ObjectiveTo summarize controversy and progress of multi-slice spiral CT in efficacy evaluation of transformation therapy for advanced gastric cancer.MethodThe recent studies published at home and abroad on the spiral CT in evaluating the therapeutic effect of transformation therapy for the advanced gastric cancer were reviewed and analyzed.ResultsIn recent years, though the energy spectrum and dual-energy CT examinations had appeared, the most common tool in evaluating of the efficacy of transformation therapy for the advanced gastric cancer was the spiral CT. The most common evaluation standard was still the RECIST standard.ConclusionsSpiral CT has its outstanding diagnostic significance in therapeutic evaluation of transformation therapy for advanced gastric cancer. Although there is some controversy, with advancements of a large number of studies, it will greatly help diagnosis and treatment of advanced gastric cancer.
Objective Using bioinformatics, we analyzed the immune landscape and gene expression patterns associated with CD8+ T-cell subtypes in papillary thyroid carcinoma, constructed a prognostic model, and performed analyses of immune infiltration characteristics. MethodsWe integrated single-cell RNA sequencing and bulk transcriptomic data and, using differential expression analysis, cell differentiation trajectory analysis, consensus clustering, and LASSO-Cox proportional hazards regression, identified CD8+ T-cell subtype-associated prognostic genes. We then developed and evaluated a risk-score prognostic model and used it to analyze immune infiltration and predict responses to immunotherapy. ResultsWe subdivided tumor-infiltrating CD8+ T cells in papillary thyroid carcinoma into 6 subtypes and using pseudotime analysis and differentiation scoring, identified CD8+ T-cells_1 as the putative origin of differentiation. We selected nine prognostic genes (LAIR2, RGS2, DEDD2, HSPA6, KLRB1, DNAJB1, CCL5, CX3CR1, and MT1M) to construct and evaluate a prognostic model. Receiver operating characteristic (ROC) curves for the training, validation, and combined cohorts demonstrated that the model has good predictive performance for 3-, 5-, and 10-year overall survival in patients with papillary thyroid carcinoma. Patients in the high-risk group had significantly shorter overall survival than those in the low-risk group (P=0.021) and exhibited lower levels of immune cell infiltration, while the low-risk group showed a higher response rate to immunotherapy (P<0.05). ConclusionsThis prognostic model can effectively predict the prognosis, immune infiltration characteristics, and response to immunotherapy in patients with papillary thyroid carcinoma, providing a theoretical basis for clinical prognostic assessment and the development of personalized treatment strategies.
Sudden cardiac arrest (SCA) is a lethal cardiac arrhythmia that poses a serious threat to human life and health. However, clinical records of sudden cardiac death (SCD) electrocardiogram (ECG) data are extremely limited. This paper proposes an early prediction and classification algorithm for SCA based on deep transfer learning. With limited ECG data, it extracts heart rate variability features before the onset of SCA and utilizes a lightweight convolutional neural network model for pre-training and fine-tuning in two stages of deep transfer learning. This achieves early classification, recognition and prediction of high-risk ECG signals for SCA by neural network models. Based on 16 788 30-second heart rate feature segments from 20 SCA patients and 18 sinus rhythm patients in the international publicly available ECG database, the algorithm performance evaluation through ten-fold cross-validation shows that the average accuracy (Acc), sensitivity (Sen), and specificity (Spe) for predicting the onset of SCA in the 30 minutes prior to the event are 91.79%, 87.00%, and 96.63%, respectively. The average estimation accuracy for different patients reaches 96.58%. Compared to traditional machine learning algorithms reported in existing literatures, the method proposed in this paper helps address the requirement of large training datasets for deep learning models and enables early and accurate detection and identification of high-risk ECG signs before the onset of SCA.
