Efficacy and safety of intracoronary pro-urokinase combined with low-pressure balloon pre-dilatation during percutaneous coronary intervention in patients with anterior ST-segment elevation myocardial infarction.

BACKGROUND: The efficacy and safety of low-pressure balloon pre-dilatation before intracoronary pro-urokinase (pro-UK) in preventing no-reflow during percutaneous coronary intervention (PCI) remains unknown. This study aimed to evaluate the clinical outcomes of intracoronary pro-UK combined with low-pressure balloon pre-dilatation in patients with anterior ST-segment-elevation myocardial infarction (STEMI). METHODS: This was a randomized, single-blind, investigator-initiated trial that included 179 patients diagnosed with acute anterior STEMI. All patients were eligible for PCI and were randomized into two groups: intracoronary pro-UK combined with (ICPpD group, n = 90) or without (ICP group, n = 89) low-pressure balloon pre-dilatation. The main efficacy endpoint was complete epicardial and myocardial reperfusion. The safety endpoints were major adverse cardiovascular events (MACEs), which were analyzed at 12 months follow-up. RESULTS: Patients in the ICPpD group presented significantly higher TIMI myocardial perfusion grade 3 (TMPG3) compared to those in the ICP group (77.78% versus 68.54%, P = 0.013), and STR ≥ 70% after PCI 30 min (34.44% versus 26.97%, P = 0.047) or after PCI 90 min (40.0% versus 31.46%, P = 0.044). MACEs occurred in 23 patients (25.56%) in the ICPpD group and in 32 patients (35.96%) in the ICP group. There was no difference in hemorrhagic complications during hospitalization between the groups. CONCLUSION: Patients with acute anterior STEMI presented more complete epicardial and myocardial reperfusion with adjunctive low-pressure balloon pre-dilatation before intracoronary pro-UK during PCI. TRIAL REGISTRATION: 2019xkj213.

Prognostic nomogram in patients with gastrointestinal stromal tumors: a SEER-based study.

Background: Gastrointestinal stromal tumor (GIST) is a common mesenchymal tumor of the gastrointestinal system. They originate from the interstitial cells of Cajal located within the muscle layer and are characterized by over-expression of the tyrosine kinase receptor KIT. Methods: Data from the Surveillance Epidemiology, and End Results (SEER) database of 1,213 patients diagnosed with GIST between 2010 and 2019 were dichotomized into a modeling set and a validation set at a 2:1 ratio. For the modeling set, both univariate and multivariate Cox regression analyses were used to identify independent prognostic factors. A nomogram was then constructed based on these determinants. Model efficacy was tested using receiver operating characteristic (ROC) curves, calibration curves, clinical decision curves, and risk stratification analysis in both subsets. Results: Identified prognostic determinants included age, sex, pathological differentiation level, tumor-node-metastasis (TNM) stage, surgical intervention, radiotherapy, and marital status. The constructed nomogram showed area under the ROC curve (AUC) values of 0.822, 0.793, and 0.779 for 1-, 3-, and 5-year overall survival (OS) in the modeling set, respectively, while in the validation set, the values were 0.796, 0.823, and 0.806, respectively. Calibration plots from both sets confirmed the concordance between predicted and observed survival. Decision curve analysis (DCA) indicated significant clinical utility for the nomogram. Risk stratification of the patient data revealed distinct survival differences between high-risk and low-risk cohorts in both sets (P<0.001). Conclusions: A novel and potent nomogram for the prognosis of GIST has been introduced. This model's precision offers crucial insights for clinical decisions, yet further external validation remains essential.

Inhibition of SIRT7 overcomes sorafenib acquired resistance by suppressing ERK1/2 phosphorylation via the DDX3X-mediated NLRP3 inflammasome in hepatocellular carcinoma.

