Compare deep learning model and conventional logistic regression model for the identification of unstable saccular intracranial aneurysms in computed tomography angiography.

Background: It is crucial to distinguish unstable from stable intracranial aneurysms (IAs) as early as possible to derive optimal clinical decision-making for further treatment or follow-up. The aim of this study was to investigate the value of a deep learning model (DLM) in identifying unstable IAs from computed tomography angiography (CTA) images and to compare its discriminatory ability with that of a conventional logistic regression model (LRM). Methods: From August 2011 to May 2021, a total of 1,049 patients with 681 unstable IAs and 556 stable IAs were retrospectively analyzed. IAs were randomly divided into training (64%), internal validation (16%), and test sets (20%). Convolutional neural network (CNN) analysis and conventional logistic regression (LR) were used to predict which IAs were unstable. The area under the curve (AUC), sensitivity, specificity and accuracy were calculated to evaluate the discriminating ability of the models. One hundred and ninety-seven patients with 229 IAs from Banan Hospital were used for external validation sets. Results: The conventional LRM showed 11 unstable risk factors, including clinical and IA characteristics. The LRM had an AUC of 0.963 [95% confidence interval (CI): 0.941-0.986], a sensitivity, specificity and accuracy on the external validation set of 0.922, 0.906, and 0.913, respectively, in predicting unstable IAs. In predicting unstable IAs, the DLM had an AUC of 0.771 (95% CI: 0.582-0.960), a sensitivity, specificity and accuracy on the external validation set of 0.694, 0.929, and 0.782, respectively. Conclusions: The CNN-based DLM applied to CTA images did not outperform the conventional LRM in predicting unstable IAs. The patient clinical and IA morphological parameters remain critical factors for ensuring IA stability. Further studies are needed to enhance the diagnostic accuracy.

Edge-relational window-attentional graph neural network for gene expression prediction in spatial transcriptomics analysis.

Spatial transcriptomics (ST), containing gene expression with fine-grained (i.e., different windows) spatial location within tissue samples, has become vital in developing innovative treatments. Traditional ST technology, however, rely on costly specialized commercial equipment. Addressing this, our article aims to creates a cost-effective, virtual ST approach using standard tissue images for gene expression prediction, eliminating the need for expensive equipment. Conventional approaches in this field often overlook the long-distance spatial dependencies between different sample windows or need prior gene expression data. To overcome these limitations, we propose the Edge-Relational Window-Attentional Network (ErwaNet), enhancing gene prediction by capturing both local interactions and global structural information from tissue images, without prior gene expression data. ErwaNet innovatively constructs heterogeneous graphs to model local window interactions and incorporates an attention mechanism for global information analysis. This dual framework not only provides a cost-effective solution for gene expression predictions but also obviates the necessity of prior knowledge gene expression information, a significant advantage in the field of cancer research where it enables a more efficient and accessible analytical paradigm. ErwaNet stands out as a prior-free and easy-to-implement Graph Convolution Network (GCN) method for predicting gene expression from tissue images. Evaluation of the two public breast cancer datasets shows that ErwaNet, without additional information, outperforms the state-of-the-art (SOTA) methods. Code is available at https://github.com/biyecc/ErwaNet.

N-glycan biosignatures as a potential diagnostic biomarker for early-stage pancreatic cancer.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis, with a 5-year survival rate of less than 10%, owing to its late-stage diagnosis. Early detection of pancreatic cancer (PC) can significantly increase survival rates. AIM: To identify the serum biomarker signatures associated with early-stage PDAC by serum N-glycan analysis. METHODS: An extensive patient cohort was used to determine a biomarker signature, including patients with PDAC that was well-defined at an early stage (stages I and II). The biomarker signature was derived from a case-control study using a case-cohort design consisting of 29 patients with stage I, 22 with stage II, 4 with stage III, 16 with stage IV PDAC, and 88 controls. We used multiparametric analysis to identify early-stage PDAC N-glycan signatures and developed an N-glycan signature-based diagnosis model called the "Glyco-model". RESULTS: The biomarker signature was created to discriminate samples derived from patients with PC from those of controls, with a receiver operating characteristic area under the curve of 0.86. In addition, the biomarker signature combined with cancer antigen 19-9 could discriminate patients with PDAC from controls, with a receiver operating characteristic area under the curve of 0.919. Glyco-model demonstrated favorable diagnostic performance in all stages of PC. The diagnostic sensitivity for stage I PDAC was 89.66%. CONCLUSION: In a prospective validation study, this serum biomarker signature may offer a viable method for detecting early-stage PDAC.

