Using data from model organisms, the authors have generated a large-scale human protein-protein interaction map. The map can be used to predict the function of human proteins. Protein-interaction maps are powerful tools for suggesting the cellular functions of genes. Although large-scale protein-interaction maps have been generated for several invertebrate species, projects of a similar scale have not yet been described for any mammal. Because many physical interactions are conserved between species, it should be possible to infer information about human protein interactions (and hence protein function) using model organism protein-interaction datasets.Here we describe a network of over 70,000 predicted physical interactions between around 6,200 human proteins generated using the data from lower eukaryotic protein-interaction maps. The physiological relevance of this network is supported by its ability to preferentially connect human proteins that share the same functional annotations, and we show how the network can be used to successfully predict the functions of human proteins. We find that combining interaction datasets from a single organism (but generated using independent assays) and combining interaction datasets from two organisms (but generated using the same assay) are both very effective ways of further improving the accuracy of protein-interaction maps.The complete network predicts interactions for a third of human genes, including 448 human disease genes and 1,482 genes of unknown function, and so provides a rich framework for biomedical research. Physical interactions between proteins underpin most biological processes. For this reason, large-scale protein-interaction mapping projects have been initiated in several model organisms -6. UnforTo transfer information on gene function between two genomes requires the identification of orthologous genes in the two genomes . However, the identification of gene orthologs is often not a trivial problem; gene duplications can result in a single gene having multiple potential orthologs in a second species. In addition, it is necessary to distinguish true gene orthologs from 'out-paralogs' (that is, genes that arose from a gene-duplication event before the divergence of two species, and so are unlikely to share functions) . One metSaccharomyces cerevisiae [Drosophila melanogaster [Caenorhabditis elegans [Protein interactions are often evolutionarily conserved between orthologous proteins from different species . Hence wrevisiae -4,10,11,nogaster  and Caen elegans . For eac elegans . A human elegans .In the absence of a comprehensive set of verified human protein interactions, we required another method to assess the accuracy of the interaction network. Proteins that interact physiologically are expected to have related functions. Therefore high-quality interaction datasets should predict a greater proportion of interactions between functionally related proteins than low quality datasets. The functions of human proteins can be systematically described using the Gene Ontology (GO) annotations  availablWe then used the same strategy to compare the accuracy of human interactions predicted by data from the three different model organisms. If the interactions from a particular model organism dataset predict fewer interactions between functionally related human proteins than the other datasets, then this dataset should be considered less reliable as a source of candidate human protein interactions. As shown in Table Next we asked how the confidence in the assignment of gene orthologs affects the accuracy of an interaction. For each predicted interaction, an orthology confidence score was calculated by summing the InParanoid orthology confidence scores for the two human and two model organism proteins . Of the predicted interactions, 24,897 have the maximum possible confidence score of 4. Of these interactions, 28%, 24% and 13% connect proteins that share GO terms at depths of 3, 5 or 7 in the GO hierarchy (excluding proteins without GO annotation). In contrast, for interactions with an orthology confidence score less than 4, these figures are 24%, 20% and 10%. Hence we conclude that the predicted human interactions with high-confidence orthology assignments can be considered more reliable than those interactions with less confidence in their orthology assignments. This confirms that the confidence scores assigned using InParanoid are indeed likely to be useful predictors of functional conservation.The worm and fly interaction mapping projects both defined a subset of high-confidence 'core' interactions that have the greatest experimental support Figure . For theIt has been shown previously that protein interactions detected by more than one high-throughput interaction assay are more accurate . We findBecause physiologically interacting proteins often have similar functions Figure , it shouThe ability to provide a reasonably accurate prediction of a gene's GO terms means that we can use the interaction network to provide probabilistic gene function predictions for novel human proteins and also to predict additional functions for proteins with some known functions. The core interaction map contains 864 proteins with no functional annotations. About 10% of these proteins interact with two or more proteins that share GO terms. The probabilistic predictions of the functions of these novel proteins are listed in Additional data file 4. Often these predicted functions are also supported by the known functions of the protein domains predicted to be encoded by these novel genes . For example, ENSG00000028310 encodes a bromodomain and interacts with six proteins annotated as 'GO:0006355 regulation of transcription, DNA-dependent', ENSG00000080608 encodes an RNA-binding domain and interacts with five proteins annotated as 'GO:0006364 rRNA processing', and ENSG00000104863 encodes a PDZ domain and interacts with three proteins with the annotations 'GO:0005887 integral to plasma membrane, GO:0007242 intracellular signaling cascade' . The complete and core interaction maps also predict interactions for 448 and 292 human disease genes , of which 55 interact with two or more proteins in the core interaction network that share a GO annotation. The functional predictions for these 55 genes are listed in Additional data file 6.We report here the use of data from model organism protein-interaction mapping projects to predict a network of human protein interactions. This network consists of over 70,000 interactions that connect over one-third of all the predicted human proteins, including 1,482 proteins of unknown function and 448 proteins encoded by human disease genes. The physiological relevance of this network is supported by its ability to preferentially connect human proteins that share biological functions Figure . As suchThe accuracy and coverage of the interactions predicted in this network depend primarily on two parameters: the quality of the original model organism interaction datasets; and the ability to identify the human orthologs of a model organism protein. Our analysis suggests that the raw yeast and worm protein-interaction datasets are currently slightly more accurate than the raw fly interaction dataset, but that when filtered for high-confidence interactions the three interaction maps are of very similar accuracy . Table The human orthologs of yeast, worm and fly genes were identified using the InParanoid algorithm, which is designed to distinguish true orthologs from out-paralogs that arose from gene duplications before the divergence of two species . The InPCore interactions were defined as those predicted by worm interactions identified more than once or that reconfirmed when retested in the two-hybrid assay , by fly Human GOs (at levels 3 or deeper in the GO hierarchy) were obtained from Ensembl (v19.34a.1) ,15 usingx or more of its interaction partners (where x varied from 1 to 6). To validate the accuracy and coverage of this approach we predicted GO terms for genes that already have associated GO terms. The accuracy was calculated as the total number of correct GO term predictions divided by the total number of GO term predictions. The coverage was calculated as the total number of correct GO term predictions divided by the total number of known GO terms. This analysis was repeated, but only considering individually GO terms at depths of 3 to 8 and greater than 8 in the GO hierarchy . To avoid biasing the results we again ignored self-interactions. For the same reason, we also only counted once GO terms associated with more than one interaction partner predicted by the same source interaction from a model organism. The InterPro protein domains [To predict the GO terms of a protein, we identified all the GO terms associated with  domains  encoded  domains .Saccharomyces cerevisiae [Drosophila melanogaster [Caenorhabditis elegans [The following additional data files are available with the online version of this article: Additional data file revisiae -4,10,11,nogaster  and Caen elegans .et al. [et al.'s confidence assignment; and whether the interaction was previously known in the literature. For more information, please see [Additional data file et al.  and contease see .Additional data file A complete list of predicted human protein interactionsClick here for additional data fileA list of all core human protein interactionsClick here for additional data fileThe accuracy and coverage of GO term predictions at different levels in the GO hierarchyClick here for additional data fileGene function predictions for 85 human genes of unknown functionClick here for additional data fileHuman disease genes with predicted protein interactionsClick here for additional data fileGene function predictions for 55 human disease genesClick here for additional data file


Mammalian ribosomes contain 79 different proteins encoded by widely scattered single copy genes. Coordinate expression of these genes at transcriptional and post-transcriptional levels is required to ensure a roughly equimolar accumulation of ribosomal proteins. To date, detailed studies of only a very few ribosomal protein (rp) promoters have been made. To elucidate the general features of rp promoter architecture, I made a detailed sequence comparison of the promoter regions of the entire set of orthologous human and mouse rp genes.2C+1TY(T)2(Y)3. At least 60 % of the rp promoters contain a largely conserved TATA box or A/T-rich motif, which should theoretically have TBP-binding capability. A remarkably high proportion of the promoters contain conserved binding sites for transcription factors that were previously implicated in rp gene expression, namely upstream GABP and Sp1 sites and downstream YY1 sites. Over 80 % of human and mouse rp genes contain a transposable element residue within 900 bp of 5' flanking sequence; very little sequence identity between human and mouse orthologues was evident more than 200 bp upstream of the transcriptional start point.A striking evolutionarily conserved feature of most rp genes is the separation by an intron of the sequences involved in transcriptional and translational regulation from the sequences with protein encoding function. Another conserved feature is the polypyrimidine initiator, which conforms to the consensus (Y)This analysis has provided some valuable insights into the general architecture of mammalian rp promoters and has identified parameters that might coordinately regulate the transcriptional activity of certain subsets of rp genes. Ribosomes are vital organelles, which catalyze protein synthesis in all living organisms. Eukaryotic ribosomes consist of four RNA molecules (rRNAs) and 79 different proteins. The mammalian genes encoding the rRNAs are multicopy and clustered at a few loci, whereas those encoding the ribosomal proteins (rp genes) are single copy and scattered throughout the genome . In addiCoordinated expression of the rp genes at transcriptional and post-transcriptional levels is required to ensure a roughly equimolar accumulation of ribosomal proteins. Transcriptional run-on measurements with nuclei of rapidly proliferating cells indicated equivalent loading of RNA polymerases on three unlinked mouse rp genes , consistDespite the obvious importance of rp gene expression for cell viability, there have been very few experimental studies of rp promoter architecture and transcriptional regulation in higher eukaryotes. To date, efforts to identify functionally relevant cis-acting regulatory elements and transcription factor binding sites have been made for only 9 mammalian ,10-23 anBecause the previous experimental studies were limited to a small subset of rp genes, it is important