuvant chemotherapy for breast cancer: wavelet transforming radiomics in MRI.

BACKGROUND: The purpose of this study was to investigate the value of wavelet-transformed radiomic MRI in predicting the pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) for patients with locally advanced breast cancer (LABC). METHODS: Fifty-five female patients with LABC who underwent contrast-enhanced MRI (CE-MRI) examination prior to NAC were collected for the retrospective study. According to the pathological assessment after NAC, patient responses to NAC were categorized into pCR and non-pCR. Three groups of radiomic textures were calculated in the segmented lesions, including (1) volumetric textures, (2) peripheral textures, and (3) wavelet-transformed textures. Six models for the prediction of pCR were Model I: group (1), Model II: group (1) + (2), Model III: group (3), Model IV: group (1) + (3), Model V: group (2) + (3), and Model VI: group (1) + (2) + (3). The performance of predicting models was compared using the area under the receiver operating characteristic (ROC) curves (AUC). RESULTS: The AUCs of the six models for the prediction of pCR were 0.816 ± 0.033 (Model I), 0.823 ± 0.020 (Model II), 0.888 ± 0.025 (Model III), 0.876 ± 0.015 (Model IV), 0.885 ± 0.030 (Model V), and 0.874 ± 0.019 (Model VI). The performance of four models with wavelet-transformed textures (Models III, IV, V, and VI) was significantly better than those without wavelet-transformed textures (Model I and II). In addition, the inclusion of volumetric textures or peripheral textures or both did not result in any improvements in performance. CONCLUSIONS: Wavelet-transformed textures outperformed volumetric and/or peripheral textures in the radiomic MRI prediction of pCR to NAC for patients with LABC, which can potentially serve as a surrogate biomarker for the prediction of the response of LABC to NAC.

Surgical techniques and effectiveness of laparoscopic resection of abdominal wall desmoid-type fibromatosis and defect reconstruction: a single-center retrospective analysis.

PURPOSE: Although the treatment of abdominal wall desmoid-type fibromatosis (DF) has evolved over the past decades, surgical treatment remains an important approach. Previously, surgeries for abdominal DF were mostly performed by laparotomy, which involves massive dissection and significant trauma. Here, we report our single-center experience of the laparoscopic management of abdominal wall DF in young female patients. METHODS: The clinical data of nine patients diagnosed with abdominal wall DF during January 2020-April 2022 at the Qilu Hospital of Shandong University were retrospectively analyzed. All patients underwent laparoscopic resection of abdominal wall DF and immediate abdominal wall reconstruction (AWR) with mesh augmentation via the intraperitoneal onlay mesh (IPOM) technique. RESULTS: Laparoscopic DF resection and AWR were successfully performed in all patients. The mean operation time was 175.56 ± 46.20 min. The width of abdominal wall defect was 8.61 ± 3.30 cm. Full- and partial-thickness myofascial closure and reapproximation were performed in five, two, and two patients, respectively. The average mesh size was 253.33 ± 71.01 cm2. The total and postoperative lengths of hospital stay were 11.00 ± 3.46 and 4.89 ± 2.03 days, respectively. Tumor recurred in one patient after 20 months of the resection. Nonetheless, death, herniation, or bulging were not observed in any patient during a mean follow-up of 16.11 ± 8.43 months. CONCLUSION: Laparoscopic resection of abdominal wall DF and immediate AWR with IPOM mesh reinforcement is safe and reliable for young female patients. Management of such patients should be decided according to the biological behavior, size, and location of tumors.

Efficacy and safety of tyrosine kinase inhibitors for advanced metastatic thyroid cancer: A systematic review and network meta-analysis of randomized controlled trials.

BACKGROUND: Tyrosine kinase inhibitors (TKIs) have been approved for treating patients with clinically advanced metastatic thyroid cancer. However among the many TKIs, it remains unknown which regimen is the best choice for these patients. METHODS: We conducted a systematic review and network meta-analysis to compare the survival benefits and efficacy of the available first-line regimens. We conducted an active search for phase II, III, or IV randomized controlled trials (RCTs) in the PubMed, Embase, and Cochrane databases to compare the effects of at least 2 drugs in the systemic treatment of advanced or metastatic thyroid cancer up to May 2023. The network meta-analysis model was adjusted using Bayesian Network model. Twelve trials with 2535 patients were included in our meta-analysis. The overall survival (OS), progression-free survival (PFS), and serious adverse events (SAEs) were taken as reference indicators. We also performed subgroup analyses of OS and PFS in medullary thyroid cancer (MTC) and radioiodine-refractory differentiated thyroid cancer (RR-DTC) to explore the variations of TKIs in different groups. RESULTS: As a result, apatinib had the best effect on overall survival (OS) (hazards ratio [HR] = 0.42, 95% confidence interval [CI] = 0.18-0.98), lenvatinib 18 mg/d has the best effect on progression-free survival (PFS) (HR = 0.13, 95% CI = 0.064-0.27), and cabozantinib 60 mg/d has the best safety profile. CONCLUSIONS: Our network meta-analysis showed that we believe that cabozantinib has the potential to become a widely used drug in clinical practice.

