A large-scale effort, termed the Secreted Protein Discovery Initiative (SPDI), was undertaken to identify novel secreted and transmembrane proteins. In the first of several approaches, a biological signal sequence trap in yeast cells was utilized to identify cDNA clones encoding putative secreted proteins. A second strategy utilized various algorithms that recognize features such as the hydrophobic properties of signal sequences to identify putative proteins encoded by expressed sequence tags (ESTs) from human cDNA libraries. A third approach surveyed ESTs for protein sequence similarity to a set of known receptors and their ligands with the BLAST algorithm. Finally, both signal-sequence prediction algorithms and BLAST were used to identify single exons of potential genes from within human genomic sequence. The isolation of full-length cDNA clones for each of these candidate genes resulted in the identification of >1000 novel proteins. A total of 256 of these cDNAs are still novel, including variants and novel genes, per the most recent GenBank release version. The success of this large-scale effort was assessed by a bioinformatics analysis of the proteins through predictions of protein domains, subcellular localizations, and possible functional roles. The SPDI collection should facilitate efforts to better understand intercellular communication, may lead to new understandings of human diseases, and provides potential opportunities for the development of therapeutics.

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K-means is a well-known and widely used partitional clustering method. While there are considerable research efforts to characterize the key features of the K-means clustering algorithm, further investigation is needed to understand how data distributions can have impact on the performance of K-means clustering. To that end, in this paper, we provide a formal and organized study of the effect of skewed data distributions on K-means clustering. Along this line, we first formally illustrate that K-means tends to produce clusters of relatively uniform size, even if input data have varied "true" cluster sizes. In addition, we show that some clustering validation measures, such as the entropy measure, may not capture this uniform effect and provide misleading information on the clustering performance. Viewed in this light, we provide the coefficient of variation (CV) as a necessary criterion to validate the clustering results. Our findings reveal that K-means tends to produce clusters in which the variations of cluster sizes, as measured by CV, are in a range of about 0.3-1.0. Specifically, for data sets with large variation in "true" cluster sizes (e.g., CV > 1.0), K-means reduces variation in resultant cluster sizes to less than 1.0. In contrast, for data sets with small variation in "true" cluster sizes (e.g., CV < 0.3), K-means increases variation in resultant cluster sizes to greater than 0.3. In other words, for the earlier two cases, K-means produces the clustering results which are away from the "true" cluster distributions.

LBC have a relatively higher level of social anxiety and poorer living conditions than non-LBC, and there are differences in social anxiety, and its relevant factors, between the two groups.

The aim of this study was to investigate the prevalence and factors associated with suicidal ideation among HIV-positive men who have sex with men (MSM) in Anhui, China. A cross-sectional study was conducted to recruit HIV-positive MSM in Anhui, China. A total of 184 HIV-positive MSM gave informed consent and completed the interview. Correlates of suicidal ideation were assessed using multivariable logistic regression. Fifty-seven (31%) of HIV-positive MSM had suicidal ideations within six months before the interview. Multivariable analyses showed that learning of their HIV status in the past 12 months (adjusted odds ratio (AOR) = 3.4, 95% CI = 1.6-7.3), perceived HIV stigma (AOR = 2.4, 95% CI = 1.1-5.2), depression symptoms (AOR = 2.6, 95% CI = 1.1-5.9) and anxiety symptoms (AOR = 2.7, 95% CI = 1.2-6.1) were significantly associated with the suicidal ideation among HIV-positive MSM. The results indicated that suicidal ideation was common among HIV-positive MSM in Anhui, China. There is an urgent need to establish psychological counselling services among HIV-positive MSM in China. Targeting of these potential risk factors could be an effective approach to reduce the suicide risk among this high-risk subgroup by the implementation of early intervention measurements.

Background: MicroRNAs (miRNAs) are small RNA molecules that regulate gene expression by targeting messenger RNAs (mRNAs) and causing mRNA cleavage or translation blockage. Of the 355 Arthropod miRNAs that have been identified, only 21 are B. mori miRNAs that were predicted computationally; of these, only let-7 has been confirmed by Northern blotting.

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