Orbital hemangiopericytoma in an Asian population

Background/PurposeHemangiopericytoma is a very rare orbital tumor. The purpose of this study was to report the clinical and histopathological features of six cases of orbital hemangiopericytoma in an Asian population.MethodsClinical and histopathological features were reviewed in six patients who were histopathologically confirmed as having primary orbital hemangiopericytoma in National Taiwan University Hospital between May 2001 and December 2010.ResultsAmong the six cases who were diagnosed as having primary orbital hemangiopericytoma, all lesions were reported as vascular tumors and featured branching “staghorn appearance” vessels. All patients, including one male and five females, presented with progressive proptosis and some associated symptoms such as extraocular motility limitation with diplopia, displacement of the globe, afferent pupillary defect, congested vessels of conjunctiva, or decreased visual acuity. On computed tomography, the orbital tumors tended to manifest as circumscribed masses with homogeneous medium-to-high enhancement with contrast studies. All six patients received surgical treatments, and four of them had additional radiotherapy. Three patients had recurrence after surgeries, and one of them had multiple metastases to lung and liver. All patients were still alive after a follow-up period of 5–10 years.ConclusionOrbital hemangiopericytoma has malignant potential, which may lead to local recurrence and/or metastasis. Histopathological findings alone are insufficient to predict the behavior of this tumor. Therefore, both clinical and histopathological findings are important to evaluate the treatment outcomes. Total excision accompanied with radiotherapy is suggested and long-term follow-up is required

Relative risks of COVID-19 fatality between the first and second waves of the pandemic in Ontario, Canada

OBJECTIVES: To examine whether the case fatality rate (CFR) of COVID-19 decreased over time and whether the COVID-19 testing rate is a driving factor for the changes if the CFR decreased. METHODS: Analyzing COVID-19 cases, deaths and tests in Ontario, Canada, we compared the CFR between the first wave and the second wave across 26 public health units in Ontario. We also explored whether a high testing rate was associated with a large CFR decrease. RESULTS: The first wave CFR ranged from 0.004 to 0.146, whereas the second wave CFR ranged from 0.003 to 0.034. The pooled RR estimate of second wave COVID-19 case fatality, compared with first wave, was 0.24 (95% CI: 0.19-0.32). Additionally, COVID-19 testing percentages were not associated with the estimated relative risk (P=0.246). CONCLUSIONS: The COVID-19 CFR decreased significantly in Ontario during the second wave, and COVID-19 testing was not a driving factor for this decrease

Improving protein secondary structure prediction based on short subsequences with local structure similarity

<p>Abstract</p> <p>Background</p> <p>When characterizing the structural topology of proteins, protein secondary structure (PSS) plays an important role in analyzing and modeling protein structures because it represents the local conformation of amino acids into regular structures. Although PSS prediction has been studied for decades, the prediction accuracy reaches a bottleneck at around 80%, and further improvement is very difficult.</p> <p>Results</p> <p>In this paper, we present an improved dictionary-based PSS prediction method called SymPred, and a meta-predictor called SymPsiPred. We adopt the concept behind natural language processing techniques and propose synonymous words to capture local sequence similarities in a group of similar proteins. A synonymous word is an <it>n-</it>gram pattern of amino acids that reflects the sequence variation in a protein’s evolution. We generate a protein-dependent synonymous dictionary from a set of protein sequences for PSS prediction.</p> <p>On a large non-redundant dataset of 8,297 protein chains (<it>DsspNr-25</it>), the average <it>Q</it>₃ of SymPred and SymPsiPred are 81.0% and 83.9% respectively. On the two latest independent test sets (<it>EVA Set_1</it> and <it>EVA_Set2</it>), the average <it>Q</it>₃ of SymPred is 78.8% and 79.2% respectively. SymPred outperforms other existing methods by 1.4% to 5.4%. We study two factors that may affect the performance of SymPred and find that it is very sensitive to the number of proteins of both known and unknown structures. This finding implies that SymPred and SymPsiPred have the potential to achieve higher accuracy as the number of protein sequences in the NCBInr and PDB databases increases.</p> <p>Conclusions</p> <p>Our experiment results show that local similarities in protein sequences typically exhibit conserved structures, which can be used to improve the accuracy of secondary structure prediction. For the application of synonymous words, we demonstrate an example of a sequence alignment which is generated by the distribution of shared synonymous words of a pair of protein sequences. We can align the two sequences nearly perfectly which are very dissimilar at the sequence level but very similar at the structural level. The SymPred and SymPsiPred prediction servers are available at <url>http://bio-cluster.iis.sinica.edu.tw/SymPred/</url>.</p