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Limited previous studies focused on the death and progression risk stratification of colorectal cancer (CRC) lung metastasis patients. The aim of this study is to construct a nomogram model combing machine learning-pathomics, radiomics features, Immunoscore and clinical factors to predict the postoperative outcome of CRC patients with lung metastasis. In this study, a total of 103 CRC patients having metastases limited to lung and undergoing radical lung resection were identified. Patch-level convolutional neural network training in weakly supervised manner was used to perform whole slides histopathological images survival analysis. Synthetic minority oversampling technique and support vector machine classifier were used to identify radiomics features and build predictive signature. The Immunoscore for each patient was calculated from the density of CD3+ and CD8+ cells at the invasive margin and the center of metastatic tumor which were assessed on consecutive sections of automated digital pathology. Finally, pathomics and radiomics signatures were successfully developed to predict the overall survival (OS) and disease free survival (DFS) of patients. The predicted pathomics and radiomics scores are negatively correlated with Immunoscore and they are three independent prognostic factors for OS and DFS prediction. The combined nomogram showed outstanding performance in predicting OS (AUC = 0.860) and DFS (AUC = 0.875). The calibration curve and decision curve analysis demonstrated the considerable clinical usefulness of the combined nomogram. Taken together, the developed nomogram model consisting of machine learning-pathomics signature, radiomics signature, Immunoscore and clinical features could be reliable in predicting postoperative OS and DFS of colorectal lung metastasis patients.

Polycaprolactone (PCL) has attracted great attention for bone regeneration attributed to its cost-efficiency, high toughness, and good processability. However, the relatively low elastic modulus, hydrophobic nature, and insufficient bioactivity of pure PCL limited its wider application for bone regeneration. In the present study, the effects of the addition of boron containing bioactive glass (B-BG) materials on the mechanical properties and biological performance of PCL polymer were investigated with different B-BG contents (0, 10, 20, 30, and 40 wt.%), in order to evaluate the potential applications of B-BG/PCL composites for bone regeneration. The results showed that the B-BG/PCL composites possess better tensile strength, human neutral pH value, and fast degradation as compared to pure PCL polymers. Moreover, the incorporation of B-BG could enhance proliferation, osteogenic differentiation, and angiogenic factor expression for rat bone marrow stromal cells (rBMSCs) as compared to pure PCL polymers. Importantly, the B-BG also promoted the angiogenic differentiation for human umbilical vein endothelial cells (HUVECs). These enhanced effects had a concentration dependence of B-BG content, while 30 wt.% B-BG/PCL composites achieved the greatest stimulatory effect. Therefore the 30 wt.% B-BG/PCL composites have potential applications in bone reconstruction fields.

Background Zinc finger protein 143(ZNF143), a member of the Krüppel C2H2-type zinc finger protein family, is strongly associated with cell cycle regulation and cancer development. A recent study suggested that ZNF143 plays as a transcriptional activator that promotes hepatocellular cancer (HCC) cell proliferation and cell cycle transition. However, the exact biological role of ZNF143 in liver regeneration and normal liver cell proliferation has not yet been investigated. Methods In our study, we constructed a stable rat liver cell line (BRL-3A) overexpressing ZNF143 and then integrated RNA-seq and Cleavage Under Targets and Tagmentation (CUT&Tag) data to identify the mechanism underlying differential gene expression. Results Our results show that ZNF143 expression is upregulated during the proliferation phase of liver regeneration after 2/3 partial hepatectomy (PH). The cell counting kit-8 (CCK-8) assay, EdU staining and RNA-seq data analyses revealed that ZNF143 overexpression (OE) significantly inhibited BRL-3A cell proliferation and cell cycle progression. We then performed CUT&Tag assays and found that approximately 10% of ZNF143-binding sites (BSs) were significantly changed genome-wide by ZNF143 OE. However, CCCTC-binding factor (CTCF) binding to chromatin was not affected. Interestingly, the integration analysis of RNA-seq and CUT&Tag data showed that some of genes affected by ZNF143 differential BSs are in the center of each gene regulation module. Gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses indicated that these genes are critical in the maintenance of cell identity. Conclusion These results indicated that the expression level of ZNF143 in the liver is important for the maintenance of cell identity. ZNF143 plays different roles in HCC and normal liver cells and may be considered as a potential therapeutic target in liver disease.