Prevalence and risk factors of fatigue and its association with quality of life among patients with chronic pancreatitis: A cross-sectional study.

BACKGROUND: Fatigue is a debilitating symptom found in various chronic diseases and is associated with more severe symptoms and worse quality of life (QoL). However, this symptom has not been adequately addressed in chronic pancreatitis (CP), and there have been no studies on fatigue in patients with CP. METHODS: This cross-sectional study was conducted at the Changhai Hospital in Shanghai, China. Data on the patients' sociodemographic, disease, and therapeutic characteristics were collected. Fatigue was assessed using the Multidimensional Fatigue Inventory-20. QoL was assessed utilizing the European Organization for the Research and Treatment of Cancer of QoL questionnaire (EORTC-QLQ-C30). Sleep quality, anxiety and depression, and pain was assessed using Pittsburgh Sleep Quality Index, the Hospital Anxiety and Depression Scale, and the Brief Pain Inventory, respectively. RESULTS: The prevalence of fatigue among Chinese patients with CP was 35.51 % (87/245). Multivariate analysis showed that steatorrhea (OR = 2.638, 95 % CI: 1.117-6.234), history of smoking (OR = 4.627, 95 % CI: 1.202-17.802), history of endoscopic treatment (OR = 0.419, 95 % CI: 0.185-0.950), depression (OR = 5.924, 95 % CI: 2.462-14.255), and sleep disorder (OR = 6.184, 95 % CI: 2.543-15.034) were influencing factors for the presence of fatigue. The scores for global health and all functional dimensions in the EORTC-QLQ-C30 significantly decreased, whereas the scores for all symptom dimensions significantly increased in patients with fatigue. CONCLUSIONS: This study indicated that Fatigue is a common symptom and has a negative impact on the QoL of patients with CP. Steatorrhea, smoking history, endoscopic treatment, depression, and sleep disorders were associated with fatigue.

Peri-lesion regions in differentiating suspicious breast calcification-only lesions specifically on contrast enhanced mammography.

PURPOSE: The explore the added value of peri-calcification regions on contrast-enhanced mammography (CEM) in the differential diagnosis of breast lesions presenting as only calcification on routine mammogram. METHODS: Patients who underwent CEM because of suspicious calcification-only lesions were included. The test set included patients between March 2017 and March 2019, while the validation set was collected between April 2019 and October 2019. The calcifications were automatically detected and grouped by a machine learning-based computer-aided system. In addition to extracting radiomic features on both low-energy (LE) and recombined (RC) images from the calcification areas, the peri-calcification regions, which is generated by extending the annotation margin radially with gradients from 1 mm to 9 mm, were attempted. Machine learning (ML) models were built to classify calcifications into malignant and benign groups. The diagnostic matrices were also evaluated by combing ML models with subjective reading. RESULTS: Models for LE (significant features: wavelet-LLL_glcm_Imc2_MLO; wavelet-HLL_firstorder_Entropy_MLO; wavelet-LHH_glcm_DifferenceVariance_CC; wavelet-HLL_glcm_SumEntropy_MLO;wavelet-HLH_glrlm_ShortRunLowGray LevelEmphasis_MLO; original_firstorder_Entropy_MLO; original_shape_Elongation_MLO) and RC (significant features: wavelet-HLH_glszm_GrayLevelNonUniformityNormalized_MLO; wavelet-LLH_firstorder_10Percentile_CC; original_firstorder_Maximum_MLO; wavelet-HHH_glcm_Autocorrelation_MLO; original_shape_Elongation_MLO; wavelet-LHL_glszm_GrayLevelNonUniformityNormalized_MLO; wavelet-LLH_firstorder_RootMeanSquared_MLO) images were set up with 7 features. Areas under the curve (AUCs) of RC models are significantly better than those of LE models with compact and expanded boundary (RC v.s. LE, compact: 0.81 v.s. 0.73, p <  0.05; expanded: 0.89 v.s. 0.81, p <  0.05) and RC models with 3 mm boundary extension yielded the best performance compared to those with other sizes (AUC = 0.89). Combining with radiologists' reading, the 3mm-boundary RC model achieved a sensitivity of 0.871 and negative predictive value of 0.937 with similar accuracy of 0.843 in predicting malignancy. CONCLUSIONS: The machine learning model integrating intra- and peri-calcification regions on CEM has the potential to aid radiologists' performance in predicting malignancy of suspicious breast calcifications.

