Methylation-Associated Nucleosomal Patterns of Cell-Free DNA in Cancer Patients and Pregnant Women.

BACKGROUND: Cell-free DNA (cfDNA) analysis offers an attractive noninvasive means of detecting and monitoring diseases. cfDNA cleavage patterns within a short range (e.g., 11 nucleotides) have been reported to correlate with cytosine-phosphate-guanine (CpG) methylation, allowing fragmentomics-based methylation analysis (FRAGMA). Here, we adopted FRAGMA to the extended region harboring multiple nucleosomes, termed FRAGMAXR. METHODS: We profiled cfDNA nucleosomal patterns over the genomic regions from -800 to 800 bp surrounding differentially methylated CpG sites, harboring approximately 8 nucleosomes, referred to as CpG-associated cfDNA nucleosomal patterns. Such nucleosomal patterns were analyzed by FRAGMAXR in cancer patients and pregnant women. RESULTS: We identified distinct cfDNA nucleosomal patterns around differentially methylated CpG sites. Compared with subjects without cancer, patients with hepatocellular carcinoma (HCC) showed reduced amplitude of nucleosomal patterns, with a gradual decrease over tumor stages. Nucleosomal patterns associated with differentially methylated CpG sites could be used to train a machine learning model, resulting in the detection of HCC patients with an area under the receiver operating characteristic curve of 0.93. We further demonstrated the feasibility of multicancer detection using a dataset comprising lung, breast, and ovarian cancers. The tissue-of-origin analysis of plasma cfDNA from pregnant women and cancer patients revealed that the placental DNA and tumoral DNA contributions deduced by FRAGMAXR correlated well with values measured using genetic variants (Pearson r: 0.85 and 0.94, respectively). CONCLUSIONS: CpG-associated cfDNA nucleosomal patterns of cfDNA molecules are influenced by DNA methylation and might be useful for biomarker developments for cancer liquid biopsy and noninvasive prenatal testing.

Predicting stone composition via machine-learning models trained on intra-operative endoscopic digital images.

OBJECTIVES: The aim of this study was to use deep learning (DL) of intraoperative images of urinary stones to predict the composition of urinary stones. In this way, the laser frequency and intensity can be adjusted in real time to reduce operation time and surgical trauma. MATERIALS AND METHODS: A total of 490 patients who underwent holmium laser surgery during the two-year period from March 2021 to March 2023 and had stone analysis results were collected by the stone laboratory. A total of 1658 intraoperative stone images were obtained. The eight stone categories with the highest number of stones were selected by sorting. Single component stones include calcium oxalate monohydrate (W1), calcium oxalate dihydrate (W2), magnesium ammonium phosphate hexahydrate, apatite carbonate (CH) and anhydrous uric acid (U). Mixed stones include W2 + U, W1 + W2 and W1 + CH. All stones have intraoperative videos. More than 20 intraoperative high-resolution images of the stones, including the surface and core of the stones, were available for each patient via FFmpeg command screenshots. The deep convolutional neural network (CNN) ResNet-101 (ResNet, Microsoft) was applied to each image as a multiclass classification model. RESULTS: The composition prediction rates for each component were as follows: calcium oxalate monohydrate 99% (n = 142), calcium oxalate dihydrate 100% (n = 29), apatite carbonate 100% (n = 131), anhydrous uric acid 98% (n = 57), W1 + W2 100% (n = 82), W1 + CH 100% ( n = 20) and W2 + U 100% (n = 24). The overall weighted recall of the cellular neural network component analysis for the entire cohort was 99%. CONCLUSION: This preliminary study suggests that DL is a promising method for identifying urinary stone components from intraoperative endoscopic images. Compared to intraoperative identification of stone components by the human eye, DL can discriminate single and mixed stone components more accurately and quickly. At the same time, based on the training of stone images in vitro, it is closer to the clinical application of stone images in vivo. This technology can be used to identify the composition of stones in real time and to adjust the frequency and energy intensity of the holmium laser in time. The prediction of stone composition can significantly shorten the operation time, improve the efficiency of stone surgery and prevent the risk of postoperative infection.

U-Net-Based Assistive Identification of Bladder Cancer: A Promising Approach for Improved Diagnosis.

