As an important research direction of knowledge reasoning, the research on knowledge mapping embedding and path information reasoning has made continuous progress. In recent years, many scholars have tried to combine the two algorithms, and the performance of the algorithm has been improved accordingly. However, most of these algorithms only slightly modify the way of calculating the weighted average of other models and path information in the design of scoring function, ignoring the different degrees of influence of different paths on reasoning results. To solve this problem, a new embedding method PTransX is proposed. In the original PTransE algorithm, the graph attention network is introduced to assign different weights to different path resources to distinguish the contribution of different paths to the inference result. In this way, while considering all the relevant paths, some of the critical paths can contribute more to the inference result because of their high reliability. Finally, the experimental results show that the performance of PTransX is improved compared with the original algorithm.
Abstract Background Hepatitis B virus (HBV) infection is one of the main leading causes of hepatocellular carcinoma (HCC) worldwide. However, it remains uncertain how the reverse-transcriptase (rt) gene contributes to HCC progression. Methods We enrolled a total of 307 patients with chronic hepatitis B (CHB) and 237 with HBV-related HCC from 13 medical centers. Sequence features comprised multidimensional attributes of rt nucleic acid and rt/s amino acid sequences. Machine-learning models were used to establish HCC predictive algorithms. Model performances were tested in the training and independent validation cohorts using receiver operating characteristic curves and calibration plots. Results A random forest (RF) model based on combined metrics (10 features) demonstrated the best predictive performances in both cross and independent validation (AUC, 0.96; accuracy, 0.90), irrespective of HBV genotypes and sequencing depth. Moreover, HCC risk scores for individuals obtained from the RF model (AUC, 0.966; 95% confidence interval, .922–.989) outperformed α-fetoprotein (0.713; .632–.784) in distinguishing between patients with HCC and those with CHB. Conclusions Our study provides evidence for the first time that HBV rt sequences contain vital HBV quasispecies features in predicting HCC. Integrating deep sequencing with feature extraction and machine-learning models benefits the longitudinal surveillance of CHB and HCC risk assessment.
Hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) are two main types of primary liver cancer, and reliable discrimination is important for optimal treatment. Aberrant glycosylation was detected in HCC and ICC. Both cross-sectional and follow-up studies were performed to establish a differential diagnosis model using N-glycans. A total of 420 participants were enrolled, with 310 patients in training cohort and 110 patients in validation cohort. The follow-up cohort was used to assess the prognosis of ICC. As the results, the diagnostic efficacy of the model was superior to alpha-fetoprotein (AFP), carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA 19-9) when identifying ICC from HCC (AUC of the nomogram: 0.845, 95%CI: 0.788-0.902; AFP: 0.793, 95%CI: 0.732-0.854; CEA: 0.592, 95%CI: 0.496-0.687; CA 19-9: 0.674, 95%CI: 0.582-0.767) in training cohort. In validation cohort, this model (AUC: 0.810, 95% CI: 0.728-0.891) also demonstrated high efficacy in distinguishing ICC from HCC. Furthermore, the nomogram helps to stratify ICC into two subgroups with high or low risk of survival and recurrence. Therefore, a nomogram integrating six N-glycans [NGA2FB(Peak2), NG1A2F (Peak3), NA2 (Peak5), NA2F (Peak6), NA3 (Peak8) and NA4 (Peak11)] was established for ICC and HCC differentiation, and for prognosis assessment in ICC patients.
Objective
To explore the value of GALAD model, including gender, age, AFP, AFP-L3 and DCP in diagnosis of primary hepatocellular carcinoma and prediction of microvascular invasion (MVI).
Methods
Using retrospective study method, 5 919 patients with primary hepatocellular carcinoma (HCC) who received radical operation from January 2015 to December 2018 in Eastern Hepatobiliary Surgery Hospital were enrolled into study group. At the same time, 1 745 patients with benign liver diseases (BLDs) were enrolled into control group. The concentration of DCP was detected by Lumipulse G1200 automatic immune analyzer, and the concentration of AFP was detected by Cobas e601 automatic immune analyzer. AFP-L3 was detected by affinity adsorption centrifugation. The non-parametric Mann Whitney test was used to compare the difference between two groups. The chi square test was used to compare the rates. The diagnostic value of single serological marker and GALAD model for primary hepatocellular carcinoma was analyzed. The predictive effect of GALAD model on MVI of primary hepatocellular carcinoma was evaluated.
