Cross-level sociodemographic homogeneity alters individual risk for completed suicide.

Among deaths of despair, the individual and community correlates of US suicides have been consistently identified and are well known. However, the suicide rate has been stubbornly unyielding to reduction efforts, promoting calls for novel research directions. Linking levels of influence has been proposed in theory but blocked by data limitations in the United States. Guided by theories on the importance of connectedness and responding to unique data challenges of low base rates, geographical dispersion, and appropriate comparison groups, we attempt a harmonization of the National Violent Death Reporting System (NVDRS) and the American Community Survey (ACS) to match individual and county-level risks. We theorize cross-level sociodemographic homogeneity between individuals and communities, which we refer to as "social similarity" or "sameness," focusing on whether having like-others in the community moderates individual suicide risks. While analyses from this new Multilevel Suicide Data for the United States (MSD-US) replicate several individual and contextual findings, considering sameness changes usual understandings of risk in two critical ways. First, high individual risk for suicide among those who are younger, not US born, widowed or married, unemployed, or have physical disabilities is cut substantially with greater sameness. Second, this moderating pattern flips for Native Americans, Alaska Natives, Asians, and Hispanics, as well as among native-born and unmarried individuals, where low individual suicide risk increases significantly with greater social similarity. Results mark the joint influence of social structure and culture, deliver unique insights on the complexity of connectedness in suicide, and offer considerations for policy and practice.

How do latent print examiners perceive proficiency testing? An analysis of examiner perceptions, performance, and print quality.

Proficiency testing has the potential to serve several important purposes for crime laboratories and forensic science disciplines. Scholars and other stakeholders, however, have criticized standard proficiency testing procedures since their implementation in laboratories across the United States. Specifically, many experts label current proficiency tests as non-representative of actual casework, at least in part because they are not sufficiently challenging (e.g., [1-4]. In the current study, we surveyed latent print examiners (n = 322) after they completed a Collaborative Testing Services proficiency test about their perceptions of test items. We also evaluated respondents' test performance and used a quality metric algorithm (LQMetrics) to obtain objective indicators of print quality on the test. Results were generally consistent with experts' concerns about proficiency testing. The low observed error rate, examiner perceptions of relative ease, and high objective print quality metrics together suggest that latent print proficiency testing is not especially challenging. Further, examiners indicated that the test items that most closely resembled real-world casework were also the most difficult and contained prints of the lowest quality. Study findings suggest that including prints of lower quality may increase both the difficulty and representativeness of proficiency testing in latent print examination.

A new statistical model for analyzing rating scale data pertaining to word meaning.

The concrete-abstract categorization scheme has guided several research programs. A popular way to classify words into one of these categories is to calculate a word's mean value in a Concreteness or Imageability rating scale. However, this procedure has several limitations. For instance, results can be highly distorted by outliers, ascribe differences among words when none may exist, and neglect rating trends in participants. We suggest using an alternative procedure to analyze rating scale data called median polish analysis (MPA). MPA is tolerant to outliers and accounts for information in multiple dimensions, including trends among participants. MPA performance can be readily evaluated using an effect size measure called analog R 2 and be integrated with bootstrap 95% confidence intervals, which can prevent assigning inexistent differences among words. To compare these analysis procedures, we asked 80 participants to rate a set of nouns and verbs using four different rating scales: Action, Concreteness, Imageability, and Multisensory. We analyzed the data using both two-way and three-way MPA models. We also calculated 95% CIs for the two-way models. Categorizing words with the Action scale revealed a continuum of word meaning for both nouns and verbs. The remaining scales produced dichotomous or stratified results for nouns, and continuous results for verbs. While the sample mean analysis generated continua irrespective of the rating scale, MPA differentiated among dichotomies and continua. We conclude that MPA allowed us to better classify words by discarding outliers, focusing on main trends, and considering the differences in rating criteria among participants.

Forensic bitemark identification: weak foundations, exaggerated claims.

