Previous economic analyses evaluating treatment of methicillin-resistant Staphylococcus aureus (MRSA) complicated skin and soft-tissue infections (cSSTI) failed to include all direct treatment costs such as outpatient parenteral antibiotic therapy (OPAT). Our objective was to develop an economic model from a US payer perspective that includes all direct inpatient and outpatient costs incurred by patients with MRSA cSSTI receiving linezolid, vancomycin, or daptomycin.
A 4-week decision model was developed for this economic analysis. Published literature and database analyses with validation by experts provided clinical, resource use, and cost inputs on data such as efficacy rate, length of stay, adverse events, and OPAT services. Base-case analysis assumed equal efficacy and equal length of stay for treatments. We conducted several sensitivity analyses where assumptions on resource use or efficacy were varied. Costs were reported in year-end 2011 US dollars.
Total treatment costs in the base-case were lower for linezolid ($10,571) than vancomycin ($11,096), and daptomycin ($13,612). Inpatient treatment costs were $740 more, but outpatient costs, $1,266 less with linezolid than vancomycin therapy due to a switch to oral linezolid when the patient was discharged. Compared with daptomycin, both inpatient and outpatient treatment costs were lower with linezolid by $87 and $2,954 respectively. In sensitivity analyses, linezolid had lower costs compared with vancomycin and daptomycin when using differential length of stay data from a clinical trial, and using success rates from a meta-analysis. In a scenario without peripherally inserted central catheter line costs, linezolid became slightly more expensive than vancomycin (by $285), but remained less costly than daptomycin (by $2,316).
Outpatient costs of managing MRSA cSSTI may be reduced by 30%–50% with oral linezolid compared with vancomycin or daptomycin. Results from this analysis support potential economic benefit and cost savings of using linezolid versus traditional OPAT when total inpatient and outpatient medical costs are evaluated.
economic model; OPAT; cost
The widespread use of clopidogrel alone or in combination with aspirin may result in gastrointestinal mucosal injury, clinically represented as recurrent ulceration and bleeding complications. Our recent work suggested that clopidogrel significantly induced human gastric epithelial cell (GES-1) apoptosis and disrupted gastric mucosal barrier, and that a p38 MAPK inhibitor could attenuate such injury. However, their exact mechanisms are largely unknown.
The GES-1 cells were used as a model system, the effects of clopidogrel on the whole gene expression profile were evaluated by human gene expression microarray and gene ontology analysis, changes of the mRNA and protein expression were determined by real-time PCR and Western blot analysis, and cell viability and apoptosis were measured by MTT assay and flow cytometry analysis, respectively.
Gene microarray analysis identified 79 genes that were differentially expressed (P<0.05 and fold-change >3) when cells were treated with or without clopidogrel. Gene ontology analysis revealed that response to stress and cell apoptosis dysfunction were ranked in the top 10 cellular events being affected, and that the major components of endoplasmic reticulum stress-mediated apoptosis pathway – CHOP and TRIB3– were up-regulated in a concentration- and time-dependent manner when cells were treated with clopidogrel. Pathway analysis demonstrated that multiple MAPK kinases were phosphorylated in clopidogrel-treated GES-1 cells, but that only SB-203580 (a p38-specific MAPK inhibitor) attenuated cell apoptosis and CHOP over-expression, both of which were induced by clopidogrel.
Increased endoplasmic reticulum stress response is involved in clopidogrel-induced gastric mucosal injury, acting through p38 MAPK activation.
Cellular signaling networks are complex and appear to include many nonfunctional elements. Recently, it was suggested that nonfunctional interactions of proteins cause signaling noise, which, perhaps, shapes the signal transduction mechanism. However, the conditions under which molecular noise influences cellular information processing remain unclear. Here, we explore a large number of simple biological models of varying network sizes to understand the architectural conditions under which the interactions of signaling proteins can exhibit specific stochastic effects—called deviant effects—in which the average behavior of a biological system is substantially altered in the presence of molecular noise. We find that a small fraction of these networks does exhibit deviant effects and shares a common architectural feature whereas most of the networks show only insignificant levels of deviations. Interestingly, addition of seemingly unimportant interactions into protein networks gives rise to deviant effects.