Lipid-hybrid cell-derived biomimetic functional materials: A state-of-the-art multifunctional weapon against tumors.

Tumors are among the leading causes of death worldwide. Cell-derived biomimetic functional materials have shown great promise in the treatment of tumors. These materials are derived from cell membranes, extracellular vesicles and bacterial outer membrane vesicles and may evade immune recognition, improve drug targeting and activate antitumor immunity. However, their use is limited owing to their low drug-loading capacity and complex preparation methods. Liposomes are artificial bionic membranes that have high drug-loading capacity and can be prepared and modified easily. Although they can overcome the disadvantages of cell-derived biomimetic functional materials, they lack natural active targeting ability. Lipids can be hybridized with cell membranes, extracellular vesicles or bacterial outer membrane vesicles to form lipid-hybrid cell-derived biomimetic functional materials. These materials negate the disadvantages of both liposomes and cell-derived components and represent a promising delivery platform in the treatment of tumors. This review focuses on the design strategies, applications and mechanisms of action of lipid-hybrid cell-derived biomimetic functional materials and summarizes the prospects of their further development and the challenges associated with it.

Peficitinib ameliorates 5-fluorouracil-induced intestinal damage by inhibiting aging, inflammatory factors and oxidative stress.

5-Fluorouracil (5-FU) is a conventional and effective drug for colorectal cancer patients, and it is an important part of combined chemotherapy and adjuvant chemotherapy. Chemotherapy intestinal mucositis (CIM) is a severe side effect caused by 5-FU that, induces cancer treatment failure and affects patients' quality of life. The mechanism of 5-FU-induced CIM is related to normal cell senescence induced by 5-FU. Peficitinib, a Janus Kinase (JAK) inhibitor, treats inflammatory disorders, including rheumatoid arthritis, psoriasis, and inflammatory bowel disease. However, the therapeutic role and underlying mechanism of peficitinib in CIM remain unclear. The main objective of our research was to investigate the effects of peficitinib on 5-FU-induced senescence and intestinal damage in human umbilical vein endothelial (HUVEC) cells, human intestinal epithelial (HIEC) cells and BABL/C mice. The results showed that 5-FU caused intestinal damage by inducing aging and increasing inflammation and oxidative stress. Peficitinib alleviated aging by reducing senescence-beta-galactosidase (SA-ß-gal) activity and the protein levels of aging indicators (p53, p21, p16). Moreover, peficitinib reversed the changes in senescence-associated secretory phenotype (SASP) expression caused by 5-FU. Besides, 5-FU induced release of inflammatory factors and oxidative stress indicators was reversed by peficitinib. Additionally, the combination of peficitinib and 5-FU reinforced the anticancer curative intent of 5-FU in two colorectal cancer cell lines (HCT116 cells and SW620 cells). In conclusion, peficitinib alleviates mucositis by alleviating aging, reducing inflammatory accumulation and oxidative stress and enhancing the antitumor activity of 5-FU.

Exogenous gibberellic acid shortening after-ripening process and promoting seed germination in a medicinal plant Panax notoginseng.

