The omohyoid sling syndrome

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Collagen-Based Scaffolds for Cell Therapies in the Injured Brain

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CFD study of dynamic wind actions on faces of a tall building

Section B: Numerical simulation and theoretical analysisThe article can be viewed at: http://wgy091.ust.hk:8080/document/HKWE1papers.pdfThis paper computes and investigates the fluctuating wind forces on different building faces of a 6:1:1 square-section tall building with LES. Time histories of aerodynamic forces on building faces are computed from which power spectra and cross correlation analysis are made. The computation results are compared to past wind tunnel data from base balance and wind pressure measurements. Most results show qualitative agreement.published_or_final_versio

Sustained Delivery of Bioactive GDNF from Collagen and Alginate-Based Cell-Encapsulating Gel Promoted Photoreceptor Survival in an Inherited Retinal Degeneration Model

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Carriers in Cell-Based Therapies for Neurological Disorders

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Dynamic wind loading of H-shaped tall buildings

Fulltext in: http://www.iawe.org/Proceedings/7APCWE/M3A_5.pdfTechnical Session: M3-A High-Rise Building, no.5Dynamic wind loads on a number of H-shaped tall buildings are measured in the wind tunnel with a highfrequency force balance for all wind incidences. The aim is to investigate the size effect of the recessed cavities on the dynamic wind loading behavior of the building. Combinations of three widths and three depths of a cavity are tested. It is found that at most wind incidences, the presence of cavities on the building faces leads to little modifications to the magnitudes and behavior of mean and fluctuating overturning moment coefficients. However, reduced magnitudes of across-wind moment fluctuations are found at normal incidence and different behavior of across-wind excitation is revealed by the across-wind moment spectra. Wind torsion is noticeably modified by the presence of the recessed cavities.link_to_subscribed_fulltex

Can HbA1c replace OGTT for the diagnosis of diabetes mellitus among Chinese patients with impaired fasting glucose?

Background. HbA1c ≥ 6.5% has been recommended as a diagnostic criterion for the detection of diabetes mellitus (DM) since 2010 because of its convenience, stability and significant correlation with diabetic complications. Nevertheless, the accuracy of HbA1c compared to glucose-based diagnostic criteria varies among subjects of different ethnicity and risk profile. Objectives. This study aimed to evaluate the accuracy of HbA1c for diagnosing DM compared to the diagnosis by oral glucose tolerance test (OGTT) and the optimal HbA1c level to diagnose DM in primary care Chinese patients with impaired fasting glucose (IFG). Methods. A cross-sectional study was carried out in three public primary care clinics in Hong Kong. About 1128 Chinese adults with IFG (i.e. FG level between 5.6 and 6.9 mmol/l in the past 18 months) were recruited to receive paired OGTT and HbA1c tests. Sensitivities and specificities of HbA1c at different threshold levels for predicting DM compared to the diagnosis by OGTT were evaluated. A receiver operating characteristic (ROC) curve was used to determine the optimal cut-off level. Results. Among the 1128 subjects (mean age 64.2±8.9 year, 48.8% male), 229 (20.3%) were diagnosed to have DM by OGTT. The sensitivity and specificity of HbA1c ≥6.5% were 33.2% and 93.5%, respectively, for predicting DM diagnosed by OGTT. The area under the ROC curve was 0.770, indicating HbA1c had fair discriminatory power. The optimal cut-off threshold of HbA1c was 6.3% for discriminating DM from non-DM, with sensitivity and specificity of 56.3% and 85.5%, respectively. HbA1c ≥ 5.6% has the highest sensitivity and negative predictive value of 96.1% and 94.5%, respectively. Conclusions. HbA1c ≥ 6.5% is highly specific in identifying people with DM, but it may miss the majority (66.8%) of the DM cases. An HbA1c threshold of <5.6% is more appropriate to be used for the exclusion of DM. OGTT should be performed for the confirmation of DM among Chinese patients with IFG who have an HbA1c between 5.6% and 6.4%.postprin

Avoid Oversimplifications in Machine Learning: Going beyond the Class-Prediction Accuracy.

Class-prediction accuracy provides a quick but superficial way of determining classifier performance. It does not inform on the reproducibility of the findings or whether the selected or constructed features used are meaningful and specific. Furthermore, the class-prediction accuracy oversummarizes and does not inform on how training and learning have been accomplished: two classifiers providing the same performance in one validation can disagree on many future validations. It does not provide explainability in its decision-making process and is not objective, as its value is also affected by class proportions in the validation set. Despite these issues, this does not mean we should omit the class-prediction accuracy. Instead, it needs to be enriched with accompanying evidence and tests that supplement and contextualize the reported accuracy. This additional evidence serves as augmentations and can help us perform machine learning better while avoiding naive reliance on oversimplified metrics

Identification of SCN1A and PCDH19 mutations in Chinese children with Dravet syndrome

Background: Dravet syndrome is a severe form of epilepsy. Majority of patients have a mutation in SCN1A gene, which encodes a voltage-gated sodium channel. A recent study has demonstrated that 16% of SCN1A-negative patients have a mutation in PCDH19, the gene encoding protocadherin-19. Mutations in other genes account for only a very small proportion of families. TSPYL4 is a novel candidate gene within the locus 6q16.3-q22.31 identified by linkage study. Objective: The present study examined the mutations in epileptic Chinese children with emphasis on Dravet syndrome. Methods: A hundred children with severe epilepsy were divided into Dravet syndrome and non-Dravet syndrome groups and screened for SCN1A mutations by direct sequencing. SCN1A-negative Dravet syndrome patients and patients with phenotypes resembling Dravet syndrome were checked for PCDH19 and TSPYL4 mutations. Results: Eighteen patients (9 males, 9 females) were diagnosed to have Dravet syndrome. Among them, 83% (15/18) had SCN1A mutations including truncating (7), splice site (2) and missense mutations (6). The truncating/splice site mutations were associated with moderate to severe degree of intellectual disability (p<0.05). During the progression of disease, 73% (11/15) had features fitting into the diagnostic criteria of autism spectrum disorder and 53% (8/15) had history of vaccination-induced seizures. A novel PCDH19 p.D377N mutation was identified in one SCN1A-negative female patient with Dravet syndrome and a known PCDH19 p.N340S mutation in a female non-Dravet syndrome patient. The former also inherited a TSPYL4 p.G60R variant. Conclusion: A high percentage of SCN1A mutations was identified in our Chinese cohort of Dravet syndrome patients but none in the rest of patients. We demonstrated that truncating/splice site mutations were linked to moderate to severe intellectual disability in these patients. A de novo PCDH19 missense mutation together with an inherited TSPYL4 missense variant were identified in a patient with Dravet syndrome. © 2012 Kwong et al.published_or_final_versio