While studies suggest optimism can predict health outcomes, the relationship has not been tested in women with pelvic organ prolapse (POP). This study seeks to (1) explore the relationship between optimism, prolapse severity, and symptoms before surgery; and (2) examine whether optimism predicts post-surgical functional status, treatment satisfaction, and treatment success.
Data from the randomized Colpopexy And Urinary Reduction Efforts (CARE) study in which stress continent women undergoing sacrocolpopexy to repair Stage II-IV POP completed a baseline assessment of optimism and validated symptom and quality of life (QOL) measures at baseline and 24-months. Relationships between optimism and demographics, clinical status, and functional and QOL outcomes were assessed.
Of 322 CARE participants, 305 (94.7%) completed 24-month follow-up interviews. At baseline, there were no significant differences in optimism with respect to POP stage or history of prior surgery for prolapse or urinary incontinence. At baseline, women with greater optimism reported significantly better physical and mental functioning (p≤0.001), and less symptom distress (p≤0.01). Two years after surgery, the difference in symptom experience across the three optimism categories narrowed as all women reported improved health status, fewer symptoms, and less impact on daily activities. Satisfaction with treatment and perception of treatment success were not associated with optimism.
In women planning surgery for POP, optimism is related to pelvic symptom severity but is not associated with satisfaction with treatment or treatment success. Abdominal sacrocolpopexy resulted in substantial improvements in QOL and functional outcomes that were not significantly influenced by optimism.
Background and Aims
Brain dysfunction in functional dyspepsia (FD) has been identified by multiple neuroimaging studies. This study aims to investigate the regional gray matter density (GMD) changes in meal-related FD patients and their correlations with clinical variables, and to explore the possible influence of the emotional state on FD patients’s brain structures.
Fifty meal-related FD patients and forty healthy subjects (HS) were included and underwent a structural magnetic resonance imaging scan. Voxel-based morphometry analysis was employed to identify the cerebral structure alterations in meal-related FD patients. Regional GMD changes' correlations with the symptoms and their durations, respectively, have been analyzed.
Compared to the HS, the meal-related FD patients showed a decreased GMD in the bilateral precentral gyrus, medial prefrontal cortex (MPFC), anterior cingulate cortex (ACC) and midcingulate cortex (MCC), left orbitofrontal cortex (OFC) and right insula (p<0.05, FWE Corrected, Cluster size>50). After controlling for anxiety and depression, the meal-related FD patients showed a decreased GMD in the bilateral middle frontal gyrus, left MCC, right precentral gyrus and insula (p<0.05, FWE Corrected, Cluster size>50). Before controlling psychological factors, the GMD decreases in the ACC were negatively associated with the symptom scores of the Nepean Dyspepsia Index (NDI) (r = −0.354, p = 0.048, Bonferroni correction) and the duration of FD (r = −0.398, p = 0.02, Bonferroni correction) respectively.
The regional GMD of meal-related FD patients, especially in the regions of the homeostatic afferent processing network significantly differed from that of the HS, and the psychological factors might be one of the essential factors significantly affecting the regional brain structure of meal-related FD patients.
Nonalcoholic fatty liver disease (NAFLD) is closely associated with type 2 diabetes mellitus. We investigated whether the deposition of fat in the liver is associated with glycemic abnormalities and evaluated the contribution of the liver fat content (LFC) to the impaired glucose regulation. We conducted a community-based study among 2836 residents (1018 males and 1818 females) without prior known diabetes mellitus from the Changfeng Study who were at least 45 years old. A standard interview, anthropometrics and laboratory parameters were performed for each participant. The standardised ultrasound hepatic-renal echo-intensity and hepatic echo-intensity attenuation rate were used to assess the LFC. The cohort was stratified according to the quintiles for LFC. Two-hour glucose and fasting blood glucose increased across the LFC quintiles after adjustment for age and gender. LFC increased continuously among glucose categories after adjustment for age and gender (NGT: 7.7±0.3%, IFG: 10.0±0.8%, IGT: 11.8±0.5%, IFG+IGT: 11.7±0.9%, new- DM: 12.4±0.6%, P<0.001). By logistic regression analysis, 1% LFC increment independently predicted prediabetes and diabetes (OR 1.032, 1.019–1.045, P<0.001; 1.021, 1.005–1.037, P = 0.012, respectively) after adjustment for all potential confounders. Furthermore, participants with LFC higher than 10% had higher odds ratios of impaired glucose regulation as compared with those with LFC below 10% in fully adjusted logistic models. These results suggest that the LFC is strongly associated with impaired glucose regulation in the Chinese population, and that an even slightly elevated LFC is associated with increased glucose dysregulation.
