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ATP-gated P2x7 receptors express at type II auditory nerves and required for efferent hearing control and noise protection

Negative feedback of the cochlear efferent system plays a critical role in control of hearing sensitivity and protection from noise trauma. Type II auditory nerves (ANs) innervate outer hair cells (OHCs) in the cochlea and provide an input to the cochlear efferent system to achieve hearing sensitivity controlling and protection; in particular, medial olivocochlear efferent nerves innervate OHCs to control OHC electromotility, which is an active cochlear amplifier in mammals. However, little is known about channel information underlying type II AN activity and consequent function. Here, we report that ATP-gated P2x7 receptor had a predominant expression at type II spiral ganglion (SG) neurons and the synaptic areas under inner hair cells and OHCs with lateral and medial olivocochlear efferent nerves. Knockout (KO) of P2x7 increased hearing sensitivity with enhanced acoustic startle response, auditory brainstem response, and cochlear microphonics by increasing OHC electromotility. P2x7 KO also increased susceptibility to noise and exacerbated ribbon synapse degeneration. Middle-level noise exposure could impair active cochlear mechanics resulting in hearing loss in P2x7 KO mice. These data demonstrate that P2x7 receptors have a critical role in type II SG neuron’s function and the cochlear efferent system to control hearing sensitivity; deficiency of P2x7 receptors can impair type II SG neuron’s function and the cochlear efferent suppression leading to increase of active cochlear amplification and hearing oversensitivity, i.e., hyperacusis, and susceptibility to noise, which may also associate with other hearing disorders, such as tinnitus.

Basic interactions responsible for thymus function explain the convoluted medulla shape

The thymus is one of the most important organs of the immune system. It is responsible for both the production of T cells and the prevention of their autoimmunity. It comprises two types of tissue: The cortex, where nascent T cells (thymocytes) are generated; and the medulla, embedded within the cortex, where autoreactive thymocytes are eliminated through negative selection. In mice, the medulla exhibits a complex, convoluted morphology, which has raised the question of whether its form impacts its function. Intriguingly, experiments also reveal a reverse dependency: The interactions between medullary stroma and thymocytes shape the medullary structure. However, an understanding of the underlying mechanisms of medulla morphogenesis emerging from these interactions remains elusive. Here, we present a conceptual theoretical model showing that central, experimentally verified signaling pathways suffice to shape the convoluted medullary structure. The mathematical analysis of the model explains the observed effects of chemotaxis on thymocyte localization, and the reported morphological changes resulting from the modulation of thymocyte production. Our findings reveal that the cross-talk between medulla growth and negative selection of thymocytes not only regulates medullary volume but also orchestrates the morphology of the thymus medulla. This mechanism of structure formation robustly organizes the medulla in a way that accelerates thymocyte negative selection by improving their chemotactic migration into the medulla. Thereby, we identify a feedback between the function of the thymus medulla and its form. Our theoretical study motivates further experimental analysis of the spatial distribution of thymic cell populations and predicts morphological changes under genetic perturbations.

Model-based algorithms shape automatic evaluative processing

Computational theories of reinforcement learning suggest that two families of algorithm—model-based and model-free—tightly map onto the classic distinction between automatic and deliberate systems of control: Deliberate evaluative responses are thought to reflect model-based algorithms, which are accurate but computationally expensive, whereas automatic evaluative responses are thought to reflect model-free algorithms, which are error-prone but computationally cheap. This framework has animated research on psychological phenomena ranging from habit formation to social learning, moral decision-making, and cognitive development. Here, we propose that model-based and model-free algorithms may not be as aligned with deliberate and automatic evaluative processing as prevailing theories suggest. Across three preregistered behavioral experiments involving adult human participants (total n = 2,572), we show that model-based algorithms shape not only deliberate but also automatic evaluations. Experiment 1 numerically replicates past findings suggesting that deliberate (but not automatic) evaluative responses are uniquely shaped by model-based algorithms but, critically, also reveals confounds that render interpretation of this evidence equivocal. Experiments 2 to 3 eliminate these confounds and reveal robust model-based contributions to automatic evaluative processing across two measures of automatic evaluation, supported by multinomial processing tree modeling. Together, these results suggest that dominant frameworks may considerably underestimate both the ubiquity of model-based algorithms and the computational sophistication of automatic evaluative processing.

