Novel non-invasive method for urine mapping: Deep-learning-enabled SERS spectroscopy for the rapid differential detection of kidney allograft injury.

The kidney allograft has been under continuous attack from diverse injuries since the very beginning of organ procurement, leading to a gradual decline in function, chronic fibrosis, and allograft loss. It is vital to routinely and precisely monitor the risk of injuries after renal transplantation, which is difficult to achieve because the traditional laboratory tests lack sensitivity and specificity, and graft biopsies are invasive with the risk of many complications and time-consuming. Herein, a novel method for the diagnosis of graft injury is demonstrated, using deep learning-assisted surface-enhanced Raman spectroscopy (SERS) of the urine analysis. Specifically, we developed a hybrid SERS substrate composed of gold and silver with high sensitivity to the urine composition under test, eliminating the need for labels, which makes measurements easy to perform and meanwhile results in extremely abundant and complex Raman vibrational bands. Deep learning algorithms were then developed to improve the interpretation of the SERS spectral fingerprints. The deep learning model was trained with SERS signals of urine samples of recipients with different injury types including delayed graft function (DGF), calcineurin-inhibitor toxicity (CNIT), T cell-mediated rejection (TCMR), antibody-mediated rejection (AMR), and BK virus nephropathy (BKVN), which explored the features of these types and achieved the injury differentiation with an overall accuracy of 93.03%. The results highlight the potential of combining label-free SERS spectroscopy with deep learning as a method for liquid biopsy of kidney allograft injuries, which can provide great potential to diagnose and evaluate allograft injuries, and thus extend the life of kidney allografts.

PARP1-stabilised FOXQ1 promotes ovarian cancer progression by activating the LAMB3/WNT/ß-catenin signalling pathway.

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/ß-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/ß-catenin pathway by stabilising FOXQ1 expression.

The function and immune role of cuproptosis associated hub gene in Barrett's esophagus and esophageal adenocarcinoma.

Barrett's esophagus (BE) is a precancerous lesion of esophageal adenocarcinoma (EAC), with approximately 3-5% of patients developing EAC. Cuproptosis is a kind of programmed cell death phenomenon discovered in recent years, which is related to the occurrence and development of many diseases. However, its role in BE and EAC is not fully understood. We used single sample Gene Set Enrichment Analysis (ssGSEA) for differential analysis of BE in the database, followed by enrichment analysis of Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO) and GSEA, Protein-Protein Interaction (PPI), Weighted Gene Co-expression Network Analysis (WGCNA), Receiver Operating Characteristic Curve (ROC) and finally Quantitative Real Time Polymerase Chain Reaction (qRT-PCR) and immunohistochemistry (IHC) of clinical tissues. Two hub genes can be obtained by intersection of the results obtained from the cuproptosis signal analysis based on BE. The ROC curves of these two genes predicted EAC, and the Area Under the Curve (AUC) values could reach 0.950 and 0.946, respectively. The mRNA and protein levels of Centrosome associated protein E (CENPE) and Shc SH2 domain binding protein 1 (SHCBP1) were significantly increased in clinical EAC tissues. When they were grouped by protein expression levels, high expression of CENPE or SHCBP1 had a poor prognosis. The CENPE and SHCBP1 associated with cuproptosis may be a factor promoting the development of BE into EAC which associated with the regulation of NK cells and T cells.

Precise pattern of lymphatic spread of esophageal squamous cell carcinoma: results of 1074 patients with N1 disease.

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.

Improved Complementary Pulmonary Nodule Segmentation Model Based on Multi-Feature Fusion.

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.

Targeted screening of genetic associations with COVID-19 susceptibility and severity.