Several forensic sciences, especially of the pattern-matching kind, are increasingly seen to lack the scientific foundation needed to justify continuing admission as trial evidence. Indeed, several have been abolished in the recent past. A likely next candidate for elimination is bitemark identification. A number of DNA exonerations have occurred in recent years for individuals convicted based on erroneous bitemark identifications. Intense scientific and legal scrutiny has resulted. An important National Academies review found little scientific support for the field. The Texas Forensic Science Commission recently recommended a moratorium on the admission of bitemark expert testimony. The California Supreme Court has a case before it that could start a national dismantling of forensic odontology. This article describes the (legal) basis for the rise of bitemark identification and the (scientific) basis for its impending fall. The article explains the general logic of forensic identification, the claims of bitemark identification, and reviews relevant empirical research on bitemark identification-highlighting both the lack of research and the lack of support provided by what research does exist. The rise and possible fall of bitemark identification evidence has broader implications-highlighting the weak scientific culture of forensic science and the law's difficulty in evaluating and responding to unreliable and unscientific evidence.

The Theory of Industrial Society and Cultural Schemata: Does the "Cultural Myth of Stigma" Underlie the WHO Schizophrenia Paradox?

The WHO's International Studies of Schizophrenia conclude that schizophrenia may have a more benign course in "developing" societies than in the West. The authors focus on this finding's most common corollary: cultural schemata are shaped by the transition from agrarian to industrial society. Developing societies are viewed as traditional, gemeinschaft cultures lacking the stigmatizing beliefs about persons with mental illness held in modern, gesellschaft cultures of developed societies. The Stigma in Global Context-Mental Health Study formalized the cultural myth of public stigma (CMPS) with propositions linking level of development to intolerant, exclusionary, and individualistic attitudes. In 17 countries, the authors find no support for the corollary; where support is found, the findings are opposite expectations, with developed societies reporting lower stigma levels. Reconceptualizing of the cultural landscape on more specific dimensions also produces null or contrary findings. This correction to nostalgic myths of cultural context in developing societies thwarts misguided treatment, policy, and stigma-reduction efforts.

Quantification of length-bias in screening trials with covariate-dependent test sensitivity.

Length-biased sampling exists in screening programs where longer duration disease is detected during the preclinical stage because a longer sojourn time (preclinical duration) has a higher probability of being screen detected. By modeling the course of disease, we quantify the effect of length-biased sampling on clinical duration when cases are subject to periodic screening with variable test sensitivity. We use the highly flexible bivariate lognormal density to jointly model preclinical and clinical durations, and we model screening test sensitivity as a function of the sojourn time and number of previous false negative screens. We show that the mean clinical duration among screen-detected cases can be up to 40% higher, with shrinking standard deviation, than those among nonscreen-detected cases, due to biased sampling alone, irrespective of any possible benefit (increased survival time arising from earlier detection or reduction in mortality). These findings will aid in the design and interpretation of screening trials.

The nutritionally responsive transcriptome of the polyphenic beetle Onthophagus taurus and the importance of sexual dimorphism and body region.

Developmental responses to nutritional variation represent one of the ecologically most important classes of adaptive plasticity. However, knowledge of genome-wide patterns of nutrition-responsive gene expression is limited. Here, we studied genome-wide transcriptional responses to nutritional variation and their dependency on trait and sex in the beetle Onthophagus taurus. We find that averaged across the transcriptome, nutrition contributes less to overall variation in gene expression than do sex or body region, but that for a modest subset of genes nutrition is by far the most important determinant of expression variation. Furthermore, our results reject the hypothesis that a common machinery may underlie nutrition-sensitive development across body regions. Instead, we find that magnitude (measured by number of differentially expressed contigs), composition (measured by functional enrichment) and evolutionary consequences (measured by patterns of sequence variation) are heavily dependent on exactly which body region is considered and the degree of sexual dimorphism observed on a morphological level. More generally, our findings illustrate that studies into the developmental mechanisms and evolutionary consequences of nutrition-biased gene expression must take into account the dynamics and complexities imposed by other sources of variation in gene expression such as sexual dimorphism and trait type.