BACKGROUND: Panax notoginseng (Burk) F.H. Chen is an essential plant in the family of Araliaceae. Its seeds are classified as a type of morphophysiological dormancy (MPD), and are characterized by recalcitrance during the after-ripening process. However, it is not clear about the molecular mechanism on the after-ripening in recalcitrant seeds. RESULTS: In this study, exogenous supply of gibberellic acid (GA3) with different concentrations shortened after-ripening process and promoted the germination of P. notoginseng seeds. Among the identified plant hormone metabolites, exogenous GA3 results in an increased level of endogenous hormone GA3 through permeation. A total of 2971 and 9827 differentially expressed genes (DEGs) were identified in response to 50 mg L-1 GA3 (LG) and 500 mg L-1 GA3 (HG) treatment, respectively, and the plant hormone signal and related metabolic pathways regulated by GA3 was significantly enriched. Weighted gene co-expression network analysis (WGCNA) revealed that GA3 treatment enhances GA biosynthesis and accumulation, while inhibiting the gene expression related to ABA signal transduction. This effect was associated with higher expression of crucial seed embryo development and cell wall loosening genes, Leafy Contyledon1 (LEC1), Late Embryogenesis Abundant (LEA), expansins (EXP) and Pectinesterase (PME). CONCLUSIONS: Exogenous GA3 application promotes germination and shorts the after-ripening process of P. notoginseng seeds by increasing GA3 contents through permeation. Furthermore, the altered ratio of GA and ABA contributes to the development of the embryo, breaks the mechanical constraints of the seed coat and promotes the protrusion of the radicle in recalcitrant P. notoginseng seeds. These findings improve our knowledge of the contribution of GA to regulating the dormancy of MPD seeds during the after-ripening process, and provide new theoretical guidance for the application of recalcitrant seeds in agricultural production and storage.

Changes in the disease burden of breast cancer along with attributable risk factors in China from 1990 to 2019 and its projections: An analysis of the global burden of disease study 2019.

BACKGROUND: To investigate the secular trends in breast cancer burden with attributable risk factors, and make projections over time, which would contribute to the control and prevention of breast cancer. METHODS: We extracted detailed data on breast cancer incident cases and age-standardized incidence rate (ASIR), deaths and age-standardized mortality rate (ASMR), disability-adjusted life-years (DALYs), and age-standardized DALYs rate (ASDR), as well as the attributable risk factors in China from the Global Burden of Diseases Study 2019. The estimated annual percentage change (EAPC) was calculated to quantify the changing trends. The national DALYs attributable to Socio-demographic Index (SDI) values were also presented. Projections to 2030 were estimated using the Bayesian age-period-cohort model. RESULTS: From 1990 to 2019, the number of breast cancer incident cases increased fourfold to 375,484, with deaths and DALYs over doubling to 96.306 and 2,957,454, respectively. The ASIR (EAPC = 2.84; 95% CI, 2.74-2.95) and ASMR (EAPC = 0.06; 95% CI, 0.00-0.12) increased, while the ASDR decreased with the EAPC of -0.13 (95% CI, -0.19 to -0.06) at the same period. The ASDR varied across provincial regions, which appeared to be in a wave-like upcurve with SDI values increasing. High body mass index became the first contribution to breast cancer DALYs for females in 2019, and alcohol use for males. Breast Cancer incident cases and deaths would increase to 587.7 and 125.6 thousand in 2030, of which there will be 577.1 and 122.7 thousand for females, and 10.6 and 2.9 thousand for males, respectively. CONCLUSION: Breast cancer remains a major public health problem in China. The absolute burden has been increasing over time, and varied across sex and regions. To control the potential risk factors and develop specific strategies will help to reduce the disease burden.

Dexmedetomidine provides type-specific tumour suppression without tumour-enhancing effects in syngeneic murine models.

