Clinical, pathological and loss of heterozygosity differences in Wilms tumors between Asian and non-Asian children.

Wilms tumor demonstrates significant interethnic epidemiological, histological and outcome differences, and is rare and poorly studied among Asians. We compared the clinicopathological, and loss of heterozygosity (LOH) profile and survival outcomes of Asian and non-Asian patients with Wilms tumor. Clinical charts and histological slides from patients with malignant renal tumors over a period of 20 years were retrospectively reviewed. We adapted a genotyping assay to determine 1p36 and 16q21-22 LOH in formalin-fixed paraffin-embedded (FFPE) specimens, and compared these characteristics between Asian and non-Asian patients. Fifty-three (79.1%) Asian and 14 (20.9%) non-Asian patients had Wilms tumors. Compared to non-Asians, Asians were younger (mean 4.6 and 4.0 years, respectively), had more equal gender distribution (female: male = 1.8 and 1.0, respectively), fewer tumors with unfavorable histology (25.0% and 4.1%, respectively, p = 0.05), and less advanced disease at presentation, yet similar nodal metastases rates (16.7% and 18.4%, respectively). No Asian patients had bilateral tumors. Our adapted genotyping assay accurately determined LOH in FFPE specimens <10 years post-fixation. Among 30 Asian patients, 1p and 16q LOH were each detected in 5 (16.7%) patients, respectively-similar to rates reported in other ethnicities. Yet after similar treatment with National Wilms Tumor Study regimens, 15-year event-free and overall survival for Asian patients was 95.7% and 96.3% respectively. In summary, despite similar nodal metastasis and LOH rates, Asian patients had fewer unfavorable histology tumors, lower-stage disease, and better survival outcomes. The bases for these differences and implications on treatment strategy for these patients warrant further study.

Use of medical administrative data for the surveillance of psychotic disorders in France.

BACKGROUND: Psychotic disorders are among the most severe psychiatric disorders that have great effects on the individuals and the society. For surveillance of chronic low prevalence conditions such as psychotic disorders, medical administrative databases can be useful due to their large coverage of the population, their continuous availability and low costs with possibility of linkage between different databases. The aims of this study are to identify the population with psychotic disorders by different algorithms based on the French medical administrative data and examine the prevalence and characteristics of this population in 2014. METHODS: The health insurance system covers the entire population living in France and all reimbursements of ambulatory care in private practice are included in a national health insurance claim database, which can be linked with the national hospital discharge databases. Three algorithms were used to select most appropriately persons with psychotic disorders through data from hospital discharge databases, reimbursements for psychotropic medication and full insurance coverage for chronic and costly conditions. RESULTS: In France in 2014, estimates of the number of individuals with psychotic disorders were 469,587 (54.6% males) including 237,808 with schizophrenia (63.6% males). Of those, 77.0% with psychotic disorders and 70.8% with schizophrenia received exclusively ambulatory care. Prevalence rates of psychotic disorders were 7.4 per 1000 inhabitants (8.3 in males and 6.4 in females) and 3.8 per 1000 inhabitants (4.9 in males and 2.6 in females) for schizophrenia. Prevalence of psychotic disorders reached a maximum of 14 per 1000 in males between 35 and 49 years old then decreased with age while in females, the highest rate of 10 per 1000 was reached at age 50 without decrease with advancing age. No such plateau was observed in schizophrenia. DISCUSSION: This study is the first in France using an exhaustive sample of medical administrative data to derive prevalence rates for psychotic disorders. Although only individuals in contact with healthcare services were included, the rates were congruent with reported estimates from systematic reviews. The feasibility of this study will allow the implementation of a national surveillance of psychotic disorders essential for healthcare management and policy planning.

Predicting drug-target interaction for new drugs using enhanced similarity measures and super-target clustering.