AIMS: Sirtuin 7 (SIRT7) plays an important role in tumor development, and has been characterized as a potent regulator of cellular stress. However, the effect of SIRT7 on sorafenib acquired resistance remains unclear and a possible anti-tumor mechanism beyond this process in HCC has not been clarified. We examined the therapeutic potential of SIRT7 and determined whether it functions synergistically with sorafenib to overcome chemoresistance. METHODS: Cancer Genome Atlas-liver HCC data and unbiased gene set enrichment analyses were used to identify SIRT7 as a potential effector molecule in sorafenib acquired resistance. Two types of SIRT7 chemical inhibitors were developed to evaluate its therapeutic properties when synergized with sorafenib. Mass spectrometry was performed to discover a direct target of SIRT7, DDX3X, and DDX3X deacetylation levels and protein stability were explored. Moreover, an in vivo xenograft model was used to confirm anti-tumor effect of SIRT7 and DDX3X chemical inhibitors combined with sorafenib. RESULTS: SIRT7 inhibition mediated DDX3X depletion can re-sensitize acquired sorafenib resistance by disrupting NLRP3 inflammasome assembly, finally suppressing hyperactive ERK1/2 signaling in response to NLRP3 inflammasome-mediated IL-1ß inhibition. CONCLUSIONS: SIRT7 is responsible for sorafenib acquired resistance, and its inhibition would be beneficial when combined with sorafenib by suppressing hyperactive pro-cell survival ERK1/2 signaling.

PhyGCN: Pre-trained Hypergraph Convolutional Neural Networks with Self-supervised Learning.

Hypergraphs are powerful tools for modeling complex interactions across various domains, including biomedicine. However, learning meaningful node representations from hypergraphs remains a challenge. Existing supervised methods often lack generalizability, thereby limiting their real-world applications. We propose a new method, Pre-trained Hypergraph Convolutional Neural Networks with Self-supervised Learning (PhyGCN), which leverages hypergraph structure for self-supervision to enhance node representations. PhyGCN introduces a unique training strategy that integrates variable hyperedge sizes with self-supervised learning, enabling improved generalization to unseen data. Applications on multi-way chromatin interactions and polypharmacy side-effects demonstrate the effectiveness of PhyGCN. As a generic framework for high-order interaction datasets with abundant unlabeled data, PhyGCN holds strong potential for enhancing hypergraph node representations across various domains.

hucMSCs treatment prevents pulmonary fibrosis by reducing circANKRD42-YAP1-mediated mechanical stiffness.

Idiopathic pulmonary fibrosis (IPF) is a fibrosing interstitial pneumonia of unknown cause. The most typical characteristic of IPF is gradual weakening of pulmonary elasticity and increase in hardness/rigidity with aging. This study aims to identify a novel treatment approach for IPF and explore mechanism of mechanical stiffness underlying human umbilical cord mesenchymal stem cells (hucMSCs) therapy. Target ability of hucMSCs was examined by labeling with cell membrane dye Dil. Anti-pulmonary fibrosis effect of hucMSCs therapy by reducing mechanical stiffness was evaluated by lung function analysis and MicroCT imaging system and atomic force microscope in vivo and in vitro. Results showed that stiff environment of fibrogenesis caused cells to establish a mechanical connection between cytoplasm and nucleus, initiating expression of related mechanical genes such as Myo1c and F-actin. HucMSCs treatment blocked force transmission and reduced mechanical force. For further exploration of mechanism, ATGGAG was mutated to CTTGCG (the binding site of miR-136-5p) in the full-length sequence of circANKRD42. Wildtype and mutant plasmids of circANKRD42 were packaged into adenovirus vectors and sprayed into lungs of mice. Mechanistic dissection revealed that hucMSCs treatment repressed circANKRD42 reverse splicing biogenesis by inhibiting hnRNP L, which in turn promoted miR-136-5p binds to 3'-Untranslated Region (3'-UTR) of YAP1 mRNA directly, thus inhibiting translation of YAP1 and reducing YAP1 protein entering nucleus. The condition repressed expression of related mechanical genes to block force transmission and reduce mechanical forces. The mechanosensing mechanism mediated directly by circANKRD42-YAP1 axis in hucMSCs treatment, which has potential general applicability in IPF treatment.

Multiregional radiomic model for breast cancer diagnosis: value of ultrasound-based peritumoral and parenchymal radiomics.

