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Sporadic prostate carcinoma is the most common male cancer in the Western world, yet many of the major genetic events involved in the progression of this often fatal cancer remain to be elucidated. Numerous cytogenetic and allelotype studies have reported frequent loss of heterozygosity on chromosomal arm 10q in sporadic prostate cancer. Deletion mapping studies have unambiguously identified a region of chromosome 10q23 to be the minimal area of loss. A new tumor suppressor gene, PTEN/MMAC1, was isolated recently at this region of chromosome 10q23 and found to be inactivated by mutation in three prostate cancer cell lines. We screened 80 prostate tumors by microsatellite analysis and found chromosome 10q23 to be deleted in 23 cases. We then proceeded with sequence analysis of the entire PTEN/MMAC1 coding region and tested for homozygous deletion with new intragenic markers in these 23 cases with 10q23 loss of heterozygosity. The identification of the second mutational event in 10 (43%) tumors establishes PTEN/MMAC1 as a main inactivation target of 10q loss in sporadic prostate cancer.

PURPOSE: Patients with daily or near-daily headaches are commonly seen in neurology practices and in headache subspecialty centers, but there is little information on the prevalence of this condition in the general population. We present the first US-based study describing the prevalence and characteristics of frequent headache in the general population. METHODS: In Baltimore County, Maryland, 13 343 individuals 18 to 65 years of age were selected by random-digit dialing and interviewed by telephone about their headaches. Subjects reporting 180 or more headaches per year were classified as having frequent headache. Three mutually exclusive subtypes of frequent headache were identified: frequent headache with migrainous features, chronic tension-type headache, and unclassified frequent headache. RESULTS: The overall prevalence of frequent headache was 4.1% (5.0% female, 2.8% male; 1.8:1 female to male ratio). Frequent headache was 33% more common in Caucasians (4.4%) than in African Americans (3.3%). In both males and females, prevalence was highest in the lowest educational category. Among frequent headache sufferers, more than half (52% female, 56% male) met criteria for chronic tension-type headache, almost one third (33% female, 25% male) met criteria for frequent headache with migrainous features, and the remainder (15% female, 19% male) were unclassified. Overall, 30% of female and 25% of male frequent headache sufferers met International Headache Society (IHS) criteria for migraine (with or without aura). CONCLUSIONS: Frequent headache is common in the general population and is more prevalent in Caucasians and in those with less than a high school education. Chronic tension-type headache is more common than frequent headache with migrainous features, though the latter is more disabling. Although more common in females than males, the female preponderance of frequent headache is less marked than in migraine. The sex ratio varies by frequent headache subtype.

Mining frequent patterns in transaction databases, time-series databases, and many other kinds of databases has been studied popularly in data mining research. Most of the previous studies adopt an Apriori-like candidate set generation-and-test approach. However, candidate set generation is still costly, especially when there exist prolific patterns and/or long patterns. In this study, we propose a novel frequent pattern tree (FP-tree) structure, which is an extended prefix-tree structure for storing compressed, crucial information about frequent patterns, and develop an efficient FP-tree-based mining method, FP-growth, for mining the complete set of frequent patterns by pattern fragment growth. Efficiency of mining is achieved with three techniques: (1) a large database is compressed into a highly condensed, much smaller data structure, which avoids costly, repeated database scans, (2) our FP-tree-based mining adopts a pattern fragment growth method to avoid the costly generation of a large number of candidate sets, and (3) a partitioning-based, divide-and-conquer method is used to decompose the mining task into a set of smaller tasks for mining confined patterns in conditional databases, which dramatically reduces the search space. Our performance study shows that the FP-growth method is efficient and scalable for mining both long and short frequent patterns, and is about an order of magnitude faster than the Apriori algorithm and also faster than some recently reported new frequent pattern mining methods.

As data mining techniques are being increasingly applied to non-traditional domains, existing approaches for finding frequent itemsets cannot be used as they cannot model the requirement of these domains. An alternate way of modeling the objects in these data sets is to use graphs. Within that model, the problem of finding frequent patterns becomes that of discovering subgraphs that occur frequently over the entire set of graphs.The authors present a computationally efficient algorithm for finding all frequent subgraphs in large graph databases. We evaluated the performance of the algorithm by experiments with synthetic datasets as well as a chemical compound dataset. The empirical results show that our algorithm scales linearly with the number of input transactions and it is able to discover frequent subgraphs from a set of graph transactions reasonably fast, even though we have to deal with computationally hard problems such as canonical labeling of graphs and subgraph isomorphism which are not necessary for traditional frequent itemset discovery.