to know whether the results of those studies can be used to predict special features of promoter architecture that characterize the entire set of rp genes or that could be used to sort the rp genes into classes with similar features. This applies not only to transcription factor-binding sites, but also to the polypyrimidine tract that spans the tsp. As an initiator element, this tract is atypical because the tsp of initiators is normally an adenine residue, flanked on both sides by pyrimidines .To address these issues, I have applied the principle of "phylogenetic footprinting", which holds that important regulatory sequences will have a tendency to be evolutionarily conserved and thus revealed by a sequence comparison of corresponding regions of orthologous genes . Some reTo make a study of the evolutionarily conserved features of ribosomal protein gene promoters, I first had to assemble a set of orthologous human and mouse rp gene sequences, in which the transcription start sites are reasonably well defined. For all of the human rp genes, annotated sequences are now available owing to the studies of Kato, Kenmochi and coworkers ,33, who In contrast to the situation with the human rp genes, accurate determinations of the tsp's of mouse rp genes have been made in only a few cases, and therefore the annotations of rp genes in the mouse genome databases are generally incomplete. To overcome this problem, I used the mVISTA alignment program  to comparpS16, rpL30 and rpL32 ). These genes were selected because the mouse orthologues have been previously studied extensively in my laboratory. Scans with a 50 bp window indicated that the conserved (> 75 % identity) flanking sequences are largely confined to regions within a few hundred base pairs of the tsp. There was very little alignment of the upstream region sequences and many gaps caused by the presence of numerous insertion elements. With this analysis, I detected only one short block of conserved sequence at -2 kb in rpL30 (77 % identity over 84 bp), one short block at -1.5 kb in rpL32 (82 % identity over 60 bp), and none in rpS16 . Neither of the conserved blocks contained any recognizable transcription factor binding sites or other remarkable characteristics. The lack of any credible long-range regulatory elements is consistent with earlier conclusions based on transient transfection experiments with these genes [In a preliminary analysis, I used the mVISTA sequence alignment program to examine six to ten kb of 5' flanking sequence of three pairs of orthologus rp genes  in the 5' flanks of a very high proportion of the rp genes see . Indeed,To evaluate the quality of TATA box motifs, I established criteria based on rules derived from a crystallographic analysis of TBP-DNA complexes . With thEmploying stringent criteria Figure , I used rpL13a (panel d) and within exon 2 of rpL30 (panel b), whereas in rpS18 (panel a) and rpS4 (panel c), it is at the extreme 3' end of exon 1. Many rp genes have this latter feature, which may be relevant to the evolution of vertebrate rp promoters (see below).Illustrative examples of four annotated promoter sequence comparisons are shown in Figure rpS18 promoter contains a conserved TATA (+) motif, while the TATA motifs of rpS4 and rpL13a were scored as (+/-) and that of rpL30 as (-). Well-conserved  consensus binding sites for GABP and/or Sp1 are located upstream of the tsp in all four examples; downstream YY1 sites are evident in rpL30 and rpL13a . The rpS18 and rpL13a promoters also contain conserved consensus binding sites for the ubiquitous AP1/ATF factors. The promoter elements that were found to have functional significance in experimental studies of the mouse rpL30 gene [rpL30 and rpL13a .The L30 gene  are all rpL29 ). In 29 % of the rp genes the AUG codon is at the extreme 3' end of exon 1 and in 47 % it is in exon 2. Thus, in 3/4 of the rp genes, the genetic elements involved in transcriptional/translational regulation are spatially separated from those with protein encoding function.The results of this type of analysis for the full set of rp promoters are tabulated in Table Contrary to previous impressions based on an incomplete set of rp genes, the rp promoters cannot generally be classified as "TATA-less". Thirty-five percent of the promoters contain, in the -25 region, a TATA box that should theoretically bind TBP with high affinity. An additional 25 % have an A/T-rich tract in this region, which might bind TBP with lower affinity, and the remainder would not be predicted to bind TBP without help from other proteins. For the most part, the TATA box quality is well conserved between the two mammalian species: the assessed quality of human and mouse TATA motifs was the same in 82 % of the rp promoters.The prevalence in rp promoters of evolutionarily conserved GABP, Sp1 and YY1 binding sites is readily apparent from these results. Conserved upstream GABP and Sp1 sites are present in 54 % and 48 % of the rp promoters, respectively. Conserved downstream YY1 sites are present in 52 % of the rp promoters. The ratio of aligned to unaligned sites in the human rp promoters is approximately 2:1 for GABP, 1:1 for Sp1 and 4:1 for YY1. The occurrence of unaligned sites in the mouse rp promoters is similar to that in the human rp promoters see . It is n2C+1TY(T)2(Y)3. A striking result is that T's are strongly preferred over C's at positions +2, +4 and +5. This preference, which is graphically illustrated in Figure The existence of a novel polypyrimidine initiator sequence in which the conventional A residue at the tsp is replaced by a C residue is well known. Moreover, the roles of this sequence in rp gene transcription and rp mRNA translation have been previously demonstrated experimentally for a few rp genes ,40-42. WrpS3  for mammals and lower vertebrates. Yet, the particular C residue within the initiator that is used as the major tsp may differ slightly. Also the adjudged quality of the TATA box for TBP binding is not always the same. Nevertheless, except for the location of upstream transcription factor-binding sites, the general features of rp promoter architecture are usually well conserved over large evolutionary distances.To determine the features of rp promoter architecture that are conserved over large evolutionary periods, I compared the promoter sequences of five chicken, six amphibian and five fish rp genes to their mammalian orthologues using the Clustal W multiple sequence alignment program. An example of such an alignment for 3 Figure  shows st3 Figure  indicategas5 and U17HG ). Annotated aligned sequences of the nine human and mouse non-rp TOP genes are presented on pages 1 through 9 of a supplementary file [see It is of interest to know which features of rp promoter architecture are specific and which might be common to other ubiquitously expressed genes. To this end, I examined the promoters of two additional sets of genes. One set consisted of non-rp genes that also produce translationally controlled mRNAs with 5'-terminal oligopyrimidine tracts (non-rp TOP genes). At the present, there are nine known genes in this category for which the tsp of at least one orthologue has been experimentally determined see . The nonfile see  and the There are some notable differences in the promoter architecture of rp genes and non-rp TOP genes. First, GABP- and YY1-binding motifs, which are prevalent in the rp promoters, are rarely found in the non-rp TOP promoters Table . Second,The second set of ubiquitously expressed genes consisted of 20 housekeeping genes randomly selected from the eukaryotic promoter database see . The proThe foregoing analysis of 79 mammalian ribosomal protein genes has revealed several features of rp promoter architecture, some of which are largely conserved over long periods of vertebrate evolution (about 450 million years) and others that are strongly conserved only in mammals. (about 90 million years). One highly conserved feature, present in over 3/4 of the rp genes, is the separation by an intron of the sequences involved in transcriptional and/or translational regulation from the sequences with protein-encoding function. In 47 % of the rp genes, the AUG translation initiation codon is in exon 2, and in 29 % of the genes, it is at the extreme 3' end of exon 1. It would seem that at an early stage of vertebrate evolution, these regulatory sequences were appended as discrete units to the loci containing the protein-encoding sequences.2C+1TY(T)2(Y)3. Thus, in addition to the C at the tsp, there is a clear preference for T over C at positions +2, +4, and +5. This preference may reflect a structural bias for transcription, e.g., ease of strand separation, or for translation, e.g., affinity of rp mRNAs for a putative repressor.The polypyrimidine tract that spans the tsp is present in all vertebrate rp genes. This tract can function as a transcriptional initiator ,41 and aThe presence of transposable element residues in the 5' flanks of the rp genes is noteworthy. Half of the rp genes contain an element (sines for humans, B1/B2 for mouse) within 500 bp of the tsp, and over 80 % of the genes contain an element within 900 bp. Some elements are moderately conserved between mouse and human, but most appear to be lineage-specific. These elements are unlikely to have any specific role in rp promoter function. They may be passively tolerated because the vast majority of conserved 5' sequence is confined to within 200 bp of the tsp. Within a segment from -200 to +100, the sequence identity between human and mouse rp orthologues ranges from 50 to 75 % with an average of 61 %, whereas the sequence match beyond -200 is of borderline significance.rpL32 , might bind TBP weakly without help from an additional protein [The observation that 35 % of the rp promoters contain a TATA box motif at -25, which would be predicted to bind TBP with high affinity, and that an additional 25 % possess A/T-rich motifs, which might bind TBP with lower affinity, was unexpected. The assessed quality of these motifs for TBP binding, made according to rules established by a detailed structural study of TBP-DNA complexes , was lar protein ,44, so tWhen human and mouse rp promoter regions from -200 to +100 were scanned for conserved  transcription factor-binding sites with the rVISTA program , which irpL30 and rpL32 genes [rpS14 and rpS6 genes [Xenopus rpL18 gene [rpS16 gene, GABP binding at the initiator decreases transcription activity both in vivo and in vitro [GABP is a heteromeric protein consisting of an ETS family member, which has DNA-binding capability, and an ankyrin repeat-containing subunit, which greatly improves the stability of GABP-DNA interactions ,46. Two-32 genes ,14, the S6 genes ,22, and L18 gene . The GABin vitro . For simrpL32 [rpL30 , a downstream YY1 interaction also contributed positively to transcriptional activity, but only when a strong upstream interaction with GABP was eliminated [Xenopus rpL18 was shown to interact with the frog homologue of YY1, but the functional significance of this interaction was not demonstrable with the reporter constructs that were used in these experiments [YY1 is a zinc finger-containing protein with a variety of gene-specific functions, including transcriptional activation and repression, positioning of RNA polymerase II, and chromatin modification ,48. FiftrpL32 . In mousiminated . Intereseriments . The diveriments , have leBased on the results of the analysis of rp promoter sequences, I have sorted the different rp promoters into eight classes according to whether they possess conserved binding sites for the three prevalent transcription factors, GABP, Sp1 and YY1 Figure . Only 10RACK1 gene is embedded in a polypyrimidine tract that conforms perfectly to the rp initiator consensus sequence. Moreover, the promoter contains a TATA box of +/- quality, an aligned upstream binding motif for Sp1 and an aligned downstream motif for YY1, but no readily detectable motifs for other ubiquitous transcription factors. Interestingly, the features of this promoter resemble those of the rpL13a gene, which also encodes a protein with apparent pleiotropic function.It is worth noting that some ribosomal proteins can also have extraribosomal functions ,51. AmonThis analysis has highlighted features of rp promoter architecture that are shared by a high proportion of the rp genes. The evolutionary conservation of these features lends strong support to their functional relevance. Yet, superimposed on this general design are variations that confer certain idiosyncratic characteristics on each promoter. There does not seem to be a single master switch that co-regulates all rp genes at the transcriptional level. Rather, the rp