Evolutionary and ecological genomics of developmental plasticity: novel approaches and first insights from the study of horned beetles.

Phenotypic plasticity pervades organismal development and physiology where it facilitates an enormous range of adaptive responses to novel or stressful environments. Plasticity also impacts evolutionary processes, reducing the probability of population extinction in the face of environmental changes and sometimes increasing speciation rates in developmentally plastic lineages. Despite the adaptive significance of plasticity, organisms are not infinitely plastic; rather they are constrained in the kinds and ranges of environmental changes to which their body parts, organs, and tissues can respond. Understanding the nature, costs, and limits of developmental plasticity requires insight into (i) the developmental-genetic and genomic mechanisms underlying plastic responses as well as (ii) their interplay with ecological and social conditions. In this chapter we review and summarize recent progress in the development of horned beetles as a study system with which to explore the interactions between changing ecological conditions and plastic, genome-wide responses in gene expression and developmental function. In particular, we focus on plastic responses to nutritional variation, which in horned beetles differ widely as a function of body region, sex, and species. We begin by introducing the study system and summarize the developmental-genetic and genomic tool set currently available for horned beetles. We then present recently developed statistical approaches that can be used to guide the design of multi-factorial genome-wide transcriptional comparisons when circumstances prohibit a fully balanced design. We present an example of such an approach in the horned beetle Onthophagus taurus and end by highlighting the growing opportunities for future ecological-genomic studies in horned beetles.

The lead time distribution when lifetime is subject to competing risks in cancer screening.

This paper extends the previous probability model for the distribution of lead time in periodic cancer screening exams, namely, in that the lifetime T is treated as a random variable, instead of a fixed value. Hence the number of screens for a given individual is a random variable as well. We use the actuarial life table from the Social Security Administration to obtain the lifetime distribution, and then use this information to project the lead time distribution for someone with a future screening schedule. Simulation studies using the HIP study group data provide estimates of the lead time under different screening frequencies. The projected lead time has two components: a point mass at zero (corresponding to interval cases detected between screening exams) and a continuous probability density. We present estimates of the projected lead time for participants in a breast cancer screening program. The model is more realistic and can inform optimal screening frequency. This study focuses on breast cancer screening, but is applicable to other kinds of cancer screening also.

Effect of length biased sampling of unobserved sojourn times on the survival distribution when disease is screen detected.

Data can arise as a length-biased sample rather than as a random sample; e.g. a sample of patients in hospitals or of network cable lines (experimental units with longer stays or longer lines have greater likelihoods of being sampled). The distribution arising from a single length-biased sampling (LBS) time has been derived (e.g. (The Statistical Analysis of Discrete Time Events. Oxford Press: London, 1972)) and applies when the observed outcome relates to the random variable subjected to LBS. Zelen (Breast Cancer: Trends in Research and Treatment. Raven Press: New York, 1976; 287-301) noted that cases of disease detected from a screening program likewise form a length-biased sample among all cases, since longer sojourn times afford greater likelihoods of being screen detected. In contrast to the samples on hospital stays and cable lines, however, the length-biased sojourns (preclinical durations) cannot be observed, although their subsequent clinical durations (survival times) are. This article quantifies the effect of LBS of the sojourn times (or pre-clinical durations) on the distribution of the observed clinical durations when cases undergo periodic screening for the early detection of disease. We show that, when preclinical and clinical durations are positively correlated, the mean, median, and quartiles of the distribution of the clinical duration from screen-detected cases can be substantially inflated-even in the absence of any benefit on survival from the screening procedure. Screening studies that report mean survival time need to take account of the fact that, even in the absence of any real benefit, the mean survival among cases in the screen-detected group will be longer than that among interval cases or among cases that arise in the control arm, above and beyond lead time bias, simply by virtue of the LBS phenomenon

Improved machine learning method for analysis of gas phase chemistry of peptides.