Predicting drug-target interaction using computational approaches is an important step in drug discovery and repositioning. To predict whether there will be an interaction between a drug and a target, most existing methods identify similar drugs and targets in the database. The prediction is then made based on the known interactions of these drugs and targets. This idea is promising. However, there are two shortcomings that have not yet been addressed appropriately. Firstly, most of the methods only use 2D chemical structures and protein sequences to measure the similarity of drugs and targets respectively. However, this information may not fully capture the characteristics determining whether a drug will interact with a target. Secondly, there are very few known interactions, i.e. many interactions are "missing" in the database. Existing approaches are biased towards known interactions and have no good solutions to handle possibly missing interactions which affect the accuracy of the prediction. In this paper, we enhance the similarity measures to include non-structural (and non-sequence-based) information and introduce the concept of a "super-target" to handle the problem of possibly missing interactions. Based on evaluations on real data, we show that our similarity measure is better than the existing measures and our approach is able to achieve higher accuracy than the two best existing algorithms, WNN-GIP and KBMF2K. Our approach is available at http://web.hku.hk/∼liym1018/projects/drug/drug.html or http://www.bmlnwpu.org/us/tools/PredictingDTI_S2/METHODS.html.

misFinder: identify mis-assemblies in an unbiased manner using reference and paired-end reads.

BACKGROUND: Because of the short read length of high throughput sequencing data, assembly errors are introduced in genome assembly, which may have adverse impact to the downstream data analysis. Several tools have been developed to eliminate these errors by either 1) comparing the assembled sequences with some similar reference genome, or 2) analyzing paired-end reads aligned to the assembled sequences and determining inconsistent features alone mis-assembled sequences. However, the former approach cannot distinguish real structural variations between the target genome and the reference genome while the latter approach could have many false positive detections (correctly assembled sequence being considered as mis-assembled sequence). RESULTS: We present misFinder, a tool that aims to identify the assembly errors with high accuracy in an unbiased way and correct these errors at their mis-assembled positions to improve the assembly accuracy for downstream analysis. It combines the information of reference (or close related reference) genome and aligned paired-end reads to the assembled sequence. Assembly errors and correct assemblies corresponding to structural variations can be detected by comparing the genome reference and assembled sequence. Different types of assembly errors can then be distinguished from the mis-assembled sequence by analyzing the aligned paired-end reads using multiple features derived from coverage and consistence of insert distance to obtain high confident error calls. CONCLUSIONS: We tested the performance of misFinder on both simulated and real paired-end reads data, and misFinder gave accurate error calls with only very few miscalls. And, we further compared misFinder with QUAST and REAPR. misFinder outperformed QUAST and REAPR by 1) identified more true positive mis-assemblies with very few false positives and false negatives, and 2) distinguished the correct assemblies corresponding to structural variations from mis-assembled sequence. misFinder can be freely downloaded from https://github.com/hitbio/misFinder.

DDGni: dynamic delay gene-network inference from high-temporal data using gapped local alignment.

MOTIVATION: Inferring gene-regulatory networks is very crucial in decoding various complex mechanisms in biological systems. Synthesis of a fully functional transcriptional factor/protein from DNA involves series of reactions, leading to a delay in gene regulation. The complexity increases with the dynamic delay induced by other small molecules involved in gene regulation, and noisy cellular environment. The dynamic delay in gene regulation is quite evident in high-temporal live cell lineage-imaging data. Although a number of gene-network-inference methods are proposed, most of them ignore the associated dynamic time delay. RESULTS: Here, we propose DDGni (dynamic delay gene-network inference), a novel gene-network-inference algorithm based on the gapped local alignment of gene-expression profiles. The local alignment can detect short-term gene regulations, that are usually overlooked by traditional correlation and mutual Information based methods. DDGni uses 'gaps' to handle the dynamic delay and non-uniform sampling frequency in high-temporal data, like live cell imaging data. Our algorithm is evaluated on synthetic and yeast cell cycle data, and Caenorhabditis elegans live cell imaging data against other prominent methods. The area under the curve of our method is significantly higher when compared to other methods on all three datasets. AVAILABILITY: The program, datasets and supplementary files are available at http://www.jjwanglab.org/DDGni/.

