Progesterone after mifepristone: A pilot prospective single arm clinical trial for women who have changed their mind after commencing medical abortion.

AIM: This pilot study aimed to assess the utility of an oral progesterone treatment protocol for women who commenced medical abortion and then changed their mind and wished instead to maintain their pregnancy. METHODS: The Progesterone-After-Mifepristone-pilot for efficacy and reproducibility (PAMper) trial was designed as a prospective single-arm pilot clinical trial, conducted via telehealth. Women aged 18 to 45 years in Australia who reported ingesting mifepristone within the last 72 h to initiate medical abortion and had not taken misoprostol were included. Initial contact was by a web-based form. Following informed consent, participants were prescribed oral progesterone to be taken 400 mg twice per day for 3 days then 400 mg at night until completion of a 19 day course. Pregnancy viability was assessed by ultrasound scan after 14 days of progesterone treatment. RESULTS: Between October 2020 and June 2021, nine women contacted the PAMper trial, of whom six enrolled and commenced progesterone treatment. These women reported ingesting mifepristone at 40-70 days of gestation, with progesterone being commenced within 5.7-72 h of mifepristone ingestion. Five participants had ongoing, live pregnancies at the primary endpoint (ultrasound at >2 weeks). One participant had a miscarriage after 9 days of progesterone treatment. There were no clinically significant adverse events. CONCLUSION: This small study demonstrated a clinically sound protocol for researching the use of progesterone-after-mifepristone for women in this circumstance. Results of this pilot study support the need for further larger scale trials in this field.

Misrepresentation of contraceptive effectiveness rates for fertility awareness methods of family planning.

AIM: Simplified contraceptive method-efficacy and/or typical-use effectiveness rates are commonly used for direct comparison of the various contraceptive methods. Use of such effectiveness rates in this manner is, however, problematic in relation to the fertility awareness methods (FAMs). The aim of this review is to critically examine current international representation of contraceptive effectiveness for the various FAMs in clinical use. This review also details important issues when appraising and interpreting studies on FAMs used for avoiding pregnancy. METHODS: Current international literature regarding contraceptive effectiveness of FAMs was surveyed and appraised. This included World Health Organization and Centers for Disease Control (USA) resources, key clinical studies and recent systematic reviews. Chinese literature was also searched, since these data have not been reported in the English literature. RESULTS: Reliance on certain historical studies has led to the misrepresentation of contraceptive effectiveness of FAMs by perpetuation of inaccurate figures in clinical guidelines, the international literature and the public domain. Interpretation of published study results for FAMs is difficult due to variability in study methodology and other clinical trial quality issues. Recent systematic analyses have noted the considerable issues with study designs and limitations. Several non-English published studies using the Billings Ovulation Method have demonstrated that a broader review of the literature is required to better capture the data potentially available. CONCLUSION: A deeper understanding by clinicians and the public of the applicability of contraceptive effectiveness rates of the various FAMs is needed, instead of reliance on the inaccurate conglomerate figures that are widely presented.

Bioethical and Moral Perspectives in Human Reproductive Medicine.

A reductive reading of Humanae vitae seeks to limit its appeal to a ban on contraception. In truth, however, it offers a vision of human sexuality and conjugal love with broad and enduring relevance. In setting forth the intrinsic complementarity and irreducibility of the unitive and procreative dimensions of the conjugal act, Paul VI has given us a hermeneutical key for assessing many contemporary ethical dilemmas in human reproductive medicine. From this perspective, this article seeks to apply the logic of Humanae vitae to several real-life scenarios confronted by medical practitioners, educators, and ethicists working in the field of fertility and reproductive health. These include a consideration of the ethics of prescribing hormonal contraceptives, the possibilities of investigating male infertility, issues of cooperation in counseling and assisting conception in same-sex relationships, the ethics pertaining to assisted reproductive technology (ART), the contested case of prenatal adoption, and the application of double-effect reasoning. SUMMARY: On the occasion of the fiftieth anniversary of the promulgation of Pope Paul VI's encyclical Humanae vitae, this article seeks to defend its enduring relevance to modern-day society, through application of its reasoning to contemporary dilemmas in reproductive medicine. It considers real cases of the ethics of prescribing hormonal contraceptives, of investigating male infertility, of cooperating in counseling and assisting conception in same-sex relationships, of ART, of prenatal adoption, and the application of double-effect reasoning.