OBJECTIVES: This study analyzed the long-term association between religious attendance and mortality to determine whether the association is explained by improvements in health practices and social connections for frequent attenders. METHODS: The association between frequent attendance and mortality over 28 years for 5286 Alameda Country Study respondents was examined. Logistic regression models analyzed associations between attendance and subsequent improvements in health practices and social connections. RESULTS: Frequent attenders had lower mortality rates than infrequent attenders (relative hazard [RH] = 0.64;95% confidence interval [CI] = 0.53,0.77). Results were stronger for females. Health adjustments had little impact, but adjustments for social connections and health practices reduced the relationship (RH = 0.77; 95% CI = 0.64, 0.93). During follow-up, frequent attenders were more likely to stop smoking, increase exercising, increase social contacts, and stay married. CONCLUSIONS: Lower mortality rates for frequent religious attenders are partly explained by improved health practices, increased social contacts, and more stable marriages occurring in conjunction with attendance. The mechanisms by which these changes occur have broad intervention implications.

Text clustering methods can be used to structure large sets of text or hypertext documents. The well-known methods of text clustering, however, do not really address the special problems of text clustering: very high dimensionality of the data, very large size of the databases and understandability of the cluster description. In this paper, we introduce a novel approach which uses frequent item (term) sets for text clustering. Such frequent sets can be efficiently discovered using algorithms for association rule mining. To cluster based on frequent term sets, we measure the mutual overlap of frequent sets with respect to the sets of supporting documents. We present two algorithms for frequent term-based text clustering, FTC which creates flat clusterings and HFTC for hierarchical clustering. An experimental evaluation on classical text documents as well as on web documents demonstrates that the proposed algorithms obtain clusterings of comparable quality significantly more efficiently than state-of-the- art text clustering algorithms. Furthermore, our methods provide an understandable description of the discovered clusters by their frequent term sets.

Association mining may often derive an undesirably large set of frequent itemsets and association rules. Recent studies have proposed an interesting alternative: mining frequent closed itemsets and their corresponding rules, which has the same power as association mining but substantially reduces the number of rules to be presented. In this paper, we propose an efficient algorithm, CLOSET, for mining closed itemsets, with the development of three techniques: (1) applying a compressed, frequent pattern tree FP-tree structure for mining closed itemsets without candidate generation, (2) developing a single prefix path compression technique to identify frequent closed itemsets quickly, and (3) exploring a partition-based projection mechanism for scalable mining in large databases. Our performance study shows that CLOSET is efficient and scalable over large databases, and is faster than the previously proposed methods. 1 Introduction It has been well recognized that frequent pattern minin...

A large number of tiny noncoding RNAs have been cloned and named microRNAs (miRs). Recently, we have reported that miR-15a and miR-16a, located at 13q14, are frequently deleted and/or down-regulated in patients with B cell chronic lymphocytic leukemia, a disorder characterized by increased survival. To further investigate the possible involvement of miRs in human cancers on a genome-wide basis, we have mapped 186 miRs and compared their location to the location of previous reported nonrandom genetic alterations. Here, we show that miR genes are frequently located at fragile sites, as well as in minimal regions of loss of heterozygosity, minimal regions of amplification (minimal amplicons), or common breakpoint regions. Overall, 98 of 186 (52.5%) of miR genes are in cancer-associated genomic regions or in fragile sites. Moreover, by Northern blotting, we have shown that several miRs located in deleted regions have low levels of expression in cancer samples. These data provide a catalog of miR genes that may have roles in cancer and argue that the full complement of miRs in a genome may be extensively involved in cancers.

Previous studies have presented convincing arguments that a frequent pattern mining algorithm should not mine all frequent patterns but only the closed ones because the latter leads to not only more compact yet complete result set but also better efficiency. However, most of the previously developed closed pattern mining algorithms work under the candidate maintenance-and-test paradigm which is inherently costly in both runtime and space usage when the support threshold is low or the patterns become long. We present, BIDE, an efficient algorithm for mining frequent closed sequences without candidate maintenance. We adopt a novel sequence closure checking scheme called bidirectional extension, and prunes the search space more deeply compared to the previous algorithms by using the BackScan pruning method and the Scan-Skip optimization technique. A thorough performance study with both sparse and dense real-life data sets has demonstrated that BIDE significantly outperforms the previous algorithms: it consumes order(s) of magnitude less memory and can be more than an order of magnitude faster. It is also linearly scalable in terms of database size.

