Measuring potential fertility through null segments: an exploratory analysis

The demographic effectiveness of a family planning program must measure the difference between actual fertility and the "gross" potential fertility, i.e., the natural fertility which would have been achieved without use of contraception. The various methods of measuring "gross" fertility which have been used are described. It is understood that users of contraception are never a random sampling of the general population; they tend to be higher in fecundability and lower in proportion of sterile. For this reason, the best strategm of measurement involves utilization of preacceptance fertility rates over some given period of time among those reporting no contraceptive usage during that period. A procedure of measurement is proposed whereby natural fecundability is estimated from null segments. Possible biases are taken into account. Application of the method is made to 2 sets of data collected in Taiwan. Results of the application of the method to the Taiwanese data are tabulated. Fecundability functions derived from unrestricted null segments are different from those constructed from restricted subsets of "closed" null segments. Choice of whether to use restricted or unrestricted null segments will depend on the nature of the data available.     

An exploratory technique for measuring fertility norms

Abstract

In an attempt to remedy inherent weaknesses in traditional methods of fertility norm measurement, the evaluative dimension of the semantic differential is used to measure such norms among college women at two Southern universities. The instrument was designed to gauge the covert evaluative response elicited in people who observe behaviors relevant to norms which they have internalized. Variations in evaluations of hypothetical couples representing the parities zero through seven are associated with the race, religious preference, religiosity, and future work orientations of respondents. The significance of differences in the relative configurations of norms is determined by a special model of analysis of variance, and subgroups are compared with respect to the intensity of the norms they hold.     

Sequence of events following adoption of contraception: An exploratory analysis of 1973 fertility history data

Abstract

Fertility histories from the 1973 United States National Survey of Family Growth are analyzed in the context of a model of contraceptive use based on a Semi‐Markov processes. This model provides a means of constructing data‐based estimates of probabilities of pregnancy following initial acceptance of a contraceptive method. The algorithm used to construct these estimates recognizes multiple intervals of contraceptive used prior to the events: pregnancy, marital dissolution, or sterilization.

Estimated probabilities of the events marital dissolution and pregnancy for women seeking to delay pregnancy are presented, as are probabilities of contraceptive sterilization for women seeking to prevent subsequent pregnancy. These estimates are compared to one‐step transition probabilities and directly observed NSFG data on pregnancy, marital dissolution, or contraceptive sterilization in an attempt to judge the validity of the model and to assess biases which may result from its use.     

An exploratory analysis of multiple mutation spectra

The last decade has witnessed a remarkable increase in the number of mutations identified both in human disease-related genes and mutation reporter genes including those in mammalian cells and transgenic animals. This has led to the curation of a number of computerised databases, which make mutation data freely available for analysis. A primary interest of both the clinical researcher and the genetic toxicologist is determination of location and types of mutation within a gene of interest. Collections of mutation data observed for a disease-related gene or, for a gene exposed to a particular chemical, permits discovery of regions of sequence along the gene prone to mutagenesis and may provide clues to the origin of a mutation. The principal tool for visualising the distribution pattern of mutant data along a gene is the mutation spectrum: the distribution and frequency of mutations along a nucleotide sequence. In genetic toxicology, the current wealth of mutation data available allows us to construct many mutation spectra of interest to investigate the mutagenic mechanisms and mutational sites for one or a group of mutagens. Using the multivariate statistical methods principal components analysis (PCA) and cluster analysis (CA) we have tested the ability of these methods to establish the underlying patterns within and between 60 UV-induced, mitomycin C-induced and spontaneous mutations in the supF gene. The spectra were derived from human, monkey and mouse cells including both repair efficient and repair deficient cell lines. We demonstrate and support the successful application of multivariate statistical methods for exploring large sets of mutation spectra to reveal underlying patterns, groupings and similarities. The methods clearly demonstrate how different patterns of spontaneous and UV-induced supF mutation spectra can result from variation in plasmid, culture medium, species origin of cell line and whether mutations arose in vivo or in vitro.     

Discovery of protein phosphorylation motifs through exploratory data analysis

Background

The need for efficient algorithms to uncover biologically relevant phosphorylation motifs has become very important with rapid expansion of the proteomic sequence database along with a plethora of new information on phosphorylation sites. Here we present a novel unsupervised method, called Motif Finder (in short, F-Motif) for identification of phosphorylation motifs. F-Motif uses clustering of sequence information represented by numerical features that exploit the statistical information hidden in some foreground data. Furthermore, these identified motifs are then filtered to find “actual” motifs with statistically significant motif scores.

