An intrinsically disordered region-mediated confinement state contributes to the dynamics and function of transcription factors.

Transcription factors (TFs) regulate gene expression by binding to specific consensus motifs within the local chromatin context. The mechanisms by which TFs navigate the nuclear environment as they search for binding sites remain unclear. Here, we used single-molecule tracking and machine-learning-based classification to directly measure the nuclear mobility of the glucocorticoid receptor (GR) in live cells. We revealed two distinct and dynamic low-mobility populations. One accounts for specific binding to chromatin, while the other represents a confinement state that requires an intrinsically disordered region (IDR), implicated in liquid-liquid condensate subdomains. Further analysis showed that the dwell times of both subpopulations follow a power-law distribution, consistent with a broad distribution of affinities on the GR cistrome and interactome. Together, our data link IDRs with a confinement state that is functionally distinct from specific chromatin binding and modulates the transcriptional output by increasing the local concentration of TFs at specific sites.

A unified framework for perceived magnitude and discriminability of sensory stimuli.

The perception of sensory attributes is often quantified through measurements of sensitivity (the ability to detect small stimulus changes), as well as through direct judgments of appearance or intensity. Despite their ubiquity, the relationship between these two measurements remains controversial and unresolved. Here, we propose a framework in which they arise from different aspects of a common representation. Specifically, we assume that judgments of stimulus intensity (e.g., as measured through rating scales) reflect the mean value of an internal representation, and sensitivity reflects a combination of mean value and noise properties, as quantified by the statistical measure of Fisher information. Unique identification of these internal representation properties can be achieved by combining measurements of sensitivity and judgments of intensity. As a central example, we show that Weber's law of perceptual sensitivity can coexist with Stevens' power-law scaling of intensity ratings (for all exponents), when the noise amplitude increases in proportion to the representational mean. We then extend this result beyond the Weber's law range by incorporating a more general and physiology-inspired form of noise and show that the combination of noise properties and sensitivity measurements accurately predicts intensity ratings across a variety of sensory modalities and attributes. Our framework unifies two primary perceptual measurements-thresholds for sensitivity and rating scales for intensity-and provides a neural interpretation for the underlying representation.

Exceptions to Fourier's Law at the Macroscale.

The usual basis to analyze heat transfer within materials is the equation formulated 200 years ago, Fourier's law, which is identical mathematically to the mass diffusion equation, Fick's law. Revisiting this assumption regarding heat transport within translucent materials, performing the experiments in vacuum to avoid air convection, we compare the model predictions to infrared-based measurements with nearly mK temperature resolution. After heat pulses, we find macroscale non-Gaussian tails in the surface temperature profile. At steady state, we find macroscale anomalous hot spots when the sample is topographically rough, and this is validated by using two additional independent methods to measure surface temperature. These discrepancies from Fourier's law for translucent materials suggest that internal radiation whose mean-free-path is millimeters interacts with defects to produce small heat sources that by secondary emission afford an additional, non-local mode of heat transport. For these polymer and inorganic glass materials, this suggests unique strategies of heat management design.

Blocking endogenous retinoic acid degradation induces oral tooth formation in zebrafish.

According to Dollo's Law of irreversibility in evolution, a lost structure is usually considered to be unable to reappear in evolution due to the accumulation over time of mutations in the genes required for its formation. Cypriniform fish are a classic model of evolutionary loss because, while they form fully operational teeth in the ventral posterior pharynx, unlike other teleosts, they do not possess oral teeth. Paleontological data show that Cypriniforms, a clade of teleost fish that includes the zebrafish, lost their oral teeth 50 to 100 Mya. In order to attempt to reverse oral tooth loss in zebrafish, we block the degradation of endogenous levels of retinoic acid (RA) using a specific inhibitor of the Cyp26 RA degrading enzymes. We demonstrate the inhibition of endogenous RA degradation is sufficient to restore oral tooth induction as marked by the re-appearance of expression of early dental mesenchyme and epithelium genes such as dlx2b and sp7 in the oral cavity. Furthermore, we show that these exogenously induced oral tooth germs are able to be at least partly calcified. Taken together, our data show that modifications of signaling pathways can have a significant effect on the reemergence of once-lost structures leading to experimentally induced reversibility of evolutionary tooth loss in cypriniforms.

A generic approach to infer community-level fitness of microbial genes.