promoters are tuned to respond to a combination of factors, including components of the general transcription machinery, a relatively small group of sequence-specific transcription factors, and modifiers of chromatin structure. The inherent functional redundancy and lack of dependence on any single factor are useful design features for genes that must be expressed in a broad spectrum of cell types and environmental situations.2C+1TY(T)2(Y)3. Contrary to previous impressions based on studies of a small subset of rp genes, the majority of rp promoters contain a TATA box or an A/T-rich motif at -25 that should theoretically have TBP-binding capability. Similarly, approximately half of the rp promoters contain conserved binding motifs for transcription factors previously implicated in rp gene expression, namely upstream GABP and Sp1 sites and downstream YY1 sites. Conserved motifs for other ubiquitous factors occurred much less frequently. Transposable element residues within 900 bp of 5'-flanking sequence were present in over 80 % of the rp genes; very little sequence conservation was evident more than 200 bp upstream of the tsp. Some of these architectural features were seen to be specific for rp promoters. From the results of this analysis, it was possible to sort the rp promoters into eight classes according to their possession of putative binding sites for GABP, Sp1 and YY1, and also to specify which promoters should have intrinsic affinity for TBP. This classification might prove useful for interpreting the results of experiments in which cell-specific or physiologically induced variations in the expression of different subsets of rp genes are observed.A sequence comparison of the promoter regions of all 79 orthologous human and mouse ribosomal protein genes has revealed several evolutionarily conserved features that are characteristic of a high proportion of the rp gene set. One such feature, which is also evident in the rp genes of lower vertebrates, is the separation by an intron of the sequences involved in transcriptional and translational regulation from the sequences with protein encoding function. Another conserved feature is the polypyrimidine initiator, which in mammals conforms to the consensus (Y)The rp gene sequences were extracted from three database sources see . The vasrRNA, ribosomal RNA; rp, ribosomal protein; tsp, transcriptional start point; TOP, terminal oligopyrimidine sequence; TBP, TATA-binding protein.ST1: Identification of the transcriptional start points (tsp's). Comparison of experimental determinations of the tsp's of human and mouse rp genes.Click here for fileST2: Promoter region sequences of rp genes. Sources of rp sequences, amount of analyzed sequence 5' of tsp, and locations of insertion elements nearest the tsp.Click here for fileAligned promoter sequences of rp genes. Annotated sequence alignments of 79 orthologous human and mouse rp promoters and a key to the annotation.Click here for fileST3: Characterization of the rp initiator. Occupancy matrix for determination of the consensus sequence of the mammalian rp initiator.Click here for fileST4: Promoter region sequences of non-rp TOP genes. Sources of non-rp TOP gene sequences, the amount of analyzed sequence 5' of the tsp, and location of insertion elements nearest the tsp.Click here for fileAligned promoter sequences of non-rp TOP genes. Annotated sequence alignments of 9 orthologous human and mouse non-rp TOP promoters.Click here for fileST5: Housekeeping gene promoters. List of 20 housekeeping gene sequences extracted from the Eukaryotic Promoter Database, which were analyzed for GABP, Sp1 and YY1 binding sites and for TATA box quality.Click here for file


This article reports the first national assessment of patterns of drinking and gambling-related rulemaking on college campuses (e.g., punitive versus recovery oriented). Analyses relating school policies to known school rates of drinking or gambling identified potentially influential policies. These results can inform and encourage the development of guidelines, or "best practices," upon which schools can base future policy.The college policy information was collected from handbooks, Web sites and supplemental materials of 119 scientifically selected colleges included in the fourth (2001) Harvard School of Public Health College Alcohol Study (CAS). A coding instrument of 40 items measured the scope and focus of school alcohol and gambling policies. This instrument included items to measure the presence of specific policies and establish whether the policies were punitive or rehabilitative. A total of 11 coders followed a process of information extraction, coding and arbitration used successfully in other published studies to codify policy information.Although all schools had a student alcohol use policy, only 26 schools (22%) had a gambling policy. Punitive and restrictive alcohol policies were most prevalent; recovery-oriented policies were present at fewer than 30% of schools. Certain alcohol and gambling policies had significant relationships with student binge drinking rates.The relative lack of college recovery-oriented policies suggests that schools might be overlooking the value of rehabilitative measures in reducing addictive behaviors among students. Since there are few college gambling-related policies, schools might be missing an opportunity to inform students about the dangers of excessive gambling. Young people are at increased risk for alcohol- and gambling-related problems compared to their older counterparts -3. ColleThe problems associated with addictive behaviors on college campuses have been well documented  . However, science can contribute to the creation of successful policy. Recognizing the important role that science can play in the development and evaluation of public policy, the federal government recently released draft "regulatory science" guidelines . The OffThe purpose of this study is to encourage the development of science guided school policy. To accomplish this goal, we will examine the prevalence and characteristics of alcohol- and gambling-related policies, including policy provisions for student recovery, in a scientifically selected sample of U.S. colleges. We will not include illicit drug policies in this analysis because illicit drug use is illegal for both adults and young people; these illegal behaviors fall under the purview of state and federal law that supersedes college policy. Our intent is to examine college policies that focus on legal activities. Therefore, using college alcohol and gambling policies, binge drinking rates and gambling frequency as evidence, this report describes the epidemiology  and influence of these assorted policies.During 1989, the federal government initiated basic alcohol and substance abuse education requirements. Previously, there was not a regulatory mandate obligating institutions of higher learning to set alcohol or drug use policy or bring students' attention to these rules if they existed. Schools also were not required to disseminate substance use policy information to parents or other interested parties. This situation changed with the passage of the federal Drug-Free Schools and Communities Act (DFSCA) of 1989.The DFSCA applies to all U.S. colleges. The act specifies that "as a condition of receiving funds or any other form of financial assistance under any Federal program, an institution of higher education (IHE) must certify that it has adopted and implemented a drug [and alcohol] prevention program...". Thus, aThe overall impact of mandated drug and alcohol programs is still unknown; as we noted before, there is some evidence that risky and addictive behaviors on college campuses are still prevalent despite targeted efforts by administrators to reduce student substance abuse ,6. SeverInconsistent policy content among institutions can create a problematic state of affairs. Although DFSCA directives aim to increase awareness of the potential dangers of alcohol and drug use among students, numerous studies continue to identify high levels of alcohol abuse on U.S. college campuses in recent years ,12-14,6.Even though individual colleges have adopted different strategies for reducing the problems associated with excessive alcohol consumption, the extent and effect of these efforts are largely unknown. One approach, perhaps in response to DFSCA, has been to develop and enforce policies on student substance abuse and recovery. Although recent psychosocial programs attempting to reduce student drinking behaviors have failed to reduce binge drinking , officiaStudents who seek help for alcohol or other substance use problems are faced with a multitude of school-provided and external treatment options. Addiction recovery programs are diverse, ranging from formal treatment programs  to less formal self-help options, (e.g., 12-step fellowships) . Regardlenforcement (i.e., application of policy consequences) of alcohol policies aimed at combating underage drinking did result in decreased alcohol consumption among students. Beneficial effects resulting from the enforcement of existing rules, however, can be difficult to interpret. For example, in that study, it is unclear whether the enforcement of rules encouraged lower levels of drinking or entry to treatment for intemperate drinking or, alternatively, simply forced problematic drinkers to withdraw from school.Binge drinking, the consumption of five or more alcoholic drinks (four or more for women) on at least one occasion at one to two week intervals , has beeSome research suggests that gambling on college campuses is commonplace. A study of student gambling at six colleges in five different states (i.e., New York, New Jersey, Nevada, Oklahoma, and Texas) showed that of 1,771 surveyed students, 23% reported that they gambled at least weekly (ranging from 11% in Texas to 39% in Nevada) . In thatFor comparison, the National Gambling Impact Study Commission (NGISC) considered the adult rates of lifetime pathological gambling from four sources . The lowOther research contradicts the findings that college students are at elevated risk for problem gambling compared to the general adult population. For example, a recently published longitudinal study of students at the University of Missouri-Columbia showed markedly lower prevalence rates than the studies summarized above . In thisDespite the frequency with which college students engage in gambling activities, some evidence suggests that administrators are unaware of the dangers associated with excessive gambling among students; in addition, colleges do not have adequate policies addressing gambling . This siThis study is the first to identify patterns of drinking and gambling-related rulemaking on college campuses (e.g., punitive versus recovery oriented). By relating school policies to known school rates of drinking or gambling ,6 we canGiven the paucity of empirical college-based policy research, this study will fill an important gap in knowledge. To fill this void, this research will test a variety of addiction-related hypotheses that have not yet been examined empirically. Based upon the extant literature, this study will test the following four primary hypotheses:• Because there are few requirements guiding the creation of school substance use and gambling policies, the content and clarity of these policies will be heterogeneous across schools and modes of policy distribution (e.g., handbooks vs. school Web sites);• College alcohol policies currently devote relatively little attention to student recovery;restrictive alcohol use policies will experience higher levels of binge drinking among students than schools with prohibitive and recovery-oriented alcohol policies;• Due to differences in enforcement, awareness of the dangers of excessive alcohol consumption, educational programs and types of students, schools with either no or only • Absent a federal mandate that requires gambling-related regulations or education on college campuses, gambling policies will be less prevalent than alcohol use policies.United States College and University Addiction and Recovery Policies. The study qualified for exemption under 46 CFR §102(f) and the assurance identification number is M1240-01.The purpose of this study is to identify and assess alcohol and gambling policies among U.S. colleges. To ensure a representative national sample of colleges, we examined the scientifically selected sample of public and private American colleges that was used in a recent series of Harvard studies (e.g., Wechsler 2002 ). The deAt the beginning of the project, we submitted an e-mail request for a hard copy of their student handbook to each school's admissions office. Each e-mail specified that we were interested in collecting school alcohol and gambling policies and requested that our inquiry be forwarded to the most appropriate school official. We gathered e-mail addresses for admissions offices from each school's official Web site. Using each school's main telephone number to initiate contact, investigators contacted schools that did not respond within thirty days to our e-mail request and verbally requested a handbook and any other existing alcohol and gambling policy materials. Typically, the person answering the call referred us to admissions offices, deans' offices, or student services offices for further assistance; we identified ourselves as calling from Harvard Medical School only when asked.To be eligible for inclusion in this study, each college policy had to meet the following five eligibility criteria:1. the policy had to prohibit, govern, or otherwise attempt to regulate alcohol use or gambling among students at a U.S. college or university;2. the policy had to be in effect ;3. the policy had to be readily available to the public, either in electronic or hard copy;4. the policy had to be written in English;5. the policy had to be available for review by project investigators no later than July 31, 2003.Our primary source of alcohol and gambling policies was each school's student handbook.  