A Surveillance System to Reduce Transmission of Pandemic H1N1 (2009) Influenza in a 2600-Bed Medical Center

BACKGROUND: Concerns have been raised about how the transmission of emerging infectious diseases from patients to healthcare workers (HCWs) and vice versa could be recognized and prevented in a timely manner. An effective strategy to block transmission of pandemic H1N1 (2009) influenza in HCWs is important. METHODOLOGY/PRINCIPAL FINDINGS: An infection control program was implemented to survey and prevent nosocomial outbreaks of H1N1 (2009) influenza at a 2,600-bed, tertiary-care academic hospital. In total, 4,963 employees at Kaohsiung Chang Gung Memorial Hospital recorded their temperature and received online education on control practices for influenza infections. Administration records provided vaccination records and occupational characteristics of all HCWs. Early recognition of a pandemic H1N1 (2009) influenza case was followed by a semi-structured questionnaire to analyze possible routes of patient contact, household contact, or unspecified contact. Surveillance spanned August 1, 2009 to January 31, 2010; 51 HCWs were confirmed to have novel H1N1 (2009) influenza by quantitative real-time reverse transcription polymerase chain reaction. Prevalence of patient contact, household contact, or unspecified contact infection was 13.7% (7/51), 13.7% (7/51), and 72.5% (37/51), respectively. The prevalence of the novel H1N1 infection was significantly lower among vaccinated HCWs than among unvaccinated HCWs (p<0.001). Higher viral loads in throat swabs were found in HCWs with patient and household contact infection than in those with unspecified contact infection (4.15 vs. 3.53 copies/mL, log(10), p = 0.035). CONCLUSION: A surveillance system with daily temperature recordings and online education for HCWs is important for a low attack rate of H1N1 (2009) influenza transmission before H1N1 (2009) influenza vaccination is available, and the attack rate is further decreased after mass vaccination. Unspecified contact infection rates were significantly higher than that of patient contact and household contact infection, highlighting the need for public education of influenza transmission in addition to hospital infection control

Inferring a protein interaction map of Mycobacterium tuberculosis based on sequences and interologs

Background: Mycobacterium tuberculosis is an infectious bacterium posing serious threats to human health. Due to the difficulty in performing molecular biology experiments to detect protein interactions, reconstruction of a protein interaction map of M. tuberculosis by computational methods will provide crucial information to understand the biological processes in the pathogenic microorganism, as well as provide the framework upon which new therapeutic approaches can be developed.Results: In this paper, we constructed an integrated M. tuberculosis protein interaction network by machine learning and ortholog-based methods. Firstly, we built a support vector machine (SVM) method to infer the protein interactions of M. tuberculosis H37Rv by gene sequence information. We tested our predictors in Escherichia coli and mapped the genetic codon features underlying its protein interactions to M. tuberculosis. Moreover, the documented interactions of 14 other species were mapped to the interactome of M. tuberculosis by the interolog method. The ensemble protein interactions were validated by various functional relationships, i.e., gene coexpression, evolutionary relationship and functional similarity, extracted from heterogeneous data sources. The accuracy and validation demonstrate the effectiveness and efficiency of our framework.Conclusions: A protein interaction map of M. tuberculosis is inferred from genetic codons and interologs. The prediction accuracy and numerically experimental validation demonstrate the effectiveness and efficiency of our method. Furthermore, our methods can be straightforwardly extended to infer the protein interactions of other bacterial species. © 2012 Liu et al.; licensee BioMed Central Ltd.Link_to_subscribed_fulltex

Rapid Detection of Heterogeneous Vancomycin-Intermediate Staphylococcus aureus Based on Matrix-Assisted Laser Desorption Ionization Time-of-Flight: Using a Machine Learning Approach and Unbiased Validation

Heterogeneous vancomycin-intermediate Staphylococcus aureus (hVISA) is an emerging superbug with implicit drug resistance to vancomycin. Detecting hVISA can guide the correct administration of antibiotics. However, hVISA cannot be detected in most clinical microbiology laboratories because the required diagnostic tools are either expensive, time consuming, or labor intensive. By contrast, matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) is a cost-effective and rapid tool that has potential for providing antibiotics resistance information. To analyze complex MALDI-TOF mass spectra, machine learning (ML) algorithms can be used to generate robust hVISA detection models. In this study, MALDI-TOF mass spectra were obtained from 35 hVISA/vancomycin-intermediate S. aureus (VISA) and 90 vancomycin-susceptible S. aureus isolates. The vancomycin susceptibility of the isolates was determined using an Etest and modified population analysis profile–area under the curve. ML algorithms, namely a decision tree, k-nearest neighbors, random forest, and a support vector machine (SVM), were trained and validated using nested cross-validation to provide unbiased validation results. The area under the curve of the models ranged from 0.67 to 0.79, and the SVM-derived model outperformed those of the other algorithms. The peaks at m/z 1132, 2895, 3176, and 6591 were noted as informative peaks for detecting hVISA/VISA. We demonstrated that hVISA/VISA could be detected by analyzing MALDI-TOF mass spectra using ML. Moreover, the results are particularly robust due to a strict validation method. The ML models in this study can provide rapid and accurate reports regarding hVISA/VISA and thus guide the correct administration of antibiotics in treatment of S. aureus infection