Measurement of the dynamic charge susceptibility near the charge density wave transition in ErTe ₃

A charge density wave (CDW) is a phase of matter characterized by a periodic modulation of valence electron density coupled with lattice distortion. Its formation is closely tied to the dynamical charge susceptibility, χ ( q , ω ) , which reflects the collective electron dynamics of the material. Despite decades of study, χ ( q , ω ) near a CDW transition has never been measured at nonzero momentum, q , with meV energy resolution. Here, we investigate the canonical CDW transition in ErTe 3 using momentum-resolved electron energy loss spectroscopy, a technique uniquely sensitive to valence band charge excitations. Unlike phonons, which soften via the Kohn anomaly, we find the electronic excitations exhibit purely relaxational dynamics well described by a diffusive model, with the diffusivity peaking just below the critical temperature, T C 1 . Additionally, we report for the first time a divergence in the real part of χ ( q , ω ) in the static limit ( ω → 0 ), a long-predicted hallmark of CDWs. Unexpectedly, this divergence occurs as T → 0 , with only a weak thermodynamic signature at T = T C 1 . Our study necessitates a reexamination of the traditional description of CDW formation in quantum materials.

Global universal scaling and ultrasmall parameterization in machine-learning interatomic potentials with superlinearity

Using machine learning (ML) to construct interatomic interactions and thus potential energy surface (PES) has become a common strategy for materials design and simulations. However, those current models of machine-learning interatomic potential (MLIP) consider no relevant physical constraints or global scaling and thus may owe intrinsic out-of-domain difficulty which underlies the challenges of model generalizability and physical scalability. Here, by incorporating the global universal scaling law, we develop an ultrasmall parameterized MLIP with superlinear expressive capability, named SUS 2 -MLIP. Due to the global scaling derived from the universal equation of state (UEOS), SUS 2 -MLIP not only has significantly reduced parameters by decoupling the element space from coordinate space but also naturally outcomes the out-of-domain difficulty and endows the model with inherent generalizability and scalability even with relatively small training dataset. The non-linearity-embedding transformation in radial function endows the model with superlinear expressive capability. SUS 2 -MLIP outperforms the state-of-the-art MLIP models with its exceptional computational efficiency, especially for multiple-element materials and physical scalability in property prediction. This work not only presents a highly efficient universal MLIP model but also sheds light on incorporating physical constraints into AI–aided materials simulation.

Deep structure–function analysis of the endonuclease Mus81 with dominant mutational scanning

Protein structure–function relationships are critical for understanding molecular mechanisms and the impacts of genetic variation. Mutational scanning approaches can deliver scalable analysis, usually through the study of loss-of-function variants. Rarer dominant negative and gain-of-function variants can be more information rich, as they retain a stable proteoform and can be used to dissect molecular function while retaining biological context. Dominant variant proteoforms can still engage substrates and interact with binding partners. Here, we probe the structure–function relationships of the Mus81 endonuclease by ectopic expression of deep mutational scanning libraries to find amino acid variants that confer dominant sensitivity to genotoxic stress and dominant synthetic lethality. Screening more than 2,200 MUS81 variants at 100 positions identified 13 amino acids that can be altered to elicit a dominant phenotype. The dominant phenotype of these variants required the presence of the obligate Mus81 binding protein, Mms4. The dominant variants affect amino acids in a contiguous surface on Mus81 and fall into two distinct classes: residues that bind the catalytic magnesium atoms and residues that form the hydrophobic wedge. Most of the variant amino acids were conserved across species and cognate variants expressed in human cell lines resulted in dominant sensitivity to replication stress and synthetic growth defects in cells lacking BLM helicase. The dominant variants in both yeast and human MUS81 resulted in phenotypes distinct from a MUS81 knockout. These data demonstrate the utility of dominant genetics using ectopic expression of amino acid site saturation variant libraries to link function to protein structure providing insight into molecular mechanisms.