Background: Breast cancer consists not only of neoplastic cells but also of significant changes in the surrounding and parenchymal stroma, which can be reflected in radiomics. This study aimed to perform breast lesion classification through an ultrasound-based multiregional (intratumoral, peritumoral, and parenchymal) radiomic model. Methods: We retrospectively reviewed ultrasound images of breast lesions from institution #1 (n=485) and institution #2 (n=106). Radiomic features were extracted from different regions (intratumoral, peritumoral, and ipsilateral breast parenchymal) and selected to train the random forest classifier with the training cohort (n=339, a subset of the institution #1 dataset). Then, the intratumoral, peritumoral, and parenchymal, intratumoral & peritumoral (In&Peri), intratumoral & parenchymal (In&P), and intratumoral & peritumoral & parenchymal (In&Peri&P) models were developed and validated on the internal (n=146, another subset of institution 1) and external (n=106, institution #2 dataset) test cohorts. Discrimination was evaluated using the area under the curve (AUC). Calibration curve and Hosmer-Lemeshow test assessed calibration. Integrated discrimination improvement (IDI) was used to assess performance improvement. Results: The performance of the In&Peri (AUC values 0.892 and 0.866), In&P (0.866 and 0.863), and In&Peri&P (0.929 and 0.911) models was significantly better than that of the intratumoral model (0.849 and 0.838) in the internal and external test cohorts (IDI test, all P<0.05). The intratumoral, In&Peri and In&Peri&P models showed good calibration (Hosmer-Lemeshow test, all P>0.05). The multiregional (In&Peri&P) model had the highest discrimination among the 6 radiomic models in the test cohorts, respectively. Conclusions: The multiregional model combining radiomic information of intratumoral, peritumoral, and ipsilateral parenchymal regions yielded better performance than the intratumoral model in distinguishing malignant breast lesions from benign lesions.

An ATG4B inhibitor blocks autophagy and sensitizes Sorafenib inhibition activities in HCC tumor cells.

Autophagy related 4B (ATG4B) which regulates autophagy by promoting the formation of autophagosome through reversible modification of LC3, is closely related to cancer cell growth and drug resistance, and therefore is an attractive therapeutic target. Recently, ATG4B inhibitors have been reported, yet with drawbacks including weak potency. To discover more promising ATG4B inhibitors, we developed a high-throughput screening (HTS) assay and identified a new ATG4B inhibitor named DC-ATG4in. DC-ATG4in directly binds to ATG4B and inhibits its enzyme activity with an IC50 of 3.08 ± 0.47 µM. We further confirmed that DC-ATG4in is an autophagy inhibitor and blocks autophagy induced by Sorafenib in Hepatocellular Carcinoma (HCC) cells. More importantly, combination of DC-ATG4in with Sorafenib synergized the cancer cell killing effect and proliferation inhibition activities on HCC cells. Our data suggested that inactivation of autophagy via ATG4B inhibition may be a viable strategy to sensitize existing targeted therapy such as Sorafenib in the future.

Ultrasound image-based deep learning to assist in diagnosing gross extrathyroidal extension thyroid cancer: a retrospective multicenter study.