BACKGROUND: Accurate peptide identification is important to high-throughput proteomics analyses that use mass spectrometry. Search programs compare fragmentation spectra (MS/MS) of peptides from complex digests with theoretically derived spectra from a database of protein sequences. Improved discrimination is achieved with theoretical spectra that are based on simulating gas phase chemistry of the peptides, but the limited understanding of those processes affects the accuracy of predictions from theoretical spectra. RESULTS: We employed a robust data mining strategy using new feature annotation functions of MAE software, which revealed under-prediction of the frequency of occurrence in fragmentation of the second peptide bond. We applied methods of exploratory data analysis to pre-process the information in the MS/MS spectra, including data normalization and attribute selection, to reduce the attributes to a smaller, less correlated set for machine learning studies. We then compared our rule building machine learning program, DataSqueezer, with commonly used association rules and decision tree algorithms. All used machine learning algorithms produced similar results that were consistent with expected properties for a second gas phase mechanism at the second peptide bond. CONCLUSION: The results provide compelling evidence that we have identified underlying chemical properties in the data that suggest the existence of an additional gas phase mechanism for the second peptide bond. Thus, the methods described in this study provide a valuable approach for analyses of this kind in the future.

"Get smart Colorado": impact of a mass media campaign to improve community antibiotic use.

CONTEXT: Large-scale strategies are needed to reduce overuse of antibiotics in US communities. OBJECTIVES: To evaluate the impact of a mass media campaign-"Get Smart Colorado"-on public exposure to campaign, antibiotic use, and office visit rates. DESIGN: Nonrandomized controlled trial. SETTING: Two metropolitan communities in Colorado, United States. SUBJECTS: The general public, managed care enrollees, and physicians residing in the mass media (2.2 million persons) and comparison (0.53 million persons) communities. INTERVENTION: : The campaign consisting of paid outdoor advertising, earned media and physician advocacy ran between November 2002 and February 2003. PRINCIPAL MEASURES: Antibiotics dispensed per 1000 persons or managed care enrollees, and the proportion of office visits receiving antibiotics measured during 10 to 12 months before and after the campaign. RESULTS: After the mass media campaign, there was a 3.8% net decrease in retail pharmacy antibiotic dispenses per 1000 persons (P = 0.30) and an 8.8% net decrease in managed care-associated antibiotic dispenses per 1000 members (P = 0.03) in the mass media community. Most of the decline occurred among pediatric members, and corresponded with a decline in pediatric office visit rates. There was no change in the office visit prescription rates among pediatric or adult managed care members, nor in visit rates for complications of acute respiratory tract infections. CONCLUSIONS: A low-cost mass media campaign was associated with a reduction in antibiotic use in the community, and seems to be mediated through decreases in office visits rates among children. The campaign seems to be cost-saving.

Systematic order-dependent effect in expression values, variance, detection calls and differential expression in Affymetrix GeneChips.

MOTIVATION: Affymetrix GeneChips are common 3' profiling platforms for quantifying gene expression. Using publicly available datasets of expression profiles from human and mouse experiments, we sought to characterize features of GeneChip data to better compare and evaluate analyses for differential expression, regulation and clustering. We uncovered an unexpected order dependence in expression data that holds across a variety of chips in both human and mouse data. RESULTS: Order dependence among GeneChips affected relative expression measures pre-processed and normalized with the Affymetrix MAS5.0 algorithm and the robust multi-array average summarization method. The effect strongly influenced detection calls and tests for differential expression and can potentially significantly bias experimental results based on GeneChip profiling.

Validation and estimation of parameters for a general probabilistic model of the PCR process.