Progesterone for preventing pregnancy termination after initiation of medical abortion with mifepristone.

INTRODUCTION: Abortion is often a difficult and traumatic decision for a woman to make. Perhaps greater distress occurs when a woman commences a medical abortion but then changes her mind and wishes to keep the now-threatened pregnancy. One published case series detailed a potential method to counter/reverse the abortifacient effect of mifepristone by administering parenteral progesterone in such situations. OBJECTIVES: The present report details cases of women in similar circumstances who have been treated with progesterone. The aims were to document occurrences of where women have changed their mind after commencing medical abortion, as well as to explore some of the controversies and clinical issues surrounding their circumstances. METHODS: Women who had commenced medical abortion by ingesting mifepristone but who had not taken misoprostol independently contacted a national pregnancy support service the same day. Those meeting criteria for treatment received progesterone pessaries per vaginum for two weeks. RESULTS: Cases: 28-year-old woman, 6 weeks plus 1 day gestation; 35-year-old woman, 8 weeks plus 5 days gestation; and 27-year-old woman, 7 weeks plus 3 days gestation. Outcomes respectively were: healthy male baby delivered at 39 weeks gestation; healthy male baby delivered at term; and completed medical abortion. CONCLUSIONS: Women have changed their mind after commencing medical abortion. Progesterone use in early pregnancy is low risk and its application to counter the effects of mifepristone in such circumstances may be clinically beneficial in preserving her threatened pregnancy. Further research is required, however, to provide definitive evidence.

Relationship Between Steroid Hormone Profile and Premenstrual Syndrome in Women Consulting for Infertility or Recurrent Miscarriage.

To determine the relationships between luteal-phase steroidal hormonal profile and PMS for a large number of women attending a dedicated fertility clinic. This was a retrospective cross-sectional study on women attending a hospital-based clinic for fertility concerns and/or recurrent miscarriage. All participants were assessed with a women's health questionnaire which also included evaluation of premenstrual symptoms. Day of ovulation was identified based on the peak mucus symptom assessed by the woman after instruction in a fertility awareness-based method (FABM). This enabled reliable timing of luteal-phase serum hormone levels to be taken and analysed. Between 2011 and 2021, 894 of the 2666 women undertaking the women's health assessment had at least one evaluable serum luteal hormone test. Serum progesterone levels were up to 10 nmol/L lower for symptomatic women compared with asymptomatic women. This difference was statistically significant (p < 0.05) for the majority of PMS symptoms at ≥ 9 days after the peak mucus symptom. A similar trend was observed for oestradiol but differences were generally not statistically significant. ROC curves demonstrated that steroid levels during the luteal phase were not discriminating in identifying the presence of PMS symptoms. Blood levels for progesterone were lower throughout the luteal phase in women with PMS, with the greatest effect seen late in the luteal phase.

Congenital and Fetal Effects After Mifepristone Exposure and Continuation of Pregnancy: A Systematic Review.