Results
Compared with single serum marker, the diagnostic value of GALAD model is higher. When the cutoff value is -0.33, the diagnostic sensitivity, specificity and accuracy reach to 91.9% (5 440/5 919), 86.8% (1 515/1 745) and 90.7% (6 955/7 664), respectively. The area under the curve can reach 0.960 [95%CI (0.955-0.964)]. Compared with no MVI (MO) group, the value of GALAD model in MVI low-risk group (M1), MVI high-risk group (M2) and MVI (M1+2) were significantly higher (Z values were-12.517, -22.883, -21.655, P<0.05), Galad model predicts MVI (M2) in high risk group,AUC was 0.717 [95%CI (0.701-0.733)] (M0 ratio M2).
Conclusion
GALAD model has better diagnostic performance in primary hepatocellular carcinoma and has certain predictive value for microvascular invasion.
Key words:
Carcinoma, hepatocellular; Liver neoplasms; Neoplasm invasiveness; Microvessels; alpha-Fetoproteins; Prothrombin
The glycosylation alterations of serum and IgG are involved in a variety of autoimmune and inflammatory diseases and have shown great potential in biomarker field. The diagnosis of immune thrombocytopenia (ITP) is exclusive. Our study aimed to discover the potential glyco-biomarkers for auxiliary diagnosis of ITP.The serum samples were obtained from 61 ITP patients and 35 healthy controls, and IgG samples were purified from 34 out of 61 ITP patients and 35 healthy controls. DNA sequencer-assisted fluorophore-assisted carbohydrate electrophoresis (DSA-FACE) was used to analyze serum and IgG N-glycan profiling.6 of 12 serum N-glycan peaks, 6 of 7 IgG N-glycan peaks, serum fucosylation, and IgG galactosylation were significantly different between ITP patients and healthy controls (p < 0.05). IgG peak 7 showed good diagnostic efficacy for discriminating ITP patients from healthy individuals (AUC 0.967). ITP patients with severe thrombocytopenia had a significantly lower serum fucosylation than ITP patients with mild and moderate thrombocytopenia (p < 0.05). Serum fucosylation and serum peak 5 were correlated with platelet counts in ITP patients with severe thrombocytopenia, and the absolute values of correlation coefficient were both over 0.5.The specific N-glycan patterns of serum and IgG were observed in ITP patients. IgG peak 7 was a potential biomarker for auxiliary diagnosis of ITP.
Support file containing the Age ranges, Pathology, location, Differentiation, Tumor size 2.65 cm, Pleura invasion, Bronchus invasion, Multicentric invasion, Angiolymphatic invasion, Neural invasion and LNM (lymph node metastasis) described in categorical variables and Tumorsize, xβ and ŷ described in continuous variables. (XLSX 32 kb)
Our objective was to explore the safety and feasibility of immune checkpoint inhibitors (ICIs) in the neoadjuvant treatment of non-small cell lung cancer (NSCLC).Embase, PubMed and Web of Science were systematically searched from 1st January 2018 to 1st August 2021 for studies with data on the treatment-related adverse reactions (TRAE), immune-related adverse events (irAE), perioperative information, major pathological response (MPR), pathologic complete remission (pCR) and objective response rate (ORR). The QUADAS-2 tool was used to assess the quality of the studies, then the data were transformed for meta-analysis. Review Manager 5.3 (Cochrane) was used for statistical analyses with a P value of <0.05 considered significant.Thirteen studies with 358 patients were included in this meta-analysis, of which, 218 patients received ICI and chemotherapy-containing regimens and 140 patients received neoadjuvant ICIs only. The 157 (72.0%) patients who received combined neoadjuvant therapy showed a higher incidence of TRAEs, while only 37 (26.4%) patients who received neoadjuvant ICIs experienced TRAEs. Grade 3 or higher irAEs were observed in 92 (25.7%) patients, of which, 81 patients belonged to the neoadjuvant immunochemotherapy subgroup. The surgical resection rate was between 38.5-100%, with only two patients experiencing a delay in surgery. Complication rates were between 3.6-100% in the 8 studies that reported postoperative complications, with more postoperative complications [35 (18.9%)] identified in the neoadjuvant immunochemotherapy subgroup. Of which 176 patients achieved MPR, 126 received ICI and chemotherapy combined neoadjuvant therapy. Seventy-one of 95 patients who had achieved pCR had undergone ICI and chemotherapy. Compared with the neoadjuvant immunotherapy group, patients undergoing ICI and chemotherapy achieved more radiological response [118 (54.1%)] than patients undergoing ICIs [25 (17.9%)] only. The odds ratio (OR) value of the MPR/pCR/ORR rate in the neoadjuvant immunochemotherapy group was higher [OR =0.55/0.32/0.39, 95% confidence interval (CI): 0.44-0.66/0.22-0.44/0.26-0.53, P=0.0004/0.14/<0.0001] after transformation.Neoadjuvant immunotherapy shows lower toxicity and fewer perioperative complications. ICI combined chemotherapy can achieve more pathological relief and clinical benefits in the neoadjuvant treatment of NSCLC but is associated with increased irAE and perioperative complications. However, the small sample size limits the reliability of the research.