A self-assembling surface layer flattens the cytokinetic furrow to aid cell division in an archaeon

The surface layer or “S-layer” is a two-dimensional lattice of proteins that coats a wide range of archaea and bacteria in place of a cell wall or capsular polysaccharides. S-layers are thought to play an important role in chemically and physically insulating cells from the external environment. Here, we show that the integrity of the S-layer in Sulfolobus acidocaldarius is maintained as cells grow via a process of self-assembly as SlaA monomers fill gaps in the lattice. Although this lattice which is physically tethered to the membrane might be expected to hinder cell division, we show that the S-layer flattens the membrane at cytokinesis to accelerate ESCRT-III-dependent cell division—and is important for robust, successful cell divisions under conditions of mechanical stress. Taken together, these results define the rules governing S-layer self-assembly and show how a flexible lattice coat that is coupled to the underlying membrane can both provide a cell with mechanical support and help to drive rapid and functionally important changes in cell shape.

Social influence during public crises: Weekly dynamics and adaptive patterns of conformity to the collective following the COVID-19 outbreak

Regional collectivism has been observed to contribute to better coping with public crises such as the COVID-19 pandemic. This study poses a reverse question: Does the eruption of public crises increase people’s conformity to the collective? To answer this question, we analyzed real-world transactions on Taobao (the largest e-commerce platform in China), each with a purchase decision and a list of candidates considered before purchasing. Conformity to the collective was measured using two indicators: whether the decision-maker opted for the A) most-sold and B) best-rated options within the candidate option set. The results reveal that both conformity variables were significantly higher in the 10 wk subsequent to January 19, 2020 (when the nationwide COVID-19 crisis erupted in China), than in the 8 wk prior. These shifts were common across subpopulations, regions, and product categories and remained significant after strictly matching across weeks and after using a within-person, longitudinal sample. These shifts were more confidently attributed to the pandemic by further conducting difference-in-differences analyses to compare pandemic-affected regions with their unaffected, comparable counterparts using data from six subsequent regional waves in China. Furthermore, regions with larger increases in conformity during the early stage of the pandemic achieved better antipandemic outcomes. These findings provide real-world evidence for previous theories on behavioral immune systems, terror management, and compensatory control. Additionally, cross-regional comparisons of effect sizes offer exploratory insights into cultural psychology. In summary, these findings capture how human societies dynamically adjust their values to better adapt to unanticipated survival challenges.

Information rate of meaningful communication

In Shannon’s seminal paper, the entropy of printed English, treated as a stationary stochastic process, was estimated to be roughly 1 bit per character. However, considered as a means of communication, language differs considerably from its printed form: i) the units of information are not characters or even words but clauses, i.e., shortest meaningful parts of speech; and ii) what is transmitted is principally the meaning of what is being said or written, while the precise phrasing that was used to communicate the meaning is typically ignored. In this study, we show that one can leverage recently developed large language models to quantify information communicated in meaningful narratives in terms of bits of meaning per clause.

Longitudinal sequencing reveals polygenic and epistatic nature of genomic response to selection

Evolutionary adaptation to new environments likely results from a combination of selective sweeps and polygenic shifts, depending on the genetic architecture of traits under selection. While selective sweeps have been widely studied, polygenic responses are thought to be more prevalent but remain challenging to quantify. The infinitesimal model makes explicit the hypothesis about the dynamics of changes in allele frequencies under selection, where only allelic effect sizes, frequencies, linkage, and gametic disequilibrium matter. Departures from this, like long-range correlations of allele frequency changes, could be a signal of epistasis in polygenic response. We performed an Evolve & Resequence experiment in Drosophila melanogaster exposing flies to a high-sugar diet for over 100 generations. We tracked allele frequency changes in >3000 individually sequenced flies and population pools and searched for loci under selection by identifying sites with allele frequency trajectories that differentiated selection regimes consistently across replicates. We estimate that at least 4% of the genome was under positive selection, indicating a highly polygenic response. The response was dominated by small, consistent allele frequency changes, with few loci exhibiting large shifts. We then searched for signatures of selection on pairwise combinations of alleles in the new environment and found several strong signals of putative epistatic interactions across unlinked loci that were consistent across selected populations. Finally, we measured differentially expressed genes (DEGs) across treatments and show that DEGs are enriched for selected SNPs. Our results suggest that epistatic contributions to polygenic selective response are common and lead to detectable signatures.