Mifepristone is an anti-progestational drug that is the first component of the standard medical abortion regimen. For women who take mifepristone and then do not take misoprostol, which is the second component of the medical abortion regimen, it is possible that their pregnancy may continue to live birth. Since mifepristone is commonly used for medical abortion up to 9-10 weeks gestation, any adverse or teratogenic effects on the developing embryo/fetus must be considered, given exposure during the critical time of its development and organogenesis. Toxicology and teratology reports have cited studies demonstrating teratogenic effect of mifepristone in some animals. Current clinical guidelines for women exposed to mifepristone in the first trimester of pregnancy state that it is not known to be teratogenic based on limited published evidence from humans. The aim of this narrative systematic review was to investigate embryonic/fetal exposure to mifepristone and any association with congenital or fetal anomalies. This study was conducted by systematic searches of health databases from inception to February 2024. The references of relevant citations were manually searched to retrieve any additional citations not captured in database searching. Congenital anomalies and adverse outcomes were encountered at various doses of mifepristone exposure. A number of the congenital anomalies encountered in this review were explained by circumstances other than exposure to mifepristone. The present systematic review did not find data to support mifepristone being implicated as a teratogen.

Molecular aspects of phytoestrogen selective binding at estrogen receptors.

Phytoestrogens are a diverse group of plant-derived compounds that structurally or functionally mimic mammalian estrogens and show potential benefits for human health. An increase in phytoestrogen research over the past few decades has demonstrated the biological complexity of phytoestrogens, which belong to several different chemical classes and act through diverse mechanisms. Identification of the estrogen receptor beta (ERbeta) and research into various ligand classes has enabled elucidation of molecular aspects important in selective ER binding. This article explores the structural characteristics and significance of functional groups as they relate to phytoestrogen selectivity for ER binding.

University rural health clubs: nurturing the future Australian rural workforce.

CONTEXT: Australian university rural health clubs (RHC) are part of a national strategy to address the rural health workforce shortage. The student members of these clubs throughout Australia comprise the National Rural Health Network (NRHN). The NRHN is a multidisciplinary body representing medical, nursing and allied health students, aiming to increase the health workforce and health outcomes for rural and remote Australians. The NRHN and its constituent clubs run a variety of activities to promote rural careers to both school-aged and university students. These have included events at local, state and national levels. ISSUES: The purpose of the present article is to describe the roles and activities of RHC and the NRHN as they aim to contribute towards developing a sustainable rural workforce. Key features of RHC and the NRHN are: (1) providing positive rural experiences; (2) peer promotion of rural health; (3) personal and professional development; (4) providing a volunteer workforce for rural health initiatives; and (5) cross-disciplinary interaction. The NRHN is currently investigating methods to quantify the impact of the RHC on the career choices of potential rural health professionals. LESSONS LEARNED: The NRHN and its constituent clubs are student-driven initiatives occupying a unique place in addressing the rural workforce shortage. Although little formal evidence exists for their success, the issues raised in this article illustrate their importance and broader benefits in this field.

Socio-economic distribution of environmental risk factors for childhood injury.

OBJECTIVE: Childhood injury remains the single most important cause of mortality in children aged between 1-14 years in many countries. It has been proposed that lower socio-economic status (SES) and poorer housing contribute to potential hazards in the home environment. This study sought to establish whether the prevalence of observed hazards in and around the home was differentially distributed by SES, in order to identify opportunities for injury prevention. METHODS: This study was a cross-sectional, random sample survey of primary school children from 32 schools in Brisbane. Interviews and house audits were conducted between July 2000 and April 2003 to collect information on SES (income, employment and education) and previously identified household hazards. RESULTS: There was evidence of a relationship between prevalence of household environmental hazards and household SES; however, the magnitude and direction of this relationship appeared to be hazard-specific. Household income was related to play equipment characteristics, with higher SES groups being more likely to be exposed to risk. All three SES indicators were associated with differences in the home safety characteristics, with the lower SES groups more likely to be exposed to risk. CONCLUSION: The differential distribution of environmental risk factors by SES of household may help explain the SES differential in the burden of injury and provides opportunities for focusing efforts to address the problem.

Multiple pharmacokinetic parameter prediction for a series of cephalosporins.