e13515 Background: Lung cancer is the leading cause of cancer related death in the US with 5-year survival of less than 1% in advance stages of disease. There is a need to find new treatment strategies to improve the survival outcomes. Mammalian target of rapamicin (mTOR) is a downstream regulatory protein of the PI3K/Akt signal transduction pathway. This is a common pathway for a several cell surface receptors including insulin-like growth factor receptor (IGFR) and epidermal growth factor receptor (EGFR). The activation of these receptors through PI3K/Akt pathway is essential in cell proliferation, angiogenesis and anti-apoptosis process. Several therapeutic agents that inhibit these receptors have shown to be active in the treatment of diverse types of cancers. Docetaxel (D) is commonly used in the treatment of lung cancer. We decided to explore the potential role of mTOR inhibition using temsirolimus (T) in the treatment of lung cancer in a lung cancer cell line (LCCL) model. The experiments also sought to elucidate the optimal sequencing of these drugs. Methods: Adenocarcinoma LCCL 2122 and 1437 were plated and exposed to temsirolimus 1000nM and docetaxel 100nM. The cell viability was measured by optical density (OD) at 24, 48 and 72h. We then tested the sequence of D for 48h followed by addition of T for another 24h and the reverse in both LCCL. Results: The combination of TD had the highest inhibition of cell proliferation after 48 hours of exposure in both 2122 (mean OD 0.31 vs. control 0.86 p=0.0003) and 1437 LCCL (mean OD 0.55 and control 0.988 p=0.001). The sequence of D followed by T decreased OD greater than the T followed by D sequence in 1437 LCCL after 72 hours (mean 0.3789 vs. 0.7175). The OD was decreased in both sequences in 2122 cell line compared to control but there was no difference between either sequence. Conclusions: The combination of TD seems to be an active regimen when tested in 2 adenocarcinoma LCCL. The sequence of these agent showed that D followed by T is more active in 1437 LCCL. Further studies in animal model exploring the combination of this regimen using the combination of TD followed by T may help determine if this is a feasible combination in the treatment of lung cancer.
Abstract Background Primary hepatocellular carcinoma (HCC) is one of the most prevalent world‐wide malignancies. Half of the newly developed HCC occurs in China. Optimizing the strategies for high‐risk surveillance and early diagnosis are pivotal for improving 5‐year survival. Constructing the scientific non‐invasive detection technologies feasible for medical and healthcare institutions is among the key routes for elevating the efficacies of HCC identification and follow‐up. Results Based on the Chinese and international guidelines, expert consensus statements, literatures and evidence‐based clinical practice experiences, this consensus statement puts forward the clinical implications, application subjects, detection techniques and results interpretations of the triple‐biomarker (AFP, AFP‐L3%, DCP) based GALAD, GALAD like models for liver cancer. Conclusions The compile of this consensus statement aims to address and push the reasonable application of the triple‐biomarker (AFP, AFP‐L3%, DCP) detections thus to maximize the clinical benefits and help improving the high risk surveillance, early diagnosis and prognosis of HCC.
'/%3e%3cuse xlink:href='%23a' transform='rotate(23.036 .093 25.536)'/%3e%3cuse xlink:href='%23a' transform='rotate(45.87 1.273 16.18)'/%3e%3cuse xlink:href='%23a' transform='rotate(69.945 .996 12.078)'/%3e%3cuse xlink:href='%23a' transform='rotate(20.66 -19.689 31.932)'/%3e%3c/svg%3e)