The student handbook is a centralized forum for regulatory information and is a primary source of official school policies for students and parents, as well as the public. In addition, the concept of a student handbook is widespread, making handbooks a common information source across many schools. Many institutions distribute student handbooks to all incoming freshmen; therefore, most students are familiar and comfortable with accessing the handbook. Student handbooks also are widely available to the public.When available, we used electronic versions (i.e., pdf or html) of each school's handbook; otherwise, we used a hard copy. Some schools, particularly large universities with many departments and/or divisions, did not have a single handbook that they distributed to all students. In these cases, we retrieved the school's policies from other official documents . Many schools also posted policy information (i.e., separate from the handbook) on their Web sites; we analyzed this information as a secondary source. We conducted an exhaustive search of each school's Web site using each site's integrated search engine and used keywords such as "alcohol," "drinking," "alcohol policy," "gambling," "wagering," "betting," "gambling policy," "substance use policy," "college (university) regulations," and "college (university) policies" to identify relevant sections of each Web site. Several sites did not include a search function; in such cases, we conducted a comprehensive visual search of the site. We also examined supplemental materials provided by schools  for comparison against handbooks and Web-based materials. We conducted a visual search of all hard-copy handbooks and supplemental policy materials and extracted all relevant information from these sources.We systematically archived all of the Web-based and other electronic regulatory sources  from each school on a computer. We filed hard copy materials, such as student handbooks and policy manuals, by school and kept these documents on site.Investigators developed a coding instrument by studying alcohol and gambling policies from a variety of U.S. schools outside the current sample and identifying the underlying characteristics of the policies. These characteristics were reduced to 40 items that reflected the scope and focus of school alcohol and gambling policies. The items were converted into a coding instrument that included 25 variables for alcohol policy and 15 variables for gambling policy. This instrument included items to measure the presence of specific policies and establish whether the policies were punitive or rehabilitative. All variables used a nominal scale that included common characteristics of each school policy; response choices varied slightly with the focus of each variable. All of the variables were arranged on a six-page coding form.To simplify coding and allow for within-school comparisons between different formats of policy dissemination (e.g. school handbook vs. school Web site), we separated each school's policy materials into three categories: (1) student handbooks (electronic or paper); (2) Web-based materials; and (3) supplementary materials (paper); a potential 357 documents required coding . However, because not every school had documents available in all three coding categories, the final document count was 164. Specifically, at the end of our data collection process, we had collected 73 student handbooks, 70 Web-based policies, and 21 supplementary documents.We assigned 11 coders the job of evaluating each school's alcohol and gambling policies. Each coder read a selection of policies and extracted relevant information in accordance with the coding form. The coding process proceeded as follows:1. Each policy document was assigned to two of eleven eligible DOA coders randomly. Each assigned coder independently abstracted information from each assigned policy document and recorded this information on separate coding forms.2. For each document, one member of the research team, designated as the "arbiter," compared the two coding forms and marked discrepant items.3. The arbiter returned the marked coding forms to their respective coders and requested that coders reconsider their answers to the items in question. Upon reconsideration, coders were free to change their answers or keep their original answers.4. Coders resubmitted their recoded documents to the arbiter who compared the discrepant items again. Discrepancies that remained were noted and resolved by the arbiter.5. Once all discrepancies had been resolved, the policy assessments on the coding forms were entered into an SPSS database using a procedure that screened entries for out-of-range values and discrepancies in branching among items.6. We assessed data entry reliability by selecting 10% of the cases in our database and rechecking each data entry point. Of the 680 items entered in these 17 randomly selected cases, there were no observed data entry errors.Shaffer and his associates have used a similar process of information extraction, coding and arbitration successfully in other published studies ,32.Our analysis of college alcohol and gambling policies generated several types of results. First, we describe the results of our coding procedure, the final sample of schools and available policy information. Next, we examine the policy evidence across information sources by analyzing the consistency between the information provided by handbooks and Web materials. We then present the prevalence of individual policy items and the results of a factor analysis that explored the underlying dimensions of the policy variables. Finally, we analyze the relationships between policies and student drinking and gambling rates using information collected in the most recent Harvard School of Public Health College Alcohol Study (CAS) .We assessed inter-coder reliability by comparing the total number of discrepant coded items to the total number of coded items. As described previously, each policy was assigned to two of eleven eligible DOA coders randomly. The participation of eleven coders yielded 55 possible coding-pair combinations; each of these pairings coded at least one policy. Specifically, the number of policies coded by each coder-pair ranged from a minimum of one (n = 6) to a maximum of six (n = 3). Coders had up to two opportunities to code each document: (a) an initial round of coding; and (b) a second round of coding to reconsider any discrepant items identified by the arbiter after the initial round of coding. The arbiter made the final coding decision on 345 out of a total of 4,100 possible items. The coding process yielded a study-wide inter-coder reliability rate of 91.6%.After thirty days had passed from our initial e-mail request, 46 of 119 schools had responded by sending hard copy materials. Eighteen of these 46 colleges sent materials completely unrelated to our request for school alcohol policies (e.g., applications for admission, school newsletters). Fourteen schools sent student handbooks, and another 14 schools sent other alcohol and/or gambling related (i.e., non-handbook) materials. Seventy-three schools did not respond to our request within thirty days. Subsequent to our follow-up telephone requests, we received student handbooks and supplemental materials from an additional 22 schools. This recruitment procedure resulted in 50 schools actively providing policy information for this study; for the remainder, policy information was obtained through other investigative procedures as described earlier (e.g., Web sites).This study sought information on alcohol and gambling policy from a representative sample of 119 colleges across the U.S. We utilized three distinct common sources of information on school alcohol policy: student handbooks, school Web sites (non-handbook related) and supplementary materials . We collected a total of 164 policy-related documents from three sources: 73 policy documents from handbooks, 70 documents from school Web sites, and 21 from supplementary materials. Table We aggregated and analyzed policy information across sources because a preliminary examination revealed content differences among handbooks, Web sites  and suppTo determine the added contribution of supplemental materials (i.e., policy information presented in the supplements that was unavailable elsewhere), we created another set of recompiled variables following the previously outlined procedure. These variables reflected the total number of policies identified for the three schools with all three types of sources . We summed the policies reflected by the recompiled variables and then subtracted the policies contributed by handbooks and Web sources; this procedure revealed that supplemental materials contributed 4 of 30 (13.3%) policy items.Although school Web sites provide a substantial amount of alcohol policy information that is not contained in the primary document customarily provided to students (i.e., handbook), the overall added contribution of the school Web site in presenting policy information varied among schools. For example, one school's Web site contained an additional eight alcohol regulations that were not included in the handbook; however, several schools' sites contained no additional information. In addition, the type of information that was presented only on Web sites also varied: while most information pertained mainly to secondary alcohol policies (e.g., school-sponsored events and drinking regulations for drinking-aged students), some schools chose to present vital alcohol policy information  on their Web site only (n = 2). Thus, although handbooks and Web sites are both important sources of alcohol policy information and supplements contribute little additional information, consistency across sources varies. The following analyses assess the agreement of information found in multiple sources.As mentioned earlier, of the 117 colleges for which we had information, all 117 (100%) had a written policy on student alcohol consumption and 26 schools (22%) had a student gambling policy. Because all schools had a written alcohol policy (and relatively few schools had a gambling policy), the following analyses focus on alcohol policies.Determining concordance between handbook and Web sources is important because administrators might be unaware of inconsistencies between official school documents. In addition, contradictory information can mislead students and potential applicants. We assessed the concordance between sources of college alcohol policy materials by determining the level of agreement (i.e., presence or absence of policy information) between handbooks and Web materials; that is, we compared the content of each type of document to identify differences in the presentation of each school's policy information between sources. We did not extend this particular analysis to include supplemental materials because, as we noted before, only a small number of schools (n = 3) had all three types of sources.Twenty-eight schools had both a handbook and Web materials; for each of these 28 schools we determined the absence or presence of the 25 alcohol policy variables in each source. We predetermined that a concordance rate of 85% would indicate a high level of agreement between documents. To be considered in agreement, complementary information had to be