Mathematical modeling of the female reproductive system: from oocyte to delivery

Nomogram for predicting the risk of nosocomial infections among obstetric inpatients: a large-scale retrospective study in China

OBJECTIVE

This study aimed to develop and validate a nomogram for assessing the risk of nosocomial infections among obstetric inpatients, providing a valuable reference for predicting and mitigating the risk of postpartum infections.

METHODS

A retrospective observational study was performed on a cohort of 28,608 obstetric patients admitted for childbirth between 2017 and 2022. Data from the year 2022, comprising 4,153 inpatients, were utilized for model validation. Univariable and multivariable stepwise logistic regression analyses were employed to identify the factors influencing nosocomial infections among obstetric inpatients. A nomogram was subsequently developed based on the final predictive model. The receiver operating characteristic (ROC) curve was utilized to calculate the area under the curve (AUC) to evaluate the predictive accuracy of the nomogram in both the training and validation datasets.

RESULTS

The gestational weeks > = 37, prenatal anemia, prenatal hypoproteinemia, premature rupture of membranes (PROM), cesarean sction, operative delivery, adverse birth outcomes, length of hospitalization (days) > 5, CVC use and catheterization of ureter were included in the ultimate prediction model. The AUC of the nomogram was 0.828 (0.823, 0.833) in the training dataset and 0.855 (0.844, 0.865) in the validation dataset.

CONCLUSION

Through a large-scale retrospective study conducted in China, we developed and independently validated a nomogram to enable personalized postpartum infections risk estimates for obstetric inpatients. Its clinical application can facilitate early identification of high-risk groups, enabling timely infection prevention and control measures.

Three-dimensional virtual histology of the rat uterus musculature using micro-computed tomography

Contractions of the uterus play an important role in menstruation and fertility, and contractile dysfunction can lead to chronic diseases such as endometriosis. However, the structure and function of the uterus are difficult to interrogate in humans, and thus animal studies are often employed to understand its function. In rats, anatomical studies of the uterus have typically been based on histological assessment, have been limited to small segments of the uterine structure, and have been time-consuming to reconstruct at the organ scale. This study used micro-computed tomography imaging to visualise the muscle structures in the entire non-pregnant rat uterus and assess its use for 3D virtual histology. An assessment of the rodent uterus is presented to (i) quantify muscle thickness variations along the horns, (ii) identify predominant fibre orientations of the muscles and (iii) demonstrate how the anatomy of the uterus can be mapped to 3D volumetric meshes via virtual histology. Micro-computed tomography measurements were validated against measurements from histological sections. The average thickness of the myometrium was found to be 0.33 ± 0.11 mm and 0.31 ± 0.09 mm in the left and right horns, respectively. The micro-computed tomography and histology thickness calculations were found to correlate strongly at different locations in the uterus: at the cervix, r = 0.87, and along the horn from the cervical end to the ovarian end, respectively, r = 0.77, r = 0.89 and r = 0.54, with p < 0.001 in every location. This study shows that micro-computed tomography can be used to quantify the musculature in the whole non-pregnant uterus and can be used for 3D virtual histology.

The Cell Physiome: What Do We Need in a Computational Physiology Framework for Predicting Single-Cell Biology?

Modern biology and biomedicine are undergoing a big data explosion, needing advanced computational algorithms to extract mechanistic insights on the physiological state of living cells. We present the motivation for the Cell Physiome project: a framework and approach for creating, sharing, and using biophysics-based computational models of single-cell physiology. Using examples in calcium signaling, bioenergetics, and endosomal trafficking, we highlight the need for spatially detailed, biophysics-based computational models to uncover new mechanisms underlying cell biology. We review progress and challenges to date toward creating cell physiome models. We then introduce bond graphs as an efficient way to create cell physiome models that integrate chemical, mechanical, electromagnetic, and thermal processes while maintaining mass and energy balance. Bond graphs enhance modularization and reusability of computational models of cells at scale. We conclude with a look forward at steps that will help fully realize this exciting new field of mechanistic biomedical data science. Expected final online publication date for the Annual Review of Biomedical Data Science, Volume 5 is August 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Mechanobiology of the female reproductive system

BACKGROUND

Mechanobiology in the field of human female reproduction has been extremely challenging technically and ethically.

METHODS

The present review provides the current knowledge on mechanobiology of the female reproductive system. This review focuses on the early phases of reproduction from oocyte development to early embryonic development, with an emphasis on current progress.