MetaCluster-TA: taxonomic annotation for metagenomic data based on assembly-assisted binning.

BACKGROUND: Taxonomic annotation of reads is an important problem in metagenomic analysis. Existing annotation tools, which rely on the approach of aligning each read to the taxonomic structure, are unable to annotate many reads efficiently and accurately as reads (~100 bp) are short and most of them come from unknown genomes. Previous work has suggested assembling the reads to make longer contigs before annotation. More reads/contigs can be annotated as a longer contig (in Kbp) can be aligned to a taxon even if it is from an unknown species as long as it contains a conserved region of that taxon. Unfortunately existing metagenomic assembly tools are not mature enough to produce long enough contigs. Binning tries to group reads/contigs of similar species together. Intuitively, reads in the same group (cluster) should be annotated to the same taxon and these reads altogether should cover a significant portion of the genome alleviating the problem of short contigs if the quality of binning is high. However, no existing work has tried to use binning results to help solve the annotation problem. This work explores this direction. RESULTS: In this paper, we describe MetaCluster-TA, an assembly-assisted binning-based annotation tool which relies on an innovative idea of annotating binned reads instead of aligning each read or contig to the taxonomic structure separately. We propose the novel concept of the 'virtual contig' (which can be up to 10 Kb in length) to represent a set of reads and then represent each cluster as a set of 'virtual contigs' (which together can be total up to 1 Mb in length) for annotation. MetaCluster-TA can outperform widely-used MEGAN4 and can annotate (1) more reads since the virtual contigs are much longer; (2) more accurately since each cluster of long virtual contigs contains global information of the sampled genome which tends to be more accurate than short reads or assembled contigs which contain only local information of the genome; and (3) more efficiently since there are much fewer long virtual contigs to align than short reads. MetaCluster-TA outperforms MetaCluster 5.0 as a binning tool since binning itself can be more sensitive and precise given long virtual contigs and the binning results can be improved using the reference taxonomic database. CONCLUSIONS: MetaCluster-TA can outperform widely-used MEGAN4 and can annotate more reads with higher accuracy and higher efficiency. It also outperforms MetaCluster 5.0 as a binning tool.

IDBA-tran: a more robust de novo de Bruijn graph assembler for transcriptomes with uneven expression levels.

MOTIVATION: RNA sequencing based on next-generation sequencing technology is effective for analyzing transcriptomes. Like de novo genome assembly, de novo transcriptome assembly does not rely on any reference genome or additional annotation information, but is more difficult. In particular, isoforms can have very uneven expression levels (e.g. 1:100), which make it very difficult to identify low-expressed isoforms. One challenge is to remove erroneous vertices/edges with high multiplicity (produced by high-expressed isoforms) in the de Bruijn graph without removing correct ones with not-so-high multiplicity from low-expressed isoforms. Failing to do so will result in the loss of low-expressed isoforms or having complicated subgraphs with transcripts of different genes mixed together due to erroneous vertices/edges. Contributions: Unlike existing tools, which remove erroneous vertices/edges with multiplicities lower than a global threshold, we use a probabilistic progressive approach to iteratively remove them with local thresholds. This enables us to decompose the graph into disconnected components, each containing a few genes, if not a single gene, while retaining many correct vertices/edges of low-expressed isoforms. Combined with existing techniques, IDBA-Tran is able to assemble both high-expressed and low-expressed transcripts and outperform existing assemblers in terms of sensitivity and specificity for both simulated and real data. AVAILABILITY: http://www.cs.hku.hk/~alse/idba_tran. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MetaCluster 5.0: a two-round binning approach for metagenomic data for low-abundance species in a noisy sample.

