An official website of the United States government
Developmental endocrinology is a fascinating and mature field that investigates the role of hormones in the growth and development of living organisms. Hormones influence various life processes, from the earliest stages of life to old age. As a study of bodily communication at the cellular and humoral level, it integrates all aspects of health. As such, women’s healthcare and research find a comfortable home here. As a multidisciplinary field, developmental endocrinology draws on knowledge and uses tools from several other areas, including developmental biology, genetics, physiology, and neuroscience. All these approaches unlock new insights into interactions involving growth and development, reproduction, metabolism, and behavior, all as influenced by hormonal action. Developmental endocrinology will continue to shed light on how hormones impact health and disease across the lifespan, and its enormous translational value makes it a crucial area of research that supports the health of women. Despite advances in the field, it is important to acknowledge that there has been a shortfall in investment in women’s health overall, including underinvestment in research in the specific context of women’s reproduction.
more »
« less
This content will become publicly available on June 1, 2026
Overcoming the “speed limit” in fusion-mediated biological processes
Condensed matter studies have shown that fusion of two lipid membranes requires drastic structural rearrangements and is thus intrinsically slow. Interestingly, all forms of life on Earth use fusion to carry out some of the most fundamental life processes—communication, growth, metabolic homeostasis—that must be accomplished on timescales as short as a fraction of a millisecond. How do living systems beat the prohibitively slow speed limit imposed by membrane fusion? How do they tune the fusion timescale so that it matches a particular biological function? Here it is argued that fusion-mediated life processes as diverse as viral infection, muscle growth, and neuronal communication have all evolved at a common strategy that can be captured through a unifying relationship between the timescale of the process and the strength of the relevant trigger. Activated motion in a bias field along an emergent collective coordinate provides a suitable physical picture. The timescale is set by a reduced quantity defined as the trigger strength in the active state scaled by a system-specific critical parameter. The unified description suggests simple physical principles that organize the complexity of living systems and evolutionarily drive them toward functional behavior.
more »
« less
- Award ID(s):
- 2232049
- PAR ID:
- 10624057
- Publisher / Repository:
- American Institute of Physics (AIP) Publishing
- Date Published:
- Journal Name:
- Low Temperature Physics
- Volume:
- 51
- Issue:
- 6
- ISSN:
- 1063-777X
- Page Range / eLocation ID:
- 798 to 803
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Cells are the basic units of all living matter which harness the flow of energy to drive the processes of life. While the biochemical networks involved in energy transduction are well-characterized, the energetic costs and constraints for specific cellular processes remain largely unknown. In particular, what are the energy budgets of cells? What are the constraints and limits energy flows impose on cellular processes? Do cells operate near these limits, and if so how do energetic constraints impact cellular functions? Physics has provided many tools to study nonequilibrium systems and to define physical limits, but applying these tools to cell biology remains a challenge. Physical bioenergetics, which resides at the interface of nonequilibrium physics, energy metabolism, and cell biology, seeks to understand how much energy cells are using, how they partition this energy between different cellular processes, and the associated energetic constraints. Here we review recent advances and discuss open questions and challenges in physical bioenergetics.more » « less
-
The tractable history of life records a successive emergence of organisms composed of hierarchically organized cells and greater degrees of individuation. The lowermost object level of this hierarchy is the cell, but it is unclear whether the organizational attributes of living systems extended backward through prebiotic stages of chemical evolution. If the systems biology attributes of the cell were indeed templated upon prebiotic synthetic relationships between subcellular objects, it is not obvious how to categorize object levels below the cell in ways that capture any hierarchies which may have preceded living systems. In this paper, we map out stratified relationships between physical components that drive the production of key prebiotic molecules starting from radiolysis of a small number of abundant molecular species. Connectivity across multiple levels imparts the potential to create and maintain far-from-equilibrium chemical conditions and to manifest nonlinear system behaviors best approximated using automata formalisms. The architectural attribute of “information hiding” of energy exchange processes at each object level is shared with stable, multitiered automata such as digital computers. These attributes may indicate a profound connection between the system complexity afforded by energy dissipation by subatomic level objects and the emergence of complex automata that could have preceded biological systems.more » « less
-
One way that researchers can test whether they understand a biological system is to see if they can accurately recreate it as a computer model. The more they learn about living things, the more the researchers can improve their models and the closer the models become to simulating the original. In this approach, it is best to start by trying to model a simple system. Biologists have previously succeeded in creating ‘minimal bacterial cells’. These synthetic cells contain fewer genes than almost all other living things and they are believed to be among the simplest possible forms of life that can grow on their own. The minimal cells can produce all the chemicals that they need to survive – in other words, they have a metabolism. Accurately recreating one of these cells in a computer is a key first step towards simulating a complete living system. Breuer et al. have developed a computer model to simulate the network of the biochemical reactions going on inside a minimal cell with just 493 genes. By altering the parameters of their model and comparing the results to experimental data, Breuer et al. explored the accuracy of their model. Overall, the model reproduces experimental results, but it is not yet perfect. The differences between the model and the experiments suggest new questions and tests that could advance our understanding of biology. In particular, Breuer et al. identified 30 genes that are essential for life in these cells but that currently have no known purpose. Continuing to develop and expand models like these to reproduce more complex living systems provides a tool to test current knowledge of biology. These models may become so advanced that they could predict how living things will respond to changing situations. This would allow scientists to test ideas sooner and make much faster progress in understanding life on Earth. Ultimately, these models could one day help to accelerate medical and industrial processes to save lives and enhance productivity.more » « less
-
null (Ed.)RF sensing based human activity and hand gesture recognition (HGR) methods have gained enormous popularity with the development of small package, high frequency radar systems and powerful machine learning tools. However, most HGR experiments in the literature have been conducted on individual gestures and in isolation from preceding and subsequent motions. This paper considers the problem of American sign language (ASL) recognition in the context of daily living, which involves sequential classification of a continuous stream of signing mixed with daily activities. In particular, this paper investigates the efficacy of different RF input representations and fusion techniques for ASL and trigger gesture recognition tasks in a daily living scenario, which can be potentially used for sign language sensitive human-computer interfaces (HCI). The proposed approach involves first detecting and segmenting periods of motion, followed by feature level fusion of the range-Doppler map, micro-Doppler spectrogram, and envelope for classification with a bi-directional long short-term memory (BiL-STM) recurrent neural network. Results show 93.3% accuracy in identification of 6 activities and 4 ASL signs, as well as a trigger sign detection rate of 0.93.more » « less