A novel protocol for the direct isolation of a highly pure and regenerative population of satellite stem cells

The utility of a pure population of highly regenerative satellite stem cells (SSCs) is a prerequisite for successful cell-based muscle therapies. Previous works have reported several methods for the SSC isolation. However, the majority of cells isolated using previous methods are fibroblasts and other nonmyogenic cell types, necessitating further expensive and time-consuming purification steps often affecting the regenerative quality of the isolated SSCs. Here, we describe a simple, time-effective, and robust protocol for the isolation of a pure population of SSCs in a single direct step, eliminating the need for further purification steps. By separating the muscle fascicles from the adjacent connective tissues (i.e., epimysium and perimysium) and utilizing a defined dissociation medium, a cell pool enriched in SSCs was successfully obtained. Immunofluorescent staining confirmed the stemness and the myogenic purity of the isolated cells (~97%). Upon myogenic induction, SSCs gave rise to multinucleated myofibers that exhibited spontaneous contraction in the culture dish for up to 21 d. Efforts to optimize the culture conditions revealed that tissue culture plates (TCPs) coated with a tissue-specific extract significantly enhanced SSCs’ attachment, growth, and differentiation compared to collagen I, Matrigel-coated TCPs, or noncoated TCPs. Further studies confirmed the robust myogenic regenerative capacity of the isolated cells, as evidenced by their ability to display key regenerative characteristics, demonstrating the mild effects of our isolation protocol on their regenerative capacity. The isolation protocol presented herein can potentially be used to obtain SSCs with high myogenic purity for skeletal muscle regenerative engineering and clinical indications.

How surface charges affect interdroplet freezing

The freezing of droplets on surfaces is closely relevant with various industrial processes such as aviation, navigation, and transportation. Previous studies mainly focus on physiochemically heterogeneous but electrically homogeneous surfaces, on which the presence of vapor pressure gradient between droplets is the predominant mechanism for interdroplet freezing bridging, propagation, and eventual frosting across the entire surface. An interesting yet unanswered question is whether electrostatic charge on surfaces affects freezing dynamics. Here, we find an interdroplet freezing relay (IFR) phenomenon on electrically heterogeneous surfaces that exhibits a three-dimensional, in-air freezing propagation pathway and an accelerated freezing rate. Theoretical and experimental investigations demonstrate that this phenomenon originates from the presence of surface charge gradient established between the frozen droplet and neighboring water droplet, which leads to a spontaneous shooting of desublimated ice needles from the frozen droplet and then triggers the freezing of neighboring water droplet in in-air manner. We further demonstrate its generality across various dielectric substrates, liquids, and droplet configurations. Our work enriches conventional perspectives on droplet freezing dynamics and emphasizes the pivotal role of electrostatics in designing passive anti-icing and antifrosting materials.

Author Correction: Augmenting apoptosis-mediated anticancer activity of lactoperoxidase and lactoferrin by nanocombination with copper and iron hybrid nanometals

Combined targeting of PRDX6 and GSTP1 as a potential differentiation strategy for neuroblastoma treatment

Neuroblastoma (NB) is a heterogeneous childhood cancer, characterized by the amplification of the MYCN oncogene in 40% of the high-risk cases. Our previous work demonstrated that MYCN drives metabolic reprogramming in NB, including upregulation of antioxidant enzymes. Here, we identify peroxiredoxin 6 (PRDX6) as a promising therapeutic target in NB. Pharmacological inhibition of PRDX6 reduces MYCN levels, induces apoptosis, and promotes neuronal differentiation accompanied by lipid droplet accumulation, essential for the phenotypic reprogramming. Moreover, combined inhibition of PRDX6 and glutathione S-transferase Pi 1 (GSTP1), a key antioxidant enzyme needed for PRDX6 activation, demonstrated synergistic effects both in vitro and in vivo. This strategy results in neuronal maturation and initiates downstream pathways distinct from the ones triggered by retinoic acid, the differentiation-inducing agent currently used in clinical practice for NB. Notably, both PRDX6 and GSTP1 are highly expressed in the developing murine adrenal gland, as well as in high-risk, MYCN -amplified NB, correlating with an undifferentiated state and poor prognosis. Together, our results provide insights into the potential of PRDX6 and GSTP1 as therapeutic targets for differentiation induction for children with NB.