MOTIVATION: Metagenomic binning remains an important topic in metagenomic analysis. Existing unsupervised binning methods for next-generation sequencing (NGS) reads do not perform well on (i) samples with low-abundance species or (ii) samples (even with high abundance) when there are many extremely low-abundance species. These two problems are common for real metagenomic datasets. Binning methods that can solve these problems are desirable. RESULTS: We proposed a two-round binning method (MetaCluster 5.0) that aims at identifying both low-abundance and high-abundance species in the presence of a large amount of noise due to many extremely low-abundance species. In summary, MetaCluster 5.0 uses a filtering strategy to remove noise from the extremely low-abundance species. It separate reads of high-abundance species from those of low-abundance species in two different rounds. To overcome the issue of low coverage for low-abundance species, multiple w values are used to group reads with overlapping w-mers, whereas reads from high-abundance species are grouped with high confidence based on a large w and then binning expands to low-abundance species using a relaxed (shorter) w. Compared to the recent tools, TOSS and MetaCluster 4.0, MetaCluster 5.0 can find more species (especially those with low abundance of say 6× to 10×) and can achieve better sensitivity and specificity using less memory and running time. AVAILABILITY: http://i.cs.hku.hk/~alse/MetaCluster/ CONTACT: chin@cs.hku.hk.

IDBA-UD: a de novo assembler for single-cell and metagenomic sequencing data with highly uneven depth.

MOTIVATION: Next-generation sequencing allows us to sequence reads from a microbial environment using single-cell sequencing or metagenomic sequencing technologies. However, both technologies suffer from the problem that sequencing depth of different regions of a genome or genomes from different species are highly uneven. Most existing genome assemblers usually have an assumption that sequencing depths are even. These assemblers fail to construct correct long contigs. RESULTS: We introduce the IDBA-UD algorithm that is based on the de Bruijn graph approach for assembling reads from single-cell sequencing or metagenomic sequencing technologies with uneven sequencing depths. Several non-trivial techniques have been employed to tackle the problems. Instead of using a simple threshold, we use multiple depthrelative thresholds to remove erroneous k-mers in both low-depth and high-depth regions. The technique of local assembly with paired-end information is used to solve the branch problem of low-depth short repeat regions. To speed up the process, an error correction step is conducted to correct reads of high-depth regions that can be aligned to highconfident contigs. Comparison of the performances of IDBA-UD and existing assemblers (Velvet, Velvet-SC, SOAPdenovo and Meta-IDBA) for different datasets, shows that IDBA-UD can reconstruct longer contigs with higher accuracy. AVAILABILITY: The IDBA-UD toolkit is available at our website http://www.cs.hku.hk/~alse/idba_ud

Cutaneous versus non-cutaneous angiosarcoma: clinicopathologic features and treatment outcomes in 60 patients at a single Asian cancer centre.

BACKGROUND: Angiosarcoma (AS) is an uncommon soft tissue sarcoma with dismal prognosis that presents either cutaneously (C-AS) or non-cutaneously (NC-AS). We compared the clinical features and treatment outcomes between these 2 groups. METHODS: A single-centre study evaluating 60 AS patients between 2002 and 2012 was performed. RESULTS: The median age was 70 years. C-AS of the scalp or face comprised 66% of patients. C-AS patients were older than NC-AS (median age 74 vs. 56 years; p < 0.001). Proportionately more C-AS patients presented with non-metastatic disease (86 vs. 50%; p = 0.007). Amongst resected C-AS and NC-AS patients, rates of positive surgical margins (53 vs. 50%; p = 1.00) and adjuvant therapy (25 vs. 43%; p = 0.626) were not significantly different, though proportionately fewer C-AS patients relapsed (36 vs. 78%; p = 0.038). Paclitaxel was the most common agent in first line palliative systemic therapy, achieving an objective response rate of 56%. Median overall survival was 11.2 months, with no significant difference between C-AS and NC-AS (11.3 vs. 9.8 months; p = 0.895). CONCLUSION: Distinct from AS in the West, our series demonstrates a clear preponderance of scalp AS. Disparities in clinical characteristics between C-AS and NC-AS did not translate into survival differences.