The gene content in a metagenomic pool defines the function potential of a microbial community. Natural selection, operating on the level of genomes or genes, shapes the evolution of community functions by enriching some genes while depriving the others. Despite the importance of microbiomes in the environment and health, a general metric to evaluate the community-wide fitness of microbial genes remains lacking. In this work, we adapt the classic neutral model of species and use it to predict how the abundances of different genes will be shaped by selection, regardless of at which level the selection acts. We establish a simple metric that quantitatively infers the average survival capability of each gene in a microbiome. We then experimentally validate the predictions using synthetic communities of barcoded Escherichia coli strains undergoing neutral assembly and competition. We further show that this approach can be applied to publicly available metagenomic datasets to gain insights into the environment-function interplay of natural microbiomes.

The planetary commons: A new paradigm for safeguarding Earth-regulating systems in the Anthropocene.

The Anthropocene signifies the start of a no-analogue trajectory of the Earth system that is fundamentally different from the Holocene. This new trajectory is characterized by rising risks of triggering irreversible and unmanageable shifts in Earth system functioning. We urgently need a new global approach to safeguard critical Earth system regulating functions more effectively and comprehensively. The global commons framework is the closest example of an existing approach with the aim of governing biophysical systems on Earth upon which the world collectively depends. Derived during stable Holocene conditions, the global commons framework must now evolve in the light of new Anthropocene dynamics. This requires a fundamental shift from a focus only on governing shared resources beyond national jurisdiction, to one that secures critical functions of the Earth system irrespective of national boundaries. We propose a new framework-the planetary commons-which differs from the global commons framework by including not only globally shared geographic regions but also critical biophysical systems that regulate the resilience and state, and therefore livability, on Earth. The new planetary commons should articulate and create comprehensive stewardship obligations through Earth system governance aimed at restoring and strengthening planetary resilience and justice.

Slow earthquake scaling reconsidered as a boundary between distinct modes of rupture propagation.

The scaling law for slow earthquakes, which is a linear relationship between seismic moment and duration, was proposed 15 y ago and initiated a debate on the difference in physical processes governing slow vs. fast (ordinary) earthquakes. Based on new observations across a wide period range, we show that linear scaling of slow earthquakes remains valid, but as a well-defined upper bound on moment rate of ~1013 Nm/s. The large gap in moment-rate between the scaling of slow and fast earthquakes remains unfilled. Slow earthquakes occur near the detectability threshold, such that we are unable to detect deformation events with lower moment rates. Observed trends within slow earthquake categories support the idea that this unobservable field is populated with events of lower moment rate. This suggests a change in perspective - that the proposed scaling should be considered as a bound, or speed limit, on slow earthquakes. We propose that slow earthquakes represent diffusional propagation, and that the bound on moment rate reflects an upper limit on the speed of those diffusional processes. Ordinary earthquakes, in contrast, occur as a coupled process between seismic wave propagation and fracture. Thus, even though both phenomena occur as shear slip, the difference of scaling reflects a difference in the physical process governing propagation.

Mechanics-based classification rule for plants.

The height of thick and solid plants, such as woody plants, is proportional to two-thirds of the power of their diameter at breast height. However, this rule cannot be applied to herbaceous plants that are thin and soft because the mechanisms supporting their bodies are fundamentally different. This study aims to clarify the rigidity control mechanism resulting from turgor pressure caused by internal water in herbaceous plants to formulate the corresponding scaling law. We modeled a herbaceous plant as a cantilever with the ground side as a fixed end, and the greatest height was formulated considering the axial tension force from the turgor pressure. The scaling law describing the relationship between the height and diameter in terms of the turgor pressure was theoretically derived. Moreover, we proposed a plant classification rule based on stress distribution.

Even lawyers do not like legalese.

Across modern civilization, societal norms and rules are established and communicated largely in the form of written laws. Despite their prevalence and importance, legal documents have long been widely acknowledged to be difficult to understand for those who are required to comply with them (i.e., everyone). Why? Across two preregistered experiments, we evaluated five hypotheses for why lawyers write in a complex manner. Experiment 1 revealed that lawyers, like laypeople, were less able to recall and comprehend legal content drafted in a complex "legalese" register than content of equivalent meaning drafted in a simplified register. Experiment 2 revealed that lawyers rated simplified contracts as equally enforceable as legalese contracts, and rated simplified contracts as preferable to legalese contracts on several dimensions-including overall quality, appropriateness of style, and likelihood of being signed by a client. These results suggest that lawyers who write in a convoluted manner do so as a matter of convenience and tradition as opposed to an outright preference and that simplifying legal documents would be both tractable and beneficial for lawyers and nonlawyers alike.

Rate-induced tipping in complex high-dimensional ecological networks.