INTRODUCTION: Bladder cancer (BC) is a major health concern that poses a significant threat to the population, with an increasing incidence rate and a high risk of recurrence and progression. The primary clinical method for diagnosing BC is cystoscopy, but due to the limitations of traditional white light cystoscopy and inadequate clinical experience among junior physicians, its detection rate for bladder tumor, especially small and flat lesions, is relatively low. However, recent years have seen remarkable advancements in the application of artificial intelligence (AI) technology in the field of medicine. This has led to the development of numerous AI algorithms that have been successfully integrated into medical practices, providing valuable assistance to clinicians. The purpose of this study is to develop a cystoscopy algorithm that is real time, cost effective, high performing, and accurate, with the aim of enhancing the detection rate of bladder tumors during cystoscopy. MATERIALS AND METHODS: For this study, a dataset of 3,500 cystoscopic images obtained from 100 patients diagnosed with BC was collected, and a deep learning model was developed utilizing the U-Net algorithm within a convolutional neural network for training purposes. RESULTS: This study randomly divided 3,500 images from 100 BC patients into training and validation groups, and each patient's pathology result was confirmed. In the validation group, the accuracy of tumor recognition by the U-Net algorithm reached 98% compared to primary urologists, with greater accuracy and faster detection speed. CONCLUSION: This study highlights the potential of U-Net-based deep learning techniques in the detection of bladder tumors. The establishment and optimization of the U-Net model is a significant breakthrough and it provides a valuable reference for future research in the field of medical image processing.

A Condition-Monitoring Method for Rolling Bearings Based on Dynamic Asynchronous Peak-Factor Ratios.

In response to issues such as the lack of capability for timely early warning and the difficulty in monitoring the status of rolling bearings, a condition-monitoring method for rolling bearings based on the Honey Badger Algorithm (HBA) for optimizing dynamic asynchronous periods is proposed. This method is founded on the peak factor and involves comparing peak factors at different periods to construct a dynamic asynchronous peak-factor-ratio-monitoring index, which is then optimized using the HBA. Simulated experiments were carried out using the XJTU-SY dataset. The results indicate that, compared to the early warning times defined by international standards, the warning times provided using this method are consistently over 33 min in advance within the test dataset. Additionally, an envelope spectrum analysis of the warning data confirms the existence of early faults. This demonstrates that the monitoring indicator developed in this paper is capable of delivering earlier and more accurate early fault warnings and condition monitoring for rolling bearings.

Differential effects and mechanisms of local anesthetics on esophageal carcinoma cell migration, growth, survival and chemosensitivity.

BACKGROUND: Retrospective analysis and pre-clinical studies suggest that local anesthetics have anti-tumoral effects. However, the association between cancer recurrence and the use of local anesthesia is inconclusive and most reports are based on single local anesthetic results. METHODS: The biological effects (growth, migration and survival) of four common local anesthetics on esophageal carcinoma cells were compared. Biochemical assays on molecules involved in cell migration and proliferation were analyzed. RESULTS: Ropivacaine and bupivacaine significantly inhibited esophageal carcinoma cell migration, at clinically relevant micromolar concentrations. Mepivacaine and lidocaine showed less potent cell migration inhibition than ropivacaine or bupivacaine. All four local anesthetics inhibited cell proliferation. Of note, the effective concentration of anti-proliferative activities requires higher doses. At millimolar concentrations of these local anesthetics, cell apoptosis was moderately affected. Drug combination analysis demonstrated that two of four local anesthetics augmented chemotherapeutic drugs in inhibiting migration. However, all four local anesthetics significantly augmented chemotherapeutic drugs in inhibiting growth and inducing apoptosis. The anti-growth and anti-survival effects of four local anesthetics were attributed to mitochondrial dysfunction and oxidative damage. The anti-migratory effect of local anesthetics is likely through decreasing Rac1 activity. CONCLUSIONS: Our work demonstrates the differential effects and proposes the mechanisms of local anesthetics on esophageal carcinoma cell migration, growth, survival and chemosensitivity.

Investigating energy-based pool structure selection in the structure ensemble modeling with experimental distance constraints: The example from a multidomain protein Pub1.