Biocompatibility and bone formation with porous modified PMMA in normal and irradiated mandibular tissue.

UNLABELLED: A cemented mandibular endoprosthesis is a potentially viable option for mandibular reconstruction after ablative surgery. The commonly used PMMA cement has the inherent weakness of a lack of bioactivity. Improvement by the addition of porosities and bioactive compounds like calcium phosphates may resolve this issue. OBJECTIVE: The objective of this study was to assess the bone and tissue response to two modified PMMA cements with post-operative radiation as an additional influencing factor. MATERIALS & METHODS: An in vivo animal study was performed using a mandibular rabbit model. A porous PMMA cement (A) and a porous cement incorporated with Beta-tricalcium phosphate particles (b-TCP) (B) were placed in bilateral mandibular defects with exposed roots and mandibular nerve of 20 animals. Half of the animals underwent additional post-operative radiation. RESULTS: The animals were healthy with only a minor complication in one rabbit. Temperature analysis showed no significant risk of thermal necrosis with the maximal in vivo cement temperature at 37.8°C. Histology demonstrated: (1) good bone ingrowth around the defect as well as within the pores of the cement and defect bridging was achieved in 70% of the specimens after 12-15 weeks of implantation, (2) no pulpal injury with minor secondary cementum response, (3) an intact mandibular nerve with no inflammation, (4) extensive degradation and resorption of the b-TCP particles by 12-15 weeks, and (5) presence of an intervening thin fibrous tissue at the bone-to-cement interface. Histomorphometrical analysis revealed that there was no difference between the different cements and the presence or absence of post-operative radiation. The 12-15 weeks specimens showed significantly more bone ingrowth and bone maturity than the 4-7 weeks specimens. CONCLUSION: Both modified PMMA cements have good biocompatibility, bioactivity and support bone ingrowth and additional post-operative radiation did not show any negative effects.

Mental health of pregnant women during the SARS-CoV-2 pandemic in France: Evolution of self-perceived psychological state during the first lockdown, and anxiety frequency two months after the lockdown ended.

Previous pandemics and related lockdowns have had a deleterious impact on pregnant women's mental health. We studied the impact of the SARS-CoV-2/Covid-19 pandemic and France's first lockdown on pregnant women's mental health. A cross-sectional study was conducted in July 2020 using a web-questionnaire completed by 500 adult women who were pregnant during the first lockdown in France (March-May 2020). Questions focused on their self-perceived psychological state and affects they felt before and during the lockdown and anxiety symptomatology (HAD) two months after it ended. A robust variance Poisson regression model was used to estimate adjusted prevalence ratios (aPR) for anxiety and self-perceived psychological state evolution. One in five respondents (21.1%) reported psychological deterioration during lockdown. Associated determinants were: i) little or no social support (self-perceived) (aRP = 1.77, 95%CI[1.18-2.66]), ii) increased workload (1.65, [1.02-2.66]), and iii) poor/moderate knowledge about SARS-CoV-2 transmission (1.60, [1.09-2.35]). Seven percent of women reporting psychological deterioration had access to professional psychological support during lockdown, while 19% did not despite wanting it. Women reported heightened powerlessness (60.3%), frustration (64%) and fear (59.2%) during lockdown. One in seven respondents (14.2%, 95%CI[10.9-18.2]) had anxiety symptoms. Determinants associated: i) at least one pregnancy-related pathology (aPR = 1.82, 95%CI[1.15-2.88]), ii) overweightness or obesity (1.61, [1.07-2.43]), iii) one child under the age of six years in the household during the lockdown (3.26, [1.24-8.53]), iv) little or no social support (self-perceived) during the lockdown (1.66, [1.07-2.58]), v) friend or relatives diagnosed with Covid-19 or with symptoms of the disease (1.66; [1.06-2.60]), vi) no access to medication for psychological distress (2.86, [1.74-4.71]), and vii) unsuccessfully seeking exchanges with healthcare professionals about their pregnancy during the pandemic (1.66, [1.08-2.55]). Our results can guide prevention and support policies for pregnant women during pandemics, current or future, with or without lockdowns. Preventing perinatal mental health problems is essential to ensure a supportive environment for the child's development.