Results and Discussion

We have applied F-Motif to several new and existing data sets and compared its performance with two well known state-of-the-art methods. In almost all cases F-Motif could identify all statistically significant motifs extracted by the state-of-the-art methods. More importantly, in addition to this, F-Motif uncovers several novel motifs. We have demonstrated using clues from the literature that most of these new motifs discovered by F-Motif are indeed novel. We have also found some interesting phenomena. For example, for CK2 kinase, the conserved sites appear only on the right side of S. However, for CDK kinase, the adjacent site on the right of S is conserved with residue P. In addition, three different encoding methods, including a novel position contrast matrix (PCM) and the simplest binary coding, are used and the ability of F-motif to discover motifs remains quite robust with respect to encoding schemes.

Conclusions

An iterative algorithm proposed here uses exploratory data analysis to discover motifs from phosphorylated data. The effectiveness of F-Motif has been demonstrated using several real data sets as well as using a synthetic data set. The method is quite general in nature and can be used to find other types of motifs also. We have also provided a server for F-Motif at http://f-motif.classcloud.org/, http://bio.classcloud.org/f-motif/ or http://ymu.classcloud.org/f-motif/.     

An evaluation of three statistics of structured exploratory data analysis

The power of structured exploratory data analysis (SEDA) to discriminate among major genic, polygenic, and nongenetic determination of phenotypes was investigated using computer simulation. Three classes of SEDA indices (the major gene index, the offspring between parents function, and the midparent-child correlation coefficient) were evaluated. These three statistics, in combination, were reasonably sensitive in detecting the presence of a major locus and in discriminating between phenotypes with genetic effects and those with no genetic component. However, they were unable to discriminate between major genic and polygenically determined phenotypic models.     

Continuous versus interrupted schedules of thermal biofeedback: An exploratory analysis with clinical subjects

Researchers administer thermal biofeedback in several different formats, although the most common are continuous administration and a series of brief trials separated by frequent rest breaks. The present study directly compared these two administration schedules with individuals suffering from migraine headache. Optimal training effects occurred for the continuous schedule of administration. Surprisingly, the interrupted schedule actually led to decreases in hand temperature over eight sessions. Possible reasons for this finding and its implications are discussed.This research was supported in part by grants from the National Institute of Neurological and Communicative Disorders and Stroke (NS-15235; NS-16891; NS-00818) and the Research Foundation of the State University of New York.     

Temperature acquisition as a function of the computer-based biofeedback system utilized: An exploratory analysis

Thermal biofeedback is widely used to treat various clinical disorders. Given its widespread utility, and the variability among the biofeedback systems currently on the market, it is important to investigate which systems are most effective for training various skills. This study compared the performance of normal subjects on two different computer-biofeedback systems. Results indicated a significant difference in subject performance between the two systems. Limitations and implications of these findings are discussed.     

The laws of Taharat HaMishpacha: potential effects on fertility

The laws of Taharat HaMishpacha (Family purity), which regulate coital activity among Orthodox Jews according to menstrual cycle phase in a population that generally does not use contraception, have potentially important effects on fertility. Analysis of these effects based on menstrual cycle and ovulatory phase lengths for women in the childbearing years shows that the majority of cycles are potentially exposed to coital activity during a fertile period and the increased likelihood of coitus following abstinence has a potentially fertility-enhancing effects. Since most Orthodox Jewish women complete the period of tumah (ritual impurity) and attend the mikveh (a ritual water immersion which marks the end of the cycle) on or before day 14 of the postmenstrual phase, only 22% of cycles are potential sources of diminished fertility as a result of restricted coitus. Any delay in the resumption of sexual relations would result in reduced fecundability for a much larger proportion of cycles. For example, if sexual relations are not resumed until day 15, the proportion of cycles wherein coitus is restricted to the postovulatory phase increases from a maximum of 30% to 41%. Observance of the laws do not greatly diminish the overall fertility of the population assuming that 1) the majority of tumah intervals do not extend beyond 14 days, and 2) coital activity is resumed immediately following return from mikveh. For the individual woman with a predominance of short cycles, delays in conception are probable.     

Breastfeeding decline in urban China: An exploratory study

Retrospective data collected in two urban neighborhoods of Tianjin, People's Republic of China, reveal a decline in the rate and duration of breastfeeding since the mid-1930's. There is no reason to suppose that this decline was stimulated by policies intended to discourage breastfeeding, or by pressures from commercial interests determined to expand the use of milk substitutes or supplements. The evidence indicates that breastfeeding declined as women became involved in work outside the home, as they adopted a form of postmarital residence that separated them from other relatives, as income increased, and as their rural origins decreased. No evidence was found to indicate a relationship between breastfeeding and parity or sex preferences.     