found in (or absent from) both sources; in cases where this requirement was not satisfied, the policies were considered in disagreement. Using these criteria, we determined that three policy variables (i.e., 12% of the policy variables) were mentioned often and were present in both handbooks and on Web sites, and consequently, showed high agreement. Either type of information resource seldom mentioned ten policy variables (i.e., 40% of the policy variables), therefore, also exhibiting high agreement. The remaining 12 policy variables (i.e., 48% of the policy variables) were often mentioned, but not consistently by both sources, indicating low agreement.Table and Web sites in nearly all cases.Policy variables that were rarely mentioned in handbooks and Web materials appear in Table Table As noted earlier, the coding process revealed that all 117 colleges (i.e., 100% of the schools for which information was available) in this sample had a written policy on student alcohol consumption, but only 26 (22%) had a published policy that addressed gambling. The small number of schools with gambling policies precludes confident analysis of the dimensional composition of our gambling variables; therefore, we applied the factor analysis that follows only to alcohol policy variables.Three policy variables represented a multi-dimensional measurement strategy to yield detailed policy information. Consequently, we collapsed these three redundant policy items into the primary or gate items from which they originated . This resulted in 22 alcohol policy variables in all remaining analyses. These dependent variables all measured different aspects of school alcohol policies (e.g., policy presence, content, and target). To empirically examine the underlying dimensions reflected by our variables, we conducted an exploratory factor analysis. This procedure employed an initial factor extraction (i.e., component matrix) and then an orthogonal rotation to simple structure. We selected the Varimax rotation to maximize the variance of loadings within factors and minimize the covariance across factors. The orthogonal solution identified eight policy clusters with Eigenvalues greater than 1.0 that explained 72.36% of the total variation. This explained variance lies within the 50–75% useful range suggested by Overall and Klett (1972). ConsequTable School policy and the law) contained only one item that loaded ≥ 0.50 and explained 4.83% of the total variance. Many schools deferred to local law entirely and did not publish other policies that were unique to the school. Factor 1 identifies this deference policy as a unique dimension. Factor 2 (i.e., Prohibition policies) expands on deference to local law and presents additional school policies that prohibit alcohol for underage and legal age students. These items accounted for 5.43% of the total variance. Factor 3 includes policies that extend restrictions to include drinking by students of legal age . Items in Factor 3 explained 6.65% of the total variance. Factors 1, 2 and 3 include alcohol policies that focus on the legal status  of students; in addition, for those of legal age, these policies range from no school specific policies to prohibitions for students who are old enough to drink legally.The eight factors are ordered according to the number of policies measuring the overall domain; that is, factors containing general, or "blanket," policy items are listed first, followed by factors containing more specific policy items. Factor 1 (i.e., Limits and restrictions – on campus) provides specific guidance about where on-campus students can drink and how much alcohol is available (i.e., housing and container and quantity restrictions); these items accounted for 9.13% of the total variance. Factor 5 policies (i.e., Events policies) accounted for 7.20% of the total variance and focus primarily on restrictions for on- and off-campus events. Factor 6 (i.e., Limits and restrictions – off campus) accounted for 13.50% of the total variance and includes policies that regulate off-campus activities .Factors 4 through 6 include policy variables directed to alcohol use on-campus and off-campus. Factor 4 (i.e., Recovery recognition policies) recognize that students can have alcohol related problems that require recovery, and that these problems can exist before entering college or develop during college; these items accounted for 20.59% of the total variance in the data. Finally, Factor 8 (i.e., Recovery facilitation) accounted for 5.03% of the total variance and includes policies that reflect how the school participates in the recovery process (i.e., triage or treatment). One item  failed to load ≥ 0.50 on any factor and was excluded from the final analysis.Different from the first 6 factors, factors 7 and 8 focus on student recovery. Factor 7 policies (i.e., Prohibition policies) to 5.4% (i.e., Limits and restrictions-off-campus).College alcohol policies varied widely. Table We conducted several analyses to determine the nature of relationships between student alcohol consumption, gambling behavior and policy content. As the factor analysis above illustrates and the relative prevalence of policies confirms, college alcohol-related policies are primarily intended to prevent, reduce or restrict alcohol use among students on college campuses. To test the relationships between alcohol policies and student drinking behaviour, we compared the mean binge drinking rates of students at schools with and without each policy variable. We obtained the mean binge drinking rates of the schools in our sample from the dataset used in Wechsler et al.'s Harvard School of Public Health College Alcohol Study (CAS). BecauseSchools that had either no policy restrictions or a prohibition policy for on-campus alcohol use by students ≥ 21 had lower mean past-month student binge drinking rates (39% and 36%, respectively) compared to schools that employed an intermediate level of restrictive policies (47%) (F = 7.07, df = 2,113, p < .001). Schools that allowed or did not mention alcohol use at on-campus sanctioned events for students ≥ 21 had a higher mean binge drinking rate (46% and 44%, respectively) than schools that prohibited legal drinking at events (33%) (F = 5.25, df = 2,113, p < .001). Schools that offered alcohol-free housing had a higher mean student binge drinking rate of 49% compared to schools that did not mention alcohol-free housing which had a binge rate of 42% (F = 4.01, df = 1,114, p < .01). Two other alcohol policy variables evidenced significant relationships with student binge drinking behaviors, but these policies lacked widespread implementation at a large number of schools. Schools that specifically allowed a leave of absence for a student to participate in recovery activities (n = 2) evidenced a higher mean binge drinking rate (69%) than schools that did not mention such a policy (43%, n = 114). Keeping the small number of schools in mind, it is worth noting that schools that prohibited off-campus alcohol consumption for students ≥ 21 (n = 4) had a lower mean binge rate (10%) than schools without this provision (45%, n = 112).There were not enough schools with gambling policies to permit a detailed analysis of the relationship between policies and student gambling behavior; therefore instead of conducting an analysis of the relationship between gambling behavior and individual policy variables, we only were able to assess gambling behavior based on whether schools had a gambling policy. Using prevalence data from LaBrie et al.'s (2003)  recent sLong ago, Pigou  noted thSchools that restricted or prohibited on-campus alcohol use for students over 21 evidenced similar mean past-year student gambling participation rates (i.e., 40% and 41%, respectively), and schools with no restrictive policy evidenced a higher student gambling participation rate (46%) (F = 2.64, df = 2,113, p < .08). Schools that did not mention or allowed alcohol at on-campus events for legal drinkers exhibited a higher mean gambling participation rate (i.e., 44% and 40%, respectively) than schools that prohibited alcohol at on-campus events (35%) (F = 5.17, df = 2,113, p < .001). Similarly, schools that did not limit the quantity of alcohol available at events showed higher past-year gambling participation among students (42%) compared to schools with no such provision (37%) (F = 5.39, df = 1,114, p < .001). Schools that had off-campus alcohol restrictions for legal-aged drinkers had a gambling rate of 38% while schools that did not had a mean gambling rate of 42% (F = 2.94, df = 1,114, p < .1).Two other alcohol policy variables evidenced significant relationships with student gambling behaviors, but these policies were not widely implemented throughout the sample. Schools that did not expressly prohibit alcohol consumption for underage drinkers (n = 3) evidenced a mean past-year student gambling rate of 51%, while schools that prohibited underage drinking (n = 116) had a gambling rate of 41% (F = 3.19, df = 1,114, p < .1). Schools that banned all alcohol consumption, whether on- or off-campus (n = 4) evidenced a lower gambling rate (30%) than schools that allowed at least some drinking (41%, n = 112) (F = 5.80, df = 1,114, p < .05).and a policy prohibiting on-campus legal-aged drinking (n = 9) had a mean binge drinking rate of 29% – much lower than schools with just an alcohol policy (40%, n = 15), a gambling policy (47%, n = 17) or neither (45%, n = 75) (F = 3.15, df = 1,112, p < .1). Schools with both a gambling policy and a policy prohibiting alcohol at on-campus events (n = 6) had a significantly lower mean binge rate (22%) than schools with just an alcohol policy (40%, n = 9), a gambling policy (46%, n = 20) or neither (45%, n = 81) (F = 5.88, df = 1,112, p < .05). Schools that prohibited alcohol at on-campus events also evidenced significantly lower past-year student gambling rates than schools without such prohibitions: 30% versus 38% or higher (F = 8.63, df = 1,112, p < .05).In addition to the direct relationships between policy variables and binge drinking and gambling, three alcohol policy variables evidenced unexpected interaction or intensification effects when gambling policies also were present. Schools that had both a policy prohibiting or restricting gambling activity among students Using written (i.e., hard copy) and Web based sources, this study examined the nature and extent of alcohol and gambling-related policies among a representative sample of U.S. colleges. Every school in this representative sample had at least one alcohol use policy; however, few schools  had at least one gambling policy available. The relative rarity of gambling-related policies on college campuses represents a lost opportunity by school administrators to (a) prevent or limit disordered gambling among students and (b) facilitate recovery for students in need of gambling treatment. A recent study showed that, while not as prevalent as previously thought, gambling on college campuses is still quite common, with 42% of students having gambled in the past year and 2.6% gambling weekly or more . The freAll the schools in our sample recognized the need for some type of alcohol policy; however, the presence of more targeted policies varied considerably. Although this variation might reflect different policymaking strategies across institutions, it also could result from a variety of other influences, including the lack of federal standards guiding the creation of alcohol policy on college campuses. The absence of policy guidelines leaves administrators with a wide range of options about how to best address student substance use and abuse. Some administrators might prefer to match policy to their perception of local needs, while others might welcome policy guidelines. Both of these circumstances encourage additional research designed to help guide administrators to identify effective policies (e.g., "best practices").Alcohol policies ranged from comprehensive restrictions and prohibition to liberal acceptance of student alcohol use. Policies encouraging recovery among students with alcohol use disorders were decidedly absent from our sample. For example, only 57.3% of schools expressed in writing that they made referrals to alcohol recovery services; all other recovery-oriented policy provisions were in place at fewer than 30% of schools, with two-thirds of these policies in effect at fewer than 10% of schools. Examination of the mean prevalence of the eight policy factors provides additional support for this finding. The mean prevalence of recovery recognition policies was 6.5% (i.e., factor 7). Although recovery facilitation policies were more common, with a mean prevalence of 