Motivation: Polyadenylation is the addition of a poly(A) tail to an RNA molecule. Identifying DNA sequence motifs that signal the addition of poly(A) tails is essential to improved genome annotation and better understanding of the regulatory mechanisms and stability of mRNA.
Existing poly(A) motif predictors demonstrate that information extracted from the surrounding nucleotide sequences of candidate poly(A) motifs can differentiate true motifs from the false ones to a great extent. A variety of sophisticated features has been explored, including sequential, structural, statistical, thermodynamic and evolutionary properties. However, most of these methods involve extensive manual feature engineering, which can be time-consuming and can require in-depth domain knowledge.
Results: We propose a novel machine-learning method for poly(A) motif prediction by marrying generative learning (hidden Markov models) and discriminative learning (support vector machines). Generative learning provides a rich palette on which the uncertainty and diversity of sequence information can be handled, while discriminative learning allows the performance of the classification task to be directly optimized. Here, we used hidden Markov models for fitting the DNA sequence dynamics, and developed an efficient spectral algorithm for extracting latent variable information from these models. These spectral latent features were then fed into support vector machines to fine-tune the classification performance.
We evaluated our proposed method on a comprehensive human poly(A) dataset that consists of 14 740 samples from 12 of the most abundant variants of human poly(A) motifs. Compared with one of the previous state-of-the-art methods in the literature (the random forest model with expert-crafted features), our method reduces the average error rate, false-negative rate and false-positive rate by 26, 15 and 35%, respectively. Meanwhile, our method makes ∼30% fewer error predictions relative to the other string kernels. Furthermore, our method can be used to visualize the importance of oligomers and positions in predicting poly(A) motifs, from which we can observe a number of characteristics in the surrounding regions of true and false motifs that have not been reported before.
firstname.lastname@example.org or email@example.com
Supplementary data are available at Bioinformatics online.
Motivation: Systematic and scalable parameter estimation is a key to construct complex gene regulatory models and to ultimately facilitate an integrative systems biology approach to quantitatively understand the molecular mechanisms underpinning gene regulation.
Results: Here, we report a novel framework for efficient and scalable parameter estimation that focuses specifically on modeling of gene circuits. Exploiting the structure commonly found in gene circuit models, this framework decomposes a system of coupled rate equations into individual ones and efficiently integrates them separately to reconstruct the mean time evolution of the gene products. The accuracy of the parameter estimates is refined by iteratively increasing the accuracy of numerical integration using the model structure. As a case study, we applied our framework to four gene circuit models with complex dynamics based on three synthetic datasets and one time series microarray data set. We compared our framework to three state-of-the-art parameter estimation methods and found that our approach consistently generated higher quality parameter solutions efficiently. Although many general-purpose parameter estimation methods have been applied for modeling of gene circuits, our results suggest that the use of more tailored approaches to use domain-specific information may be a key to reverse engineering of complex biological systems.
Supplementary data are available at Bioinformatics online.
Arginine is a semiessential amino acid required for the growth of melanoma and hepatocellular carcinoma, and the enzymatic removal of arginine by pegylated arginine deiminase (ADI) or arginase is being tested clinically. Here, we report a genetically engineered arginase FC fusion protein exhibiting a prolonged half-life and enhanced efficacy. The use of this enzyme to treat different tumor lines both inhibited cell proliferation and impaired cellular migration in vitro and in vivo. Our data reinforce the hypothesis that nutritional depletion is a key strategy for cancer treatment.