Accurate segmentation of lung nodules from pulmonary computed tomography (CT) slices plays a vital role in the analysis and diagnosis of lung cancer. Convolutional Neural Networks (CNNs) have achieved state-of-the-art performance in the automatic segmentation of lung nodules. However, they are still challenged by the large diversity of segmentation targets, and the small inter-class variances between the nodule and its surrounding tissues. To tackle this issue, we propose a features complementary network according to the process of clinical diagnosis, which made full use of the complementarity and facilitation among lung nodule location information, global coarse area, and edge information. Specifically, we first consider the importance of global features of nodules in segmentation and propose a cross-scale weighted high-level feature decoder module. Then, we develop a low-level feature decoder module for edge feature refinement. Finally, we construct a complementary module to make information complement and promote each other. Furthermore, we weight pixels located at the nodule edge on the loss function and add an edge supervision to the deep supervision, both of which emphasize the importance of edges in segmentation. The experimental results demonstrate that our model achieves robust pulmonary nodule segmentation and more accurate edge segmentation.

It has been reported that kidney retransplant patients had high rates of early acute rejection due to previous sensitization. In addition to the acute antibody-mediated rejection (ABMR) that has received widespread attention, the early acute T-cell-mediated rejection (TCMR) may be another important issue in renal retransplantation. In the current single-center retrospective study, we included 33 retransplant patients and 90 first transplant patients with similar protocols of induction and maintenance therapy. Analysis focused particularly on the incidence and patterns of early acute rejection episodes, as well as one-year graft and patient survival. Excellent short-term clinical outcomes were obtained in both groups, with one-year graft and patient survival rates of 93.9%/100% in the retransplant group and 92.2%/95.6% in the first transplant group. Impressively, with our strict immunological selection and desensitization criteria, the retransplant patients had a very low incidence of early acute ABMR (6.1%), which was similar to that in the first transplant patients (4.4%). However, a much higher rate of early acute TCMR was observed in the retransplant group than in the first transplant group (30.3% versus 5.6%, P<0.001). Acute TCMR that develops early after retransplantation should be monitored in order to obtain better transplant outcomes.

Metastasis is an important factor that causes ovarian cancer (OC) to become the most lethal malignancy of the female reproductive system, but its molecular mechanism is not fully understood. In this study, through bioinformatics analysis, as well as analysis of tissue samples and clinicopathological characteristics and prognosis of patients in our centre, it was found that Forkhead box Q1 (FOXQ1) was correlated with metastasis and prognosis of OC. Through cell function experiments and animal experiments, the results show that FOXQ1 can promote the progression of ovarian cancer in vivo and in vitro. Through RNA-seq, chromatin immunoprecipitation sequencing (ChIP-seq), Kyoto Encyclopedia of Genes and Genomes (KEGG), gene set enrichment analysis (GSEA), Western blotting (WB), quantitative real-time polymerase chain reaction (qRT‒PCR), immunohistochemistry (IHC), luciferase assay, and ChIP-PCR, it was demonstrated that FOXQ1 can mediate the WNT/β-catenin pathway by targeting the LAMB promoter region. Through coimmunoprecipitation (Co-IP), mass spectrometry (MS), ubiquitination experiments, and immunofluorescence (IF), the results showed that PARP1 could stabilise FOXQ1 expression via the E3 ubiquitin ligase Hsc70-interacting protein (CHIP). Finally, the whole mechanism pathway was verified by animal drug combination experiments and clinical specimen prognosis analysis. In summary, our results suggest that PARP1 can promote ovarian cancer progression through the LAMB3/WNT/β-catenin pathway by stabilising FOXQ1 expression.