The COVID-19 pandemic has resulted in great morbidity and mortality worldwide and human genetic factors have been implicated in the susceptibility and severity of COVID-19. However, few replicate researches have been performed, and studies on associated genes mainly focused on genic regions while regulatory regions were a lack of in-depth dissection. Here, based on previously reported associated variants and genes, we designed a capture panel covering 1,238 candidate variants and 25 regulatory regions of 19 candidate genes and targeted-sequenced 96 mild and 145 severe COVID-19 patients. Genetic association analysis was conducted between mild and severe COVID-19 patients, between all COVID-19 patients and general population, or between severe COVID-19 patients and general population. A total of 49 variants were confirmed to be associated with susceptibility or severity of COVID-19 (p < 0.05), corresponding to 18 independent loci. Specifically, rs1799964 in the promoter of inflammation-related gene TNF, rs9975538 in the intron of interferon receptor gene IFNAR2, rs429358 in the exon of APOE, rs1886814 in the intron of FOXP4-AS1 and a list of variants in the widely reported 3p21.31 and ABO gene were confirmed. It is worth noting that, for the confirmed variants, the phenotypes of the cases and controls were highly consistent between our study and previous reports, and the confirmed variants identified between mild and severe patients were quite different from those identified between patients and general population, suggesting the genetic basis of susceptibility and severity of SARS-CoV-2 infection might be quite different. Moreover, we newly identified 67 significant associated variants in the 12 regulatory regions of 11 candidate genes (p < 0.05). Further annotation by RegulomeDB database and GTEx eQTL data filtered out two variants (rs11246060 and rs28655829) in the enhancer of broad-spectrum antiviral gene IFITM3 that might affect disease severity by regulating the gene expression. Collectively, we confirmed a list of previously reported variants and identified novel regulatory variants associated with susceptibility and severity of COVID-19, which might provide biological and clinical insights into COVID-19 pathogenesis and treatment.

The role of ZNF143 overexpression in rat liver cell proliferation.

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.

Changes in Higher-Order Chromosomal Structure of Klebsiella pneumoniae Under Simulated Microgravity.

Our previous work have shown that certain subpopulations of Klebsiella pneumoniae exhibit significant phenotypic changes under simulated microgravity (SMG), including enhanced biofilm formation and cellulose synthesis, which may be evoked by changes in gene expression patterns. It is well known that prokaryotic cells genomic DNA can be hierarchically organized into different higher-order three-dimensional structures, which can highly influence gene expression. It is remain elusive whether phenotypic changes induced by SMG in the subpopulations of K. pneumoniae are driven by genome higher-order structural changes. Here, we investigated the above-mentioned issue using the wild-type (WT) K. pneumoniae (WT was used as a control strain and continuously cultivated for 2 weeks under standard culture conditions of normal gravity) and two previous identified subpopulations (M1 and M2) obtained after 2 weeks of continuous incubation in a SMG device. By the combination of genome-wide chromosome conformation capture (Hi-C), RNA-seq and whole-genome methylation (WGS) analyses, we found that the along with the global chromosome interactions change, the compacting extent of M1, M2 subpopulations were much looser under SMG and even with an increase in active, open chromosome regions. In addition, transcriptome data showed that most differentially expressed genes (DEGs) were upregulated, whereas a few DEGs were downregulated in M1 and M2. The functions of both types DEGs were mainly associated with membrane fractions. Additionally, WGS analysis revealed that methylation levels were lower in M1 and M2. Using combined analysis of multi-omics data, we discovered that most upregulated DEGs were significantly enriched in the boundary regions of the variable chromosomal interaction domains (CIDs), in which genes regulating biofilm formation were mainly located. These results suggest that K. pneumoniae may regulate gene expression patterns through DNA methylation and changes in genome structure, thus resulting in new phenotypes in response to altered gravity.

MetaLnc9-Antisense RNA Contributes to Lung Cancer Metastasis via Modulating RNA-RNA Duplex with MetaLnc9.

Lung cancer is a common life-threatening tumor with high malignancy and high invasiveness. Long non-coding RNAs (lncRNAs) are involved in almost every stage of tumor initiation and progression. Here, we identified an antisense lncRNA, MetaLnc9 antisense (Metalnc9-AS), which arises from the antisense strand of Metalnc9, located on chr9q34.11, while its biological function and mechanism are not clear in lung cancer. In this study, we demonstrated that the expression of Metalnc9-AS was upregulated in non-small cell lung cancer (NSCLC) tissues compared with corresponding non-tumorous tissues. The gain of MetaLnc9-AS was highly associated with the malignant features of NSCLC. Overexpression of MetaLnc9-AS enhanced tumor metastasis in vitro and in vivo. Mechanically, MetaLnc9-AS could form an RNA-RNA hybrid with its cognate sense counterpart, MetaLnc9, to regulate its expression in NSCLC cells, and that such complexes were protected from ribonuclease degradation. Thus, Metalnc9-AS might be a potential and effective treatment for NSCLC.

Development of a novel combined nomogram model integrating deep learning-pathomics, radiomics and immunoscore to predict postoperative outcome of colorectal cancer lung metastasis patients.

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.

Stimulatory Effects of Boron Containing Bioactive Glass on Osteogenesis and Angiogenesis of Polycaprolactone: In Vitro Study.

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.

Patterns of Early Rejection in Renal Retransplantation: A Single-Center Experience.

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.

Role of Memory T Cells and Perspectives for Intervention in Organ Transplantation.

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.