PNAS nexus最新文献

Scratch wound healing assays are widely used to study collective cell migration, essential for understanding tissue regeneration, drug effects, and wound healing mechanisms. However, conventional analyses often rely on wound edge dynamics or individual cell tracks, limiting spatial insight into migration behavior. We present a sector-based analytical framework that reinterprets time-lapse microscopy data by dividing each image into defined spatial regions across the field of view. This enables spatially resolved characterization of how cell populations migrate over time. To address challenges of low contrast and uneven illumination in bright-field microscopy, we apply a level-set segmentation algorithm that robustly detects the wound edge. Using this approach, we show that both cell velocity and trajectory vary with distance from the wound boundary. We introduce a novel metric, the sector-boundary distance, to identify regions where cells migrate faster along nonradial paths. To assess chemotactic activation, cells were treated with the chemokine CXCL10 to stimulate motility via CXCR3-mediated signaling. Statistical testing showed that, in treated cells, the proportion of highly motile cells was significantly associated with wound closure, even in regions distant from the scratch, whereas directionality played a limited role. By contrast, untreated cells exhibited weaker and less organized migration patterns. These findings highlight how local cellular activity contributes to healing in a treatment-dependent manner. Our method bridges global wound-level analysis and local cell-scale behavior by combining single-cell tracking with precise boundary detection. The complete framework is available as open-source software, including a user-friendly web application that enables interactive analysis of microscopy data.

A prevailing notion in sustainability science is that irrigated agriculture underpins global food and water security because it accounts for 40% of crop production and 70% of freshwater withdrawals. Through a network citation analysis of 3,500 documents, we reveal that this belief has spread through the literature with minimal empirical support: 60-80% of all citation paths lead to sources that lack supporting data or that do not even contain the 40 or 70% numbers. We also demonstrate that these figures mask a much more uncertain contribution of irrigation to global crop production and water withdrawals, which can lie anywhere between 18-50 and 45-90%, respectively. These ranges should be understood as lower bounds on the true uncertainty. Our findings underscore the need to rigorously evaluate foundational claims in sustainability science and embrace ambiguity to produce robust research and policy-making.

The National Institutes of Health (NIH) awards additional funds for extramural research to support research infrastructure and administration, such that the total cost of a given research project depends on where it is conducted. We sought to understand whether greater indirect rates were associated with a greater scientific impact of NIH-funded work. The NIH RePORTER database was queried to retrieve all R01, R21, or R03-funded research proposals for which National Institute of Mental Health was listed as the primary funding source for proposals funded between 2012 and 2023. We applied multivariable regression to examine the association between indirect rate and measures of scientific impact, including number of publications, their citation impact in terms of H-index per grant and total citations, and the number of patents associated with each grant. Of 5,143 projects, reflecting $9.85 billion, mean indirect rate was 47.9% (SD 16.2%). Greater indirect rate was associated with modest but statistically significantly greater number of publications (+0.30 per 10% increase in indirect rate, 95% CI 0.08-0.51); H-index at 5 years (+0.25 per 10% increase in indirect rate, 95% CI 0.18-0.33; Fig. 1); and total citations (+29.71 per 10% increase in indirect rate, 95% CI 17.86-41.57). Each 10% increase in indirect rate was associated with a 20% increase in odds of patent filing (aOR 1.20, 95% CI 1.05-1.37). The results suggest modest but statistically significantly greater benefits from conduct of research at institutions with higher indirect costs and provide data for policymakers to consider in weighing the costs against potential benefits of work at such institutions.

Pain is a basic sensation associated with tissue injury. Although facial expression is a useful indicator of pain in mammals, its assessment in rodents requires expertise and experience. Here, we aimed to establish an automated pain assessment method using the facial images of free-moving mice. A convolutional neural network (CNN) was trained with the facial images of untreated mice and those subjected to acetic acid (AC)-induced pain. The trained CNN successfully predicted the faces of AC-, capsaicin-, and calcitonin gene-related peptide-induced pain that had not been used for CNN training. It also detected the analgesic effect of diclofenac, a nonsteroidal anti-inflammatory drug, against AC-induced pain. We used dimensionality reduction algorithms to select images with similar compositions and visualized the regions focused on by the CNN during predictions. The CNN focused on the head, forehead, ear, eye, cheek, and nose to predict pain or no pain. In conclusion, we established a method for automated pain assessment using the facial images of free-moving mice.

The signal regulatory protein alpha (SIRPα)-CD47 axis regulates self-tolerance by delivering inhibitory signals to phagocytic cells and influencing immune responses in transplantation. This study examined the impact of SIRPα polymorphisms on CD47 binding capacity and T cell activation and analyzed the role of SIRPα genotypes in acute rejection following allogeneic liver transplantation. Peripheral blood mononuclear cells from healthy volunteers and data from liver transplant recipients were analyzed. Results showed that V2 SIRPα exhibited significantly higher CD47 binding capacity and enhanced costimulatory activity on CD4⁺ T cell proliferation compared V1 under both CD28^- and CD28⁺ conditions, with further augmentation in the CD28⁺ setting. In the liver transplant cohort, SIRPα V2 was associated with higher acute rejection incidences than V1. These findings suggest that SIRPα polymorphisms, particularly V2, enhance T cell activation and modulate alloimmune responses through both innate and adaptive immunity, with potential implications for transplant outcomes. SIRPα genotyping may serve as one component within broader, multiparameter risk models for acute rejection and help inform optimization of immunosuppressive strategies.