Meta-IDBA: a de Novo assembler for metagenomic data.

MOTIVATION: Next-generation sequencing techniques allow us to generate reads from a microbial environment in order to analyze the microbial community. However, assembling of a set of mixed reads from different species to form contigs is a bottleneck of metagenomic research. Although there are many assemblers for assembling reads from a single genome, there are no assemblers for assembling reads in metagenomic data without reference genome sequences. Moreover, the performances of these assemblers on metagenomic data are far from satisfactory, because of the existence of common regions in the genomes of subspecies and species, which make the assembly problem much more complicated. RESULTS: We introduce the Meta-IDBA algorithm for assembling reads in metagenomic data, which contain multiple genomes from different species. There are two core steps in Meta-IDBA. It first tries to partition the de Bruijn graph into isolated components of different species based on an important observation. Then, for each component, it captures the slight variants of the genomes of subspecies from the same species by multiple alignments and represents the genome of one species, using a consensus sequence. Comparison of the performances of Meta-IDBA and existing assemblers, such as Velvet and Abyss for different metagenomic datasets shows that Meta-IDBA can reconstruct longer contigs with similar accuracy. AVAILABILITY: Meta-IDBA toolkit is available at our website http://www.cs.hku.hk/~alse/metaidba. CONTACT: chin@cs.hku.hk.

A robust and accurate binning algorithm for metagenomic sequences with arbitrary species abundance ratio.

MOTIVATION: With the rapid development of next-generation sequencing techniques, metagenomics, also known as environmental genomics, has emerged as an exciting research area that enables us to analyze the microbial environment in which we live. An important step for metagenomic data analysis is the identification and taxonomic characterization of DNA fragments (reads or contigs) resulting from sequencing a sample of mixed species. This step is referred to as 'binning'. Binning algorithms that are based on sequence similarity and sequence composition markers rely heavily on the reference genomes of known microorganisms or phylogenetic markers. Due to the limited availability of reference genomes and the bias and low availability of markers, these algorithms may not be applicable in all cases. Unsupervised binning algorithms which can handle fragments from unknown species provide an alternative approach. However, existing unsupervised binning algorithms only work on datasets either with balanced species abundance ratios or rather different abundance ratios, but not both. RESULTS: In this article, we present MetaCluster 3.0, an integrated binning method based on the unsupervised top--down separation and bottom--up merging strategy, which can bin metagenomic fragments of species with very balanced abundance ratios (say 1:1) to very different abundance ratios (e.g. 1:24) with consistently higher accuracy than existing methods. AVAILABILITY: MetaCluster 3.0 can be downloaded at http://i.cs.hku.hk/~alse/MetaCluster/.

Hospitalization for COVID-19 is associated with a higher risk of subsequent hospitalization for psychiatric disorders: A French nationwide longitudinal study comparing hospitalizations for COVID-19 and for other reasons.