Earlier work rigorously derived a general probabilistic model for the PCR process that includes as a special case the Velikanov-Kapral model where all nucleotide reaction rates are the same. In this model, the probability of binding of deoxy-nucleoside triphosphate (dNTP) molecules with template strands is derived from the microscopic chemical kinetics. A recursive solution for the probability function of binding of dNTPs is developed for a single cycle and is used to calculate expected yield for a multicycle PCR. The model is able to reproduce important features of the PCR amplification process quantitatively. With a set of favorable reaction conditions, the amplification of the target sequence is fast enough to rapidly outnumber all side products. Furthermore, the final yield of the target sequence in a multicycle PCR run always approaches an asymptotic limit that is less than one. The amplification process itself is highly sensitive to initial concentrations and the reaction rates of addition to the template strand of each type of dNTP in the solution. This paper extends the earlier Saha model with a physics based model of the dependence of the reaction rates on temperature, and estimates parameters in this new model by nonlinear regression. The calibrated model is validated using RT-PCR data.

A-to-I pre-mRNA editing of the serotonin 2C receptor: comparisons among inbred mouse strains.

The serotonin receptor 5HT2CR pre-mRNA is subject to adenosine deamination (RNA editing) at five residues located within a 15 nucleotide stretch of the coding region. Such changes of adenosine to inosine (A-to-I) can produce 32 mRNA variants, encoding 24 different protein isoforms, some of which vary in biochemical and pharmacological properties. Because serotonin mediates diverse neurological processes relevant to behavior and because inbred mouse strains vary in their responses to tests of learning and behavior, we have examined the A-to-I editing patterns of the 5HT2CR mRNA in whole brains from eight mouse strains. By sequencing approximately 100 clones from individual mice, we generated detailed information on levels of editing at each site and patterns of editing that identify a total of 28 mRNA and 20 protein isoforms. Significant differences between individuals from different strains were found in total editing frequency, in the proportion of transcripts with 1 and 4 edited sites, in editing frequency at the A, B, E and D sites, in amino acid frequencies at positions 157 and 161, and in subsets of major protein isoforms. Primer extension assays were used to show that individuals within strains (six C3H.B-+rd1 and four 129SvImrJ) displayed no significant differences in any feature. These findings suggest that genetic background contributes to subtle variation in 5HT2CR mRNA editing patterns which may have consequences for pharmacological treatments and behavioral testing.

The "minimizing antibiotic resistance in Colorado" project: impact of patient education in improving antibiotic use in private office practices.

OBJECTIVE: To assess the marginal impact of patient education on antibiotic prescribing to children with pharyngitis and adults with acute bronchitis in private office practices. DATA SOURCES/STUDY SETTING: Antibiotic prescription rates based on claims data from four managed care organizations in Colorado during baseline (winter 2000) and study (winter 2001) periods. STUDY DESIGN: A nonrandomized controlled trial of a household and office-based patient educational intervention was performed. During both periods, Colorado physicians were mailed antibiotic prescribing profiles and practices guidelines as part of an ongoing quality improvement program. Intervention practices (n=7) were compared with local and distant control practices. DATA COLLECTION/EXTRACTION METHODS: Office visits were extracted by managed care organizations using International Classification of Diseases-9-Clinical Modification codes for acute respiratory tract infections, and merged with pharmacy claims data based on visit and dispensing dates coinciding within 2 days. PRINCIPAL FINDINGS: Adjusted antibiotic prescription rates during baseline and study periods increased from 38 to 39 percent for pediatric pharyngitis at the distant control practices, and decreased from 39 to 37 percent at the local control practices, and from 34 to 30 percent at the intervention practices (p=.18 compared with distant control practices). Adjusted antibiotic prescription rates decreased from 50 to 44 percent for adult bronchitis at the distant control practices, from 55 to 45 percent at the local control practices, and from 60 to 36 percent at the intervention practices (p<.002 and p=.006 compared with distant and local control practices, respectively). CONCLUSIONS: In office practices, there appears to be little room for improvement in antibiotic prescription rates for children with pharyngitis. In contrast, patient education helps reduce antibiotic use for adults with acute bronchitis beyond that achieved by physician-directed efforts.

Computational methods in medical decision making: to screen or not to screen?