There are remarkable disparities among patients of different races with prostate cancer; however, the mechanism underlying this difference remains unclear. Here, we present a comprehensive landscape of the transcriptome profiles of 14 primary prostate cancers and their paired normal counterparts from the Chinese population using RNA-seq, revealing tremendous diversity across prostate cancer transcriptomes with respect to gene fusions, long noncoding RNAs (long ncRNA), alternative splicing and somatic mutations. Three of the 14 tumors (21.4%) harbored a TMPRSS2-ERG fusion, and the low prevalence of this fusion in Chinese patients was further confirmed in an additional tumor set (10/54=18.5%). Notably, two novel gene fusions, CTAGE5-KHDRBS3 (20/54=37%) and USP9Y-TTTY15 (19/54=35.2%), occurred frequently in our patient cohort. Further systematic transcriptional profiling identified numerous long ncRNAs that were differentially expressed in the tumors. An analysis of the correlation between expression of long ncRNA and genes suggested that long ncRNAs may have functions beyond transcriptional regulation. This study yielded new insights into the pathogenesis of prostate cancer in the Chinese population.
prostate cancer; RNA sequencing; gene fusions; long ncRNAs; alternative splicing
Oxidative stress (OS) plays a role in hyperglycemia induced islet β cell dysfunction, however, studies on classic anti-oxidants didn’t show positive results in treating diabetes. We previously demonstrated that the prescribed Chinese herbal medicine preparation “Qing Huo Yi Hao” (QHYH) improved endothelial function in type 2 diabetic patients. QHYH protected endothelial cells from high glucose-induced damages by scavenging superoxide anion and reducing production of reactive oxygen species. Its active component protected C2C12 myotubes against palmitate-induced oxidative damage and mitochondrial dysfunction. In the present study, we investigated whether QHYH protected islet β cell function exacerbated by high fat diet (HFD) in hyperglycemic GK rats. 4-week-old male rats were randomly divided into high HFD feeding group (n = 20) and chow diet feeding group (n = 10). Each gram of HFD contained 4.8 kcal of energy, 52% of which from fat. Rats on HFD were further divided into 2 groups given either QHYH (3 ml/Kg/d) or saline through gastric tube. After intervention, serum glucose concentrations were monitored; IPGTTs were performed without anesthesia on 5 fasting rats randomly chosen from each group on week 4 and 16. Serum malondialdehyde (MDA) concentrations and activities of serum antioxidant enzymes were measured on week 4 and 16. Islet β cell mass and OS marker staining was done by immunohistochemistry on week 16. QHYH prevented the exacerbation of hyperglycemia in HFD feeding GK rats for 12 weeks. On week 16, it improved the exacerbated glucose tolerance and prevented the further loss of islet β cell mass induced by HFD. QHYH markedly decreased serum MDA concentration, increased serum catalase (CAT) and SOD activities on week 4. However, no differences of serum glucose concentration or OS were observed on week 16. We concluded that QHYH decreased hyperglycemia exacerbated by HFD in GK rats by improving β cell function partly via its antioxidant effect.
Genome-wide association studies (GWAS) have identified more than 30 single nucleotide polymorphisms (SNPs) that were reproducibly associated with prostate cancer (PCa) risk in populations of European descent. In aggregate, these variants have shown potential to predict risk for PCa in European men. However, their utility for PCa risk prediction in Chinese men is unknown.
We selected 33 PCa risk-related SNPs that were originally identified in populations of European descent. Genetic scores were estimated for subjects in a Chinese case-control study (1,108 cases and 1,525 controls) based on these SNPs. To assess the performance of the genetic score on its ability to predict risk for PCa, we calculated Area under the curve (AUC) of the receiver operating characteristic (ROC) in combination with 10-fold cross-validation.
The genetic score was significantly higher for cases than controls (P = 5.91×10-20), and was significantly associated with risk of PCa in a dose-dependent manner (P for trend: 4.78×10-18). The AUC of the genetic score was 0.604 for risk prediction of PCa in Chinese men. When ORs derived from this Chinese study population were used to calculate genetic score, the AUCs were 0.631 for all 33 SNPs and 0.617 when using only the 11 significant SNPs.