BACKGROUND: Dexmedetomidine is a widely used anaesthetic adjuvant for cancer resection surgeries. However, recent reports suggest that it may promote tumour growth or metastasis, so it is essential to clarify its tumour-related effects. METHODS: Seven syngeneic murine tumour models were used to assess the impact of dexmedetomidine on primary tumour growth, spontaneous tumour metastasis, and surgical resection-associated metastasis. Cancer cell proliferation and apoptosis experiments, terminal deoxynucleotidyl transferase dUTP nick-end labelling assays, immune cell analysis, specific T-cell depletion experiments, and gene transcription analysis were conducted to identify the underlying mechanisms. RESULTS: Dexmedetomidine did not affect growth of EO771 or 4T1 breast tumours, LAP0297 or LLC lung tumours, MCA205 fibrosarcoma, or their spontaneous lung metastases. It did not promote lung metastasis after breast cancer resection. Dexmedetomidine significantly suppressed MCA38 and CT26 colorectal tumour growth (P<0.01) and promoted apoptosis in MCA38 tumour tissues (P<0.05) without affecting proliferation and apoptosis of MCA38 tumour cells in vitro, suggesting indirect anti-tumour effects. Dexmedetomidine increased the proportions of intratumour CD4+ T (P<0.01), CD8+ T (P<0.001), and natural killer cells (P<0.01), and it upregulated transcription of the cytotoxicity-related genes Infg, Tnfa, and Cxcl9 (P<0.05) in MCA38 tumours. Either CD8+ or CD4+ T-cell depletion reversed the anti-tumour effects of dexmedetomidine on MCA38 tumours (P<0.05). CONCLUSIONS: Dexmedetomidine conferred colorectal tumour-type specific suppression by modulation of tumour CD4+ and CD8+ T cells without tumour-enhancing effects.

Primary treatment and recent survival trends in patients with primary diffuse large B-cell lymphoma of central nervous system, 1995-2016: A population-based SEER analysis.

This retrospective cohort study aimed to evaluate primary treatment and recent survival trends in patients with primary diffuse large B-cell lymphoma of central nervous system (CNS) from 1995 to 2016. Using the SEER data, patients diagnosed with non-HIV-associated primary central nervous system lymphoma (PCNSL)-diffuse large B-cell lymphoma (DLBCL) aged ⩾18 years between 1995 and 2016 were identified. The year of diagnosis was divided into the time period-1 (1995-2002), the time period-2 (2003-2012), and the time period-3 (2013-2016). Chi-square tests, the Kaplan-Meier method, log-rank test, and Cox regression model were used in the analysis. Overall, 3760 patients were included. Both the use of radiotherapy alone and the application of combined chemoradiotherapy decreased significantly, following the wider use of chemotherapy alone during 1995-2016. There was a significant improvement in PCNSL cause-specific survival (CSS) (period-1: 13 months vs. period-2: 19 months vs. period-3: 41 months, p < 0.001). Survival of patients aged above 70 years did not change from the time period-1 to the time period-2 (p = 0.101). However, there was an increase in CSS from the time period-2 to the time period-3 in the elderly patients (period-2: 5 months vs. period-3: 9 months, p < 0.001). On multivariable analyses, diagnosed in the time period-3 was significantly and independently associated with better CSS (hazard ratio 0.577, 95% confidence interval 0.506-0.659, p < 0.001). Our analysis shows the use of radiotherapy in the treatment of PCNSL has waned over the study span. There was a significant improvement in CSS during 1995-2016, which reflected developments in treatment over time. The elderly patient population also gained a significant CSS benefit in the most recent period.

Radiomics for differentiating tumor deposits from lymph node metastasis in rectal cancer.

BACKGROUND: Tumor deposits (TDs) are not equivalent to lymph node (LN) metastasis (LNM) but have become independent adverse prognostic factors in patients with rectal cancer (RC). Although preoperatively differentiating TDs and LNMs is helpful in designing individualized treatment strategies and achieving improved prognoses, it is a challenging task. AIM: To establish a computed tomography (CT)-based radiomics model for preoperatively differentiating TDs from LNM in patients with RC. METHODS: This study retrospectively enrolled 219 patients with RC [TDs+LNM- (n = 89); LNM+ TDs- (n = 115); TDs+LNM+ (n = 15)] from a single center between September 2016 and September 2021. Single-positive patients (i.e., TDs+LNM- and LNM+TDs-) were classified into the training (n = 163) and validation (n = 41) sets. We extracted numerous features from the enhanced CT (region 1: The main tumor; region 2: The largest peritumoral nodule). After deleting redundant features, three feature selection methods and three machine learning methods were used to select the best-performing classifier as the radiomics model (Rad-score). After validating Rad-score, its performance was further evaluated in the field of diagnosing double-positive patients (i.e., TDs+LNM+) by outlining all peritumoral nodules with diameter (short-axis) > 3 mm. RESULTS: Rad-score 1 (radiomics signature of the main tumor) had an area under the curve (AUC) of 0.768 on the training dataset and 0.700 on the validation dataset. Rad-score 2 (radiomics signature of the largest peritumoral nodule) had a higher AUC (training set: 0.940; validation set: 0.918) than Rad-score 1. Clinical factors, including age, gender, location of RC, tumor markers, and radiological features of the largest peritumoral nodule, were excluded by logistic regression. Thus, the combined model was comprised of Rad-scores of 1 and 2. Considering that the combined model had similar AUCs with Rad-score 2 (P = 0.134 in the training set and 0.594 in the validation set), Rad-score 2 was used as the final model. For the diagnosis of double-positive patients in the mixed group [TDs+LNM+ (n = 15); single-positive (n = 15)], Rad-score 2 demonstrated moderate performance (sensitivity, 73.3%; specificity, 66.6%; and accuracy, 70.0%). CONCLUSION: Radiomics analysis based on the largest peritumoral nodule can be helpful in preoperatively differentiating between TDs and LNM.