Spiders amplify their physical capabilities by synthesizing multiple high performing silks. Renowned for its toughness, major ampullate (MA) silk composes the spiderweb frame, providing support and absorbing high-energy impacts. In ecribellate orb-weavers, proline-rich motifs in MaSp2 proteins of MA silk are linked to a range of mechanical properties, including extensibility, elasticity, stiffness, and supercontraction. We show a modification of these motifs outside of this clade in a spider that constructs a spring-loaded web. The triangle weaver spider Hyptiotes cavatus (family Uloboridae) stores energy in the support lines of its triangular web, then rapidly releases the tension to catapult forward, collapsing the web around prey. Hyptiotes has an expanded set of MaSp2 genes which encode proteins with far higher proline contents than typical MaSp2. The predominant GPGPQ motifs present in Hyptiotes spidroins also occur abundantly in MaSp sequences of distantly related spiders that produce the most extensible dragline, implying silk protein convergence. Proline-rich MaSp2 proteins constitute half of all MA gland expression in Hyptiotes, and we show that the resulting fibers are the most proline-rich spider silk measured to date. This unique silk composition suggests a functional importance that may facilitate the spring-loaded prey capture mechanism of this species' web and may inspire the design of novel biomaterials using protein engineering.

The nucleus of a cell contains its genetic information in the form of chromatin: polymers of DNA and associated proteins. The physical nature of this polymer system is yet to be understood. Orthogonal experimental approaches probing chromosome structure, dynamics, and mechanics typically suggest the existence of scaling relationships, leading to the widespread use of scale-free, or fractal, models to represent interphase chromosomes. However, currently, there is no single physical model consistent with all reported scaling exponents. Here, we consider the space of possible scale-free models of chromosome structure, dynamics, and mechanics, and examine the fundamental connections between these physical properties. We demonstrate the existence of two algebraic relationships between the scaling exponents-connecting structure with dynamics, and dynamics with mechanics, respectively-outlining the necessary physical conditions for a model to match specific exponent values. Applied to values reported in metazoans, our theory identifies the family of models consistent with all observed scalings, which notably excludes the classical Rouse, Zimm, and fractal globule polymer models. Our theory highlights dynamic correlations between distal genomic loci as necessary to reconnect seemingly contradictory measurements. Consequently, we propose new experiments to narrow down the space of possible models. We expect this framework to serve as a guide for understanding past and future measurements, and for building new physical models of interphase chromosomes.

Persuasive communication in marketing, political, and health domains influences sales, elections, and public health. We present a mega-analysis (a pooled analysis of raw data) of 16 functional MRI datasets (572 participants, 739 messages, and 21,688 experimental trials) assessing the neural correlates of the effectiveness of messages in individual message receivers and at scale (in large groups of message receivers who did not undergo neuroimaging). Existing theories suggest that decision-making is driven by expected rewards and perceived social relevance associated with the expected outcomes of a given choice. Consistent with these theories, we find that (i) brain activity implicated in reward and social processing is associated with message effectiveness in individuals and at scale across diverse domains (e.g. marketing and health campaigns); (ii) exploratory analysis further suggests language, emotion, and sensorimotor processes as pertinent to message effectiveness; and (iii) brain activity provides complementary information on message effectiveness at scale beyond self-reports provided by the same neuroimaging participants. This study offers novel insights into the neurocognitive mechanisms underlying effective messaging, highlights a path toward greater unity and efficiency in persuasion research, and suggests practical intervention targets for message design.

Several enzymes receive functional signals from allosteric site to the active site through conformational dynamics while domain dynamics can also play a significant role. Current investigation identifies a claw-like regulatory region near the active site of dengue protease, which remains in dynamic equilibrium as active (open) and inactive (closed) forms. Enhanced sampling with metadynamics showed that the flexibility of the T[RK][SN]G loop of the claw region is crucial for the protease activity as it helps in the opening of the claw-like structure near the active site, and allows the C-terminal hydrophilic part of NS2B cofactor to enter the claw and transform the protease into its active conformation. Binding kinetics and thermodynamics studies further reveal that allosteric modulator epigallocatechin-3-gallate (EGCG) binds to the enzyme in a biphasic manner and disrupts the active/inactive conformational dynamics and locks the enzyme in an inactive conformation. The inhibitor binding in this region introduces an energy barrier in the free energy landscape of NS2B cofactor binding. In the stronger mode, EGCG could directly bind into the claw, induces conformational changes, locking the dynamic loops in a closed position, preventing NS2B binding and rendering the enzyme inactive. Whereas in the weaker mode, EGCG binds to the T[RK][SN]G loop and perturbs its flexibility driving the claw structure into a more closed conformation and maintaining the protease in an inactive state. The understanding of the mechanism, therefore, would help researchers design more potent inhibitors targeting dengue protease and homologous enzymes.