Preserving User Preferences in Document-Category Management: An Ontology-based Evolution Approach

Preserving the user’s preference in document-category management is essential because it affects his/her search efficiency, cognitive processing load, and satisfaction. Prior research has investigated automated document category evolution by using lexicon-based documentcategory evolution techniques which take into account the document categories previously created by the user. However, comparing documents at the lexical level cannot solve word mismatch or ambiguity problems effectively. To address such problems inherent to the lexicon-based approach, we propose an ONtology-based Category Evolution (ONCE) technique, which uses an appropriate ontology to support document-category evolution at the conceptual level rather than at the lexical level. Specifically, we develop an Ontology Enrichment (OE) technique for automatic leaning of concept descriptors in the adopted ontology. We empirically evaluate the effectiveness of the proposed ONCE technique, using a lexicon-based document-category evolution technique (i.e., CE2) and the hierarchical agglomerative clustering (HAC) technique for benchmark purposes. According to our empirical results, ONCE appears more effective than CE2 and HAC, and achieves higher clustering recall and precision

Subject-relevant Document Recommendation: A Reference Topic-Based Approach

Knowledge-intensive workers, such as academic researchers, medical professionals or patent engineers, have a demanding need of searching information relevant to their work. Content-based recommender system (CBRS) makes recommendation by analyzing similarity of textual contents between documents and users’ preferences. Although content-based filtering has been one of the promising approaches to document recommendations, it encounters the over-specialization problem. CBRS tends to recommend documents that are similar to what have been in user’s preference profile. Rationally, citations in an article represent the intellectual/affective balance of the individual interpretation in time and domain understanding. A cited article shall be associated with and may reflect the subject domain of its citing articles. Our study addresses the over-specialization problem to support the information needs of researchers. We propose a Reference Topic-based Document Recommendation (RTDR) technique, which exploits the citation information of a focal user’s preferred documents and thereby recommends documents that are relevant to the subject domain of his or her preference. Our primary evaluation results suggest the outperformance of the proposed RTDR to the benchmarks

Relationship between borderline personality symptoms and Internet addiction: The mediating effects of mental health problems

Aim To examine the relationship between borderline personality symptoms and Internet addiction as well as the mediating role of mental health problems between them. Methods A total of 500 college students from Taiwan were recruited and assessed for symptoms of Internet addiction using the Chen Internet Addiction Scale, borderline personality symptoms using the Taiwanese version of the Borderline Symptom List and mental health problems using four subscales from the Symptom Checklist-90-Revised Scale (interpersonal sensitivity, depression, anxiety, and hostility). Structural equation modeling (SEM) was used to test our hypothesis that borderline personality symptoms are associated with the severity of Internet addiction directly and also through the mediation of mental health problems. Results SEM analysis revealed that all paths in the hypothesized model were significant, indicating that borderline personality symptoms were directly related to the severity of Internet addiction as well as indirectly related to the severity of Internet addiction by increasing the severity of mental health problems. Conclusion Borderline personality symptoms and mental health problems should be taken into consideration when designing intervention programs for Internet addiction

Sequence Variants of Peroxisome Proliferator-Activated Receptor-Gamma Gene and the Clinical Courses of Patients with End-Stage Renal Disease

Background. PPAR-single nucleotide polymorphisms (SNPs) reportedly play an important role in determining metabolic risk among diverse population. Whether PPAR-SNPs affect the clinical courses in ESRD patients is unknown. Methods. From a multicenter cohort, we identified 698 patients with prevalent ESRD between 2002 and 2003, and other 782 healthy subjects as control. Two PPAR-SNPs, Pro12Ala (rs1801282) and C161T (rs3856806), were genotyped and their association with ESRD was examined. Both groups were prospectively followed until 2007, and the predictability of genotypes for the long-term survival of ESRD patients was analyzed. Results. After multivariable-adjusted regression, GG genotype of Pro12Ala was significantly more likely to associate with ESRD ( < 0.001) among patients with non-diabetes-related ESRD. Cox's proportional hazard regression showed that both Pro12Ala and C161T polymorphisms were significant predictors of mortality in ESRD patients with DM (Pro12Ala: GG versus other genotypes, hazard ratio [HR] <0.01; < 0.001; for C161T, CC versus TT genotypes, HR 2.86; < 0.001; CT versus TT genotypes, HR 1.93; < 0.001). Conclusion. This is the first and largest study to evaluate PPAR-SNPs in ESRD patients. Further mechanistic study is needed to elucidate the role of PPAR-among ESRD patients

Assessment of latent tuberculosis infection in psychiatric inpatients: A survey after tuberculosis outbreaks

AbstractBackground/PurposeTo investigate risk factors of latent tuberculosis infection (LTBI) among inpatients of chronic psychiatric wards with tuberculosis (TB) outbreaks.MethodsIn April 2013, inpatients of four all-male wards with TB outbreaks were tested for LTBI using the QuantiFERON-TB Gold in Tube (QFT) method. Based on this investigation, a retrospective study was conducted to assess risk factors for LTBI. Inpatients exposed to cluster-A or cluster-B TB cases were defined as contacts of cluster-A or cluster-B, and others, as nonclustered contacts.ResultsAmong 355 inpatients with TB exposure, 134 (38%) were QFT-positive for LTBI. Univariate analysis showed that significant predictors for QFT-positivity were age, case-days of exposure to all TB cases (TB-all) and to sputum smear positive cases, number of source cases with cough, and exposure to cluster-A TB cases. Independent risk factors for LTBI were higher age [adjusted odds ratio (OR) 1.03, 95% confidence intervals (CI: 1.01–1.05)], TB-all exposure case-days ≥ 200 [adjusted OR 2.04 (1.06–3.92)] and exposure to cluster-A TB cases [adjusted OR 2.82 (1.30–6.12)] after adjustment for the sputum smear positivity, and cough variables of the source cases. The contacts of cluster-A had a greater risk of LTBI than did those of cluster-B, especially in the younger population (≤50 years) after adjustment [adjusted OR 2.64 (1.03–6.76)].ConclusionAfter TB outbreaks, more than one third of inpatients were QFT-positive for LTBI. Our findings suggest that, beside the infectiousness of source cases, intensity of exposure, and age of contacts, exposure to TB cases in potential genotyping clusters may be predictive for LTBI in this male psychiatric population

Predicting serum levels of lithium-treated patients: A supervised machine learning approach

Routine monitoring of lithium levels is common clinical practice. This is because the lithium prediction strategies available developed by previous studies are still limited due to insufficient prediction performance. Thus, we used machine learning approaches to predict lithium concentration in a large real-world dataset. Real-world data from multicenter electronic medical records were used in different machine learning algorithms to predict: (1) whether the serum level was 0.6-1.2 mmol/L or 0.0-0.6 mmol/L (binary prediction), and (2) its concentration value (continuous prediction). We developed models from 1505 samples through 5-fold cross-validation and used 204 independent samples to test their performance by evaluating their accuracy. Moreover, we ranked the most important clinical features in different models and reconstructed three reduced models with fewer clinical features. For binary and continuous predictions, the average accuracy of these models was 0.70-0.73 and 0.68-0.75, respectively. Seven features were listed as important features related to serum lithium levels of 0.6-1.2 mmol/L or higher lithium concentration, namely older age, lower systolic blood pressure, higher daily and last doses of lithium prescription, concomitant psychotropic drugs with valproic acid and -pine drugs, and comorbid substance-related disorders. After reducing the features in the three new predictive models, the binary or continuous models still had an average accuracy of 0.67-0.74. Machine learning processes complex clinical data and provides a potential tool for predicting lithium concentration. This may help in clinical decision-making and reduce the frequency of serum level monitoring

Patients Infected with CRF07_BC Have Significantly Lower Viral Loads than Patients with HIV-1 Subtype B: Mechanism and Impact on Disease Progression