The structural variations of multidomain proteins with flexible parts mediate many biological processes, and a structure ensemble can be determined by selecting a weighted combination of representative structures from a simulated structure pool, producing the best fit to experimental constraints such as interatomic distance. In this study, a hybrid structure-based and physics-based atomistic force field with an efficient sampling strategy is adopted to simulate a model di-domain protein against experimental paramagnetic relaxation enhancement (PRE) data that correspond to distance constraints. The molecular dynamics simulations produce a wide range of conformations depicted on a protein energy landscape. Subsequently, a conformational ensemble recovered with low-energy structures and the minimum-size restraint is identified in good agreement with experimental PRE rates, and the result is also supported by chemical shift perturbations and small-angle X-ray scattering data. It is illustrated that the regularizations of energy and ensemble-size prevent an arbitrary interpretation of protein conformations. Moreover, energy is found to serve as a critical control to refine the structure pool and prevent data overfitting, because the absence of energy regularization exposes ensemble construction to the noise from high-energy structures and causes a more ambiguous representation of protein conformations. Finally, we perform structure-ensemble optimizations with a topology-based structure pool, to enhance the understanding on the ensemble results from different sources of pool candidates.

A Method for Determining Structure Ensemble of Large Disordered Protein: Application to a Mechanosensing Protein.

Structure characterization of intrinsically disordered proteins (IDPs) remains a key obstacle in understanding their functional mechanisms. Due to the highly dynamic feature of IDPs, structure ensembles instead of static unique structures are often derived from experimental data. Several state-of-the-art computational methods have been developed to select an optimal ensemble from a pregenerated structure pool, but they suffer from low efficiency for large IDPs. Here we present a matching pursuit genetic algorithm (MPGA) for structure ensemble determination, which takes advantages from both matching pursuit (MP) to reduce the search space and genetic algorithm (GA) to reduce the restriction on constraint types. The MPGA method is validated using a reference ensemble with predefined structures. In comparison with the conventional GA, MPGA takes much less computational time for large IDPs. The utility of the method is demonstrated by application to structure ensemble determination of a mechanosensing protein domain with 306 amino acids. The structure ensemble determined reveals that the N-terminal region 1-240 is more compact than the C-terminal region 240-306. The unique structural feature explains why only a small portion of YXXP tyrosine residues can be phosphorylated easily by kinases in the absence of extension force and why the phosphorylation is force-dependent.

Incarvine C suppresses proliferation and vasculogenic mimicry of hepatocellular carcinoma cells via targeting ROCK inhibition.

BACKGROUND: Studies have described vasculogenic mimicry (VM) as an alternative circulatory system to blood vessels in multiple malignant tumor types, including hepatocellular carcinoma (HCC). In the current study, we aimed to seek novel and more efficient treatment strategies by targeting VM and explore the underlying mechanisms in HCC cells. METHODS: Cell counting kit-8 (CCK-8) assay and colony survival assay were performed to explore the inhibitory effect of incarvine C (IVC) on human cancer cell proliferation. Flow cytometry was performed to analyze the cell cycle distribution after DNA staining and cell apoptosis by the Annexin V-PE and 7-AAD assay. The effect of IVC on Rho-associated, coiled-coil-containing protein kinase (ROCK) was determined by western blotting and stress fiber formation assay. The inhibitory role of IVC on MHCC97H cell VM formation was determined by formation of tubular network structures on Matrigel in vitro, real time-qPCR, confocal microscopy and western blotting techniques. RESULTS: We explored an anti-metastatic HCC agent, IVC, derived from traditional Chinese medicinal herbs, and found that IVC dose-dependently inhibited the growth of MHCC97H cells. IVC induced MHCC97H cell cycle arrest at G1 transition, which was associated with cyclin-dependent kinase 2 (CDK-2)/cyclin-E1 degradation and p21/p53 up-regulation. In addition, IVC induced apoptotic death of MHCC97H cells. Furthermore, IVC strongly suppressed the phosphorylation of the ROCK substrate myosin phosphatase target subunit-1 (MYPT-1) and ROCK-mediated actin fiber formation. Finally, IVC inhibited cell-dominant tube formation in vitro, which was accompanied with the down-regulation of VM-key factors as detected by real time-qPCR and immunofluorescence. CONCLUSIONS: Taken together, the effective inhibitory effect of IVC on MHCC97H cell proliferation and neovascularization was associated with ROCK inhibition, suggesting that IVC may be a new potential drug candidate for the treatment of HCC.

Identify BCAT1 plays an oncogenic role and promotes EMT in KIRC via single cell RNA-seq and experiment.