Follicular lymphoma (FL) and diffuse large B-cell lymphoma (DLBCL) are the two most common non-Hodgkin lymphomas (NHLs). Here we sequenced tumour and matched normal DNA from 13 DLBCL cases and one FL case to identify genes with mutations in B-cell NHL. We analysed RNA-seq data from these and another 113 NHLs to identify genes with candidate mutations, and then re-sequenced tumour and matched normal DNA from these cases to confirm 109 genes with multiple somatic mutations. Genes with roles in histone modification were frequent targets of somatic mutation. For example, 32% of DLBCL and 89% of FL cases had somatic mutations in MLL2, which encodes a histone methyltransferase, and 11.4% and 13.4% of DLBCL and FL cases, respectively, had mutations in MEF2B, a calcium-regulated gene that cooperates with CREBBP and EP300 in acetylating histones. Our analysis suggests a previously unappreciated disruption of chromatin biology in lymphomagenesis. Despite being a focus of research activity for many years, the mutations driving the two most common non-Hodgkin lymphomas — follicular lymphoma and diffuse large B-cell lymphoma — have remained cryptic. Whole genome sequencing, combined with transcriptome analysis and further resequencing of candidate genes in additional tumours, now show that histone methyltransferases and acetylases are frequently affected by mutations in these tumours. This study suggests a previously unappreciated importance of chromatin biology in lymphomagenesis.

Allele loss is a hallmark of chromosome regions harboring recessive oncogenes. Lung cancer frequently demonstrates loss of heterozygosity on 17p. Recent evidence suggests that the p53 gene located on 17p13 has many features of such an antioncogene. The p53 gene was frequently mutated or inactivated in all types of human lung cancer. The genetic abnormalities of p53 include gross changes such as homozygous deletions and abnormally sized messenger RNAs along with a variety of point or small mutations, which map to the p53 open reading frame and change amino acid sequence in a region highly conserved between mouse and man. In addition, very low or absent expression of p53 messenger RNA in lung cancer cell lines compared to normal lung was seen. These findings, coupled with the previous demonstration of 17p allele loss in lung cancer, strongly implicate p53 as an anti-oncogene whose disruption is involved in the pathogenesis of human lung cancer.

The present study aimed to analyse the influence of speed and power abilities in goal situations in professional football. During the second half of the season 2007/08, videos of 360 goals in the first German national league were analysed by visual inspection. For the assisting and the scoring player the situations immediately preceding the goal were evaluated. The observed actions were categorised as: no powerful action, rotation (around the body's centre-line), straight sprint, change-in-direction sprint, jump, or a combination of those categories. Two hundred and ninety-eight (83%) goals were preceded by at least one powerful action of the scoring or the assisting player. Most actions for the scoring player were straight sprints (n = 161, 45% of all analysed goals, P < 0.001) followed by jumps (n = 57, 16%), rotations and change-in-direction sprints (n = 22, 6% each). Most sprints were conducted without an opponent (n = 109, P < 0.001) and without the ball (n = 121, P < 0.001). Similarly, for the assisting player the most frequent action was a straight sprint (n = 137, P < 0.001) followed by rotations (n = 28), jumps (n = 22) and change-in-direction sprints (n = 18). The straight sprints were mostly conducted with the ball (n = 93, P = 0.003). In conclusion, straight sprinting is the most frequent action in goal situations. Power and speed abilities are important within decisive situations in professional football and, thus, should be included in fitness testing and training.

ABSTRACT As a result of climate change in recent past and unsustainable land management, drought became one of the most impacting disasters and, with the projected global warming, it is expected to progressively cause more damages by the end of the 21st century. This study investigates changes in drought occurrence, frequency, and severity in Europe in the next decades. A combined indicator based on the predominance of the drought signal over normal/wet conditions has been used. The indicator, which combines the standardized precipitation index (SPI, which accounts for anomalous low rainfall), the standardized precipitation evapotranspiration index (SPEI, which accounts for high temperatures and scarce precipitations), and the reconnaissance drought indicator (RDI, similar to SPEI but more affected by extreme events), has been computed at 3‐ and 12‐month accumulation scales to characterize trends in seasonal and annual events from 1981 to 2100. Climate data from 11 bias‐adjusted high‐resolution (0.11°) simulations from the EURO‐CORDEX (coordinated regional climate downscaling experiment) have been used in the analyses. For each simulation, the frequency and severity of drought and extreme drought events for 1981–2010, 2041–2070, and 2071–2100 have been analysed. Under the moderate emission scenario (RCP4.5), droughts are projected to become increasingly more frequent and severe in the Mediterranean area, western Europe, and Northern Scandinavia, whereas the whole European continent, with the exception of Iceland, will be affected by more frequent and severe extreme droughts under the most severe emission scenario (RCP8.5), especially after 2070. Seasonally, drought frequency is projected to increase everywhere in Europe for both scenarios in spring and summer, especially over southern Europe, and less intensely in autumn; on the contrary, winter shows a decrease in drought frequency over northern Europe.

