No abstract

ObjectiveTo investigate risk factors for advanced melanoma over 50 years of age and to develop and validate a new line chart and classification system.MethodsThe SEER database was screened for patients diagnosed with advanced melanoma from 2010 to 2019 and Cox regression analysis was applied to select variables affecting patient prognosis. The area under curve (AUC), relative operating characteristic curve (ROC), Consistency index (C-index), decision curve analysis (DCA), and survival calibration curves were used to verify the accuracy and utility of the model and to compare it with traditional AJCC tumor staging. The Kaplan-Meier curve was applied to compare the risk stratification between the model and traditional AJCC tumor staging.ResultsA total of 5166 patients were included in the study. Surgery, age, gender, tumor thickness, ulceration, the number of primary melanomas, M stage and N stage were the independent prognostic factors of CSS in patients with advanced melanoma (P<0.05). The predictive nomogram model was constructed and validated. The C-index values obtained from the training and validation cohorts were 0.732 (95%CI: 0.717-0.742) and 0.741 (95%CI: 0.732-0.751). Based on the observation and analysis results of the ROC curve, survival calibration curve, NRI, and IDI, the constructed prognosis model can accurately predict the prognosis of advanced melanoma and performs well in internal verification. The DCA curve verifies the practicability of the model. Compared with the traditional AJCC staging, the risk stratification in the model has a better identification ability for patients in different risk groups.ConclusionThe nomogram of advanced melanoma and the new classification system were successfully established and verified, which can provide a practical tool for individualized clinical management of patients.

As a typical non-Gaussian vector variable, a neutral vector variable contains nonnegative elements only, and its l1 norm equals one. Additionally, its neutral properties make it significantly different from the commonly studied vector variables (e.g., Gaussian vector variables). Due to the aforementioned properties, the conventionally applied linear transformation approaches (e.g., principal component analysis (PCA), independent component analysis (ICA)) are not suitable for neutral vector variables, as PCA cannot transform a neutral vector variable, which is highly negatively correlated, into a set of mutually independent scalar variables and ICA cannot preserve the bounded property after transformation. In recent work, we proposed an efficient nonlinear transformation approach, the parallel nonlinear transformation (PNT), for decorrelating neutral vector variables. In this paper, we extensively compare PNT with PCA and ICA, through both theoretical analysis and experimental evaluations. The results of our investigations demonstrate the superiority of PNT for decorrelating the neutral vector variables.

When the labelling information is not deterministic, traditional supervised learning algorithms cannot be applied. In this case, stochastic supervision models provide a valuable alternative to classification. However, these models are restricted in several aspects, which critically limits their applicabil-

Primary systemic amyloidosis (PSA) is a systemic disease caused by amyloid deposition in various tissues and organs. In the early stages of the disease, approximately 40% of patients have skin damage, which may be the only clinical manifestation. This report described the case of a 67-year-old male with PSA who presented with characteristic cutaneous manifestations. Physical examination showed seborrheic keratotic-like plaques around the orbit, purpura and ecchymosis on the neck and dorsum manus, as well as nail dystrophy. An auxiliary examination indicated a 24-h urine protein content of 2.89 g, and serum immunoelectrophoresis showed a monoclonal λ light chain. Echocardiography showed decreased left ventricular diastolic function and mild pulmonary hypertension. The dermoscopic features were multiple comedo-like openings and milia-like cysts. Histopathology showed multiple keratinous cysts in the dermis and eosinophilic, acellular, homogenous material in the dermis that was Congo red-positive. The diagnosis was confirmed through biopsy of skin lesions and kidney.Skin lesions of this case are rare.Skin lesions around the orbit need to arouse the vigilance of dermatologists. PSA should be considered if the patient with multisystemic symptoms.Skin biopsy and Congo red staining were very important for early diagnosis of PSA.

Nuclear factor of activated T-cells, cytoplasmic 4 (NFATC4) has been implicated in keratinocyte development and several types of cancer. A well-defined role for NFATC4 in cutaneous squamous cell carcinoma (CSCC) has not yet been established. In this study, NFATC4 gene function in CSCC development was examined. Quantitative reverse transcription polymerase chain reaction (RT-qPCR) was used to measure the mRNA expression of NFATC4 in CSCC tissues and controls. A431 and Colo16 cell proliferation, invasion, and apoptosis were measured by CCK-8 assay, transwell invasion, and flow cytometry, respectively, after an NFATC4 expression lentivirus infection. Animal models were applied to validate the function of the NFATC4 gene. (1) CSCC tissues showed a significant decrease in NFATC4 expression compared to controls. (2) Overexpression of NFATc4 suppresses A431 and Colo16 cell proliferation and invasion but promotes cell apoptosis. (3) Mouse models overexpressing NFATC4 showed reduced tumourigenesis. It was suggested that NFATC4 might be a tumour suppressor gene in CSCC.