New Model and Public Online Prediction Platform for Risk Stratification of Vocal Cord Leukoplakia.

OBJECTIVE: To extract texture features from vocal cord leukoplakia (VCL) images and establish a VCL risk stratification prediction model using machine learning (ML) techniques. METHODS: A total of 462 patients with pathologically confirmed VCL were retrospectively collected and divided into low-risk and high-risk groups. We use a 5-fold cross validation method to ensure the generalization ability of the model built using the included dataset and avoid overfitting. Totally 504 texture features were extracted from each laryngoscope image. After feature selection, 10 ML classifiers were utilized to construct the model. The SHapley Additive exPlanations (SHAP) was employed for feature analysis. To evaluate the model, accuracy, sensitivity, specificity, and the area under the receiver operating characteristic (ROC) curve (AUC) were utilized. In addition, the model was transformed into an online application for public use and further tested in an independent dataset with 52 cases of VCL. RESULTS: A total of 12 features were finally selected, random forest (RF) achieved the best model performance, the mean accuracy, sensitivity, specificity, and AUC of the 5-fold cross validation were 92.2 ± 4.1%, 95.6 ± 4.0%, 85.8 ± 5.8%, and 90.7 ± 4.9%, respectively. The result is much higher than the clinicians (AUC between 63.1% and 75.2%). The SHAP algorithm ranks the importance of 12 texture features to the model. The test results of the additional independent datasets were 92.3%, 95.7%, 90.0%, and 93.3%, respectively. CONCLUSION: The proposed VCL risk stratification prediction model, which has been developed into a public online prediction platform, may be applied in practical clinical work. LEVEL OF EVIDENCE: 3 Laryngoscope, 2024.

SHMT2 promotes papillary thyroid cancer metastasis through epigenetic activation of AKT signaling.

Cancer cells alter their metabolism and epigenetics to support cancer progression. However, very few modulators connecting metabolism and epigenetics have been uncovered. Here, we reveal that serine hydroxymethyltransferase-2 (SHMT2) generates S-adenosylmethionine (SAM) to epigenetically repress phosphatase and tensin homolog (PTEN), leading to papillary thyroid cancer (PTC) metastasis depending on activation of AKT signaling. SHMT2 is elevated in PTC, and is associated with poor prognosis. Overexpressed SHMT2 promotes PTC metastasis both in vitro and in vivo. Proteomic enrichment analysis shows that AKT signaling is activated, and is positively associated with SHMT2 in PTC specimens. Blocking AKT activation eliminates the effects of SHMT2 on promoting PTC metastasis. Furthermore, SHMT2 expression is negatively associated with PTEN, a negative AKT regulator, in PTC specimens. Mechanistically, SHMT2 catalyzes serine metabolism and produces activated one-carbon units that can generate SAM for the methylation of CpG islands in PTEN promoter for PTEN suppression and following AKT activation. Importantly, interference with PTEN expression affects SHMT2 function by promoting AKT signaling activation and PTC metastasis. Collectively, our research demonstrates that SHMT2 connects metabolic reprogramming and epigenetics, contributing to the poor progression of PTC.

Construction and validation of a PANoptosis-related lncRNA signature for predicting prognosis and targeted drug response in thyroid cancer.

