Tailor: a computational framework for detecting non-templated tailing of small silencing RNAs

Small silencing RNAs, including microRNAs, endogenous small interfering RNAs (endo-siRNAs) and Piwi-interacting RNAs (piRNAs), have been shown to play important roles in fine-tuning gene expression, defending virus and controlling transposons. Loss of small silencing RNAs or components in their pathways often leads to severe developmental defects, including lethality and sterility. Recently, non-templated addition of nucleotides to the 3\u27 end, namely tailing, was found to associate with the processing and stability of small silencing RNAs. Next Generation Sequencing has made it possible to detect such modifications at nucleotide resolution in an unprecedented throughput. Unfortunately, detecting such events from millions of short reads confounded by sequencing errors and RNA editing is still a tricky problem. Here, we developed a computational framework, Tailor, driven by an efficient and accurate aligner specifically designed for capturing the tailing events directly from the alignments without extensive post-processing. The performance of Tailor was fully tested and compared favorably with other general-purpose aligners using both simulated and real datasets for tailing analysis. Moreover, to show the broad utility of Tailor, we used Tailor to reanalyze published datasets and revealed novel findings worth further experimental validation. The source code and the executable binaries are freely available at https://github.com/jhhung/Tailor

Economic gains and health benefits from a new cigarette tax scheme in Taiwan: a simulation using the CGE model

BACKGROUND: This study evaluates the impact of an increase in cigarette tax in Taiwan in terms of the effects it has on the overall economy and the health benefits that it brings. METHODS: The multisector computable general equilibrium (CGE) model was used to simulate the impact of reduced cigarette consumption resulting from a new tax scheme on the entire economy gains and on health benefits. RESULTS: The results predict that because of the new tax scheme, there should be a marked reduction in cigarette consumption but a notable increase in health benefits that include saving between 28,125 and 56,250 lives. This could save NT$1.222~2.445 billion (where US$1 = NT$34.6) annually in life-threatening, cigarette-related health insurance expenses which exceeds the projected decrease of NT$1.275 billion in Gross Domestic Product (GDP) because of reduced consumption and therefore tax revenue. CONCLUSION: Overall, the increased cigarette excise tax will be beneficial in terms of both the health of the general public and the economy as a whole

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

The 5p15.33 Locus Is Associated with Risk of Lung Adenocarcinoma in Never-Smoking Females in Asia

Genome-wide association studies of lung cancer reported in populations of European background have identified three regions on chromosomes 5p15.33, 6p21.33, and 15q25 that have achieved genome-wide significance with p-values of 10−7 or lower. These studies have been performed primarily in cigarette smokers, raising the possibility that the observed associations could be related to tobacco use, lung carcinogenesis, or both. Since most women in Asia do not smoke, we conducted a genome-wide association study of lung adenocarcinoma in never-smoking females (584 cases, 585 controls) among Han Chinese in Taiwan and found that the most significant association was for rs2736100 on chromosome 5p15.33 (p = 1.30×10−11). This finding was independently replicated in seven studies from East Asia totaling 1,164 lung adenocarcinomas and 1,736 controls (p = 5.38×10−11). A pooled analysis achieved genome-wide significance for rs2736100. This SNP marker localizes to the CLPTM1L-TERT locus on chromosome 5p15.33 (p = 2.60×10−20, allelic risk = 1.54, 95% Confidence Interval (CI) 1.41–1.68). Risks for heterozygote and homozygote carriers of the minor allele were 1.62 (95% CI; 1.40–1.87), and 2.35 (95% CI: 1.95–2.83), respectively. In summary, our results show that genetic variation in the CLPTM1L-TERT locus of chromosome 5p15.33 is directly associated with the risk of lung cancer, most notably adenocarcinoma

Identification of IGF1, SLC4A4, WWOX, and SFMBT1 as Hypertension Susceptibility Genes in Han Chinese with a Genome-Wide Gene-Based Association Study