The circulating recombinant form (CRF) 07_BC is the most prevalent HIV-1 strain among injection drug users (IDUs) in Taiwan. It contains a 7 amino-acid deletion in its p6gag. We conducted a cohort study to compare viral loads and CD4 cell count changes between patients infected with subtype B and CRF07_BC and to elucidate its mechanism. Twenty-one patients infected with CRF07_BC and 59 patients with subtype B were selected from a cohort of 667 HIV-1/AIDS patients whom have been followed up for 3 years. Generalized estimated equation was used to analyze their clinical data and the results showed that patients infected with CRF07_BC had significantly lower viral loads (about 58,000 copies per ml less) than patients with subtype B infection (p = 0.002). The replicative capacity of nine CRF07_BC and four subtype B isolates were compared and the results showed that the former had significantly lower replicative capacity than the latter although all of them were CCR5- tropic and non-syncytium inducing viruses. An HIV-1-NL4-3 mutant virus which contains a 7 amino-acid deletion in p6gag (designated as 7d virus) was generated and its live cycle was investigated. The results showed that 7d virus had significantly lower replication capacity, poorer protease-mediated processing and viral proteins production. Electron microscopic examination of cells infected with wild-type or 7d virus demonstrated that the 7d virus had poorer and slower viral maturation processes: more viruses attached to the cell membrane and higher proportion of immature virions outside the cells. The interaction between p6gag and Alix protein was less efficient in cells infected with 7d virus. In conclusion, patients infected with CRF07_BC had significantly lower viral loads than patients infected with subtype B and it may due to the deletion of 7 amino acids which overlaps with Alix protein-binding domain of the p6gag

Transmission of acute infectious illness among cases of Kawasaki disease and their household members

Background/purposeKawasaki disease (KD) is a disease of unknown cause and the causative agent is most likely to be infectious in nature. To investigate the household transmission pattern of infectious illness and etiology, we thus initiated a prospective case and household study.MethodsWe enrolled KD cases and their household members from February 2004 to September 2008. The KD cases and their household members accepted questionnaire-based interviews of the contact history, signs of infection, and symptoms to check whether clusters of infectious illness occurred.ResultsA total of 142 KD cases and 561 household members were enrolled. Among the 142 KD cases, 136 cases (96%) were typical KD, and six (4%) were atypical KD. Of the 561 household members, 17% were siblings, 46% were parents, 18% were grandparents, and the others were cousins or babysitters. Prior to the onset of their KD illness, 66% (94/142) KD cases had contact with ill household members. On the same day of the onset of KD cases' illness, 4% (6/142) KD cases had household members with illness. After KD cases' disease onset, 70% (100/142) KD cases had at least one other family member with illness. Overall, 61% (343/561) of all the household members had acute infectious illness during KD cases' acute stage, and 92% (130/142) of the families had clusters of infectious illness.ConclusionA total of 66% KD cases had positive contact with ill household members prior to their disease onset and 92% of families had clusters of infectious illness, so KD is strongly associated with infections

PYCR1 and PYCR2 Interact and Collaborate with RRM2B to Protect Cells from Overt Oxidative Stress

Ribonucleotide reductase small subunit B (RRM2B) is a stress response protein that protects normal human fibroblasts from oxidative stress. However, the underlying mechanism that governs this function is not entirely understood. To identify factors that interact with RRM2B and mediate anti-oxidation function, large-scale purification of human Flag-tagged RRM2B complexes was performed. Pyrroline-5-carboxylate reductase 1 and 2 (PYCR1, PYCR2) were identified by mass spectrometry analysis as components of RRM2B complexes. Silencing of both PYCR1 and PYCR2 by expressing short hairpin RNAs induced defects in cell proliferation, partial fragmentation of the mitochondrial network, and hypersensitivity to oxidative stress in hTERT-immortalized human foreskin fibroblasts (HFF-hTERT). Moderate overexpression of RRM2B, comparable to stress-induced level, protected cells from oxidative stress. Silencing of both PYCR1 and PYCR2 completely abolished anti-oxidation activity of RRM2B, demonstrating a functional collaboration of these metabolic enzymes in response to oxidative stress