Background: The presence of gross extrathyroidal extension (ETE) in thyroid cancer will affect the prognosis of patients, but imaging examination cannot provide a reliable diagnosis for it. This study was conducted to develop a deep learning (DL) model for localization and evaluation of thyroid cancer nodules in ultrasound images before surgery for the presence of gross ETE. Methods: From January 2016 to December 2021 grayscale ultrasound images of 806 thyroid cancer nodules (4451 images) from 4 medical centers were retrospectively analyzed, including 517 no gross ETE nodules and 289 gross ETE nodules. 283 no gross ETE nodules and 158 gross ETE nodules were randomly selected from the internal dataset to form a training set and validation set (2914 images), and a multitask DL model was constructed for diagnosing gross ETE. In addition, the clinical model and the clinical and DL combined model were constructed. In the internal test set [974 images (139 no gross ETE nodules and 83 gross ETE nodules)] and the external test set [563 images (95 no gross ETE nodules and 48 gross ETE nodules)], the diagnostic performance of DL model was verified based on the pathological results. And then, compared the results with the diagnosis by 2 senior and 2 junior radiologists. Findings: In the internal test set, DL model demonstrated the highest AUC (0.91; 95% CI: 0.87, 0.96), which was significantly higher than that of two senior radiologists [(AUC, 0.78; 95% CI: 0.71, 0.85; P < 0.001) and (AUC, 0.76; 95% CI: 0.70, 0.83; P < 0.001)] and two juniors radiologists [(AUC, 0.65; 95% CI: 0.58, 0.73; P < 0.001) and (AUC, 0.69; 95% CI: 0.62, 0.77; P < 0.001)]. DL model was significantly higher than clinical model [(AUC, 0.84; 95% CI: 0.79, 0.89; P = 0.019)], but there was no significant difference between DL model and clinical and DL combined model [(AUC, 0.94; 95% CI: 0.91, 0.97; P = 0.143)]. In the external test set, DL model also demonstrated the highest AUC (0.88, 95% CI: 0.81, 0.94), which was significantly higher than that of one of senior radiologists [(AUC, 0.75; 95% CI: 0.66, 0.84; P = 0.008) and (AUC, 0.81; 95% CI: 0.72, 0.89; P = 0.152)] and two junior radiologists [(AUC, 0.72; 95% CI: 0.62, 0.81; P = 0.002) and (AUC, 0.67; 95 CI: 0.57, 0.77; P < 0.001]. There was no significant difference between DL model and clinical model [(AUC, 0.85; 95% CI: 0.79, 0.91; P = 0.516)] and clinical + DL model [(AUC, 0.92; 95% CI: 0.87, 0.96; P = 0.093)]. Using DL model, the diagnostic ability of two junior radiologists was significantly improved. Interpretation: The DL model based on ultrasound imaging is a simple and helpful tool for preoperative diagnosis of gross ETE thyroid cancer, and its diagnostic performance is equivalent to or even better than that of senior radiologists. Funding: Jiangxi Provincial Natural Science Foundation (20224BAB216079), the Key Research and Development Program of Jiangxi Province (20181BBG70031), and the Interdisciplinary Innovation Fund of Natural Science, Nanchang University (9167-28220007-YB2110).

Immune landscape and prognostic index for pancreatic cancer based on TCGA database and in vivo validation.

The immunotherapy efficacy on pancreatic cancer remains unsatisfactory. Therefore, it is still necessary to further clarify the pancreatic immune cell infiltration and search for immune-related prognostic indicators. We analyzed the 135 pancreatic cancer patients' data retrieved from the TCGA database for the immune cell infiltration, tumor microenvironment score and the correlation of the immune cells, followed by identification of prognostic immune clusters and genes clusters. The R language was used for the immune score calculation, and immune cells proportion related survival differences identification. The function of immune cells was verified through datasets in the GEO database and in vivo experiments. The results showed that M0 Macrophages had negative relations to CD8 + T cells and immune scores. There were differences in median survival in ICI clusters, gene clusters, and immune score groups (p < 0.05). M0 macrophages accounted for more than 9.8%, indicating a poor prognosis, while T cells accounted for more than 9.2%, indicating a good prognosis. In vivo results showed that M0 macrophages promote pancreatic cancer growth. Elimination of M0 macrophages may be a hopeful strategy against pancreatic cancer.

The complex genome and adaptive evolution of polyploid Chinese pepper (Zanthoxylum armatum and Zanthoxylum bungeanum).

Zanthoxylum armatum and Zanthoxylum bungeanum, known as 'Chinese pepper', are distinguished by their extraordinary complex genomes, phenotypic innovation of adaptive evolution and species-special metabolites. Here, we report reference-grade genomes of Z. armatum and Z. bungeanum. Using high coverage sequence data and comprehensive assembly strategies, we derived 66 pseudochromosomes comprising 33 homologous phased groups of two subgenomes, including autotetraploid Z. armatum. The genomic rearrangements and two whole-genome duplications created large (~4.5 Gb) complex genomes with a high ratio of repetitive sequences (>82%) and high chromosome number (2n = 4x = 132). Further analysis of the high-quality genomes shed lights on the genomic basis of involutional reproduction, allomones biosynthesis and adaptive evolution in Chinese pepper, revealing a high consistent relationship between genomic evolution, environmental factors and phenotypic innovation. Our study provides genomic resources and new insights for investigating diversification and phenotypic innovation in Chinese pepper, with broader implications for the protection of plants under severe environmental changes.