ObjectiveTo summarize the clinicopathological characteristics of papillary thyroid cancer (PTC) in adolescents and analyze the risk factors affecting lateral lymph node metastasis and prognosis. MethodsIn retrospectively, 150 adolescent PTC patients admitted to the Department of Thyroid Surgery of the First Affiliated Hospital of Zhengzhou University from January 2012 to January 2022 and meeting the inclusion and exclusion criterias were collected as the study subjects (adolescent group), and 100 adult PTC patients were selected as adult group. Statistical analysis was performed with SPSS 25.0 software to compare the clinicopathological characteristics of the patients in the two groups, and to explore the risk factors for lateral lymph node metastasis and recurrence in adolescent PTC patients by using logistic regression and Cox proportional hazards regression models, respectively. ResultsAdolescents with PTC were more prone to extrandular invasion [30.0% (45/150) versus 17.0% (17/100), P=0.020], neck lymph node metastasis [79.3% (119/150) versus 48.0% (48/100), P<0.001], central lymph node metastasis [78.7% (118/150) versus 48.0% (48/100), P<0.001], lateral lymph node metastasis [44.0% (66/150) versus 12.0% (12/100), P<0.001]; and had a greater maximum tumor diameter (1.75 cm versus 0.75 cm, P＜0.001) and higher ratio of greater maximum tumor diameter ＞2 cm [45.3% (68/150) versus 8.0% (8/100), P＜0.001] in adolescent PTC patients. In adolescent PTC patients, extraglandular invasion (OR=2.654, P=0.022), multifoci (OR=4.860, P<0.001) and maximum tumor diameter>2 cm (OR=3.845, P=0.001) were risk factors for lateral lymph node metastasis; lateral lymph node metastasis (RR=10.105, P=0.040) and distant metastasis (RR=7.058, P=0.003) were predictors of postoperative recurrence in adolescent PTC patients. ConclusionsCompared with adult PTC patients, adolescent PTC patients have more aggressive tumors. Adolescent PTC with extraglandular invasion, multilesions, and maximum tumor diameter>2 cm should be considered for lateral lymph node dissection; and adolescent PTC patients with lateral lymph node metastasis and distant metastasis should pay close attention to their recurrence status.
ObjectiveTo explore the value of multi-slice spiral CT (MSCT) in the judgment of N stage and lymph node metastasis of patients with advanced gastric cancer who underwent surgery after transformation therapy.MethodsClinical data of 27 patients with advanced gastric cancer who underwent surgery after transformation therapy, form July 2017 to July 2019 in Affiliated Yantai Yuhuangding Hospital of Qingdao University were analyzed retrospectively, and all of patients underwent SOX regimen transformation therapy. The MSCT enhanced scan was performed before operation, and the postoperative pathology was used as the gold standard. The preoperative N stage and lymph node metastasis groups were evaluated by MSCT enhanced scan and compared with the pathological results.Results Before the operation, MSCT was used to evaluate the lymph node metastasis of the patients with advanced gastric cancer after transformation therapy, and compared with the lymph nodes metastasis of the corresponding pathological results, the accuracy rates of lymph node groups in No.1, No.3, No.5, No.6, No.7, No.8, and No.16 were 77.78% (21/27), 81.48% (22/27), 85.19% (23/27), 88.89% (24/27), 85.19% (23/27), 74.07% (20/27), and 96.30% (26/27), respectively. Compared with pathological results, the total accuracy of N stage after transformation therapy that evaluated by MSCT was 62.96% (17/27), with the Kappa coefficient was 0.419 (P=0.003).ConclusionsMSCT has high accuracy and consistency for the N stage of advanced gastric cancer after transformation therapy. Besides, MSCT has a certain diagnostic rate for lymph node metastasis in patients with advanced gastric cancer in lymph node groups of No.1, No.3, No.5, No.6, No.7, No.8, and No.16.
Objective To summarize application status of carbon nanomaterial in gastric cancer therapy. Method The relevant literatures about the application of the carbon nanomaterial in the gastric cancer were reviewed. Results The carbon nanomaterial was as a lymph tracer with good effects for dying and tracing, which could improve the number of lymph nodes and the detection rate of metastasis lymph nodes. As be made as a transition of chemotherapy drugs, the carbon nanomaterial could improve the concentration of the drug in the lymph node, then inhibit the gastric cancer cell to spread. Conclusion Carbon nanomaterial provides an effective help in treatment for gastric cancer, but whether it could improve prognosis of patient with gastric cancer remains to be studied.