42.8% (i.e., factor 8), this rate simply reflects that many schools report making referrals to outside treatment facilities. In contrast, the prevalence of prohibition policies was 92.3% (i.e., factor 1). This limited of consideration for student recovery and emphasis on punitive and prohibitive measures might reflect an underlying institutional bias against accommodating students with special needs and an unsupportive atmosphere for those who are at most risk for developing alcohol problems. The higher prevalence of policies that direct referrals to outside treatment resources might indicate an eagerness among administrators to export students with addiction problems to non-school affiliated assistance. Alternatively, placing little emphasis on recovery might simply represent a lack of understanding about addictive behaviors and addiction recovery among school administrators.Even though the results of this study indicate that schools with recovery policies can evidence higher rates of binge drinking, this rate might reflect a pre-existing campus problem (i.e., policy as a consequence of behavior) rather than be a result of recovery policy implementation. Future policy research needs to examine whether a better balance between punishment and treatment policies will yield improved student health services, less substance misuse and, consequently, a better campus life for all students.As hypothesized, there were considerable and important differences between the information that was available in handbooks and on the Web. This observation is not surprising because there are few requirements guiding the creation of school substance use and gambling policies and no standards requiring consistency among sources. Also, the factor analysis illustrated that alcohol policies currently concentrate primarily upon prevention and punishment, and devote relatively limited attention to student recovery. Finally, as we expected, schools with no policy restrictions on alcohol consumption or restrictive alcohol policies often experienced higher levels of binge drinking among students than schools with prohibitive alcohol policies. Nevertheless, alcohol policies were associated inconsistently with student binge drinking rates; few policy variables exerted influence on patterns of student drinking. In some cases, policies designed to reduce student alcohol consumption showed an opposite effect.The results of this policy analysis suggest diverse and perhaps ambivalent tolerance toward alcohol use among U.S. colleges that has led to a deep underlying problem: there is a lack of model policy guidelines to assist colleges in (a) preventing addictive behaviors among students and (b) providing assistance to students already struggling with addiction. Optimally, if available, such guidelines would provide school administrators with "best practice" model policies that address the many aspects of addiction among students  and would outline strategies for implementing and enforcing such policies. In the absence of an explicit regulatory framework (i.e., the current policy environment), schools are left to regulate addictive behaviors based upon the local attitudes and expectations of communities and implicit moral values held by school administrators. This circumstance can lead colleges to install policies intended to have immediate and drastic results (i.e., prevention and punishment policies) while neglecting policies that would promote recovery and provide lasting benefit to students. The absence of evidence-based policy leaves school administrators in a position of promulgating policy that might have effects that are contrary to their intentions. For example, the Boston Globe reported on October 30, 2002 that, "Forty-seven Massachusetts colleges will sign onto a statewide campaign today designed to punish students who abuse alcohol and to cut down on the rate of binge drinking on campuses by providing alcohol-awareness training for students, athletes, and Greek system members". This tyThe prevalence of alcohol-related problems at U.S. colleges highlights the need for comprehensive student policies addressing all aspects of alcohol use. Further, for policy to be effective students need to be aware of and understand school requirements; this requires that students know how to access policy information. Because schools currently are not required to disseminate alcohol policies in any particular form or through any specific medium, the availability of existing policy information can vary substantially among schools. Though most commonly printed in student handbooks, substance use policies also appear in policy manuals, pamphlets and, increasingly, on school Web sites. One recent study of college Web-based alcohol policy information  found thTables This study reveals that to gain a complete understanding of the components of a school's alcohol policy, it is necessary to consult both the handbook and the school Web site whenever possible. However, schools do not alert students and parents to this fact, and it is unreasonable for school administrators to expect inquiring persons to conduct complex searches for information that is considered to be freely available in the public domain.The results of the factor analysis provide a stark portrait of the current composition of college policies on potentially addictive behaviors. This analysis reveals that six of eight factors contained prohibitive and/or punitive policy variables. Although the factor analysis merely revealed the underlying psychometric properties of our instrument, the prevalence of specific policy variables across schools provides additional support for this finding. Whereas the results suggest that prohibition-oriented policies have been effective in reducing binge drinking and gambling under certain conditions, the relative scarcity of recovery-oriented policies prevents us from properly comparing the efficacy of these two strategies.The analysis of policy variables and binge drinking rates revealed a variety of relationships among policy variables and student drinking behaviors. Specifically, four policy variables related to student binge drinking  a policy prohibiting alcohol at on-campus events and (b) a prohibitive gambling policy also had small enrollment (i.e., below the 50th percentile among schools in our sample); four of these six schools were state-operated. Underlying characteristics of students who seek out small state schools might be associated with the reduced binge rates reported among these institutions. These results suggest that, despite the role for shared policy guidelines, schools will benefit from analyzing the composition of their student body and tailoring new and modified alcohol policies to students' specific characteristics. Although competing explanations prevent the establishment of concrete cause-and-effect relationships in this study, the observed interaction effects between alcohol and gambling policies provide significant impetus for future research into effective policy strategy on college campuses.The interaction effects observed among alcohol policy variables and the presence of gambling policy on binge drinking behavior and past-year student gambling behavior presents an interesting and unanticipated finding. Because schools that have prohibitive alcohol policies From an observer's perspective, it appears that the many policy inconsistencies – and policy presentation inconsistencies – observed in this study reflect reactive policymaking strategies that are not guided by empirical evidence. The evidence suggests that effective school alcohol and drug policies, and student awareness of these policies, are important for many reasons. For example, college-aged individuals in recovery are extremely vulnerable to relapse; in addition to the generally high rate of relapse during the first year of recovery ,48, thisIt is especially important for school administrators to address risky drinking behaviors among students who do not currently have a drinking problem. Research has shown that addictive disorders originate with risk factors that always include exposure to potential objects of addiction ,50,52. MSeveral methodological limitations to this study should be noted. First, this study relied solely upon written policy materials. Although we conducted an exhaustive search of the Internet and requested hard materials from schools, it is possible that we failed to identify some publicly available policy materials that could have provided additional information about schools in our sample. In addition, we identified our policy variables by examining existing policies and identifying relevant regulatory components; however, others attempting to replicate this study might identify and measure different aspects of policy and, consequently, obtain different results. Further, this study considered official alcohol policy content across a sample of U.S. colleges; however, assessing official policy provides no data on whether or how schools enforce their stated policies. It is possible, and in many cases even likely, that schools rely on informal rules and established precedents to govern alcohol use or gambling violations. Due to the complex nature of the relationships between school administrators, students, parents and legal authorities, many schools likely assess alcohol or gambling violations on a case-by-case basis; consequently, practice policy might be very different from the formal rules described by official school documentation.This study has shown that there are many opportunities and perhaps an obligation to scientifically investigate the complex relationships between college alcohol and gambling policies and addictive behaviors. Future research, for example, should focus on policy enforcement and informal policies adopted by school administrators to provide a better understanding of current college practices regarding alcohol use and abuse. In addition, as schools begin to reevaluate and amend their substance abuse policies, longitudinal research could provide insight into the effects of policy revision on student behaviors. In addition, to advance our understanding of policy effects on intemperate patterns of behavior, future college-based research will need to examine the influence of policies on more specific behaviors. New research should deconstruct the macro indices (e.g., average rates) of binge drinking to determine whether policies can impact college violence, crime, driving under the influence, etc.College alcohol and gambling policy data holds important potential for future research. For example, for students with alcohol or gambling related disorders attending colleges with policies that interfere with treatment or fail to support recovery, the rate of relapse is likely to be higher than under a more treatment favorable public policy context. Similarly, research can demonstrate that policies can influence the likelihood of early identification and intervention: under some unsympathetic regimes, students with addiction problems will not come forward for assistance or adhere to a prescribed treatment program. Finally, new research needs to show that without supportive policies to guide college staff responses to treatment seeking students, this population will miss both the college experience and the opportunity to build a healthy foundation for their future.In this study, we analyzed a representative sample of U.S. colleges to determine the attentiveness of school policies toward students with addictive disorders and their recovery. The results encourage the development and implementation of reporting tools (e.g., a rating system) that could prove valuable as both a resource for parents of at-risk students and a vehicle to raise public awareness. Identifying trends in collegiate policymaking as well as distinguishing strong and weak policies will allow us to begin to develop evidence based guidelines, or "best practices," upon which schools can base the development of future policy.The author(s) declare that they have no competing interests.HS conceived the study, was its principal architect, and was responsible for its overall conduct and exposition. AD was responsible for the data acquisition, adjudicated the reviewer ratings, and contributed to the drafting of the manuscript. RL was responsible for the statistical design, execution, and exposition. RK provided direct assistance to AD and participated in the preparation of the manuscript. DL contributed to the study structure, data analyses, and manuscript preparation. All the authors were members of the team that critically reviewed and coded the college policies. All authors read and approved the final manuscript.