PLAU is associated with cell migration and invasion and is regulated by transcription factor YY1 in cervical cancer.

Cervical cancer, one of the most common malignancies, has a poor survival rate. The identification of more biomarkers for cervical cancer diagnosis and therapy is urgently needed. Plasminogen activator urokinase (PLAU) exerts multiple biological effects in various physiological and pathological processes; however the role of PLAU in cervical cancer progression is not fully understood. In the present study, the involvement and transcriptional regulation of PLAU in cervical cancer were explored. The expression of PLAU in cervical cancer was first analyzed, and PLAU was found to be overexpressed. In vitro experiments demonstrated that the migration and invasion of HeLa and HT3 cells were significantly suppressed by PLAU knockdown. Additionally, the core promoter of PLAU was confirmed, and the transcription factor YinYang 1 (YY1) was found to regulate PLAU mRNA expression. Overall, the present study elucidated the direct association between PLAU and cervical cancer, suggesting the YY1/PLAU axis as a potential novel therapeutic target for cervical cancer.

Upregulation of Glutaminyl Cyclase Contributes to ERS-Induced Apoptosis in PC12 Cells.

Glutaminyl cyclase (QC) is responsible for converting the N-terminal glutaminyl and glutamyl of the proteins into pyroglutamate (pE) through cyclization. It has been confirmed that QC catalyzes the formation of neurotoxic pE-modified Aß in the brain of AD patients. But the effects of upregulated QC in diverse diseases have not been much clear until recently. Here, RNA sequencing was applied to identify differentially expressed genes (DEGs) in PC12 cells with QC overexpressing or knockdown. A total of 697 DEGs were identified in QC overexpressing cells while only 77 in QC knockdown cells. Multiple bioinformatic approaches revealed that the DEGs in QC overexpressing group were enriched in endoplasmic reticulum stress (ERS) related signaling pathways. The gene expression patterns of 23 DEGs were confirmed by RT-qPCR, in which the genes related to ERS showed the highest consistency. We also revealed the protein levels of GRP78, PERK, CHOP, and PARP-1, and caspase family was significantly upregulated by overexpressing QC. Moreover, overexpressing QC significantly increased apoptosis of PC12 cells in a time dependent manner. However, no significant alteration was observed in QC knockdown cells. Therefore, our study indicated that upregulated QC could induce ERS and apoptosis, which consequently trigger diseases by catalyzing the generation of pE-modified mediators.

Targeted therapy in NPM1-mutated AML: Knowns and unknowns.

Acute myeloid leukemia (AML) is a heterogeneous disease characterized by malignant proliferation of myeloid hematopoietic stem/progenitor cells. NPM1 represents the most frequently mutated gene in AML and approximately 30% of AML cases carry NPM1 mutations. Mutated NPM1 result in the cytoplasmic localization of NPM1 (NPM1c). NPM1c interacts with other proteins to block myeloid differentiation, promote cell proliferation and impair DNA damage repair. NPM1 is a good prognostic marker, but some patients ultimately relapse or fail to respond to therapy. It is urgent for us to find optimal therapies for NPM1-mutated AML. Efficacy of multiple drugs is under investigation in NPM1-mutated AML, and several clinical trials have been registered. In this review, we summarize the present knowledge of therapy and focus on the possible therapeutic interventions for NPM1-mutated AML.

PD-L1/TLR7 dual-targeting nanobody-drug conjugate mediates potent tumor regression via elevating tumor immunogenicity in a host-expressed PD-L1 bias-dependent way.