Thyroid cancer (TC) is the most prevalent malignancy of the endocrine system. PANoptosis, a newly discovered cell death pathway, is of interest in tumor research. However, the relationship between PANoptosis-related lncRNAs (PRlncRNAs) and TC remains unclear. The study aimed to develop a prognostic model based on PRlncRNAs in TC. Gene expression data of PANoptosis-associated genes and clinical information on TC from The Cancer Genome Atlas (TCGA) database were analyzed by Pearson correlation analysis, univariate/multivariate Cox analysis, and Lasso Cox regression analysis. A PRlncRNA signature was constructed and used to develop a nomogram to predict overall survival (OS). We further explored the correlation between the risk score and tumor immune microenvironment, immune checkpoints, and drug sensitivity. Moreover, we verified the expression and biological function of lncRNAs in TC cell lines. Finally, seven PRlncRNAs were used to construct a prognostic model for predicting the OS of TC patients. We found that the risk score was associated with the tumor microenvironment (TME) and the expression of critical immune checkpoints. In addition, we screened for drugs that high- or low-risk TC groups might be sensitive to. Quantitative real-time polymerase chain reaction (qRT-PCR) results showed differential expression of four PRlncRNAs (GAPLINC, IDI2-AS1, LINC02154, and RBPMS-AS1) between tumor and normal tissues. Besides, a GEO database (GSE33630) was used to verify the expression differences of PRLncRNAs in THCA tissues and normal tissues. Finally, RBPMS-AS1 was found to inhibit the proliferation and migration of TC cells. In conclusion, we developed a PANoptosis-related lncRNA prognostic risk model that offers a comprehensive understanding of TME status in patients with TC and establishes a foundation for the choice of sensitive medications and immunotherapy.

Identification and validation of key biomarkers associated with macrophages in nonalcoholic fatty liver disease based on hdWGCNA and machine learning.

BACKGROUND: NAFLD has attracted increasing attention because of its high prevalence and risk of progression to cirrhosis or even hepatocellular carcinoma. Therefore, research into the root causes and molecular indicators of NAFLD is crucial. METHODS: We analyzed scRNA-seq data and RNA-seq data from normal and NAFLD liver samples. We utilized hdWGCNA to find module-related genes associated with the phenotype. Multiple machine learning algorithms were used to validate the model diagnostics and further screen for genes that are characteristic of NAFLD. The NAFLD mouse model was constructed using the MCD diet to validate the diagnostic effect of the genes. RESULTS: We identified a specific macrophage population called NASH-macrophages by single-cell sequencing analysis. Cell communication analysis and Pseudo-time trajectory analysis revealed the specific role and temporal distribution of NASH-macrophages in NAFLD. The hdWGCNA screening yielded 30 genes associated with NASH-macrophages, and machine learning algorithms screened and obtained two genes characterizing NAFLD. The immune infiltration indicated that these genes were highly associated with macrophages. Notably, we verified by RT-qPCR, IHC, and WB that MAFB and CX3CR1 are highly expressed in the MCD mouse model and may play important roles. CONCLUSIONS: Our study revealed a macrophage population that is closely associated with NAFLD. Using hdWGCNA analysis and multiple machine learning algorithms, we identified two NAFLD signature genes that are highly correlated with macrophages. Our findings may provide potential feature markers and therapeutic targets for NAFLD.

Perylenequinone derivatives from the endolichenic fungus Phialocephala fortinii.

Five undescribed perylenequinone derivatives (PQDs) phialocephalarins H - L (1 - 5), together with two known PQDs phialocephalarins A - B (6, 7) and one known spirobisnaphthalene palmarumycin P3 (8) were isolated from the endolichenic fungus Phialocephala fortinii. Their structures were elucidated on the basis of NMR and HRESIMS data as well as electronic circular dichroism (ECD) calculations. Compounds 1, 2, 4, and 6 - 8 were evaluated for cytotoxic activities against NCI-H460, NCI-H446, PC3, and EC109 cell lines. The results showed that compounds 1, 2, 6, and 8 showed cytotoxic activities against EC109 cells with IC50 values ranging from 24.5 to 33.3 µM.

Influence of Data Distribution on Federated Learning Performance in Tumor Segmentation.

Purpose: To investigate the correlation between differences in data distributions and federated deep learning (Fed-DL) algorithm performance in tumor segmentation on CT and MR images. Materials and Methods: Two Fed-DL datasets were retrospectively collected (from November 2020 to December 2021): one dataset of liver tumor CT images (Federated Imaging in Liver Tumor Segmentation [or, FILTS]; three sites, 692 scans) and one publicly available dataset of brain tumor MR images (Federated Tumor Segmentation [or, FeTS]; 23 sites, 1251 scans). Scans from both datasets were grouped according to site, tumor type, tumor size, dataset size, and tumor intensity. To quantify differences in data distributions, the following four distance metrics were calculated: earth mover's distance (EMD), Bhattacharyya distance (BD), χ2 distance (CSD), and Kolmogorov-Smirnov distance (KSD). Both federated and centralized nnU-Net models were trained by using the same grouped datasets. Fed-DL model performance was evaluated by using the ratio of Dice coefficients, θ, between federated and centralized models trained and tested on the same 80:20 split datasets. Results: The Dice coefficient ratio (θ) between federated and centralized models was strongly negatively correlated with the distances between data distributions, with correlation coefficients of -0.920 for EMD, -0.893 for BD, and -0.899 for CSD. However, KSD was weakly correlated with θ, with a correlation coefficient of -0.479. Conclusion: Performance of Fed-DL models in tumor segmentation on CT and MRI datasets was strongly negatively correlated with the distances between data distributions.Keywords: CT, Abdomen/GI, Liver, Comparative Studies, MR Imaging, Brain/Brain Stem, Convolutional Neural Network (CNN), Federated Deep Learning, Tumor Segmentation, Data Distribution Supplemental material is available for this article. © RSNA, 2023See also the commentary by Kwak and Bai in this issue.