Use of Composite Acellular Dermal Matrix-Ultrathin Split-Thickness Skin in Hand Hot-Crush Injuries: A One-Step Grafting Procedure.

Background: Hot-crush injuries to the hands can be devastating, and early debridement and coverage with skin autograft remains the golden standard of wound treatment. However, this type of treatment is not feasible or unlikely to succeed due to limited donor sites and wound characteristics of hot-crush injuries on hands. Thus, the composite grafting of acellular dermal matrix (ADM) and split-thickness skin graft (STSG) as a novel alternative method has been attempted. In this series, the results are presented to demonstrate the feasibility and effectiveness of the use of one-stage procedure for early reconstruction in hand hot-crush injuries. Methods: All consecutive patients with hand hot-crush injuries, who underwent one-stage procedure of ADM and ultrathin STSG for soft tissue coverage at our institution from December 2018 to November 2019, were retrospectively analyzed. Wound dressings were opened on 7 days after operation to examine graft survival and complications. Patients were followed up for at least 9 months to evaluate their hand profiles. Results: Samples of 14 patients with a total of 23 wounds were involved in the study. Thirteen of the 23 third-fourth-degree wounds had varying degrees of tendon exposure. On 7 days postoperation, the composite grafts survived in 12 patients with minimal focal graft losses and liquefaction and necrosis in 2 patients, which achieved successful healing following new coverage of ultrathin STSG. All the wounds healed with hospital stays ranging from 9 days to 32 days (median: 24.5 days). At the final follow-up (from 9 months to 20 months), all patients achieved excellent or good total active motion grade and good scar quality (Vancouver scar scale scored 1-3) with no revision surgery. Conclusions: One-stage composite grafting of ADM and ultrathin STSG is a reliable alternative for early reconstruction in hand hot-crush injuries, which delivers good functional outcomes and a good cosmetic appearance.

Robust and durable response to first-line treatment of pembrolizumab combined with chemotherapy in two patients with metastatic thymic squamous cell carcinoma: Case report.

Thymic carcinoma is a rare and aggressive disease with poor outcome. There is no established treatment regimen for advanced thymic carcinoma. While the efficacy of pembrolizumab was proved to be promising, as a single agent, in patients with refractory/recurrent thymic carcinoma that progressed after chemotherapy, the efficacy and safety of combination of pembrolizumab and chemotherapy as front-line treatment in metastatic thymic carcinoma have not been explored yet. Herein, we report the first two cases of metastatic thymic squamous cell carcinoma receiving the combined approaches of pembrolizumab and chemotherapy as first-line treatment. Of the two patients, one had a complete radiological response of mediastinal masses with sustained remission over 3 years, and the other one with widespread disease had a good partial response over 20 months and achieved no evidence of disease radiologically after undergoing percutaneous radiofrequency ablation for residual liver metastases. Next-generation sequencing (NGS) showed low tumor mutation burden and MSS in both patients. Immunohistochemistry analysis of the tumor showed high PD-L1 expression in patient 1 and low PD-L1 expression in patient 2. Pembrolizumab combined with chemotherapy may be an attractive strategy for the first-line treatment of metastatic thymic carcinoma and thus warrants further evaluation.