A real-world pharmacovigilance study of lorazepam based on the FDA adverse event reporting system database

Abstract Lorazepam is extensively used to treat anxiety disorders and anxiety associated with depression. This study evaluates the safety of lorazepam based on real-world data from the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS). Data were collected from January 2004 to June 2024. After standardizing the data, we quantified signals using four algorithms, including the Reporting Odds Ratio (ROR), the Proportional Reporting Ratio (PRR), the Bayesian Confidence Propagation Neural Network (BCPNN), and the Multi-Item Gamma Poisson Shrinker (MGPS) to quantize the signal by Bayesian analysis and disproportionation analysis. AE signals were predominantly involved psychiatric disorders, nervous system disorders, injury, poisoning and procedural complications, and cardiac disorders. Notably, new potential AE signals of clinical value were identified in this study, including tachycardia, rhabdomyolysis, neologism, phagophobia, pancreatic fibrosis, and pneumonia. Sex-stratified analysis showed that the risk of poisoning was more pronounced in females and the AEs of sedation were more pronounced in males. Age-stratified analysis demonstrated variations in AEs across different age groups.The findings of this study were consistent with clinical trials, and identified several new potential AE signals. In addition, there are gender and age differences in some AEs. These findings provide valuable insights into lorazepam in clinical practice.

Metabolic control of glycosylation forms for establishing glycan-dependent protein interaction networks

Protein–protein interactions (PPIs) are crucial for comprehending the molecular mechanisms and signaling pathways underlying diverse biological processes and disease progression. However, investigating PPIs involving membrane proteins is challenging due to the complexity and heterogeneity of glycosylation. To tackle this challenge, we developed an approach termed glycan-dependent affinity purification coupled with mass spectrometry (GAP–MS), specifically designed to characterize changes in glycoprotein PPIs under varying glycosylation conditions. GAP–MS integrates metabolic control of glycan profiles in cultured cells using small molecules referred to as glycan modifiers with affinity purification followed by mass spectrometry analysis (AP–MS). Here, GAP–MS was applied to characterize and compare the interaction networks under five different glycosylation states for four bait glycoproteins: BSG, CD44, EGFR, and SLC3A2. This analysis identified a network comprising 156 interactions, of which 131 were determined to be glycan dependent. Notably, the GAP–MS analysis of BSG provided distinct information regarding glycosylation-influenced interactions compared to the commonly used glycosylation site mutagenesis approach combined with AP–MS, emphasizing the unique advantages of GAP–MS. Collectively, GAP–MS presents distinct insights over existing methods in elucidating how specific glycosylation forms impact glycoprotein interactions. Additionally, the glycan-dependent interaction networks generated for these four glycoproteins serve as a valuable resource for guiding future functional investigations and therapeutic developments targeting the glycoproteins discussed in this study.

Author Correction: EZH2 regulates oncomiR-200c and EMT markers in esophageal squamous cell carcinomas

Telescopes team up to probe distant worlds

Author Correction: Detection of cotton crops diseases using customized deep learning model

Reciprocal interaction between cortical SST and PV interneurons in top–down regulation of retinothalamic refinement

Refinement of thalamic circuits is crucial for the proper maturation of sensory circuits. In the visual system, this process is regulated by corticothalamic feedback during the experience-dependent phase of development. Yet the cortical circuits modulating this feedback remain elusive. Here, we demonstrate opposing roles for cortical somatostatin (SST) and parvalbumin (PV) interneurons in shaping retinogeniculate connectivity during the thalamic sensitive period (P20-30). Early in the refinement process, SST interneurons promote the strengthening and pruning of retinal inputs in the thalamus, as evidenced by disrupted synaptic refinement following their ablation. In contrast, PV interneurons, which mature later, act as a brake on this refinement, with their ablation leading to enhanced pruning of retinogeniculate connections. Notably, manipulating the relative balance between these inhibitory circuits can regulate sensory deprivation-induced retinogeniculate remodeling. Taken together, our findings show that cortical SST and PV interneuron circuits drive experience-dependent reciprocal antagonism that gates cortical feedback regulation of feedforward thalamic refinement.