Our results indicate that genetic variants related to PCa risk may be useful for risk prediction in Chinese men. Prospective studies are warranted to further evaluate these findings.
Genetic score; Cumulative risk; Prostate cancer; AUC; Risk prediction; Susceptibility; Chinese
Background and Purpose
Laparoendoscopic single-site (LESS) surgery through the retroperitoneal approach has been seldom reported. We aimed to compare the feasibility and outcomes of LESS and conventional laparoscopic surgery via the retroperitoneal approach in the management of large, impacted ureteral stones.
Patients and Methods
From June 2010 to May 2011, LESS ureterolithotomy through the retroperitoneal approach was performed in 10 patients (the LESS group). Another 15 patients who underwent conventional retroperitoneal laparoscopic ureterolithotomy (the conventional laparoscopic group) by the same surgeon were involved and compared. The operative time, complications, and surgical outcomes were evaluated.
All the operations were completed successfully, without conversion to conventional laparoscopic or open surgeries. The operative time of the LESS group and of the conventional laparoscopic group were 132.7±16.3 and 128.1±20.1 minutes, respectively (P=0.782). The estimated blood loss were 30.7±5.9 vs 28.0±4.5 mL (P=0.620). Duration of analgesia postoperatively was 2.0±0.8 vs 3.5±0.5 days (P=0.005). All targeted stones were successfully extracted without major complications. Postoperative urine leakage was noted in one patient in each group. Cosmetic results were superior in the LESS group according to both the study nurse's and the patients' assessments (8.5 vs 5.3; P=0.012, and 8.3 vs 5.6; P=0.025, respectively). All patients showed no obstructions or stricture formations on postoperative follow-up.
In experienced hands, LESS for ureterolithotomy through the retroperitoneal approach is feasible and can acquire outcomes equal to those of conventional multiport laparoscopic surgery. Prospective long-term follow-up studies with a larger number of patients are needed to further evaluate its benefits.
Non-negative matrix factorization (NMF) has been shown to be a powerful tool for clustering gene expression data, which are widely used to classify cancers. NMF aims to find two non-negative matrices whose product closely approximates the original matrix. Traditional NMF methods minimize either the l2 norm or the Kullback-Leibler distance between the product of the two matrices and the original matrix. Correntropy was recently shown to be an effective similarity measurement due to its stability to outliers or noise.
We propose a maximum correntropy criterion (MCC)-based NMF method (NMF-MCC) for gene expression data-based cancer clustering. Instead of minimizing the l2 norm or the Kullback-Leibler distance, NMF-MCC maximizes the correntropy between the product of the two matrices and the original matrix. The optimization problem can be solved by an expectation conditional maximization algorithm.
Extensive experiments on six cancer benchmark sets demonstrate that the proposed method is significantly more accurate than the state-of-the-art methods in cancer clustering.
A wide range of microalbuminuria cutoff values are currently used for diagnosing the early stage of nephropathy in type 2 diabetes (T2D). This study analyzed the relationships between oxidant and antioxidant markers of nephropathy and the severity of microalbuminuria. The study included 50 healthy controls (Group 1), 50 diabetic patients with no nephropathy (Group 2), 50 diabetic patients with nephropathy and a urinary albumin excretion (UAE) of 30–200 mg/24 h (Group 3), and 50 diabetic patients with UAE 200–300 mg/24 h (Group 4). Serum nitrotyrosine, conjugated dienes, 8-hydroxy-2′-deoxyguanosine (8-OHdG), superoxide dismutase (SOD), and total antioxidant capacity (T-AOC) levels were determined. Oxidative stress is increased in the early stage of nephropathy in patients with T2D. There was a significant correlation between the extent of microalbuminuria and markers of oxidative stress. Multiple linear regression analysis identified lipid oxidative stress as a possible independent marker for evaluating the degree of renal damage in diabetic nephropathy. Stratifying microalbuminuria values during the early stage of nephropathy might be an important factor in facilitating earlier and more specific interventions.
