Cronkhite-Canada syndrome: An investigation in clinical features and pathogenesis.

OBJECTIVE: This study aimed to investigate the clinical features and potential pathogenesis of a rare nonhereditary polyposis syndrome, Cronkhite-Canada syndrome (CCS). METHODS: Medical records of eight patients with CCS who were admitted to our hospital from January 2005 to November 2019 were reviewed. Transcriptome profiling was performed in one patient to investigate its difference between gastric polyp tissue and normal mucosa. Differentially expressed genes (DEGs) were determined for functional analysis. The expression of inhibin beta A (INHBA) was further assessed by using immunohistochemistry. RESULTS: All patients presented with gastrointestinal polyposis, accompanied by diarrhea, skin hyperpigmentation, hair loss and nail dystrophy. Hyperplastic polyps were observed in seven patients, tubular adenoma in two, inflammatory polyps in one and hamartomatous polyps in one, respectively. All patients underwent comprehensive treatment and five achieved clinical remission. A total of 2107 DEGs, including 1265 upregulated and 842 downregulated, were found in the gastric polyp. Gene ontology analysis showed that upregulated genes were significantly enriched in the positive regulation of cell proliferation, epithelium development and angiogenesis. A protein-protein interaction analysis suggested that INHBA was at the center of the interaction network and might play an important role in CCS. Immunohistochemistry confirmed that INHBA expression was upregulated in CCS gastric polyps. CONCLUSIONS: CCS is a rare disease and its diagnosis mainly depends on typical clinical manifestations, endoscopic findings and histological features. INHBA upregulation may contribute to its pathogenesis.

Abnormal serum carbohydrate antigen 19-9 levels in a patient with splenic retiform haemangioendothelioma concomitant with hepatic amyloidosis: A case report.

BACKGROUND: Carbohydrate antigen 19-9 (CA 19-9) is a glycoprotein that is used as a reliable tool for monitoring pancreatic cancer. Serum CA 19-9 levels are increased in patients suffering from liver, lung, and other non-malignant diseases. Haemangioendothelioma is a vascular neoplasm with a borderline biological behaviour. However, no case of haemangioendothelioma has yet been reported to be associated with CA 19-9. CASE SUMMARY: A 54-year-old Chinese man was referred to our hospital for discontinuous fatigue and unintentional weight loss for over one year. Laboratory investigations revealed an elevated serum CA 19-9 concentration of 39 IU/mL (reference interval, 0-37 IU/mL) over one year before admission. Afterwards, coagulopathy appeared, and the patient's serum CA 19-9 concentration increased continuously. At the time of admission, abdominal pain and haemorrhagic shock burst occurred, and emergency medical operation was performed. Laboratory investigations conducted upon admission showed a serum CA19-9 concentration of 392.56 IU/mL. Surgical resection of the spleen was undertaken, and pathological examination showed retiform haemangioendothelioma. The patient developed jaundice ten days after surgical excision of the spleen. Pathological examination of needle biopsy samples of the liver yielded a diagnosis of hepatic amyloidosis. CONCLUSION: We describe a rare case of splenic retiform haemangioenthelioma concomitant with hepatic amyloidosis. Physicians should note abnormal serum CA 19-9 levels with early symptoms of fatigue and unintentional weight loss.

Enhanced community structure detection in complex networks with partial background information.

Community structure detection in complex networks is important since it can help better understand the network topology and how the network works. However, there is still not a clear and widely-accepted definition of community structure, and in practice, different models may give very different results of communities, making it hard to explain the results. In this paper, different from the traditional methodologies, we design an enhanced semi-supervised learning framework for community detection, which can effectively incorporate the available prior information to guide the detection process and can make the results more explainable. By logical inference, the prior information is more fully utilized. The experiments on both the synthetic and the real-world networks confirm the effectiveness of the framework.