Injectable Zwitterionic Physical Hydrogel with Enhanced Chemodynamic Therapy and Tumor Microenvironment Remodeling Properties for Synergistic Anticancer Therapy.

Surgical resection is the first-line therapy for breast cancer. However, residual tumor cells and the highly immunosuppressive tumor microenvironment (TME) continue to have a serious impact on tumor recurrence and metastasis postresection. Implantation of an in situ hydrogel system postresection has shown to be an effective treatment with great clinical potential. Herein, an injectable zwitterionic hydrogel system was developed for local drug delivery with enhanced immune activation and prevention of tumor recurrence. Driven by electrostatic interactions, poly(sulfobetaine methacrylate) (PSBMA) self-assembles into a hydrogel in saline, achieving low protein adsorption and tunable biodegradability. The chemotherapy drug doxorubicin (DOX) was loaded into copper peroxide nanoparticles (CuO2/DOX), which were coated with macrophage membranes to form tumor-targeting nanoparticles (M/CuO2/DOX). Next, M/CuO2/DOX and the stimulator of interferon genes (STING) agonist 2',3'-cGAMP were coloaded into PSBMA hydrogel (Gel@M/CuO2/DOX/STING). The hydrophilic STING agonist was first released by diffusion from hydrogel to activate the STING pathway and upregulate interferon (IFN) signaling related genes, remodeling the immunosuppressive TME. Then, M/CuO2/DOX targeted the residual tumor cells, combining with DOX-induced DNA damage, immunogenic tumor cell death, and copper death. Hence, this work combines chemodynamic therapy with STING pathway activation in TME, encouraging residual tumor cell death, promoting the maturation of dendritic cells, enhancing tumor-specific CD8+ T cell infiltration, and preventing postoperative recurrence and metastasis.

LINC01431 Promotes Histone H4R3 Methylation to Impede HBV Covalently Closed Circular DNA Transcription by Stabilizing PRMT1.

Covalently closed circular DNA (cccDNA) is the transcriptional template of hepatitis B virus (HBV), which interacts with both host and viral proteins to form minichromosome in the nucleus and is resistant to antiviral agents. Identification of host factors involved in cccDNA transcriptional regulation is expected to prove a new venue for HBV therapy. Recent evidence suggests the involvement of long noncoding RNAs (lncRNAs) in mediating the interaction of host factors with various viruses, however, lncRNAs that HBV targets and represses cccDNA transcription have not been fully elucidated. Here, the authors identified LINC01431 as a novel host restriction factor for HBV transcription. Mechanically, LINC01431 competitively bound with type I protein arginine methyltransferase (PRMT1) to block the HBx-mediated PRMT1 ubiquitination and degradation. Consequently, LINC01431 increased the occupancy of PRMT1 on cccDNA, leading to enhanced H4R3me2a modification and reduced acetylation of cccDNA-bound histones, thereby repressing cccDNA transcription. In turn, to facilitate viral replication, HBV transcriptionally repressed LINC01431 expression by HBx-mediated repression of transcription factor Zinc fingers and homeoboxes 2 (ZHX2). Collectively, the study demonstrates LINC01431 as a novel epigenetic regulator of cccDNA minichromosome and highlights a feedback loop of HBx-LINC01431-PRMT1 in HBV replication, which provides potential therapeutic targets for HBV treatment.

cccDNA Surrogate MC-HBV-Based Screen Identifies Cohesin Complex as a Novel HBV Restriction Factor.