More than 30 prostate cancer (PCa) risk-associated loci have been identified in populations of European descent by genome-wide association studies (GWAS). We hypothesized that a subset of these loci may be associated with PCa risk in Chinese men. To test this hypothesis, 33 single nucleotide polymorphisms (SNPs), one each from the 33 independent PCa risk-associated loci reported in populations of European descent, were investigated for their associations with PCa risk in a case-control study of Chinese men (1,108 cases and 1,525 controls). We found that 11 of the 33 SNPs were significantly associated with PCa risk in Chinese men (P < 0.05). The reported risk alleles were associated with increased risk for PCa, with allelic odds ratios ranging from 1.12 to 1.44. The most significant locus was located on 8q24 Region 2 (rs16901979, P = 5.14×10−9) with a genome-wide significance (P < 10−8), and three loci reached the Bonferroni correction significance level (P < 1.52×10−3), including 8q24 Region 1 (rs1447295, P = 7.04×10−6), 8q24 Region 5 (rs10086908, P = 9.24×10−4), and 8p21 (rs1512268, P = 9.39×10−4). Our results suggest that a subset of the PCa risk-associated SNPs discovered by GWAS among men of European descent is also associated with PCa risk in Chinese men. This finding provides evidence of ethnic differences and similarity in genetic susceptibility to PCa. GWAS in Chinese men are needed to identify Chinese-specific PCa risk-associated SNPs.
Cooperia oncophora and Ostertagia ostertagi are among the most important gastrointestinal nematodes of cattle worldwide. The economic losses caused by these parasites are on the order of hundreds of millions of dollars per year. Conventional treatment of these parasites is through anthelmintic drugs; however, as resistance to anthelmintics increases, overall effectiveness has begun decreasing. New methods of control and alternative drug targets are necessary. In-depth analysis of transcriptomic data can help provide these targets.
The assembly of 8.7 million and 11 million sequences from C. oncophora and O. ostertagi, respectively, resulted in 29,900 and 34,792 transcripts. Among these, 69% and 73% of the predicted peptides encoded by C. oncophora and O. ostertagi had homologues in other nematodes. Approximately 21% and 24% were constitutively expressed in both species, respectively; however, the numbers of transcripts that were stage specific were much smaller (~1% of the transcripts expressed in a stage). Approximately 21% of the transcripts in C. oncophora and 22% in O. ostertagi were up-regulated in a particular stage. Functional molecular signatures were detected for 46% and 35% of the transcripts in C. oncophora and O. ostertagi, respectively. More in-depth examinations of the most prevalent domains led to knowledge of gene expression changes between the free-living (egg, L1, L2 and L3 sheathed) and parasitic (L3 exsheathed, L4, and adult) stages. Domains previously implicated in growth and development such as chromo domains and the MADF domain tended to dominate in the free-living stages. In contrast, domains potentially involved in feeding such as the zinc finger and CAP domains dominated in the parasitic stages. Pathway analyses showed significant associations between life-cycle stages and peptides involved in energy metabolism in O. ostertagi whereas metabolism of cofactors and vitamins were specifically up-regulated in the parasitic stages of C. oncophora. Substantial differences were observed also between Gene Ontology terms associated with free-living and parasitic stages.
This study characterized transcriptomes from multiple life stages from both C. oncophora and O. ostertagi. These data represent an important resource for studying these parasites. The results of this study show distinct differences in the genes involved in the free-living and parasitic life cycle stages. The data produced will enable better annotation of the upcoming genome sequences and will allow future comparative analyses of the biology, evolution and adaptation to parasitism in nematodes.
Cattle; Parasite; Nematode; Transcripts; Ostertagia ostertagi; Cooperia oncophora; Comparative genomics
Although the association between alanine aminotransferase (ALT) levels and risk of type 2 diabetes is well-studied, the effects of slightly increased ALT levels within the normal range on the temporal normal glucose profile remains poorly understood.
A total of 322 Chinese subjects without impaired glucose tolerance or previous diagnoses of diabetes were recruited for study from 10 hospitals in urban areas across China. All subjects wore a continuous glucose monitoring (CGM) system for three consecutive days. The diurnal (06∶00–20∶00) and nocturnal (20∶00–06∶00) mean blood glucose (MBG) levels were calculated. Subjects were stratified by ALT quartile level and correlation analyses were performed.