MAIN FINDINGS RESULTS

Optimal, well-controlled mechanical cues are required for female reproductive system physiology. Many important questions remain unanswered; whether and how mechanical imbalances among the embryo, decidua, and uterine muscle contractions affect early human embryonic development, whether the biomechanical properties of oocytes/embryos are potential biomarkers for selecting high-quality oocytes/embryos, whether mechanical properties differ between the two major compartments of the ovary (cortex and medulla) in normally ovulating human ovaries, whether durotaxis is involved in several processes in addition to embryonic development. Progress in mechanobiology is dependent on development of technologies that enable precise physical measurements.

CONCLUSION

More studies are needed to understand the roles of forces and changes in the mechanical properties of female reproductive system physiology. Recent and future technological advancements in mechanobiology research will help us understand the role of mechanical forces in female reproductive system disorders/diseases.

Preimplantation loss of fertilized human ova: estimating the unobservable

STUDY QUESTION

What proportion of fertilized human ova are lost before implantation?

SUMMARY ANSWER

An estimated 40 to 50% of fertilized ova fail to implant.

WHAT IS KNOWN ALREADY

Preimplantation loss is not detectable with current technology. Published estimates of preimplantation loss range from 10 to 70%.

STUDY DESIGN, SIZE, DURATION

We combine data from epidemiologic, demographic, laboratory and in vitro fertilization studies to construct an empirical framework for the estimation of preimplantation loss. This framework is summarized in a user-friendly Excel file included in supplement.

PARTICIPANTS/MATERIALS, SETTING, METHODS

We draw from multiple sources to generate plausible estimates of fecundability, sterility, transient anovulation, intercourse patterns and the proportion of ova fertilized in the presence of sperm. We combine these estimates to generate a summary estimate of preimplantation loss. This estimate can be considered an average for couples in their prime reproductive years.

MAIN RESULTS AND THE ROLE OF CHANCE

Under a plausible range of assumptions, we estimate that 40 to 50% of fertilized ova fail to implant.

LIMITATIONS, REASONS FOR CAUTION

A crucial factor in estimating preimplantation loss is the probability that an ovum will be fertilized when exposed to sperm. Human data are available only from in vitro fertilization (IVF), which may not accurately represent events in vivo. We therefore assume a range of in vivo fertilization rates, from 64% (human IVF data) to 90% (mouse data).

WIDER IMPLICATIONS OF THE FINDINGS

Our estimate of preimplantation loss takes into account the biological processes relevant to fertilization and loss. Using this empirical basis for estimation, we find support for the usual assumption that risk of loss is highest in the earliest days following fertilization. Furthermore, this framework can provide improved estimates as better reproductive data become available. To the extent that our estimates are accurate, more fertilized ova are apparently lost in vitro than in vivo, suggesting that further improvements in IVF success rates may be possible.

STUDY FUNDING/COMPETING INTEREST(S)

This study was supported by the Intramural Program of the National Institute of Environmental Health Sciences, NIH. Professor Adashi serves as Co-Chair of the Safety Advisory Board of Ohana Biosciences, Inc. The other authors have no competing interests.

TRIAL REGISTRATION NUMBER

N/A.

Biomechanics of Early Life in the Female Reproductive Tract

Early human life that starts at the onset of fertilization and ends with implantation of the embryo in the uterine wall is the foundation for a successful pregnancy. The different stages during this period require biomechanical mechanisms, which are mostly unknown due to difficulties to conduct in vivo studies in humans.

Endothelins and their receptors in embryo implantation

As a critical stage of pregnancy, the implantation of blastocysts into the endometrium is a progressive, excessively regulated local tissue remodeling step involving a complex sequence of genetic and cellular interplay executed within an optimal time frame. For better understanding the causes of infertility and, more importantly, for developing powerful strategies for successful implantations and combating infertility, an increasing number of recent studies have been focused on the identification and study of newly described substances in the reproductive tree. The endothelins (ET), a 21-aminoacidic family of genes, have been reported to be responsible for the contraction of vascular and nonvascular smooth muscles, including the smooth muscles of the uterus. Therefore, this review aims to comprehensively discuss the physiological role of endothelins and signaling through their receptors, as well as their probable involvement in the implantation process.

Blood flow and transport in the human placenta

The placenta is a multi-functional organ that exchanges blood gases and nutrients between a mother and her developing fetus. In humans, fetal blood flows through intricate networks of vessels confined within villous trees, the branches of which are bathed in pools of maternal blood. Fluid mechanics and transport processes play a central role in understanding how these elaborate structures contribute to the function of the placenta, and how their disorganization may lead to disease. Recent advances in imaging and computation have spurred significant advances in simulations of fetal and maternal flows within the placenta, across a range of lengthscales. Models describe jets of maternal blood emerging from spiral arteries into a disordered and deformable porous medium, and solute uptake by fetal blood flowing through elaborate three-dimensional capillary networks. We survey recent developments and emerging challenges in modeling flow and transport in this complex organ.