Background: Kidney renal clear cell carcinoma (KIRC) is a major subtype of renal cell carcinoma with poor prognosis due to its invasive and metastatic nature. Despite advances in understanding the molecular underpinnings of various cancers, the role of branched-chain amino acid transferase 1 (BCAT1) in KIRC remains underexplored. This study aims to fill this gap by investigating the oncogenic role of BCAT1 in KIRC using single-cell RNA-seq data and experimental validation. Methods: Single-cell transcriptomic data GSE159115 was utilized to investigate potential biomarkers in KIRC. After screening, we used BCAT1 as a target gene and investigated its function and mechanism in KIRC through databases such as TCGA-GTEx, using genome enrichment analysis (GSEA), genome variation analysis (GSVA), gene ontology (GO) and Kyoto Encyclopedia of the Genome (KEGG). BCAT1 expression was detected in clinical tissue samples using Western Blotting (WB) and immunohistochemical (IHC) staining techniques. We established cell lines stably overexpressing and knocking down BCAT1 and performed WB, qRT-PCR, cell scratch assay and transwell assay. Results: BCAT1 was highly expressed in KIRC and was associated with disease prognosis and TME. Patients with mutations in the BCAT1 gene had shorter overall survival (OS) and disease-free survival (DFS). patients with high BCAT1 expression had shorter OS, progression-free interval (PFI), and disease-specific survival (DSS). GSEA showed that BCAT1 was significantly enriched in epithelial mesenchymal transition (EMT). Bioinformatics analysis and WB and IHC staining showed that BCAT1 expression was higher in KIRC than in paracancerous tissues. In vitro experiments confirmed that BCAT1 in KIRC cells may promote EMT affecting its invasion, migration. We constructed a protein interaction network (PPI) to hypothesize proteins that may interact with BCAT1. Single-sample gene set enrichment analysis (ssGSEA) revealed the immune infiltration environment of BCAT1. Furthermore, hypomethylation of the BCAT1 promoter region in KIRC may contribute to disease progression by promoting BCAT1 expression. Conclusion: BCAT1 promotes KIRC invasion and metastasis through EMT and has prognostic predictive value and potential as a biomarker. It may become a novel biomarker.

Establishment and application of a nomogram diagram for predicting calcium oxalate stones in patients with urinary tract stones.

This retrospective study aims to examine the correlation between calcium oxalate (CaOx) stones and common clinical tests, as well as urine ionic composition. Additionally, we aim to develop and implement a personalized model to assess the accuracy and feasibility of using charts to predict calcium oxalate stones in patients with urinary tract stones. A retrospective analysis was conducted on data from 960 patients who underwent surgery for urinary stones at the First Affiliated Hospital of Soochow University from January 1, 2010, to December 31, 2022. Among these patients, 447 were selected for further analysis based on screening criteria. Multivariate logistic regression analysis was then performed to identify the best predictive features for calcium oxalate stones from the clinical data of the selected patients. A prediction model was developed using these features and presented in the form of a nomogram graph. The performance of the prediction model was assessed using the C-index, calibration curve, and decision curve, which evaluated its discriminative power, calibration, and clinical utility, respectively. The nomogram diagram prediction model developed in this study is effective in predicting calcium oxalate stones which is helpful in screening and early identification of high-risk patients with calcium oxalate urinary tract stones, and may be a guide for urologists in making clinical treatment decisions.

Spatial heterogeneity: Necessary and feasible for revealing soil trace elements pollution, sources, risks, and their links.

The source diversity and health risk of trace elements (TEs) in soil make it necessary to reveal the relationship between pollution, source, and risk. However, neglect of spatial heterogeneity restricts the reliability of existing identification methods. In this study, spatial heterogeneity is proposed as a necessary and feasible factor for accurately dissecting the pollution-source-risk link of soil TEs. A comprehensive framework is developed by integrating positive matrix factorization, Geodetector, and risk evaluation tools, and successfully applied in a mining-intensive city in northern China. Overall, the TEs are derived from natural background (28.5 %), atmospheric deposition (25.6 %), coal mining (21.8 %), and metal industry (24.1 %). The formation mechanism of heterogeneity for high-variance TEs (Se, Hg, Cd) is first systematically deciphered by revealing the heterogeneous source-sink relationship. Specifically, Se is dominated (76.5 %) by heterogeneous coal mining (q=0.187), Hg is determined (92.6 %) by the heterogeneity of metal mining (q=0.183) and smelting (q=0.363), and Cd is caused (50.9 %) by heterogeneous atmospheric deposition (q>0.254) co-influenced by the terrains and soil properties. Highly heterogeneous sources are also noteworthy for their potential to pose extreme risks (THI=1.122) in local areas. This study highlights the necessity of integrating spatial heterogeneity in pollution and risk assessment of soil TEs.