The median ALT level was 17 IU/L, and subjects with ALT ≥17 IU/L had higher nocturnal MBG level than those with ALT <17 IU/L (P<0.05). Nocturnal MBG was positively correlated with ALT levels (Pearson correlation analysis: r = 0.187, P = 0.001), and the correlation remained significant after correction for the homeostatic model assessment of insulin resistance index (HOMA-IR) (r = 0.105, P = 0.041). No correlations were found between diurnal MBG and ALT, and nocturnal or diurnal MBG and aspartate aminotransferase or gamma-glutamyltransferase (all, P>0.05). Multivariate stepwise regression analysis of elevated nocturnal MBG identified increased HOMA-IR, elevated ALT levels, and decreased homeostatic model assessment of ß-cell function as independent factors (all, P<0.05).
Mildly elevated ALT levels, within the normal range, are associated with unfavorable nocturnal glucose profiles in Chinese subjects with normal glucose regulation.
A recent genome-wide association study has identified five new genetic variants for prostate cancer susceptibility in a Japanese population, but it is unknown whether these newly identified variants are associated with prostate cancer risk in other populations, including Chinese men. We genotyped these five variants in a case–control study of 1524 patients diagnosed with prostate cancer and 2169 control subjects from the Chinese Consortium for Prostate Cancer Genetics (ChinaPCa). We found that three of the five genetic variants were associated with prostate cancer risk (P = 4.33 × 10−8 for rs12653946 at 5p15, 4.43 × 10−5 for rs339331 at 6q22 and 8.42 × 10−4 for rs9600079 at 13q22, respectively). A cumulative effect was observed in a dose-dependent manner with increasing numbers of risk variant alleles (Ptrend = 2.58 × 10−13), and men with 5–6 risk alleles had a 2-fold higher risk of prostate cancer than men with 0–2 risk alleles (odds ratio = 2.26, 95% confidence interval = 1.78–2.87). Furthermore, rs339331 T allele was significantly associated with RFX6 and GPRC6A higher messenger RNA expression, compared with the C allele. However, none of the variants was associated with clinical stage, Gleason score or family history. These results provide further evidence that the risk loci identified in Japanese men also contribute to prostate cancer susceptibility in Chinese men.
Few data are available regarding the epidemiology of invasive aspergillosis (IA) in ICU patients. The aim of this study was to examine epidemiology and economic outcomes (length of stay, hospital costs) among ICU patients with IA who lack traditional risk factors for IA, such as cancer, transplants, neutropenia or HIV infection.
Retrospective cohort study using Premier Inc. Perspective™ US administrative hospital database (2005–2008). Adults with ICU stays and aspergillosis (ICD-9 117.3 plus 484.6) who received initial antifungal therapy (AF) in the ICU were included. Patients with traditional risk factors (cancer, transplant, neutropenia, HIV/AIDS) were excluded. The relationship of antifungal therapy and co-morbidities to economic outcomes were examined using Generalized linear models.
From 6,424 aspergillosis patients in the database, 412 (6.4%) ICU patients with IA were identified. Mean age was 63.9 years and 53% were male. Frequent co-morbidities included steroid use (77%), acute respiratory failure (76%) and acute renal failure (41%). In-hospital mortality was 46%. The most frequently used AF was voriconazole (71% received at least once). Mean length of stay (LOS) was 26.9 days and mean total hospital cost was $76,235. Each 1 day lag before initiating AF therapy was associated with 1.28 days longer hospital stay and 3.5% increase in costs (p < 0.0001 for both).
Invasive aspergillosis in ICU patients is associated with high mortality and hospital costs. Antifungal timing impacts economic outcomes. These findings underscore the importance of timely diagnosis, appropriate treatment, and consideration of Aspergillus as a potential etiology in ICU patients.