Infection of plants by necrotizing pathogens can lead to the rapid and localized induction of a complex set of defense responses resulting in a restriction of pathogen growth and spread. Subsequently, an increase of plant resistance against a broad spectrum of pathogens is observed systemically. This plant immunity is known as Systemic Acquired Resistance. To identify components of the transduction pathway, we cloned and analysed the expression pattern of several mRNAs accumulating in cucumber plants after induction of Systemic Acquired Resistance.N-Acetylglucosaminyltranferase III and a putative pathogenesis related protein. The time course of accumulation of the three corresponding mRNAs was analysed by northern blotting in plants treated by BTH or in plants infected by Colletotrichum lagenarium.We tested on cucumber different compounds known to induce systemic acquired resistance. Among these, BTH (benzo(1,2,3)thiadiazole-7-carbothioic acid S-methyl ester) proved to be very effective. mRNA RT-PCR differential display was used to identify mRNA sequences induced 24 hours after the application of 10 μM BTH to cucumber plants. A cDNA library constructed from cucumber plants sprayed with 10 μM BTH was screened to get corresponding full length cDNAs. Among the identified cDNAs were those coding for a putative ras-related GTP-binding protein, a putative beta-1,4-N-acetylglucosaminyltranferase III have been reported to be components of signal transduction pathways in mammals and plants.The mRNA RT-PCR differential display technique allowed the identification of three genes possibly involved in Systemic Acquired Resistance in cucumber. Pathogenesis-related proteins are known to be involved in plant defence against pathogens. GTP-binding protein and  Infection of plants by necrotizing pathogens can lead to the induction of a complex set of defense responses resulting in a restriction of pathogen growth and spread. The infected leaves develop a hypersensitive response (HR), i.e., rapid, localized cell death occurring at the sites of pathogen entry . ConcomiArabidopsis thaliana [Salicylic acid was identified as an important signal in the SAR transduction pathway. It was shown to accumulate during the onset of SAR in cucumber , tobaccothaliana . Exogenothaliana . Plants thaliana ,8.A. thaliana mutants has revealed that the NPR1 protein  is required for SAR induction and acts downstream of salicylic acid in the SAR pathway. Plants carrying mutations in this gene fail to express several PR genes and display enhanced susceptibility to infection [PR-1 gene [Arabidopsis thaliana [Analysis of nfection ,10. The R-1 gene -13. The R-1 gene , while cR-1 gene . Other cthaliana . They inthaliana .PR genes include 2,6-dichloroisonicotinic acid (INA), benzo(1,2,3)thiadiazole-7-carbothioic acid S-methyl ester (BTH) and L-α-amino butyric acid (ABA) [Besides pathogens, SAR is also induced by exogenously applied chemicals. In addition to salicylic acid, well-known chemical inducers of id (ABA) -23. SAR id (ABA)  that invid (ABA) . Local aid (ABA) -28.The aim of the present work was to identify and clone mRNAs accumulating after induction of SAR in cucumber plants. These sequences could correspond to proteins potentially involved in the signal transduction pathway leading to SAR or to proteins responsible for the state of resistance. In a first set of experiments, potential SAR inducing chemicals were tested in order to set up a reproducible system of activation of this resistance in cucumber. The mRNA RT-PCR differential display method  was then2. Control plants were infiltrated with water. In a parallel experiment, four-week-old cucumber plants (with two true leaves) were sprayed with 5 mM salicylic acid, 50 mM L-α-amino butyric acid, 0.78 mM 2-thiouracil, 1 mM thiamine, 20 mM BaCl2 or 1 mM BTH. Control plants were sprayed with water or left untreated. Total RNAs were extracted from treated leaves 6 h, 24 h or 48 h after treatment. Induction of PR-8 gene was assayed by Northern blotting followed by hybridization with a cucumber PR-8 cDNA probe. PR-8 cucumber gene encodes an acidic chitinase which accumulates after tobacco necrosis virus (TNV) infection or salicylic acid induction and is considered as a SAR molecular marker [The SAR inducing activity of different chemicals has already been documented in one or several plant species -23. To er marker .PR-8 gene could be due to wounding during infiltration, the effect of wounding alone was evaluated by making a cut from the midvein to the outer edge of the cotyledons. A strong signal was obtained after wounding which could be explained by induction of the acidic chitinase itself or of an isoform. Therefore infiltration did not prove to be an appropriate method for applying SAR inducers in cucumber, because it probably induced a wound response.In infiltration experiments (results not shown), control plants showed positive hybridization signals. To check whether this activation of the 2 induced slightly PR-8 expression (results not shown). RNA from control plants did not show any hybridization signal indicating that spraying itself did not induce PR-8 expression. BTH, which is an analogue of salicylic acid, showed the strongest PR-8 induction. But cucumber plants treated with 1 mM BTH showed a reduced growth . As BTH was shown to be a very efficient activator of disease resistance in different plant species [When applied by spraying, BTH, L-α-amino butyric acid and 2-thiouracil strongly induced PR-8 mRNA accumulation, while SA treatment led to a lower induction level Fig. . Thiamin species -23, we tColletotrichum lagenarium and salicylic acid treatment was shown to induce resistance against this pathogen [C. lagenarium. Two weeks after inoculation, the plants were scored for spreading lesions, i.e. lesions showing a larger size than the initial inoculated area. As shown in figure C. lagenarium showed large spreading lesions and thus extensive fungal growth. Treatment of plants with BTH prior to C. lagenarium inoculation resulted in a markedly decreased lesion formation  were respectively 86% and 83.5%. In BTH treated plants, 38 % (10 μM BTH) or 12 % (50 μM BTH) of inoculated sites developed spreading lesions . In the remaining case (dd2), no signal could be observed on the slot blots. This absence of hybridization signal could be due to a lack of sensitivity of the slot blot hybridization procedure.Plants were sprayed with 10 μM BTH or water. Sampling was performed 24 h after treatment in order to point out early-induced differences in gene expression. RT-PCR products were separated on polyacrylamide gels. Bands that appeared on the display of RNA only from BTH treated plants, or only from water treated plants were likely to correspond to differentially expressed mRNAs. Twelve differentially expressed bands were identified Table . Their sA. thaliana. It will be referred to as CRG (cucumber RAS-related GTP-binding protein). The cDNA dd4 matched to a translation releasing factor 2. It will be referred to as CTR (cucumber translation releasing factor 2). The cDNA dd6 matched to a putative β-1,4-N-Acetylglucosaminyltranferase III from A. thaliana. This protein was named CGT (cucumber acetylglucosaminyltransferase III). The cDNA dd11 matched to a putative pathogenesis related protein from A. thaliana and, with slightly less homology, to a pathogenesis related protein from barley induced by fungal infection [The dd3, dd4, dd5, dd6, dd7 and dd11 cDNA fragments were sequenced. Blast analysis did not lead to identification of any homology with known sequences. This is not surprising as mRNA differential display generates fragments corresponding to 3'untranslated regions for which homologies are difficult to find. Two of the six fragments were proved to be part of the same gene (dd5 and dd7). A cDNA library was constructed from cucumber plants sprayed with 10 μM BTH (leaves were sampled 24 h after treatment). The library was screened with the five differentially expressed fragments. Hits were obtained for four of these probes (corresponding to dd3, dd4, dd6 and dd11). Full length cDNAs corresponding to dd4, dd6 and dd11 were obtained. Homology between cloned cDNA and sequences in databases is presented in table nfection . It willPR-8, CPR, CRG and CGT genes in cucumber, the two first leaves of four-week old plants were sprayed with 10 μM BTH. In another batch of plants, the first leaf was inoculated with C. lagenarium. Total RNA was extracted from treated leaves or upper untreated leaves at various times after treatment. Accumulation of the PR-8, CPR, CRG and CGT mRNAs was assayed by Northern blotting followed by hybridization with the corresponding cDNA probes  and by inoculation with C. lagenarium (with a maximum at 72 h) in the leaves submitted to the treatment. A systemic induction could also be observed in untreated leaves from C. lagenarium inoculated plants (as from 72 h after infection).nts fig. . NeverthCRG gene was too low to allow us to show an induction of the expression (data not shown).The expression level of the PR-8 and CPR genes was only observed in the cut leaf 24 h after wounding. No expression was observed later nor in the uncut upper leaf. The CGT and CRG genes were not induced by wounding (results not shown).Expression of the same genes was analyzed in wounded cucumber plants. A cut was made from the midvein