INTRODUCTION: Although COVID-19 has been associated with psychiatric symptoms in patients, no study to date has examined the risk of hospitalization for psychiatric disorders after hospitalization for this disease. OBJECTIVE: We aimed to compare the proportions of hospitalizations for psychiatric disorders in the 12 months following either hospitalization for COVID-19 or hospitalization for another reason in the adult general population in France during the first wave of the current pandemic. METHODS: We conducted a retrospective longitudinal nationwide study based on the national French administrative healthcare database. RESULTS: Among the 2,894,088 adults hospitalized, 96,313 (3.32%) were admitted for COVID-19. The proportion of patients subsequently hospitalized for a psychiatric disorder was higher for COVID-19 patients (11.09 vs. 9.24%, OR = 1.20 95%CI 1.18-1.23). Multivariable analyses provided similar results for a psychiatric disorder of any type and for psychotic and anxiety disorders (respectively, aOR = 1.06 95%CI 1.04-1.09, aOR = 1.09 95%CI 1.02-1.17, and aOR = 1.11 95%CI 1.08-1.14). Initial hospitalization for COVID-19 in intensive care units and psychiatric history were associated with a greater risk of subsequent hospitalization for any psychiatric disorder than initial hospitalization for another reason. DISCUSSION: Compared with hospitalizations for other reasons, hospitalizations for COVID-19 during the first wave of the pandemic in France were associated with a higher risk of hospitalization for a psychiatric disorder during the 12 months following initial discharge. This finding should encourage clinicians to increase the monitoring and assessment of psychiatric symptoms after hospital discharge for COVID-19, and to propose post-hospital care, especially for those treated in intensive care.

Hospitalised traumatic brain injury victims in France: An analysis of the French hospital discharge database for 2011-2016.

BACKGROUND: Traumatic brain injury (TBI) is a major public health problem because of its severity and frequency. No recent national epidemiological study on TBI victims is currently available in France. OBJECTIVE: This study aimed to quantify and characterise TBI victims and analyse temporal trends. METHODS: French hospitalisation data were used in this study. All hospitalised patients residing in France with at least one International Classification of Disease, 10th revision, code S06.0 to S06.9 during 2011-2016 were selected. Incidence and hospital case-fatality rates were calculated. Quasi-Poisson models were used to analyse temporal trends. RESULTS: In 2016, the incidence rate was 230.6/100,000 people, higher among men than women regardless of age. Incidence and hospital case-fatality rates were also higher among older than younger people. Incidence rates increased during 2011-2016, mainly due to the higher incidence rate with age ≥65 years than younger age. During 2011-2016, hospital case-fatality rates decreased, mainly due to the decrease in the older age group (≥65 years old). CONCLUSIONS: To our knowledge, this is the first national study in France to provide recent data on hospitalised TBI victims. Our study shows that TBI is a major public health concern in France. As a priority, older people represent a risk group that should be targeted with preventive actions because they have both the highest incidence and case-fatality rates and had the largest increase in incidence rates over the study period.

Unsupervised binning of environmental genomic fragments based on an error robust selection of l-mers.

BACKGROUND: With the rapid development of genome sequencing techniques, traditional research methods based on the isolation and cultivation of microorganisms are being gradually replaced by metagenomics, which is also known as environmental genomics. The first step, which is still a major bottleneck, of metagenomics is the taxonomic characterization of DNA fragments (reads) resulting from sequencing a sample of mixed species. This step is usually referred as "binning". Existing binning methods are based on supervised or semi-supervised approaches which rely heavily on reference genomes of known microorganisms and phylogenetic marker genes. Due to the limited availability of reference genomes and the bias and instability of marker genes, existing binning methods may not be applicable in many cases. RESULTS: In this paper, we present an unsupervised binning method based on the distribution of a carefully selected set of l-mers (substrings of length l in DNA fragments). From our experiments, we show that our method can accurately bin DNA fragments with various lengths and relative species abundance ratios without using any reference and training datasets. Another feature of our method is its error robustness. The binning accuracy decreases by less than 1% when the sequencing error rate increases from 0% to 5%. Note that the typical sequencing error rate of existing commercial sequencing platforms is less than 2%. CONCLUSIONS: We provide a new and effective tool to solve the metagenome binning problem without using any reference datasets or markers information of any known reference genomes (species). The source code of our software tool, the reference genomes of the species for generating the test datasets and the corresponding test datasets are available at http://i.cs.hku.hk/~alse/MetaCluster/.