Purpose The route of lymphatic spread in esophageal cancer remains unclear. The present study aimed to determine the pattern of lymphatic metastasis in its early stages. Methods The data were reviewed of 1074 patients who underwent curative esophagectomy for thoracic esophageal squamous cell carcinoma and metastasis in 1–2 lymph nodes between January 2015 and December 2021. The frequencies of lymph node metastasis were analyzed by the anatomic sites and regions involved. Results Of the 1074 patients, 668 patients (62.2%) with one positive lymph node and 406 (37.8%) with two positive lymph nodes. Paracardial lymph nodes were the most frequently involved nodes (35.1%), followed by right thoracic recurrent nerve nodes (24.0%), middle thoracic paraesophageal nodes (14.7%), left thoracic recurrent nerve nodes (10.4%), subcarinal nodes (8.0%), lower thoracic paraesophageal nodes (7.8%), and upper thoracic paraesophageal nodes (5.7%). The frequency of lymph node metastasis in other sites was less than 3%. The majority of lymph node metastases occurred in the longitudinal direction to the perigastric (36.5%) and bilateral recurrent nerve regions (33.4%) and in the transverse direction to the paraesophageal region (27.7%). As the tumor location changed from the upper to the lower thoracic esophagus, the frequencies of lymph node metastasis decreased in the bilateral recurrent nerve region but increased in the perigastric region. Conclusion Bilateral recurrent nerve nodes, paraesophageal lymph nodes, and perigastric nodes were the most common sites of early lymph node metastasis. Esophageal squamous cell carcinoma involves more longitudinal than transverse lymph node metastases.

Memory T cells are necessary for protective immunity against invading pathogens, especially under conditions of immunosuppression. However, their presence also threatens transplant survival, making transplantation a great challenge. Significant progress has been achieved in recent years in advancing our understanding of the role that memory T cells play in transplantation. This review focuses on the latest advances in our understanding of the involvement of memory T cells in graft rejection and transplant tolerance and discusses potential strategies for targeting memory T cells in order to minimize allograft rejection and optimize clinical outcomes.

A new coronavirus, known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is the aetiological agent responsible for the 2019–2020 viral pneumonia outbreak of coronavirus disease 2019 (COVID-19) 1 – 4 . Currently, there are no targeted therapeutic agents for the treatment of this disease, and effective treatment options remain very limited. Here we describe the results of a programme that aimed to rapidly discover lead compounds for clinical use, by combining structure-assisted drug design, virtual drug screening and high-throughput screening. This programme focused on identifying drug leads that target main protease (M pro ) of SARS-CoV-2: M pro is a key enzyme of coronaviruses and has a pivotal role in mediating viral replication and transcription, making it an attractive drug target for SARS-CoV-2 5 , 6 . We identified a mechanism-based inhibitor (N3) by computer-aided drug design, and then determined the crystal structure of M pro of SARS-CoV-2 in complex with this compound. Through a combination of structure-based virtual and high-throughput screening, we assayed more than 10,000 compounds—including approved drugs, drug candidates in clinical trials and other pharmacologically active compounds—as inhibitors of M pro . Six of these compounds inhibited M pro , showing half-maximal inhibitory concentration values that ranged from 0.67 to 21.4 μM. One of these compounds (ebselen) also exhibited promising antiviral activity in cell-based assays. Our results demonstrate the efficacy of our screening strategy, which can lead to the rapid discovery of drug leads with clinical potential in response to new infectious diseases for which no specific drugs or vaccines are available. A programme of structure-assisted drug design and high-throughput screening identifies six compounds that inhibit the main protease of SARS-CoV-2, demonstrating the ability of this strategy to isolate drug leads with clinical potential.

A new coronavirus (SARS-CoV-2) has been identified as the etiologic agent for the COVID-19 outbreak. Currently, effective treatment options remain very limited for this disease; therefore, there is an urgent need to identify new anti-COVID-19 agents. In this study, we screened over 6,000 compounds that included approved drugs, drug candidates in clinical trials, and pharmacologically active compounds to identify leads that target the SARSCoV-2 papain-like protease (PLpro). Together with main protease (Mpro), PLpro is responsible for processing the viral replicase polyprotein into functional units. Therefore, it is an attractive target for antiviral drug development. Here we discovered four compounds, YM155, cryptotanshinone, tanshinone I and GRL0617 that inhibit SARS-CoV-2 PLpro with IC50 values ranging from 1.39 to 5.63 μmol/L. These compounds also exhibit strong antiviral activities in cell-based assays. YM155, an anticancer drug candidate in clinical trials, has the most potent antiviral activity with an EC50 value of 170 nmol/L. In addition, we have determined the crystal structures of this enzyme and its complex with YM155, revealing a unique binding mode. YM155 simultaneously targets three \"hot\" spots on PLpro, including the substratebinding pocket, the interferon stimulating gene product 15 (ISG15) binding site and zinc finger motif. Our results demonstrate the efficacy of this screening and repurposing strategy, which has led to the discovery of new drug leads with clinical potential for COVID-19 treatments.