BACKGROUND: Various tumors are insensitive to immune checkpoint blockade (ICB) therapy. Toll-like receptors (TLRs) establish the link between innate and adaptive immunity, which can assist T-cell activation and serve as promising targets for combination to enhance ICB therapy. Here, we aimed to improve efficacy for anti-programmed death ligand 1 (PD-L1) therapy by developing a PD-L1/TLR7 dual-targeting nanobody-drug conjugate (NDC), based on the PD-L1 nanobodies and TLR7 agonist we developed. METHODS: PD-L1 nanobodies were obtained by phage display screening and identified through T-cell activation bioassay, in vivo imaging and quantitative biodistribution study. Immune activation and PD-L1-inducing of TLR7 agonists were evaluated in diverse innate cell models. We constructed PD-L1/TLR7 dual-targeting NDCs by chemically coupling PD-L1 nanobodies and TLR7 agonists. The antitumor effect was evaluated via several murine or humanized solid tumor models. Immunophenotyping, immune cell depletion, tumor rechallenge, RNA sequencing and PD-L1-deficient models were combined to determine the mechanism for NDCs function. The dynamics of the in vivo behaviors of NDCs were assessed based on multiorgan changes in PD-L1 levels. RESULTS: The screened PD-L1 nanobodies were characterized as tumor-targeting and alleviated T-cell immunosuppression. The TLR7 agonists induced broad innate immune responses and intratumoral PD-L1 expression on antigen-presenting cells (APCs), and its antitumor effect was dependent on intratumoral delivery. The combination of TLR7 agonists and PD-L1 nanobodies activated both innate and adaptive immunity and upregulated PD-L1-related signaling pathways. After coupling to form dual-targeting NDCs, TLR7 agonists and PD-L1 nanobodies exerted synergistic antitumor effects and safety in either 'hot' or 'cold' tumor and early or advanced tumor models, reshaped the tumor immune microenvironment and induced antitumor immune memory. CD8+ T cells and natural killer cells were the main effector cells for NDCs to function. NDCs can promote PD-L1 expression on intratumoral APCs and tumor cells, and subsequently achieve targeted enrichment in tumors. Moreover, the efficacy of NDCs is biased toward dependence on host expression of PD-L1. CONCLUSIONS: The novel PD-L1/TLR7 dual-targeting NDC exhibited potent efficacy against heterogeneous tumors through orchestrating innate and adaptive immunity, which could act as a promising strategy to improve ICB therapy and shows prospects for clinical development.

Carotid contrast-enhanced ultrasonography combined with sirtuin-3 in the diagnosis of plaques in carotid atherosclerosis.

BACKGROUND: Carotid atherosclerosis (CAS) is one of the main causes of ischemic stroke. Currently, the clinical evidence for contrast-enhanced ultrasonography (CEUS) as a method for diagnosing CAS is still inadequate. Sirtuin-3 (SIRT3) is associated with the inflammation response; however, few studies have evaluated SIRT3 in CAS. OBJECTIVES: To investigate the role of SIRT3 in CAS patients and its diagnostic value for unstable plaques when combined with CEUS. MATERIAL AND METHODS: This is a prospective observational study including 517 CAS patients who were admitted to our hospital from January 2015 to December 2020. All patients received a normal Doppler ultrasound, CEUS and magnetic resonance imaging (MRI). The latter was used as the gold standard in evaluating plaque conditions. Serum SIRT3 levels were measured using an enzyme-linked immunosorbent assay (ELISA). Serum levels of total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-ch), low-density lipoprotein cholesterol (LDL-ch), C-reactive protein (CRP), and interleukin (IL)-6 levels were measured and recorded. RESULTS: Patients with severe CAS showed significantly higher levels of CRP, IL-6, TC, and LDL-ch, a higher frequency of unstable plaques, as well as a lower level of HDL-ch. In patients with severe CAS and CAS patients with stable plaques, the levels of SIRT3 were markedly lower. Patients with a high expression of SIRT3 showed significantly lower levels of CRP, IL-6, TC and LDL-ch, and higher levels of HDL-ch, as well as a lower frequency of unstable plaques. Receiver operating characteristic (ROC) curves showed that the combination of CEUS and SIRT3 could achieve high sensitivity and specificity in the diagnosis of unstable plaques. High levels of C-reactive protein, IL-6, TC, TG and LDL-ch, as well as low levels of SIRT3 and HDL-ch, and current smoking were risk factors of unstable plaques in CAS patients. CONCLUSIONS: A low expression of SIRT3 predicted a higher risk for unstable plaques in CAS patients. The combination of CEUS and SIRT3 is a potential strategy for diagnosing unstable plaques.

Aptamer-mediated DNA concatemer functionalized magnetic nanoparticles for reversible capture and release of circulating tumor cells.

Effectively capturing, releasing, and reanalyzing circulating tumor cells (CTCs) are critical in cancer diagnosis and individualized treatment. Traditional immunomagnetic separation has disadvantages of low sensitivity and specificity, and is time-consuming and costly in CTCs capture. It is also easily disturbed by the microenvironment in releasing and analyzing CTCs. Here, we proposed an aptamer-mediated DNA concatemer functionalized magnetic nanoparticles (MNPs-AMDC) for the reversible capture and release of CTCs. In this study, aptamers were used both for efficiently capturing CTCs without complicated assembly steps and stimulus-response switch for releasing CTCs with little influence on cellular activity. The MNPs-AMDC was demonstrated to effectively capture (83%) and release CTCs with a good viability rate (92%). Moreover, this device was also tested in clinical blood samples, which would provide a universal tool for diagnosing cancer and treating individuals.

Function of normal oral mucosa revealed by single-cell RNA sequencing.

The functions of oral mucosa include barrier, sensation, and secretion. The barrier protection function is particularly important, which includes physical barrier and immunological barrier. Few studies have revealed the function of oral mucosa by displaying the map of normal oral mucosal cells from the perspective of single cells. Here, single-cell transcriptome sequencing was used to bring a relatively comprehensive map of the normal oral mucosal cells. In total, 26,398 cells from three cases of normal oral mucosa were analyzed by single-cell RNA-sequencing and 14 distinct cell groups were defined, 7 of which were immune cells. We performed subgroup classification and heterogeneity analysis of epithelial cells, T cells, and macrophagocytes, which found a subpopulation of epithelial cells with high expression of major histocompatibility complex class II molecules, a subpopulation CD8+ GZMK+ T cells, and two kinds of active macrophagocytes. Meanwhile, we identified ligand-receptor pairs among the major cell types to explore the interactions and how they maintain the homeostasis of normal oral mucosa. Based on these results, the epithelial barrier function, immunological barrier function, and potential maintenance function of stromal cells in the oral mucosa were described at the single-cell level, which provides basic data resources for further studies of oral mucosal diseases.

Integrating network pharmacology and experimental models to investigate the efficacy of QYHJ on pancreatic cancer.

ETHNOPHARMACOLOGICAL RELEVANCE: The Qingyihuaji decoction (QYHJ) is composed of seven herbs: Scutellaria barbata D.Don (Banzhilian, HSB), Gynostemma pentaphyllum (Thunb.) Makino (Jiaogulan, GP), Oldenlandia diffusa (Willd.) Roxb. (Baihuasheshecao, HDH), Ganoderma lucidum (Leyss. ex Fr.) Karst. (Lingzhi, GL), Myristica fragrans Houtt. (Doukou, AK), and Amorphophallus kiusianus (Makino) Makino (Sheliugu, RA), and Coix lacryma-jobi var. ma-yuen (Rom.Caill.) Stapf (Yiyiren, CL). QYHJ has been reported to exhibit clinical efficacy in the treatment of pancreatic adenocarcinoma (PAAD). However, the molecular mechanism remains unclear. AIM OF THE STUDY: This study explores the therapeutic mechanism of QYHJ in the treatment of PAAD using network pharmacology to identify related targets and pathways in vivo and in vitro. MATERIALS AND METHODS: The bioactive compounds of QYHJ were retrieved and screened using the ADME network pharmacology approach, followed by compound-target prediction and overlapping genes between PAAD oncogenes and QYHJ target genes. The compound-target-pathway network was established using The KEGG pathway, GO analysis, and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) analysis to identify potential action pathways. The effects of QYHJ on PAAD were evaluated in vivo and in vitro, and the predicted targets and potential pathways related to QYHJ in PAAD treatment were evaluated using qRT-PCR and immunoblotting. RESULTS: A total of 68 bioactive compounds of QYHJ fulfilled the ADME screening criterion, and their respective 242 target genes were retrieved. The compound-target-disease network identified 11 possible target genes. The KEGG pathway analysis showed significant enrichment of pathways in cancers, involving regulating cancer-related pathways of inflammation, oxidative stress, and apoptosis. Furthermore, QYHJ inhibited PAAD growth in vivo; suppressed cell proliferation, invasion, and migration of PAAD; and induced cellular apoptosis in vitro. The qRT-PCR results showed that QYHJ suppressed the mRNA expression of ICAM1, VCAM1, and Bcl2, and increased that of HMOX1 and NQO1. Immunoblotting revealed changes in the PI3K/AKT/mTOR, Keap1/Nrf2/HO-1/NQO1, and Bcl2/Bax pathways upon QYHJ treatment. CONCLUSIONS: QYHJ can suppress PAAD growth and progression through various mechanisms, including anti-inflammation and apoptosis-induction.