Screening for a disease such as cancer is often regarded as a beneficial and successful strategy for reducing mortality. However, as with any clinical treatment or intervention, benefit cannot be assumed, and screening can entail both costs and harms, so the screening as a 'treatment' must undergo evaluation. An evaluation requires a definition of the treatment 'benefit', design of studies to measure that benefit with as little bias and variance as possible, and the development of methods for estimating the potential benefit. In screening studies, the factors most central to the evaluation are unobservable (e.g. earliest point in time at which disease becomes detectable, or 'preclinical'; time at which disease might have been detected in the absence of screening; test sensitivity). Thus, screening programs should be evaluated on scenarios in which these factors are varied, to ensure the robustness of the estimated benefit under a variety of circumstances. This article describes the importance of computational methods and simulations to assess the benefit of screening programs, particularly for cancer, based on randomized screening trials, with special attention to benefit time, lead time, and bias due to length-biased sampling.

Appropriate antibiotic use: variation in knowledge and awareness by Hispanic ethnicity and language.

BACKGROUND: Recent campaigns are informing the public that antibiotics are inappropriate for viral respiratory infections. As little is known about their effect on populations challenged by less access to care, lower education, low income, low English proficiency, or non-mainstream cultural backgrounds, this study assessed knowledge, attitudes, and awareness in an ethnically diverse community. METHODS: A telephone survey in English or Spanish of a cross-sectional, random sample of 692 non-Hispanic whites (NHWs) and 300 Hispanics in Colorado. RESULTS: For all respondent groups, knowledge of appropriate antibiotic use for colds and bronchitis was low. Hispanics surveyed in Spanish, compared with non-Hispanic whites, had significantly lower knowledge about antibiotics for colds, higher knowledge for bronchitis, lower awareness about antibiotic resistance, and greater dissatisfaction if an antibiotic were not prescribed. In all comparisons, English-language Hispanics tended to reflect non-Hispanic white response patterns. Independent predictors of awareness were ethnicity, education, and age. Independent predictors of dissatisfaction were ethnicity, knowledge about antibiotic use for colds, and bronchitis. Ethnicity was an independent predictor of knowledge about the inappropriateness of antibiotics for colds and bronchitis. CONCLUSIONS: To bridge knowledge gaps, educational campaigns for all segments of the population are needed. Content should be responsive to heterogeneity within populations.

A general probabilistic model of the PCR process.

This work describes a general probabilistic model for the PCR process; this model includes as a special case the Velikanov-Kapral model where all nucleotide reaction rates are the same. In this model the probability of binding of deoxynucleoside triphosphate (dNTP) molecules with template strands is derived from the microscopic chemical kinetics. A recursive solution for the probability distribution of binding of dNTPs is developed for a single cycle and is used to calculate expected yield for a multicycle PCR. The model is able to reproduce important features of the PCR amplification process quantitatively. This model also suggests that the amplification process itself is highly sensitive to initial concentrations and the reaction rates of addition to the template strand of each type of dNTP in the solution.

Alternative definitions of comparable case groups and estimates of lead time and benefit time in randomized cancer screening trials.

Randomized screening trials provide the optimal means of assessing the benefit of screening for cancer and other chronic diseases. Unlike therapy trials, however, where strict eligibility criteria assure the comparability of cases of disease in the arms of the trial, the cancer cases identified during follow-up are a subset of all randomized participants. Furthermore, those cases detected by screening tend to arise from length biased sampling which also can bias estimates of the screening benefit and of average lead time. To reduce or eliminate this bias, we propose several methods for defining comparable groups of cases from the trial arms. We examine, via simulation, these methods with respect to their effects on (i). point and interval estimates of average lead time and average benefit time and (ii). the logrank test statistic for a mortality effect of screening. The most successful new method for defining comparable case groups uses an estimate of the mean sojourn time (mean preclinical duration), and results in nearly unbiased estimates of average lead time and average benefit time as well as an unbiased logrank test statistic.