Hypertension is a complex disorder with high prevalence rates all over the world. We conducted the first genome-wide gene-based association scan for hypertension in a Han Chinese population. By analyzing genome-wide single-nucleotide-polymorphism data of 400 matched pairs of young-onset hypertensive patients and normotensive controls genotyped with the Illumina HumanHap550-Duo BeadChip, 100 susceptibility genes for hypertension were identified and also validated with permutation tests. Seventeen of the 100 genes exhibited differential allelic and expression distributions between patient and control groups. These genes provided a good molecular signature for classifying hypertensive patients and normotensive controls. Among the 17 genes, IGF1, SLC4A4, WWOX, and SFMBT1 were not only identified by our gene-based association scan and gene expression analysis but were also replicated by a gene-based association analysis of the Hong Kong Hypertension Study. Moreover, cis-acting expression quantitative trait loci associated with the differentially expressed genes were found and linked to hypertension. IGF1, which encodes insulin-like growth factor 1, is associated with cardiovascular disorders, metabolic syndrome, decreased body weight/size, and changes of insulin levels in mice. SLC4A4, which encodes the electrogenic sodium bicarbonate cotransporter 1, is associated with decreased body weight/size and abnormal ion homeostasis in mice. WWOX, which encodes the WW domain-containing protein, is related to hypoglycemia and hyperphosphatemia. SFMBT1, which encodes the scm-like with four MBT domains protein 1, is a novel hypertension gene. GRB14, TMEM56 and KIAA1797 exhibited highly significant differential allelic and expressed distributions between hypertensive patients and normotensive controls. GRB14 was also found relevant to blood pressure in a previous genetic association study in East Asian populations. TMEM56 and KIAA1797 may be specific to Taiwanese populations, because they were not validated by the two replication studies. Identification of these genes enriches the collection of hypertension susceptibility genes, thereby shedding light on the etiology of hypertension in Han Chinese populations

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

Meeting abstrac

Predicting the Mortality of ICU Patients by Topic Model with Machine-Learning Techniques

Predicting clinical patients’ vital signs is a leading critical issue in intensive care units (ICUs) related studies. Early prediction of the mortality of ICU patients can reduce the overall mortality and cost of complication treatment. Some studies have predicted mortality based on electronic health record (EHR) data by using machine learning models. However, the semi-structured data (i.e., patients’ diagnosis data and inspection reports) is rarely used in these models. This study utilized data from the Medical Information Mart for Intensive Care III. We used a Latent Dirichlet Allocation (LDA) model to classify text in the semi-structured data of some particular topics and established and compared the classification and regression trees (CART), logistic regression (LR), multivariate adaptive regression splines (MARS), random forest (RF), and gradient boosting (GB). A total of 46,520 ICU Patients were included, with 11.5% mortality in the Medical Information Mart for Intensive Care III group. Our results revealed that the semi-structured data (diagnosis data and inspection reports) of ICU patients contain useful information that can assist clinical doctors in making critical clinical decisions. In addition, in our comparison of five machine learning models (CART, LR, MARS, RF, and GB), the GB model showed the best performance with the highest area under the receiver operating characteristic curve (AUROC) (0.9280), specificity (93.16%), and sensitivity (83.25%). The RF, LR, and MARS models showed better performance (AUROC are 0.9096, 0.8987, and 0.8935, respectively) than the CART (0.8511). The GB model showed better performance than other machine learning models (CART, LR, MARS, and RF) in predicting the mortality of patients in the intensive care unit. The analysis results could be used to develop a clinically useful decision support system

Sweat Scanner [cystic fibrosis scanner]

Cystic Fibrosis (CF) is diagnosed by a sweat test and genetic testing. The sweat test is considered the gold standard for screening for CF due to its distinct symptom of five times the normal amount of sodium and chloride in patient’s sweat. This test involves inducing a sweat and sending the results to a lab for further analysis. This is an unrealistic standard for developing countries as the current infrastructure is not available to send lab samples from all the newborns to the lab.   Our Sweat Scanner has two major objectives. One is to create a user friendly and real time medical device that can be used to detect the amount of sodium and chloride that exists within a patient’s sweat in a non-invasive manner. The other goal is to provide an affordable and reliable screening test for CF in third countries. The product will be carefully designed in such a way that it is easy to use by any individual and will be able to provide consistent and accurate measurements of sodium and chloride content to provide reliable testing result. With the technology, CFTR solutions believes that we can help to fight cystic fibrosis