to the outer edge of the first leaf. Total RNA was extracted from the cut leaf or the upper leaf, 24 and 48 h after wounding. An induction of the expression of Pseudomonas putida BTP1 suspension, a plant growth-promoting rhizobacteria known to promote induced systemic resistance in cucumber [PR-8, CPR, CGT and CRG did not show any induction of expression in these conditions (results not shown).Expression of these genes was also analyzed in cucumber plants showing rhizobacteria-induced systemic resistance. Plants were grown in compost drenched with a cucumber . Total RPR-8 gene, which encodes an acidic chitinase from cucumber, was used as an indicator of the activation of the defense response. The accumulation of this acidic chitinase after tobacco necrosis virus infection or salicylic acid induction correlates with induced resistance [PR-8 gene expression. The protective effects of BTH on cucumber were confirmed in challenge experiments with C. lagenarium. Spraying cucumber plants with BTH (10 μM or 50 μM) allowed effective local and systemic protection against C. lagenarium. BTH was recently identified as a safe, reliable and non phytotoxic plant protection agent by scientists at Novartis. Exogenous application of BTH to tobacco, A. thaliana, wheat and cucumber has been shown to activate a number of SAR associated genes leading to enhanced plant protection against various pathogens [We tested here two different techniques and several compounds to induce SAR in cucumber. The expression of sistance . Among tathogens -22,28.N-acetylglucosaminyltranferase III (CGT) and a putative pathogenesis related protein (CPR). Expression of PR-8, CPR and CGT genes was shown to be induced by 10 μM BTH treatment as well as C. lagenarium infection. The response to BTH was observed earlier (5 h after treatment) than the one developed after pathogen inoculation (72 h after infection). However, systemic expression of these genes was only observed in C. lagenarium infected plants.Identifying SAR induced genes could provide clues to elucidate the signal transduction pathway leading to plant defense responses. We used RT-PCR differential display in BTH-treated cucumber plants to detect SAR associated mRNAs. We have identified four BTH-inducible genes: a putative ras-related GTP binding protein (CRG), a putative translation releasing factor 2 (CTR), a putative β-1,4-N-Acetylglucosaminyltranferase III catalyses the addition of N-acetylglucosamine to the β-mannoside of the tri-mannose core in N-glycans, resulting in the suppression of further processing and elongation. In mammals, N-acetylglucosaminyltransferase III expression is associated with differentiation, cell adhesion and tumor progression [2O2-induced activation of protein kinase C [N-linked glycans were shown to be widely distributed in plants and highly expressed at the cell surface, which might suggest a putative function in cell/cell communication [N-Acetylglucosaminyltranferase has never been described in the context of a plant-pathogen interaction. Several cDNAs or gene encoding enzymes involved in the biosynthesis of complex N-linked glycans have been cloned from plants. They include N-acetylglucosaminyltranferase I cDNAs from A. thaliana, potato and tobacco [N-acetylglucosaminyltransferase II cDNA from A. thaliana [N-acetylglucosaminyltranferases are involved in important mechanisms, notably signaling pathways and therefore seem of high interest. The putative PR protein, which has been first identified in barley after fungal infection [Small GTP-binding proteins form a large family of nucleotide triphosphatases whose activity is related to the binding, hydrolysis and release of guanosine triphosphate . MAP kingression ,44. It wkinase C ,46. N-linication . To our  tobacco , N-acetythaliana  and defethaliana . GTP-binnfection  has no kPR-8 and CPR genes were induced by wounding but not systemically. PR-8 and CPR genes were not induced by P. putida BTP1 treatment, which triggers induced systemic resistance (ISR) in cucumber. ISR is phenotypically similar to SAR but the mechanisms of this resistance were shown to be different: although this was not tested with P. putida BTP1, in other experimental systems ISR was shown to be dependent on NPR/NIM1 function, but does not involve salicylic acid, nor PR protein accumulation [A. thaliana was independent of PR genes expression [CGT and CRG expression, as these genes were not induced by P. putida BTP1.Only mulation . Our respression . In the C. lagenarium. Using RT-PCR differential display, we identified four BTH-inducible genes, including a putative ras-related GTP binding protein (CRG), a translation releasing factor 2 (CTR), a putative β-1,4-N-acetylglucosaminyltranferase III (CGT) and a putative pathogenesis related protein (CPR). Genes expression studies confirmed the local induction of CGT and CPR after BTH treatment or C. lagenarium infection and their systemic induction in response to C. lagenarium infection. Moreover CPR was locally induced by wounding. The significant level of expression of CGT and CPR genes during defense responses suggests a potential role for the gene products in the SAR pathway or in the state of resistance in cucumber.Among different SAR inducers tested on cucumber, BTH proved to be very efficient. Applied by spraying, BTH induced PR-8 mRNA accumulation and allowed effective local and systemic protection against Cucumis sativus cv. Marketer) were grown in compost at 22°C with a 16 h light photoperiod.Cucumber plants . Chemicals were dissolved in water and the pH adjusted to 6.6 with NaOH except for thiamine, BaClPseudomonas putida BTP1 suspension (4.108 CFU/ml in 0.85% NaCl). Control seeds were soaked in 0.85% NaCl. Cucumber seeds were sown in 10 cm-pots containing sterilized potting soil previously mixed with a P. putida BTP1 inoculum to a final concentration of 3.107 CFU/g or with an equal volume of sterile water for control plants. Cucumber were germinated at 25°C with a 16 h light photoperiod. Six and 12 days after sowing, 20 ml of a bacterial suspension at 108 CFU/ml were added as a drench to the roots. Control plants were watered with 20 ml of 0.85% NaCl.Prior to planting, disinfected cucumber seeds were soaked for 10 min in a C. lagenarium (106 spores/ml). In challenge experiments, inoculation was performed 5 (or 7) days after chemical treatment on the second or third leaf.Plants were placed in a humidity chamber 48 hours before infection experiments. The first true leaf was inoculated with 10 drops (10 μl) of a conidial suspension of 32P PR-8, CPR, CGT or CRG cDNA probe (Random Primed DNA labeling kit, Roche).The extraction of total RNA from cucumber leaves (5 plants per treatment) was performed using a phenol/SDS method . Norther35S dATP, separated by electrophoresis on denaturing 6% polyacrylamide gels and visualized by autoradiography. PCR reactions showing differentially displayed bands were repeated twice on two different RNA samples in order to reduce the number of false-positives.The mRNA differential display was performed using the differential display kit from Eurogentec (Belgium) and following the instructions of the supplier. PCR products were labeled with α-2O followed by boiling during 10 min, then precipitated and suspended in 10 μl of H2O. A second PCR amplification was performed on 4 μl of DNA following the same protocol than for the differential display itself. Products were cloned in pGEM-T vector (Promega) and manually sequenced by the dideoxy sequencing method. Available public databases (i.e. EMBL) were searched for homology with our sequences using the GCG software package .Differentially displayed bands were excised and eluted during 30 min in 100 μl of H32P labeled RT-PCR corresponding products from either BTH or H2O treated plants.PCR amplified DNA from four to ten clones of each differentially displayed band was blotted on a positively charged nylon membrane using a filtration manifold and following the instructions of the supplier (Hoefer). Blots were hybridized with the 32P labeled cDNA probes. cDNA sequencing was performed at Genome Express, France. Available public databases (i.e. EMBL) were searched for homology with our sequences using the GCG software package .mRNA from cucumber plants sprayed with 10 μM BTH (leaves were sampled 24 h after treatment) were purified with the PolyATractmRNA Isolation System III from Promega. The cDNA library was performed with the SMART cDNA Library Construction Kit from Clontech following the instructions of the supplier for cDNA synthesis by primer extension. The library was screened with CB carried out the plants treatments, the molecular biology studies and the database research and drafted the manuscript. MO supplied the pathogen and participated in the challenge and ISR induction experiments. JD and PT participated in the design and coordination of the study. All authors read and approved the manuscript.PR-8 mRNA accumulation in cucumber leaves in response to different concentrations of BTH. Total RNA was extracted from cucumber leaves 24 h and 48 h after spraying with water, 10 μM BTH, 30 μM BTH, 100 μM BTH or from untreated leaves (UT). RNA was fractionated by electrophoresis on agarose gel. Northern blot was probed with α-32P labeled PR-8 cDNA. Loading of equal amounts of RNA was confirmed by ethidium bromide (Et Br) staining.Click here for file