In an ecosystem, environmental changes as a result of natural and human processes can cause some key parameters of the system to change with time. Depending on how fast such a parameter changes, a tipping point can occur. Existing works on rate-induced tipping, or R-tipping, offered a theoretical way to study this phenomenon but from a local dynamical point of view, revealing, e.g., the existence of a critical rate for some specific initial condition above which a tipping point will occur. As ecosystems are subject to constant disturbances and can drift away from their equilibrium point, it is necessary to study R-tipping from a global perspective in terms of the initial conditions in the entire relevant phase space region. In particular, we introduce the notion of the probability of R-tipping defined for initial conditions taken from the whole relevant phase space. Using a number of real-world, complex mutualistic networks as a paradigm, we find a scaling law between this probability and the rate of parameter change and provide a geometric theory to explain the law. The real-world implication is that even a slow parameter change can lead to a system collapse with catastrophic consequences. In fact, to mitigate the environmental changes by merely slowing down the parameter drift may not always be effective: Only when the rate of parameter change is reduced to practically zero would the tipping be avoided. Our global dynamics approach offers a more complete and physically meaningful way to understand the important phenomenon of R-tipping.

Science, evidence, law, and justice.

For nearly 25 y, the Committee on Science, Technology, and Law (CSTL), of the National Academies of Sciences, Engineering, and Medicine, has brought together distinguished members of the science and law communities to stimulate discussions that would lead to a better understanding of the role of science in legal decisions and government policies and to a better understanding of the legal and regulatory frameworks that govern the conduct of science. Under the leadership of recent CSTL co-chairs David Baltimore and David Tatel, and CSTL director Anne-Marie Mazza, the committee has overseen many interdisciplinary discussions and workshops, such as the international summits on human genome editing and the science of implicit bias, and has delivered advisory consensus reports focusing on topics of broad societal importance, such as dual use research in the life sciences, voting systems, and advances in neural science research using organoids and chimeras. One of the most influential CSTL activities concerns the use of forensic evidence by law enforcement and the courts, with emphasis on the scientific validity of forensic methods and the role of forensic testimony in bringing about justice. As coeditors of this Special Feature, CSTL alumni Tom Albright and Jennifer Mnookin have recruited articles at the intersection of science and law that reveal an emerging scientific revolution of forensic practice, which we hope will engage a broad community of scientists, legal scholars, and members of the public with interest in science-based legal policy and justice reform.

The metabolomic physics of complex diseases.

Human diseases involve metabolic alterations. Metabolomic profiles have served as a vital biomarker for the early identification of high-risk individuals and disease prevention. However, current approaches can only characterize individual key metabolites, without taking into account the reality that complex diseases are multifactorial, dynamic, heterogeneous, and interdependent. Here, we leverage a statistical physics model to combine all metabolites into bidirectional, signed, and weighted interaction networks and trace how the flow of information from one metabolite to the next causes changes in health state. Viewing a disease outcome as the consequence of complex interactions among its interconnected components (metabolites), we integrate concepts from ecosystem theory and evolutionary game theory to model how the health state-dependent alteration of a metabolite is shaped by its intrinsic properties and through extrinsic influences from its conspecifics. We code intrinsic contributions as nodes and extrinsic contributions as edges into quantitative networks and implement GLMY homology theory to analyze and interpret the topological change of health state from symbiosis to dysbiosis and vice versa. The application of this model to real data allows us to identify several hub metabolites and their interaction webs, which play a part in the formation of inflammatory bowel diseases. The findings by our model could provide important information on drug design to treat these diseases and beyond.

"Choice of law" in precision medicine research.

Large-scale precision medicine research requires massive amounts of data representing people from all walks of life; thus, in the US, it is often multistate research. Significant legal and ethical quandaries arise as a result of the patchwork of laws states have enacted that may apply to research, are not preempted by federal law, and may impose requirements or provide participant rights and protections that differ from other states. Determining which state's laws apply, and under what circumstances, is not solved by the transition to a single-IRB model and researchers cannot simply choose one state's laws to apply uniformly. At a minimum, the current process of meeting each state's requirements could be made more reliable and efficient. To fundamentally change this status quo, however, requires action at multiple levels. Federally, well-known gaps in the Genetic Information Nondiscrimination Act should be closed, and a coherent system of compensation for research injury-including non-physical injuries-should be developed. States should clarify which of their laws are intended to apply to research and work collaboratively to harmonize them. At the level of individual research projects, numerous policies and procedures could be standardized through authoritative guidelines. Examples include clarifying the scope of broad consent, understanding and upholding Certificates of Confidentiality, offering individual research results responsibly, and consistently disseminating aggregate results to participants and the public. Overall, development of a choice of law framework specific to the research context could significantly promote clarity and consistency.