bluuebunny/crossref_metadata_2025_split huggingface dataset:
Color-neutral and reversible tissue transparency enables longitudinal deep-tissue imaging in live mice
Authors: Keck Carl H.C. , Schmidt Elizabeth L. , Roth Richard H. , Floyd Brendan M. , Tsai Andy P. , Garcia Hassler B. , Cui Miao , Chen Xiaoyu , Wang Chonghe , Park Andrew , Zhao Su , Liao Pinyu A. , Casey Kerriann M. , Reineking Wencke , Cai Sa , Zhang Ling-Yi , Yang Qianru , Yuan Lei , Baghdasaryan Ani , Lopez Eduardo R. , Cooper Lauren , Cui Han , Esquivel Daniel , Brinson Kenneth , Chen Xiaoke , Wyss-Coray Tony , Coleman Todd P. , Brongersma Mark L. , Bertozzi Carolyn R. , Wang Gordon X. , Ding Jun B. , Hong Guosong 
Published: February 2025

AbstractLight scattering in biological tissue presents a significant challenge for deepin vivoimaging. Our previous work demonstrated the ability to achieve optical transparency in live mice using intensely absorbing dye molecules, which created transparency in the red spectrum while blocking shorter-wavelength photons. In this paper, we extend this capability to achieve optical transparency across the entire visible spectrum by employing molecules with strong absorption in the ultraviolet spectrum and sharp absorption edges that rapidly decline upon entering the visible spectrum. This new color-neutral and reversible tissue transparency method enables optical transparency for imaging commonly used fluorophores in the green and yellow spectra. Notably, this approach facilitates tissue transparency for structural and functional imaging of the live mouse brain labeled with yellow fluorescent protein and GCaMP through the scalp and skull. We show that this method enables longitudinal imaging of the same brain regions in awake mice over multiple days during development. Histological analyses of the skin and systemic toxicology studies indicate minimal acute or chronic damage to the skin or body using this approach. This color-neutral and reversible tissue transparency technique opens new opportunities for noninvasive deep-tissue optical imaging, enabling long-term visualization of cellular structures and dynamic activity with high spatiotemporal resolution and chronic tracking capabilities.Significance StatementTissue scattering represents a major barrier to deep tissue imagingin vivo. We recently showed that tissue can be rendered transparent in the red spectrum using intensely absorbing dye molecules. Here, we introduce a new, color-neutral and reversible tissue transparency approach. We demonstrate longitudinal structural and functional imaging in the deep tissue of awake mice.
An Fc-SPINK1 fusion protein inhibits pancreatic inflammation in a mouse model
Authors: Way J. C. , Heid D. , Theiss M. , Nørrelykke S. , Barck L. , Burger L. , Bredl J. A. , Dobbertin T. , Höflich P. , Stadelmann T. , Niopek D. , Chan K. Redfield , Sivaraman R. , Graveline A. R. , Vernet A. , Sanchez-Ventura M. , Silver P. A. 
Published: February 2025

AbstractPancreatitis results from premature activation and impaired inactivation of pancreatic proteases, primarily trypsin, leading to self-digestion, tissue necrosis, fibrosis, and inflammation. SPINK1 is a pancreas-specific inhibitor of trypsin that prevents premature trypsin activation, and could be a candidate therapeutic. However, because of its small size, SPINK1 would be subject to rapid renal clearance, making it ineffective. To construct a long half-life therapeutic inhibitor of trypsin for pancreatitis treatment we fused this protein to the C-terminus of an IgG1 antibody Fc element, increasing the size to ∼78 kDa, thereby exceeding the renal clearance threshold and providing for FcRn-mediated recycling out of cells. A non-glycosylated form of Fc-SPINK1 was expressed in the yeastPichia pastoris. Fc-SPINK1 inhibits trypsin enzyme activityin vitro. The blood pharmacokinetics in mice are consistent with a three-compartment distribution model and a terminal half-life of ∼3 days. In a caerulein-induced mouse model of pancreatitis, Fc-SPINK1 significantly ameliorated cell death and immune cell infiltration. We developed an automated image analysis technique to quantify pancreatitis-associated loss of tissue cohesion, and found that Fc-SPINK1 also reduced this effect. This study demonstrates the potential of Fc-SPINK1 as a rationally designed therapy for pancreatitis.
Fibrillarin-mediated ribosomal RNA maturation is a novel therapeutic vulnerability in triple-negative breast cancer
Authors: Jouines Camille , Lo Monaco Piero , Gaucherot Angéline , Radermecker Julie , Isaac Caroline , Bourdelais Fleur , Monet Marie-Ambre , Meyer Marion , Chalabi-Dchar Mounira , Nguyen Van Long Flora , Baillon Laury , Froment Carine , Marcoux Julien , Vanbelle Christophe , Fenouil Tanguy , Durand Sébastien , Giraud Stéphane , Diaz Jean-Jacques , Marcel Virginie , Catez Frédéric 
Published: February 2025