The G1613A Mutation in the HBV Genome Affects HBeAg Expression and Viral Replication through Altered Core Promoter Activity

Infection of hepatitis B virus (HBV) causes acute and chronic hepatitis and is closely associated with the development of cirrhosis and hepatocellular carcinoma (HCC). Previously, we demonstrated that the G1613A mutation in the HBV negative regulatory element (NRE) is a hotspot mutation in HCC patients. In this study, we further investigated the functional consequences of this mutation in the context of the full length HBV genome and its replication. We showed that the G1613A mutation significantly suppresses the secretion of e antigen (HBeAg) and enhances the synthesis of viral DNA, which is in consistence to our clinical result that the G1613A mutation associates with high viral load in chronic HBV carriers. To further investigate the molecular mechanism of the mutation, we performed the electrophoretic mobility shift assay with the recombinant RFX1 protein, a trans-activator that was shown to interact with the NRE of HBV. Intriguingly, RFX1 binds to the G1613A mutant with higher affinity than the wild-type sequence, indicating that the mutation possesses the trans-activating effect to the core promoter via NRE. The trans-activating effect was further validated by the enhancement of the core promoter activity after overexpression of RFX1 in liver cell line. In summary, our results suggest the functional consequences of the hotspot G1613A mutation found in HBV. We also provide a possible molecular mechanism of this hotspot mutation to the increased viral load of HBV carriers, which increases the risk to HCC

Women with endometriosis have higher comorbidities: Analysis of domestic data in Taiwan

AbstractEndometriosis, defined by the presence of viable extrauterine endometrial glands and stroma, can grow or bleed cyclically, and possesses characteristics including a destructive, invasive, and metastatic nature. Since endometriosis may result in pelvic inflammation, adhesion, chronic pain, and infertility, and can progress to biologically malignant tumors, it is a long-term major health issue in women of reproductive age. In this review, we analyze the Taiwan domestic research addressing associations between endometriosis and other diseases. Concerning malignant tumors, we identified four studies on the links between endometriosis and ovarian cancer, one on breast cancer, two on endometrial cancer, one on colorectal cancer, and one on other malignancies, as well as one on associations between endometriosis and irritable bowel syndrome, one on links with migraine headache, three on links with pelvic inflammatory diseases, four on links with infertility, four on links with obesity, four on links with chronic liver disease, four on links with rheumatoid arthritis, four on links with chronic renal disease, five on links with diabetes mellitus, and five on links with cardiovascular diseases (hypertension, hyperlipidemia, etc.). The data available to date support that women with endometriosis might be at risk of some chronic illnesses and certain malignancies, although we consider the evidence for some comorbidities to be of low quality, for example, the association between colon cancer and adenomyosis/endometriosis. We still believe that the risk of comorbidity might be higher in women with endometriosis than that we supposed before. More research is needed to determine whether women with endometriosis are really at risk of these comorbidities

Local governments’ incentives and governing practices in low-carbon transition: A comparative study of solar water heater governance in four Chinese cities

Urban sustainability transitions have been increasingly imperative to address global environmental challenges, and local governments are expected to play a critical role. There is a pressing need to explore local governments’ underlying motivations and their impacts on governing practices. Taking China as an example, this paper builds an incentive matrix to distinguish the levels of local governments’ economic interest and environmental interest in specific low-carbon innovations and investigates how different incentive typologies affect their governing practices. By comparing four Chinese municipal governments’ incentives and governing practices in promoting solar water heater adoption, this paper finds that Chinese local governments’ environmental incentive is still not compelling or stable enough, while governments that are motivated by economic interests would resort to more substantial governance practices to promote the low-carbon innovations. These results indicate potential in latecomer cities in developing both economic and environmental incentives towards low-carbon innovations because green activities could also be favored if they are well aligned with local economic development

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

When guanxi meets structural holes : exploring the guanxi networks of Chinese entrepreneurs on digital platforms

In this exploratory study, we investigate how Chinese entrepreneurs on digital platforms interact and leverage guanxi (a system of relationships and social network) to buffer the negative impacts of structural holes on knowledge orchestration. We develop our research model and formulate ten hypotheses by drawing on the literature. We adopt a mixed-methods research approach in which we use quantitative surveys to test the hypotheses, and qualitative interviews to explain why certain relationships are stronger in one stage of entrepreneurial development than the other. The study contributes to the literature on digital entrepreneurship in two ways. First, this study offers an initial understanding of the dynamics of guanxi networks for knowledge mobilisation and knowledge coordination across start-up and growth stages of Chinese entrepreneurs on digital platforms. Second, by drawing on the relevant literature, our findings extend the current understanding of knowledge orchestration of digital entrepreneurs and contribute to the literatures of structural holes theory and guanxi

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms