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At the boundary: Law and AI
Recapitulating gestational progression: a high-throughput 3D bioprinted vascularized human placenta demonstrating stage-specific molecular and functional signatures of human pregnancy
Abstract The placenta is a highly dynamic organ that supports the growth and development of the fetus during gestation. Malfunction of the placenta causes disorders of the pregnancy, including preeclampsia and pre-term birth. The study of the pathophysiology of the placenta throughout pregnancy has been hindered by limited access to the human placenta and lack of predictive cellular and animal models. Here, we describe 3D bioprinted human placenta barrier (hPB) tissue models using primary human trophoblasts and stroma cells that recapitulate the physiology of the human placenta at early and late stages of gestation. These bioprinted vascularized hPB tissue models mimic the architecture and function early and late-stages human placenta, including barrier function, nutrient uptake, transporters activity and hormones secretion. Assembled in a 96-well transwell plate format, this deeply characterized platform provides a robust high-fidelity system for predictive screening of therapeutics and potentially hazardous agents for placenta diseases and safety, and a better understanding of placental pathophysiology.
Echolocating bats sacrifice binaural localization cues for target-focused hearing during high-speed foraging
Accurate sound localization is critical to navigation and foraging in echolocating animals. During both passive listening and active echolocation, bats are thought to rely solely on interaural level differences (ILDs) between the two ears, attaining very large ILDs by orienting their outer ears apart. However, detecting weak prey echoes during high-speed foraging should instead favor target-focused pinnae that maximize sonar range and reduce clutter interference. Therefore, we propose that flying bats orient their pinnae toward prey. We test this hypothesis using a unique wind tunnel and by employing deep-learning-facilitated high-speed stereo photogrammetry and show that freely flying bats indeed orient their pinnae forward, directly on target. This produces large spatial overlap between each ear’s receiving beams, markedly reducing ILDs, and rejects the hypothesis that bats rely solely on ILDs for localization in flight. Instead, bats achieve a highly directional acoustic field of view through coordinated alignment of the emitted and received sonar beams, which amplifies the central acoustic axis and attenuates off-axis echoes. Parallel to visual object tracking, flying bats likely prioritize signal-to-noise ratio, trading off large ILDs for clutter-filtering and sonar range, which allows them to use very weak echoes and simplify their self-generated auditory scene. We hypothesize that this highly directional acoustic field of view aids in localization, potentially in combination with interaural time differences, in the absence of large ILDs. This envisions an inherently simplified acoustic scene that better accounts for how bats hunt efficiently in complex environments.
Phytochemical profiling, antioxidant activity, and allelopathic potential of Jatropha podagrica Hook. leaf extract and fractions
Refinement of robot-assisted nipple-sparing mastectomy utilizing the da Vinci SP system and SP access port device: the RASPB-1 Pilot Trial
Legal infrastructure for transformative AI governance
Most of our AI governance efforts focus on substance: What rules do we want in place? What limits or checks do we want to impose on AI development and deployment? But a key role for law is not only to establish substantive rules but also to establish legal and regulatory infrastructure to generate and implement rules. The transformative nature of AI calls especially for attention to building legal and regulatory frameworks. In this Perspective, I review three examples: the creation of registration regimes for frontier models; the creation of registration and identification regimes for autonomous agents; and the design of regulatory markets to facilitate a role for private companies to innovate and deliver AI regulatory services.
Multi-objective optimization of a hybrid photovoltaic–thermal energy system under load demand uncertainties using Bat algorithm
LARP1 at the nexus of oncogenic MYC and mTOR signaling
Wearable near-infrared photoimmunotherapy using a flexible LED sheet light device
The backfiring effect of weak AI safety regulation
Recent policy proposals aim to improve the safety of general-purpose AI, but there is little understanding of the efficacy of different regulatory approaches. We present a strategic model that explores interactions between safety regulation, general-purpose AI technology creators, and domain specialists—those who adapt the technology for specific applications. Our analysis examines how regulatory measures targeting different parts of the AI development chain affect the outcome of this game. Our model assumes AI technology is characterized by two key attributes: safety and performance. The regulator first sets a minimum safety requirement that applies to one or both players. The general-purpose creator then invests in the technology, establishing its initial safety and performance levels. Next, domain specialists refine the AI for their use cases, updating the safety and performance levels and taking the product to market. Resulting revenue is shared between the specialist and generalist. Our analysis reveals two insights: first, weak safety regulation imposed predominantly on domain specialists can backfire. While it might seem logical to regulate AI use cases, our analysis shows that weak regulations targeting domain specialists alone can reduce safety in a large class of parameterizations. Second, in contrast to the previous finding, we observe that stronger, well-placed regulation can mutually benefit all players. When regulators impose appropriate safety standards on both general-purpose AI creators and domain specialists, the regulation can function as a commitment device, leading to safety and performance gains, surpassing what is achievable under no regulation or regulating only one player.
FractureAgent: a multi-tool LLM-based intelligent agent for personalized fracture rehabilitation management
Correction for Buche et al., Trait-mediated interactions drive local diversity
Synergistic action of different molecular mechanisms causes striking levels of insecticide resistance in the malaria vector <i>Anopheles gambiae</i>
Intensifying insecticide resistance in the malaria vector Anopheles gambiae poses a serious threat to the progress achieved the last decades in reducing malaria deaths in Africa. The genetic basis of insecticide resistance is often complex, involving multiple genes and mutations. However, we still lack a clear understanding of how each mechanism contributes to overall resistance and how highly resistant phenotypes arise. In this study, we generated a suite of transgenic An. gambiae strains carrying either individual mechanisms or combinations that frequently co-occur in nature. We show that co-overexpression of different detoxification enzymes (CYP6P3, CYP6M2, CYP9K1, ABCH2, GSTE2, and COEAE6G), as well as the overexpression of detoxification enzymes in the presence of target site resistance mutations, can lead to substantially greater levels of resistance. Our findings suggest that increased resistance strength is a primary driver for selection of multimechanism resistance and are transformative for the scientific insight required to design robust molecular diagnostics for timely and reliable resistance detection in the field. We further show that P450 based resistance can constitute an Achilles heel for highly resistant mosquitoes, making them more vulnerable to proinsecticides; compounds that typically require P450 activation. Our results advance our understanding of the mechanistic basis of insecticide resistance and have important implications for the design and implementation of effective and evidence-based resistance management strategies.
Shape instabilities of active epithelial domes under hydraulic stress: Growth, collapse, and oscillation
Fluid-filled epithelial cavities arise in a wide range of biological contexts, from developmental lumens and embryonic cavities to epithelial domes formed by monolayer delamination. Yet how hydraulic pressure and adhesive rupture coordinate their dynamic shape changes remains poorly understood. Here, using Madin-Darby Canine Kidney (MDCK) epithelial domes as a model system, we combine live imaging with a minimal theoretical model to elucidate the mechanisms governing liquid dome shape dynamics. Our model integrates active ion transport, strain-stiffening tissue mechanics, and cell–cell adhesion rupture-healing kinetics. We identify five distinct dynamic phases: collapse, stable growth, growth-collapse, oscillation, and unbounded growth. These phases emerge from the competition between ion-pumping-induced hydraulic pressure and fracture of cell-substrate and cell–cell adhesions. Crucially, the hydraulic feedback between osmotic influx and rupture-mediated leakage produces self-sustained oscillations akin to stick–slip instabilities in fracture mechanics. Pharmacological experiments further validate the model’s predictions that active ion pumping and adhesion strength control both the observed phase transitions and the characteristics of oscillatory phase. Consistent with the model predictions, measuring the hydrostatic pressure via 3D traction force microscopy reveals that pressure increases with enhanced ion transport and cell-substrate adhesion, but decreases with reduced cell–cell adhesion. These findings establish hydraulic fracture as a central regulator of epithelial dome morphodynamics and suggest a physical mechanism that may contribute to lumen formation and stability in developing tissues.
Correction for Patel, The simplicity of the Hodge bundle
Correction for Sabzehei et al., Exploring PrP <sup>C</sup> unfolding as a critical step preceding its refolding in the context of PrP <sup>Sc</sup> propagation
Assessing the feasibility of collective licensing of in-copyright works as training data for generative AI systems
Copyright owners have sued several developers of large-scale generative AI systems for copyright infringement because of their uses of massive quantities of in-copyright works as training data for building AI models. Fair use will be the main defense against these charges. If fair use defenses succeed, developers will be free to continue to commercially exploit models already built on copyrighted data as well as to use these data to train new models or fine-tune existing ones. If copyright owners prevail, developers may be liable for billions of dollars of damages. Developers could also be enjoined from further model development on in-copyright works and even ordered to destroy models trained on infringing works. Numerous commentators have proposed collective licensing as a compromise solution to the copyright-training-data dilemma. Other commentators have questioned the feasibility of such a compromise. This article discusses several proposals for collective licensing to enable development of generative AI systems while providing some compensation to copyright owners. It assesses the complex normative, economic, and practical problems that must be addressed if such a regime is to become feasible. It discusses the implications of a licensing mandate not only for the large firms whose models are widely used today, but also for start-ups, research centers, and higher education developers of generative AI systems, as well as the general public.
Shifting cultivation as a self-organizing social–ecological system
A transition toward flightlessness in Mallards, Indian Runner Ducks, and their hybrid offspring
Many studies have explored wing function in volant birds, and how flight is gained over ontogeny and evolution. However, flight is often secondarily reduced or lost, and how birds transition from wing- to leg-dependence is unknown. Most losses occurred long ago, so stages of wing reduction have never been functionally evaluated or even observed. Here, we assess the anatomical changes and locomotor consequences of a transition toward flightlessness in a unique group: flying Mallards ( Anas platyrhynchos ), flightless Indian Runner Ducks (Mallard-derivative), and their experimentally produced hybrid offspring. Based on wild birds, we hypothesized that shifts in development would lead to wing reductions in Hybrids and especially Runners, with compensatory increases in leg size and performance. Our results show that Runners indeed share many features with wild flightless birds, and that Hybrids are intermediate. However, the assembly of these features is surprising. Wings become relatively smaller due to increases in body size rather than reductions in wing area or muscle, which are conserved. Legs, in contrast, are labile: Runners invest proportionally less in their leg muscles as juveniles but more as adults than Mallards. This contrast between wing conservation and body and leg peramorphosis suggests that for at least some flight losses, bodies and legs change before wings, which get proportionally smaller before being reduced. Given that juveniles with incipient flight and adults with reduced flight both engaged their wings and legs cooperatively, wing-leg coordination may facilitate shifts along a flightless-to-flying spectrum, exemplifying how specialized structures can be gained or lost.