Deep Learning Radiomics Nomogram to Predict Lung Metastasis in Soft-Tissue Sarcoma: A Multi-Center Study.

Objectives: To build and evaluate a deep learning radiomics nomogram (DLRN) for preoperative prediction of lung metastasis (LM) status in patients with soft tissue sarcoma (STS). Methods: In total, 242 patients with STS (training set, n=116; external validation set, n=126) who underwent magnetic resonance imaging were retrospectively enrolled in this study. We identified independent predictors for LM-status and evaluated their performance. The minimum redundancy maximum relevance (mRMR) method and least absolute shrinkage and selection operator (LASSO) algorithm were adopted to screen radiomics features. Logistic regression, decision tree, random forest, support vector machine (SVM), and adaptive boosting classifiers were compared for their ability to predict LM. To overcome the imbalanced distribution of the LM data, we retrained each machine-learning classifier using the synthetic minority over-sampling technique (SMOTE). A DLRN combining the independent clinical predictors with the best performing radiomics prediction signature (mRMR+LASSO+SVM+SMOTE) was established. Area under the receiver operating characteristics curve (AUC), calibration curves, and decision curve analysis (DCA) were used to assess the performance and clinical applicability of the models. Result: Comparisons of the AUC values applied to the external validation set revealed that the DLRN model (AUC=0.833) showed better prediction performance than the clinical model (AUC=0.664) and radiomics model (AUC=0.799). The calibration curves indicated good calibration efficiency and the DCA showed the DLRN model to have greater clinical applicability than the other two models. Conclusion: The DLRN was shown to be an accurate and efficient tool for LM-status prediction in STS.

MicroRNA214 expression inhibits HCC cell proliferation through PTK2b/ Pyk2.

MicroRNAs (miRNAs/miRs) are crucial regulatory molecules that act as the most significantly downregulated microRNAs in hepatocellular carcinoma (HCC). PTK2b/Pyk2 is a non-receptor protein tyrosine kinase, which plays an important role in the development and metastasis of cancer. In this study, we explored the expression level and functional relationship between MicroRNA-214 (miR-214) and PTK2b/ Pyk2 in liver cancer cells. For this purpose, we analyzed the expression of miR-214 and PTK2b/Pyk2 in 38 cases of HCC and paired non-neoplastic tissue specimens using real-time PCR. MTT, cell cycle and construct recombinant plasmids analysis were used to explore the effects of miR-214 and PTK2b/Pyk2 on liver cancer cell proliferation. Results showed that the expression level of mir-214 in liver cancer tissues and liver cancer cell lines was significantly lower than that in normal tissues and cells, while the expression of PTK2b/Pyk2 was significantly increased. The overexpression of mir-214 or inhibition PTK2b/Pyk2 inhibited the proliferation of HCC cells. This research showed that mir-214 has an inhibitory effect on liver cancer through the expression of PTK2b/Pyk2.

Overexpression of GNA13 correlates with poor prognosis in esophageal squamous cell carcinoma after esophagectomy.

BACKGROUND: This study aimed to explore the expression and clinical implication of guanine nucleotide-binding protein alpha 13 (GNA13) in esophageal squamous cell carcinoma (ESCC). METHODS: We first employed western blot analysis to test the GNA13 protein expression level in ESCC tissues. Subsequently, we used immunohistochemistry assays to detect the GNA13 in ESCC specimens from 173 patients who underwent esophagectomy. Survival analysis was performed to define the impact of GNA13 expressions on the prognosis of the ESCC patients based on the clinical and follow-up data. RESULTS: The GNA13 protein was shown to be considerably higher in ESCC tissues than in normal esophageal tissues. The level of expression was closely related to the tumor, node, TNM stage, and tumor size. More importantly, ESCC patients with high GNA13 expression carried an increased risk of tumor recurrence compared to those with low GNA13 expression. In addition, a high GNA13 expression level could independently predict worse overall survival and disease-free survival in ESCC. CONCLUSIONS: GNA13 could be a novel prognostic biomarker for ESCC patients after esophagectomy.