Aspergillosis; Voriconazole; Fluconazole; ICU; Length of stay; Hospital costs
A common issue in bioinformatics is that computational methods often generate a large number of predictions sorted according to certain confidence scores. A key problem is then determining how many predictions must be selected to include most of the true predictions while maintaining reasonably high precision. In nuclear magnetic resonance (NMR)-based protein structure determination, for instance, computational peak picking methods are becoming more and more common, although expert-knowledge remains the method of choice to determine how many peaks among thousands of candidate peaks should be taken into consideration to capture the true peaks. Here, we propose a Benjamini-Hochberg (B-H)-based approach that automatically selects the number of peaks. We formulate the peak selection problem as a multiple testing problem. Given a candidate peak list sorted by either volumes or intensities, we first convert the peaks into -values and then apply the B-H-based algorithm to automatically select the number of peaks. The proposed approach is tested on the state-of-the-art peak picking methods, including WaVPeak  and PICKY . Compared with the traditional fixed number-based approach, our approach returns significantly more true peaks. For instance, by combining WaVPeak or PICKY with the proposed method, the missing peak rates are on average reduced by 20% and 26%, respectively, in a benchmark set of 32 spectra extracted from eight proteins. The consensus of the B-H-selected peaks from both WaVPeak and PICKY achieves 88% recall and 83% precision, which significantly outperforms each individual method and the consensus method without using the B-H algorithm. The proposed method can be used as a standard procedure for any peak picking method and straightforwardly applied to some other prediction selection problems in bioinformatics. The source code, documentation and example data of the proposed method is available at http://sfb.kaust.edu.sa/pages/software.aspx.
It is desirable in genomic studies to select biomarkers that differentiate between normal and diseased populations based on related data sets from different platforms, including microarray expression and proteomic data. Most recently developed integration methods focus on correlation analyses between gene and protein expression profiles. The correlation methods select biomarkers with concordant behavior across two platforms but do not directly select differentially expressed biomarkers. Other integration methods have been proposed to combine statistical evidence in terms of ranks and p-values, but they do not account for the dependency relationships among the data across platforms.
In this paper, we propose an integration method to perform hypothesis testing and biomarkers selection based on multi-platform data sets observed from normal and diseased populations. The types of test statistics can vary across the platforms and their marginal distributions can be different. The observed test statistics are aggregated across different data platforms in a weighted scheme, where the weights take into account different variabilities possessed by test statistics. The overall decision is based on the empirical distribution of the aggregated statistic obtained through random permutations.
In both simulation studies and real biological data analyses, our proposed method of multi-platform integration has better control over false discovery rates and higher positive selection rates than the uncombined method. The proposed method is also shown to be more powerful than rank aggregation method.
As advances in life sciences and information technology bring profound influences on bioinformatics due to its interdisciplinary nature, bioinformatics is experiencing a new leap-forward from in-house computing infrastructure into utility-supplied cloud computing delivered over the Internet, in order to handle the vast quantities of biological data generated by high-throughput experimental technologies. Albeit relatively new, cloud computing promises to address big data storage and analysis issues in the bioinformatics field. Here we review extant cloud-based services in bioinformatics, classify them into Data as a Service (DaaS), Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS), and present our perspectives on the adoption of cloud computing in bioinformatics.
This article was reviewed by Frank Eisenhaber, Igor Zhulin, and Sandor Pongor.
Cloud computing; Bioinformatics; Big data; Data storage; Data analysis
EuPathDB (http://eupathdb.org) resources include 11 databases supporting eukaryotic pathogen genomic and functional genomic data, isolate data and phylogenomics. EuPathDB resources are built using the same infrastructure and provide a sophisticated search strategy system enabling complex interrogations of underlying data. Recent advances in EuPathDB resources include the design and implementation of a new data loading workflow, a new database supporting Piroplasmida (i.e. Babesia and Theileria), the addition of large amounts of new data and data types and the incorporation of new analysis tools. New data include genome sequences and annotation, strand-specific RNA-seq data, splice junction predictions (based on RNA-seq), phosphoproteomic data, high-throughput phenotyping data, single nucleotide polymorphism data based on high-throughput sequencing (HTS) and expression quantitative trait loci data. New analysis tools enable users to search for DNA motifs and define genes based on their genomic colocation, view results from searches graphically (i.e. genes mapped to chromosomes or isolates displayed on a map) and analyze data from columns in result tables (word cloud and histogram summaries of column content). The manuscript herein describes updates to EuPathDB since the previous report published in NAR in 2010.