The goal of quantitative structure-pharmacokinetic relationship analyses is to develop useful models that can predict one or more pharmacokinetic properties of a particular compound. In the present study, a multiple-output artificial neural network model was constructed to predict human half-life, renal and total body clearance, fraction excreted in urine, volume of distribution, and fraction bound to plasma proteins for a series of cephalosporins. Descriptors generated solely from drug structure were used as inputs for the model, and the six pharmacokinetic parameters were simultaneously predicted as outputs. The final 10 descriptor model contained sufficient information for successful predictions using both internal and external test compounds. Descriptors were found to contribute to individual pharmacokinetic parameters to differing extents, such that descriptor importance was independent of the relationships between pharmacokinetic parameters. This technique provides the advantage of simultaneous prediction of multiple parameters using information obtained by nonexperimental means, with the potential for use during the early stages of drug development.

Pharmacokinetic parameter prediction from drug structure using artificial neural networks.

Simple methods for determining the human pharmacokinetics of known and unknown drug-like compounds is a much sought-after goal in the pharmaceutical industry. The current study made use of artificial neural networks (ANNs) for the prediction of clearances, fraction bound to plasma proteins, and volume of distribution of a series of structurally diverse compounds. A number of theoretical descriptors were generated from the drug structures and both automated and manual pruning were used to derive optimal subsets of descriptors for quantitative structure-pharmacokinetic relationship models. Models were trained on one set of compounds and validated with another. Absolute predicted ability was evaluated using a further independent test set of compounds. Correlations for test compounds ranged from 0.855 to 0.992. Predicted values agreed closely with experimental values for total clearance, renal clearance, and volume of distribution, while predictions for protein binding were encouraging. The combination of descriptor generation, ANNs, and the speed and success of this technique compared with conventional methods shows strong potential for use in pharmaceutical product development.

Seizure and embolic stroke secondary to patent foramen ovale in a migrant girl.

Episodes of loss-of-consciousness in school-aged children are not uncommon and include metabolic, cardiovascular, neurological, and psychiatric/psychosocial causes. This case describes a first episode of seizure in an 11-year-old migrant girl. History and language issues contributed to the diagnostic dilemma. Ongoing neurological symptoms prompted transfer to a tertiary care facility where investigation revealed patent foramen ovale (PFO) with likely paradoxical embolus. Prevalence and management of this condition is briefly reviewed in the context of the current presentation.

Pesticides as estrogen disruptors: QSAR for selective ERα and ERß binding of pesticides.

Evidence suggests that environmental exposure to estrogen-like compounds can cause adverse effects in humans and wildlife. The Endocrine Disruptor Screening and Testing Advisory Committee (EDSTAC) has advised screening of 87,000 compounds in the interest of human safety. This may best be accomplished by pre-screening using quantitative structure-activity relationship (QSAR) modelling. The present study aimed to develop in silico QSARs based on natural, semi-synthetic, synthetic, and phytoestrogens, to predict the potential estrogenic toxicity of pesticides. A diverse set of 170 compounds including steroidal-, synthetic- and phytoestrogens, as well as pesticides was used to construct the QSAR models using artificial neural networks (ANNs). Mean correlation coefficients between experimentally measured and predicted binding affinities were all greater than 0.7 and models had few false negative results, an important consideration for screening tools. This study demonstrated the utility of ANNs as QSAR models for pre-screening of potential endocrine disruptors.

Structure-activity relationships for serotonin transporter and dopamine receptor selectivity.

Antipsychotic medications have a diverse pharmacology with affinity for serotonergic, dopaminergic, adrenergic, histaminergic and cholinergic receptors. Their clinical use now also includes the treatment of mood disorders, thought to be mediated by serotonergic receptor activity. The aim of our study was to characterise the molecular properties of antipsychotic agents, and to develop a model that would indicate molecular specificity for the dopamine (D(2)) receptor and the serotonin (5-HT) transporter. Back-propagation artificial neural networks (ANNs) were trained on a dataset of 47 ligands categorically assigned antidepressant or antipsychotic utility. The structure of each compound was encoded with 63 calculated molecular descriptors. ANN parameters including hidden neurons and input descriptors were optimised based on sensitivity analyses, with optimum models containing between four and 14 descriptors. Predicted binding preferences were in excellent agreement with clinical antipsychotic or antidepressant utility. Validated models were further tested by use of an external prediction set of five drugs with unknown mechanism of action. The SAR models developed revealed the importance of simple molecular characteristics for differential binding to the D(2) receptor and the 5-HT transporter. These included molecular size and shape, solubility parameters, hydrogen donating potential, electrostatic parameters, stereochemistry and presence of nitrogen. The developed models and techniques employed are expected to be useful in the rational design of future therapeutic agents.