LINC00525 enhances ZNF460-regulated CD24 expression through the sponge miR-125a-5p to promote malignant progression of breast cancer.

INTRODUCTION: CD24 is a highly glycosylated glycosylphosphatidylinositol anchored membrane protein that plays an important role in tumor progression. The aim of this study was to investigate the effect of abnormal expression of CD24 on the proliferation, migration and invasion of breast cancer (BC) cells, and the molecular mechanism of regulating CD24 expression in breast cancer. METHODOLOGY: The bioinformatics method was used to predict the expression level of CD24 in BC and its relationship with the occurrence and development of BC. IHC, RT-qPCR and WB were used to detect the expression of CD24 in BC tissues and cells. The proliferation of CD24 was evaluated by CCK-8 and colony formation assay, and the migration and invasion of CD24 were evaluated by wound healing and transwell. In addition, the effect of CD24 on the malignancy of BC in vivo was further evaluated by subcutaneous tumorigenesis assay. Molecular mechanisms were measured by luciferase reporter assays, biotin-labeled miRNA pull-down assay, RIP, and western blotting. RESULTS: The results show that CD24 is highly expressed in breast cancer tissues and cell lines, and knockdown of CD24 in vivo and in vitro can inhibit the proliferation, migration and invasion of BC cells. Mechanistically, the transcription factor ZNF460 promotes its expression by binding to the CD24 promoter, and the expression of ZNF460 is regulated by miR-125a-5p, which inhibits its expression by targeting the 3'UTR of ZNF460. In addition, LINC00525 acts as a ceRNA sponge to adsorb miR-125a-5p and regulate its expression. CONCLUSIONS: Overexpression of CD24 is involved in the development and poor prognosis of BC, which can be used as a potential target for the treatment of BC and provide a theoretical basis for the treatment of BC.

Therapeutic drug monitoring of amikacin: quantification in plasma by liquid chromatography-tandem mass spectrometry and work experience of clinical pharmacists.

OBJECTIVES: As part of the service provided by clinical pharmacists in our hospital, an assay for plasma amikacin quantification by liquid chromatography-tandem mass spectrometry (LC-MS/MS) has been established for clinical use since 2018. This study was undertaken to describe: (1) the establishment of this assay; (2) the application and results of the testing; and (3) the analysis and impact for patients. METHODS: The amikacin quantification assay was validated and the plasma amikacin concentration data were extracted and analysed. The clinical data for related patients were collected from electronic health and medical records. RESULTS: 121 plasma samples from 53 patients were included in this statistical analysis. The use of amikacin was mostly monitored in the intensive care unit and the haematology department, and the monitoring range of amikacin concentrations were about 0.1-57µg/mL. The main indications for amikacin concentration detection were combined medications, impaired renal function, or people over 65 years old, which may increase the incidence of adverse reactions. Amikacin prescribing decisions were diversified due to the combination of assay results and clinical disease progression, and the effective rate of amikacin administration was about 52.8% (28/53). CONCLUSIONS: The assay for plasma amikacin concentration has been successfully established to monitor the clinical use of amikacin, and the assay results served as one of the references for amikacin prescribing decisions.

Tissue-specific cell-free DNA degradation quantifies circulating tumor DNA burden.

Profiling of circulating tumor DNA (ctDNA) may offer a non-invasive approach to monitor disease progression. Here, we develop a quantitative method, exploiting local tissue-specific cell-free DNA (cfDNA) degradation patterns, that accurately estimates ctDNA burden independent of genomic aberrations. Nucleosome-dependent cfDNA degradation at promoters and first exon-intron junctions is strongly associated with differential transcriptional activity in tumors and blood. A quantitative model, based on just 6 regulatory regions, could accurately predict ctDNA levels in colorectal cancer patients. Strikingly, a model restricted to blood-specific regulatory regions could predict ctDNA levels across both colorectal and breast cancer patients. Using compact targeted sequencing (<25 kb) of predictive regions, we demonstrate how the approach could enable quantitative low-cost tracking of ctDNA dynamics and disease progression.