A global coupled climate model shows that there is a distinct geographic pattern to future changes in heat waves. Model results for areas of Europe and North America, associated with the severe heat waves in Chicago in 1995 and Paris in 2003, show that future heat waves in these areas will become more intense, more frequent, and longer lasting in the second half of the 21st century. Observations and the model show that present-day heat waves over Europe and North America coincide with a specific atmospheric circulation pattern that is intensified by ongoing increases in greenhouse gases, indicating that it will produce more severe heat waves in those regions in the future.

Peripheral blood lymphocytes from patients with the acquired immunodeficiency syndrome (AIDS) or with signs or symptoms that frequently precede AIDS (pre-AIDS) were grown in vitro with added T-cell growth factor and assayed for the expression and release of human T-lymphotropic retroviruses (HTLV). Retroviruses belonging to the HTLV family and collectively designated HTLV-III were isolated from a total of 48 subjects including 18 of 21 patients wih pre-AIDS, three of four clinically normal mothers of juveniles with AIDS, 26 of 72 adult and juvenile patients with AIDS, and from one of 22 normal male homosexual subjects. No HTLV-III was detected in or isolated from 115 normal heterosexual subjects. The number of HTLV-III isolates reported here underestimates the true prevalence of the virus since many specimens were received in unsatisfactory condition. Other data show that serum samples from a high proportion of AIDS patients contain antibodies to HTLV-III. That these new isolates are members of the HTLV family but differ from the previous isolates known as HTLV-I and HTLV-II is indicated by their morphological, biological, and immunological characteristics. These results and those reported elsewhere in this issue suggest that HTLV-III may be the primary cause of AIDS.

Frequent subgraph mining is an active research topic in the data mining community. A graph is a general model to represent data and has been used in many domains like cheminformatics and bioinformatics. Mining patterns from graph databases is challenging since graph related operations, such as subgraph testing, generally have higher time complexity than the corresponding operations on itemsets, sequences, and trees, which have been studied extensively. We propose a novel frequent subgraph mining algorithm: FFSM, which employs a vertical search scheme within an algebraic graph framework we have developed to reduce the number of redundant candidates proposed. Our empirical study on synthetic and real datasets demonstrates that FFSM achieves a substantial performance gain over the current start-of-the-art subgraph mining algorithm gSpan.

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Pancreatic neuroendocrine tumors (PanNETs) are a rare but clinically important form of pancreatic neoplasia. To explore the genetic basis of PanNETs, we determined the exomic sequences of 10 nonfamilial PanNETs and then screened the most commonly mutated genes in 58 additional PanNETs. The most frequently mutated genes specify proteins implicated in chromatin remodeling: 44% of the tumors had somatic inactivating mutations in MEN1, which encodes menin, a component of a histone methyltransferase complex, and 43% had mutations in genes encoding either of the two subunits of a transcription/chromatin remodeling complex consisting of DAXX (death-domain-associated protein) and ATRX (α thalassemia/mental retardation syndrome X-linked). Clinically, mutations in the MEN1 and DAXX/ATRX genes were associated with better prognosis. We also found mutations in genes in the mTOR (mammalian target of rapamycin) pathway in 14% of the tumors, a finding that could potentially be used to stratify patients for treatment with mTOR inhibitors.

Numerous studies show that happy individuals are successful across multiple life domains, including marriage, friendship, income, work performance, and health. The authors suggest a conceptual model to account for these findings, arguing that the happiness-success link exists not only because success makes people happy, but also because positive affect engenders success. Three classes of evidence--crosssectional, longitudinal, and experimental--are documented to test their model. Relevant studies are described and their effect sizes combined meta-analytically. The results reveal that happiness is associated with and precedes numerous successful outcomes, as well as behaviors paralleling success. Furthermore, the evidence suggests that positive affect--the hallmark of well-being--may be the cause of many of the desirable characteristics, resources, and successes correlated with happiness. Limitations, empirical issues, and important future research questions are discussed.