Quantitative structure-retention-pharmacokinetic relationship studies.

Since the majority of lead compounds identified for drug clinical trials fail to reach the market due to poor efficacy in humans or poor pharmacokinetics (PKs), the prediction of PK properties in humans plays an important role in selection of potential drug candidates. The aim of the present study was to develop novel models for the prediction of separate PK parameters for a diverse set of drugs. Prediction would be based on the retention of each drug using micellar liquid chromatography (MLC) and selected theoretically-derived descriptors. Retention time, half life (t((1/2))), and volume of distribution (Vd) for each of the 26 training drugs were extracted from literature while molecular descriptors were generated using Molecular Modeling Pro. A total of 35 molecular descriptors describing molecular size, shape and solubility were calculated from the 3D molecular structure of each compound. Artificial neural network (ANN) modeling was used to correlate the calculated descriptors and retention time with half life and volume of distribution. A sensitivity analysis procedure was used to refine the models. The final predictive models showed significant correlations with literature values of t((1/2)) and Vd: 0.854 and 0.855 respectively for the internal testing data and 0.720 and 0.827 respectively for the external validation set of compounds. Absolute predicted values were in good agreement with literature values. Analysis of descriptors in the optimum models revealed a large degree of overlap. Solubility characteristics, hydrogen bonding, and molecular size and shape were shown to play important roles in determining drug t((1/2)) and Vd. The reciprocal of retention time was also included in both optimum models attesting to the significance of this particular physicochemical parameter and the complexity of the models developed. This novel combination of theoretical and experimental data for pharmacokinetic modeling may lead to further progress in drug development.

Bioavailability prediction based on molecular structure for a diverse series of drugs.

PURPOSE: Radial basis function artificial neural networks and theoretical descriptors were used to develop a quantitative structure-pharmacokinetic relationship for structurally diverse drug compounds. METHODS: Human bioavailability values were taken from the literature and descriptors were generated from the drug structures. All models were trained with 137 compounds and tested with a further 15, after which they were evaluated for predictive ability with an additional 15 compounds. RESULTS: The final model possessed a 10-31-1 topology and training and testing correlation coefficients were 0.736 and 0.897, respectively. Predictions for independent compounds agreed well with experimental literature values, especially for compounds that were well absorbed and/or had high observed bioavailability. Important theoretical descriptors included solubility parameters, electronic descriptors, and topological indices. CONCLUSIONS: Useful information regarding drug bioavailability was gained from drug structure alone, reducing the need for experimental methods in drug development.

Selective descriptor pruning for QSAR/QSPR studies using artificial neural networks.

Selection of optimal descriptors in quantitative structure-activity-property relationship (QSAR/QSPR) studies has been a perennial problem. Artificial Neural Networks (ANNs) have been used widely in QSAR/QSPR studies but less widely in descriptor selection. The current study used ANNs to select an optimal set of descriptors using large numbers of input variables. The effects of clean, noisy, and random input descriptors with linear, nonlinear, and periodic data on synthetic and real data QSAR/QSPR sets were examined. The optimal set of descriptors could be determined using a signal-to-noise ratio method. The optimal values for the rho parameter, which relates sample size to network architecture, were found to vary with the type of data. ANNs were able to detect meaningful descriptors in the presence of large numbers of random false descriptors.