Inhibition of carrageenan-induced dental inflammatory responses owing to decreased TRPV1 activity by Dexmedetomidine.

BACKGROUND: Dexmedetomidine (Dex) is a highly selective agonist of the α2 adrenergic receptor and a common sedative; however, its anti-inflammatory effect has been studied. In this study, the inhibitory effect of Dex on inflammation in dental pulp cells was assessed. For this, the effect of Dex on inflammation induced by carrageenan (Car) in human dental pulp cells (hDPCs) was evaluated. Car incubation induced a robust inflammatory response in hDPCs as well as activation of PKA-STAT3 and PKC-nuclear factor kappa B (NF-κB) signaling pathways. RESULTS: Dex reduced the expression of inflammatory cytokines in a dose-dependent manner. Meanwhile, the phosphorylation of PKA, PKC, STAT3, and NF-κB as well as the nuclear accumulation of STAT3 and NF-κB were significantly increased in Dex-treated Car-induced hDPCs. Western blotting results also showed that the phosphorylation level of transient receptor potential cation channel subfamily V member 1 (TRPV1) was downregulated as a result of Dex treatment. Furthermore, we found that administration of the TRPV1 agonist capsaicin (Cap) reversed the effects of Dex on proinflammatory cytokines; however, the expression and activation of PKA-STAT3 and PKC-NF-κB signals were not altered owing to Cap administration. CONCLUSIONS: These results indicate that Dex plays a defensive role in dental pulp inflammation by regulating the TRPV1 channel and can be used as a potential target for human dental pulp inflammation intervention.

Bupivacaine inhibits angiogenesis through oxidative stress-dependent inhibition of Akt/mTOR and activation of AMPK.

Although substantial evidence shows the link of local anesthesia and decreased tumor recurrence, the role of amide-linked local anesthetics, particularly bupivacaine, on angiogenesis (a hallmark of tumor progression and metastasis) has not been revealed. In this work, we demonstrate the anti-angiogenic activity of bupivacaine and its underlying mechanism in endothelial cells. We show that bupivacaine inhibits early stage of capillary network formation via suppressing endothelial cell migration without affecting adhesion to matrix. Bupivacaine also inhibits endothelial cell growth and survival. Mechanism analysis indicates that bupivacaine inhibits mitochondrial respiration via decreasing mitochondrial respiratory activity of complex I and II but not IV or V, resulting in energy depletion, oxidative stress, inhibition of Akt/mTOR, and activation of AMPK pathway. The rescue of an antioxidant NAC on the effects of bupivacaine confirms that bupivacaine inhibits angiogenesis through oxidative stress-dependent inhibition of Akt/mTOR and activation of AMPK. Our work clearly demonstrates the inhibitory effects of bupivacaine on angiogenesis via targeting mitochondria. Our findings are in line with the previous work providing the preclinical evidence on how local anesthetics could influence the outcome of cancer patients.

Conformational states of Zika virus non-structural protein 3 determined by molecular dynamics simulations with small-angle X-Ray scattering data.

Zika virus (ZIKV) has become a great public health emergency. Its non-structural protein 3 (NS3) is a key enzyme in viral replication and has been considered as a potential therapeutic target. A conformational characterization of ZIKV NS3 is critical for a comprehensive understanding of its molecular interactions and functions. However, the high conformational flexibility of solution NS3 obstacles the structural characterization of NS3 solely from the experimental observable that averages over its heterogeneous conformations. Here, we employed replica exchange with solute tempering (REST) method to simulate the di-domain protein ZIKV NS3. Three independent MD simulations identified a conserved conformational ensemble of NS3, consisting of a major conformational state and several minor states from compact to loose conformations. The major state agrees well with the scattering profile from small-angle X-ray scattering (SAXS) experiments. Moreover, the simulated ensemble is supported by a direct data-fitting result that requires both short- and long-range structural contacts to recover the experimental data. We discussed the interplay between simulation and experiment in ensemble construction of flexible biomolecules and shed light on the physically derived conformational ensembles.

RhoC/ROCK2 promotes vasculogenic mimicry formation primarily through ERK/MMPs in hepatocellular carcinoma.