Artificial Neural Network-Based Ultrasound Radiomics Can Predict Large-Volume Lymph Node Metastasis in Clinical N0 Papillary Thyroid Carcinoma Patients.

Objective: To evaluate the ability of artificial neural network- (ANN-) based ultrasound radiomics to predict large-volume lymph node metastasis (LNM) preoperatively in clinical N0 disease (cN0) papillary thyroid carcinoma (PTC) patients. Methods: From January 2020 to April 2021, 306 cN0 PTC patients admitted to our hospital were retrospectively reviewed and divided into a training (n = 183) cohort and a validation cohort (n = 123) in a 6 : 4 ratio. Radiomic features quantitatively extracted from ultrasound images were pruned to train one ANN-based radiomic model and three conventional machine learning-based classifiers in the training cohort. Furthermore, an integrated model using ANN was constructed for better prediction. Meanwhile, the prediction of the two models was evaluated in the papillary thyroid microcarcinoma (PTMC) and conventional papillary thyroid cancer (CPTC) subgroups. Results: The radiomic model showed better discrimination than other classifiers for large-volume LNM in the validation cohort, with an area under the receiver operating characteristic curve (AUROC) of 0.856 and an area under the precision-recall curve (AUPR) of 0.381. The performance of the integrated model was better, with an AUROC of 0.910 and an AUPR of 0.463. According to the calibration curve and decision curve analysis, the radiomic and integrated models had good calibration and clinical usefulness. Moreover, the models had good predictive performance in the PTMC and CPTC subgroups. Conclusion: ANN-based ultrasound radiomics could be a potential tool to predict large-volume LNM preoperatively in cN0 PTC patients.

A model based on two-dimensional shear wave elastography for acute-on-chronic liver failure development in patients with acutely decompensated hepatitis B cirrhosis.

Background: To evaluate the accuracy of two-dimensional (2D) shear wave elastography (SWE), develop and validate a novel prognostic model in predicting acute-on-chronic liver failure (ACLF) development in patients with acutely decompensated hepatitis B cirrhosis. Methods: This prospective cohort study enrolled 221 patients in the First Affiliated Hospital of Nanchang University from September 2019 to January 2021, and randomly assigned them to the derivation and validation cohorts (7:3 ratio). Ultrasound, 2D SWE, clinical and laboratory data were collected, and outcome (ACLF developed) was recorded during a 90-day follow-up period. We evaluated the ability of 2D SWE to predict the outcome, developed a model for predicting ACLF development in the derivation cohort, and assessed the model in the validation cohort. Results: 2D SWE values were significantly higher in patients with ACLF development (P<0.05). The accuracy of 2D SWE in predicting the outcome was better than that of serum parameters of liver fibrosis (all P<0.05). The SWE model for ACLF development had good calibration and discrimination [concordance index (C-index): 0.855 and 0.840 respectively] in derivation and validation cohorts, outperforming serum prognostic scores (all P<0.05). Conclusions: The SWE model, superior to serum prognostic scores in predicting ACLF development, could be a noninvasive tool to guide the individual management of patients with acutely decompensated hepatitis B cirrhosis.