OMERACT-based fibromyalgia symptom subgroups: an exploratory cluster analysis

Introduction

The aim of this study was to identify subsets of patients with fibromyalgia with similar symptom profiles using the Outcome Measures in Rheumatology (OMERACT) core symptom domains.

Methods

Female patients with a diagnosis of fibromyalgia and currently meeting fibromyalgia research survey criteria completed the Brief Pain Inventory, the 30-item Profile of Mood States, the Medical Outcomes Sleep Scale, the Multidimensional Fatigue Inventory, the Multiple Ability Self-Report Questionnaire, the Fibromyalgia Impact Questionnaire–Revised (FIQ-R) and the Short Form-36 between 1 June 2011 and 31 October 2011. Hierarchical agglomerative clustering was used to identify subgroups of patients with similar symptom profiles. To validate the results from this sample, hierarchical agglomerative clustering was repeated in an external sample of female patients with fibromyalgia with similar inclusion criteria.

Results

A total of 581 females with a mean age of 55.1 (range, 20.1 to 90.2) years were included. A four-cluster solution best fit the data, and each clustering variable differed significantly (P <0.0001) among the four clusters. The four clusters divided the sample into severity levels: Cluster 1 reflects the lowest average levels across all symptoms, and cluster 4 reflects the highest average levels. Clusters 2 and 3 capture moderate symptoms levels. Clusters 2 and 3 differed mainly in profiles of anxiety and depression, with Cluster 2 having lower levels of depression and anxiety than Cluster 3, despite higher levels of pain. The results of the cluster analysis of the external sample (n = 478) looked very similar to those found in the original cluster analysis, except for a slight difference in sleep problems. This was despite having patients in the validation sample who were significantly younger (P <0.0001) and had more severe symptoms (higher FIQ-R total scores (P = 0.0004)).

Conclusions

In our study, we incorporated core OMERACT symptom domains, which allowed for clustering based on a comprehensive symptom profile. Although our exploratory cluster solution needs confirmation in a longitudinal study, this approach could provide a rationale to support the study of individualized clinical evaluation and intervention.     

An exploratory data analysis method to reveal modular latent structures in high-throughput data

Background  

Modular structures are ubiquitous across various types of biological networks. The study of network modularity can help reveal regulatory mechanisms in systems biology, evolutionary biology and developmental biology. Identifying putative modular latent structures from high-throughput data using exploratory analysis can help better interpret the data and generate new hypotheses. Unsupervised learning methods designed for global dimension reduction or clustering fall short of identifying modules with factors acting in linear combinations.     

An analysis of the mammalian ventricular action potential

Summary A Hodgkin-Huxley model for ventricular excitation is abstracted from electrophysiological data. A singular perturbation analysis of the 8-dimensional phase portrait of the model characterizes the role of calcium during the plateau phase of the ventricular action potential and demonstrates how the calcium refractory period prevents tetanization. Supported in part by the Undergraduate Research Opportunities Program, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA     

Measuring the sustainability of cities: An analysis of the use of local indicators

We analyze 17 studies of the use of urban sustainable development indicators (SDI) in developed western countries. The analysis reveals a lack of consensus not only on the conceptual framework and the approach favored, but also on the selection and optimal number of indicators. First, by performing different classifications and categorizations of SDI we identify problems inherent in territorial practices that use SDI. Second, we argue that the lack of consensus in several steps of the creation of SDI stems notably from the ambiguity in the definitions of sustainable development, objectives for the use of such indicators, the selection method and the accessibility of qualitative and quantitative data. Third, based on the reviewed studies, we propose a selection strategy for SDI through which we demonstrate the need to adopt a parsimonious list of SDI covering the sustainable development components and their constituent categories as broadly as possible while minimizing the number of indicators retained.     

Becoming voluntarily childless: An exploratory study in a Scottish city

Abstract

This paper looks at motives that inform the decision to remain voluntarily childless. It is assumed that voluntary childlessness is not a pathological condition nor is it determined by specific social situations. Situations provide the context within which motives emerge, in the case of voluntary childlessness providing individuals or couples with the opportunity to consider unconventional interpretations of family life that may eventually lead to its rejection. Individuals who become childless prior to finding a “partner” tend to come from families which deviated from the nuclear ideal and to reject parenthood. Those whose decision emerges after a “partnership” has been formed tend to have created alternative life styles and wish to protect the advantages of living without children. It is tentatively concluded that the proportion of couples remaining childless will increase.     

Engene: the processing and exploratory analysis of gene expression data

Engene is a versatile, and platform-independent web tool for exploratory analysis of gene expression data that aims at storing, visualizing and processing large sets of gene expression patterns.