Time trends in hospital-referred stroke and transient ischemic attack: results of a 7-year nationwide survey in France.

BACKGROUND: Nationwide evaluations of the burden of stroke are scarce. We aimed to evaluate trends in stroke and transient ischemic attack (TIA) hospitalization, in-hospital case fatality rates (CFRs) and mortality rates in France during 2000-2006. METHODS: Hospitalizations for stroke and TIA were determined from National Hospital Discharge Diagnosis Records that used the International Classification of Disease, 10th revision, codes I60, I61, I63, I64, G45, G46. CFRs and mortality rates were estimated from the national death certificates database. RESULTS: The total number of stays for stroke increased between 2000 and 2006 (88,371 vs. 92,118) contrasting with a decrease in that for TIA. The age-standardized (European population) hospitalization rates for TIA decreased in men (52.2 vs. 44.5/100,000/year, p = 0.002), whereas they remained stable in women (32.4 vs. 31.0/ 100,000/year). Concerning stroke, a decrease in hospitalization rates was observed in both men (from 135.3 to 123.4/ 100,000/year, p < 0.001) and women (from 85.1 to 80.7, p < 0.001). Whatever the age group and the sex, a sharp decrease in in-hospital stroke CFRs was noted. In addition, a 23% decrease in mortality rates was observed. This decrease was greater in patients >65 years. CONCLUSION: Our results demonstrate a decline in hospitalization rates for stroke, and in both stroke CFRs and mortality rates between 2000 and 2006. Improvements in stroke prevention and acute stroke care may have contributed to these results, and may have been initiated by recent advances in health policy with regard to this disease in France.

Finding optimal threshold for correction error reads in DNA assembling.

BACKGROUND: DNA assembling is the problem of determining the nucleotide sequence of a genome from its substrings, called reads. In the experiments, there may be some errors on the reads which affect the performance of the DNA assembly algorithms. Existing algorithms, e.g. ECINDEL and SRCorr, correct the error reads by considering the number of times each length-k substring of the reads appear in the input. They treat those length-k substrings appear at least M times as correct substring and correct the error reads based on these substrings. However, since the threshold M is chosen without any solid theoretical analysis, these algorithms cannot guarantee their performances on error correction. RESULTS: In this paper, we propose a method to calculate the probabilities of false positive and false negative when determining whether a length-k substring is correct using threshold M. Based on this optimal threshold M that minimizes the total errors (false positives and false negatives). Experimental results on both real data and simulated data showed that our calculation is correct and we can reduce the total error substrings by 77.6% and 65.1% when compared to ECINDEL and SRCorr respectively. CONCLUSION: We introduced a method to calculate the probability of false positives and false negatives of the length-k substring using different thresholds. Based on this calculation, we found the optimal threshold to minimize the total error of false positive plus false negative.

Clustering-based approach for predicting motif pairs from protein interaction data.

UNLABELLED: Predicting motif pairs from a set of protein sequences based on the protein-protein interaction data is an important, but difficult computational problem. Tan et al. proposed a solution to this problem. However, the scoring function (using chi(2) testing) used in their approach is not adequate and their approach is also not scalable. It may take days to process a set of 5000 protein sequences with about 20,000 interactions. Later, Leung et al. proposed an improved scoring function and faster algorithms for solving the same problem. But, the model used in Leung et al. is complicated. The exact value of the scoring function is not easy to compute and an estimated value is used in practice. In this paper, we derive a better model to capture the significance of a given motif pair based on a clustering notion. We develop a fast heuristic algorithm to solve the problem. The algorithm is able to locate the correct motif pair in the yeast data set in about 45 minutes for 5000 protein sequences and 20,000 interactions. Moreover, we derive a lower bound result for the p-value of a motif pair in order for it to be distinguishable from random motif pairs. The lower bound result has been verified using simulated data sets. AVAILABILITY: http://alse.cs.hku.hk/motif_pair.