Objective: To investigate the difference between routine hematoxylin-eosin (HE) staining and immunohistochemistry in diagnosing metastatic melanoma in sentinel lymph node (SLN) metastases, and to evaluate the association of SLN tumor burden with the status of non-sentinel lymph nodes (NSLN). Methods: 126 melanoma patients were treated with SLN biopsy and further examined with immunohistochemistry at Fudan University Shanghai Cancer Center between 2010 and 2016, and the status of SLN was respectively estimated by HE stain and immunohistochemistry (S-100 protein, HMB45, Melan A and SOX10). In 39 patients who were treated with complete lymph node dissection, characteristics of SLN tumor burden (maximum diameter of the tumor deposit, tumor penetrative depth and the microanatomic location of the metastasis) and the associations of SLN tumor burden with the involvement of NSLN were all evaluated. Results: Of the total 126 cases, 33 (26.2%) were positive by HE staining and 49 (38.3%) were positive by immunohistochemistry. S-100 protein was positive in 48 out of 49 cases (98.0%). HMB45 was positive in 46 out of 49 cases (93.9%). Melan A was positive in 47 out of 49 cases (96.0%). SOX10 was positive in 8 out of 8 cases. The outcome indicated that the application of immunohistochemistry identified positive SLN missed by HE stain in about 12.1% of cases. Of the 39 patients who were treated with complete lymph node dissection, six showed metastases in NSLN. The frequency of metastases in NSLN was 15.4% (6/39) when SLN was positive. Additionally, the frequency of metastases in NSLN in cases with SLN metastatic deposits ≤2 mm was significantly lower than that in cases with SLN metastatic deposits >2 mm; eight cases with SLN metastatic deposits <0.2 mm had no additional positive NSLN. Conclusions The findings suggest that immunohistochemistry could effectively improve the detection of positive SLN in melanoma. Cases with SLN metastatic deposits ≤2 mm are less likely to have further metastases in NSLN. There is a need for prospective large-population based studies to identify a subgroup of SLN positive patients who can safely be spared complete lymph node dissection.

Objective: To evaluate the sensitivity, specificity and clinical value of anti-BRAF V600E antibody (clone VE1) in detection of the BRAF V600E mutant in formalin-fixed and paraffin-embedded (FFPE) melanoma specimens by immunohistochemical (IHC) methods. Methods: A total of 50 melanoma samples collected between 2008 and 2016 from 40 patients were analyzed for BRAF mutation (exon 15) by DNA sequencing using FFPE. These tissues were immunostained with VE1 antibody, and the results were analyzed and compared with those by DNA sequencing. Results: By DNA sequencing, 36 cases showed BRAF mutation while others were BRAF wild type. Among the 36 cases with BRAF mutation, 32 harbored BRAF V600E, two harbored BRAF V600K, one had BRAF K601E and one had BRAF D594N, respectively. IHC staining showed 30 specimens were VE1 positive, while 19 were negative. The determination of IHC result for one case was obscured by heavy pigments. Of the BRAF-mutated specimens, four specimens with BRAF mutation other than V600E were all negative for VE1. The sensitivity and specificity of the VE1 immunostaining was 96.8% and 100.0% respectively.Concordance of BRAF V600E detection between immunostaining and DNA sequencing was 98.0%(48/49). Conclusions High sensitivity and specificity for VE1 immunostaining in detecting BRAF V600E in melanomas are demonstrated. It is a rapid and cost-effective method for detecting BRAF V600E mutations in melanoma patients. Hence, VE1 immunostaining can be used as an important screening method for BRAF mutation in laboratories.

The conversion of the normal cellular prion protein (PrP) to the misfolded pathogenic scrapie prion protein (PrP) is the biochemical hallmark of prion replication. So far, various chemical compounds that inhibit this conformational conversion have been identified. Here, we report the novel anti-prion activity of SGI-1027 and its meta/meta analogue (M/M), previously known only as potent inhibitors of DNA methyltransferases (DNMTs). These compounds effectively decreased the level of PrP in cultured cells with permanent prion infection, without affecting PrP at the transcriptional or translational levels. Furthermore, SGI-1027 prevented effective prion infection of the cells. In a PrP aggregation assay, both SGI-1027 and M/M blocked the formation of misfolded PrP aggregates, implying that binding of these compounds hinders the PrP conversion process. A series of binding and docking analyses demonstrated that both SGI-1027 and M/M directly interacted with the C-terminal globular domain of PrP, but only SGI-1027 bound to a specific region of PrP with high affinity, which correlates with its potent anti-prion efficacy. Therefore, we report SGI-1027 and related compounds as a novel class of potential anti-prion agents that preferentially function through direct interaction with PrP.

Sleep apnea causes cardiac arrest, sleep rhythm disorders, nocturnal hypoxia and abnormal blood pressure fluctuations in patients, which eventually lead to nocturnal target organ damage in hypertensive patients. The incidence of obstructive sleep apnea hypopnea syndrome (OSAHS) is extremely high, which seriously affects the physical and mental health of patients. This study attempts to extract features associated with OSAHS from 24-hour ambulatory blood pressure data and identify OSAHS by machine learning models for the differential diagnosis of this disease. The study data were obtained from ambulatory blood pressure examination data of 339 patients collected in outpatient clinics of the Chinese PLA General Hospital from December 2018 to December 2019, including 115 patients with OSAHS diagnosed by polysomnography (PSG) and 224 patients with non-OSAHS. Based on the characteristics of clinical changes of blood pressure in OSAHS patients, feature extraction rules were defined and algorithms were developed to extract features, while logistic regression and lightGBM models were then used to classify and predict the disease. The results showed that the identification accuracy of the lightGBM model trained in this study was 80.0%, precision was 82.9%, recall was 72.5%, and the area under the working characteristic curve (AUC) of the subjects was 0.906. The defined ambulatory blood pressure features could be effectively used for identifying OSAHS. This study provides a new idea and method for OSAHS screening.
Blood Pressure ; Blood Pressure Monitoring, Ambulatory ; Humans ; Hypertension/complications* ; Polysomnography ; Sleep Apnea, Obstructive/diagnosis*