BACKGROUND & AIMS: Covalently closed circular DNA (cccDNA) of hepatitis B virus (HBV), existing as a stable minichromosome in the hepatocyte, is responsible for persistent HBV infection. Maintenance and sustained replication of cccDNA require its interaction with both viral and host proteins. However, the cccDNA-interacting host factors that limit HBV replication remain elusive. METHODS: Minicircle HBV (MC-HBV), a recombinant cccDNA, was constructed based on chimeric intron and minicircle DNA technology. By mass spectrometry based on pull-down with biotinylated MC-HBV, the cccDNA-hepatocyte interaction profile was mapped. HBV replication was assessed in different cell models that support cccDNA formation. RESULTS: MC-HBV supports persistent HBV replication and mimics the cccDNA minichromosome. The MC-HBV-based screen identified cohesin complex as a cccDNA binding host factor, leading to reduced HBV replication. Mechanistically, with the help of CCCTC-binding factor (CTCF), which has specific binding sites on cccDNA, cohesin loads on cccDNA and reshapes cccDNA confirmation to prevent RNA polymerase II enrichment. Interestingly, HBV X protein transcriptionally reduces structural maintenance of chromosomes complex expression to partially relieve the inhibitory role of the cohesin complex on HBV replication. CONCLUSIONS: Our data not only provide a feasible approach to explore cccDNA-binding factors, but also identify cohesin/CTCF complex as a critical host restriction factor for cccDNA-driven HBV replication. These findings provide a novel insight into cccDNA-host interaction and targeted therapeutic intervention for HBV infection.

Hinokitiol chelates intracellular iron to retard fungal growth by disturbing mitochondrial respiration.

Introduction: The increasing morbidity of fungal infections and the prevalence of drug resistance highlighted the discovery of novel antifungal agents and investigation of their modes of action. Iron chelators have been used to treat superficial fungal infections or potentiate the efficacy of certain antifungal drugs. Hinokitiol exhibits potent antifungal activity and iron-chelating ability. However, their relationships have not been established. Objectives: This study aims to explore the selectivity of hinokitiol against fungal cells and mammalian cells and determine the role of iron-chelating for the antifungal activity of hinokitiol. Methods: Iron probe FeRhonox-1 was used to determine intracellular Fe2+ content. 5-Cyano-2,3-ditolyl tetrazolium chloride probe and Cell Counting Kit-8 were used to detect the mitochondrial respiratory activities. Quantitative real-time PCR and rescue experiments were performed to determine the effect of iron on the antifungal activity of hinokitiol. The effects of hinokitiol on fungal mitochondria were further evaluated using reactive oxygen species probes and several commercial Assay Kits. The ability of hinokitiol to induce resistance in Candida species was carried out using a serial passage method. The in vivo therapeutic effect of hinokitiol was evaluated using Galleria mellonella as an infectious model. Results: Hinokitiol was effective against a panel of Candida strains with multiple azole-resistant mechanisms and persistently inhibited Candida albicans growth. Mechanism investigations revealed that hinokitiol chelated fungal intracellular iron and inhibited the respiration of fungal cells but had minor effects on mammalian cells. Hinokitiol further inhibited the activities of mitochondrial respiratory chain complexes I and II and reduced mitochondrial membrane potential, thereby decreasing intracellular ATP synthesis and increasing detrimental intracellular reductive stress. Moreover, hinokitiol exhibited low potential for inducing resistance in several Candida species and greatly improved the survival of Candida-infected Galleria mellonella. Conclusions: These findings suggested the potential application of hinokitiol as an iron chelator to treat fungal infections.

Multi-Omics Analysis of Fatty Acid Metabolism in Thyroid Carcinoma.

OBJECTIVE: Papillary thyroid carcinoma (PTC) accounts for the majority of thyroid cancer and affects a large number of individuals. The pathogenesis of PTC has not been completely elucidated thus far. Metabolic reprogramming is a common feature in tumours. Our previous research revealed the reprogramming of lipid metabolism in PTC. Further studies on lipid metabolism reprogramming may help elucidate the pathogenesis of PTC. METHODS: Clinical samples of PTC and para-tumour tissue were analysed using lipidomic, proteomic, and metabolomic approaches. A multi-omics integrative strategy was adopted to identify the important pathways in PTC. The findings were further confirmed using western blotting, tissue microarray, bioinformatics, and cell migration assays. RESULTS: Multi-omics data and the results of integrated analysis revealed that the three steps of fatty acid metabolism (hydrolysis, transportation, and oxidation) were significantly enhanced in PTC. Especially, the expression levels of LPL, FATP2, and CPT1A, three key enzymes in the respective steps, were elevated in PTC. Moreover, LPL, FATP2 and CPT1A expression was associated with the TNM stage, lymph node metastasis of PTC. Moreover, high levels of FATP2 and CPT1A contributed to poor prognosis of PTC. In addition, ectopic overexpression of LPL, FATP2 and CPT1A can each promote the migration of thyroid cancer cells. CONCLUSIONS: Our data suggested that enhanced fatty acid metabolism supplied additional energy and substrates for PTC progression. This may help elucidating the underlying mechanism of PTC pathogenesis and identifying the potential therapeutic targets for PTC.