Vasculogenic mimicry (VM) results in the formation of an alternative circulatory system that can improve the blood supply to multiple malignant tumors, including hepatocellular carcinoma (HCC). However, the potential mechanisms of RhoC/ROCK in VM have not yet been investigated in HCC. Here, RhoC expression was upregulated in HCC tissues, especially the VM-positive (VM+) group, compared to noncancerous tissues (P < 0.01), and patients with high expression of RhoC had shorter survival times (P < 0.001). The knockdown of RhoC via short hairpin RNA (shRNA) in SK-Hep-1 cells significantly decreased VM formation and cell motility. In contrast, cell motility and VM formation were remarkably enhanced when RhoC was overexpressed in HepG2 cells. To further assess the potential role of ROCK1 and ROCK2 on VM, we stably knocked down ROCK1 or ROCK2 in MHCC97H cells. Compared to ROCK1 shRNA, ROCK2 shRNA could largely affect VM formation, cell motility and the key VM factors, as well as the epithelial-mesenchymal transition (EMT) markers in vitro and in vivo. Moreover, p-ERK, p-MEK, p-FAK, p-paxillin, MT1-MMP and MMP2 levels were clearly altered following the overexpression of RhoC, but ROCK2 shRNA had little effect on the expression of p-FAK, which indicated that RhoC regulates FAK/paxillin signaling, but not through ROCK2. In conclusion, our results show that RhoC/ROCK2 may have a major effect on VM in HCC via ERK/MMPs signaling and might be a potential therapeutic target for the treatment of HCC.

Inhibition of gastric cancer by local anesthetic bupivacaine through multiple mechanisms independent of sodium channel blockade.

BACKGROUND: Retrospective studies of patients undergoing cancer surgery suggest the use of local anesthesia may decrease tumor recurrence and improve survival. The mechanisms on the benefits of local anesthesia on cancer recurrence are complex and remain to be elucidated. METHODS: This study investigated the effects of bupivacaine on various cellular activities of gastric cancer using proliferation, migration, apoptosis assay. The underlying mechanism was analyzed focusing on mitochondrial functions and the activities of Rho family members. RESULTS: We show that bupivacaine at low concentrations (eg, 0.01 and 0.05 mM) inhibits migration whereas only at high concentrations (1 and 5 mM) inhibits growth and survival in two human gastric cancer cell lines. Bupivacaine also significantly augments 5-Fluorouracil in inhibiting growth and survival but not migration in gastric cancer cells. In addition, the mechanisms of bupivacaine's action on the growth and survival are different from those on the migration. We demonstrate that bupivacaine inhibits gastric cancer cell growth and survival through inhibiting mitochondrial respiratory complex I and II, leading to decreased mitochondrial oxidation and ATP production. In contrast, bupivacaine inhibits gastric cancer cell migration through decreasing RhoA and Rac1 activities without affecting their expression. Particularly, we demonstrate that bupivacaine inhibits gastric cancer cell migration via inhibiting RhoA/ROCK/MLC pathway. We further show that the action of bupivacaine on mitochondrial functions, RhoA, and Rac1 activities are independent of sodium channel blockade. CONCLUSIONS: Our work demonstrates that bupivacaine has direct anti-cancer activities with the dominant inhibitory effects on gastric cancer migration rather than growth and survival. Our findings also guide a proper understanding and provide underlying mechanisms on how local aesthesis could affect cancer patients.

Coarse-Grained Molecular Modeling of the Solution Structure Ensemble of Dengue Virus Nonstructural Protein 5 with Small-Angle X-ray Scattering Intensity.

An ensemble-modeling scheme incorporating coarse-grained simulations with experimental small-angle X-ray scattering (SAXS) data is applied to dengue virus 2 (DENV2) nonstructural protein 5 (NS5). NS5 serves a key role in viral replication through its two domains that are connected by a 10-residue polypeptide segment. A set of representative structures is generated from a simulated structure pool using SAXS data fitting by the non-negativity least squares (NNLS) or standard ensemble optimization method (EOM) based on a genetic algorithm (GA). It is found that a proper low-energy threshold of the structure pool is necessary to produce a conformational ensemble of two representative structures by both NNLS and GA that agrees well with the experimental SAXS profile. The stability of the constructed ensemble is validated also by molecular dynamics simulations with an all-atom force field. The constructed ensemble successfully revealed the domain-domain orientation and domain-contacting interface of DENV2 NS5. Using experimental data fitting and additional investigations with synthesized data, it is found that energy restraint on the conformational pool is necessary to avoid overinterpretation of experimental data by spurious conformational representations.