AbstractTriple-negative breast cancer (TNBC) remains one of the most challenging breast cancer subtypes to treat due to the lack of effective therapeutic options. Ribosome biogenesis has recently emerged as a promising therapeutic target across various cancers. Despite the current targeting of ribosome biogenesis through RNA polymerase I (RNA Pol I) inhibition, we speculated that other factors essential for ribosome assembly, such as rRNA maturation factors, may also represent therapeutic targets in TNBC. Here, we demonstrate that ribosome biogenesis-related genes are notably overexpressed in TNBC compared to other breast cancer subtypes, highlighting its critical role in TNBC progression. Accordingly, we show that RNA Pol I inhibition exerts potent anti-proliferative effects in pre-clinical models of TNBC, bothin vitroandin vivo. However, the DNA-damaging activity of RNA Pol I inhibitors raises safety concerns, highlighting the need for alternative strategies to inhibit ribosome biogenesis. To this end, we show that targeting a downstream rRNA maturation step, specifically pre-rRNA cleavage, by inhibiting the maturation factor Fibrillarin, also inhibits tumor growth in TNBC models. Notably, ribosome biogenesis inhibition, through either RNA Pol I or Fibrillarin targeting, induces cell cycle arrest without triggering significant cell death. These findings establish ribosome biogenesis as a therapeutic vulnerability in TNBC and identify rRNA maturation, and Fibrillarin in particular, as novel targets for potential therapeutic intervention.SignificanceTargeting ribosome biogenesis, through inhibition of either rRNA synthesis or maturation, induces anti-tumoral effects in TNBC, representing a novel therapeutic vulnerability with potential to improve patient outcomes.
A hierarchical immune receptor network in lettuce reveals contrasting patterns of evolution in sensor and helper NLRs
Authors: Pai Hsuan , Sakai Toshiyuki , Posbeyikian Andres , Frijters Raoul , Sugihara Yu , Contreras Mauricio P. , Kourelis Jiorgos , Adachi Hiroaki , Kamoun Sophien , Toghani AmirAli 
Published: February 2025

ABSTRACTNucleotide-binding domain and leucine-rich repeat immune receptors (NLRs) are known for their rapid evolution, even at the intraspecific level, yet the rates of evolution differ significantly across various NLR classes. Within the NRC (NLR Required for Cell Death) network, NLRs operate in complex sensor-helper configurations to confer immunity against a diverse array of pathogens, particularly in Asterids. While helper NLRs are typically conserved and evolve slowly, sensor NLRs tend to evolve more rapidly. However, the functional connections between slow and fast-evolving NLRs remain poorly understood, notably in important crop species. We conducted a comparative analysis of NLRs across 40 Solanales and 29 Asterales genomes to explore NRC network expansion and diversification within the less-studied Asterales order. Our findings reveal that the NRC network has expanded less in Asterales compared to Solanales. We functionally validated a minimal Asterales NRC network with 2 helpers and 9 sensors in common lettuce (Lactuca sativa). Through selection and diversification analysis and structural modeling of NRC helper and sensor subclades in theLactucagenus, we found varying evolutionary diversification rates between NRC helpers and sensors. We found a correlation between sensor diversification rates and helper dependency, with sensors reliant on a phylogenetically conserved helpers experiencing limited diversification pressure. Our results highlight the lineage- and function-specific evolution of the NRC network, offering insights into the evolutionary pressures shaping plant immune receptor networks.
Transmission ofStaphylococcus aureusin the neonatal intensive care unit predicts invasive infection
Authors: She Qianxuan , Srinivasan Lakshmi , Theiller Erin , Galis Bianca E. , Napper T’Nia , Feder Andries , Arvanitis Alex , Jones Steven M. , Hayes Ericka , Puopolo Karen M. , Baldassano Robert N. , David Michael Z. , Coffin Susan E. , Gibbs Kathleen A. , Smith Kenneth , Harris Rebecca M. , Zackular Joseph P. , Moustafa Ahmed M. , Planet Paul J. 
Published: February 2025

ABSTRACTBackgroundStaphylococcus aureusis a leading cause of healthcare-associated infection and is one of the most common pathogens causing serious invasive infection in the neonatal intensive care unit (NICU). Asymptomatic colonization byS. aureuspresents a significant risk for subsequent infection of the colonized infant and for patient-to-patient transmission. Transmission of more virulentS. aureusstrains in the NICU could increase infection risk in this vulnerable population.MethodsWe performed a three-year, unit-wide screening forS. aureusin the Children’s Hospital of Philadelphia (CHOP) NICU, with whole genome sequencing (WGS) of 1,670 isolates from patient colonization surveillance, blood cultures from both NICU and non-NICU patients, and environmental surfaces. We used comparative genomic epidemiological approaches to investigate the transmission dynamics ofS. aureusin the NICU setting.FindingsOur analyses revealed 490 unique strains with multiple, highly related, clones among NICUS. aureusgenomes. We identified sixty-nine transmission clusters, of which 87% (60/69) were methicillin susceptibleS. aureus(MSSA), and 28% (19/69) included isolates from both colonizing sites and bacteremia. The largest invasive cluster persisted over 2 years, involved 30 infants, and caused 4 cases of bacteremia. Spatial and temporal epidemiological links were found in 88% of clusters, and suggest that shared spaces served as the predominant means of transmission in the NICU setting. NICU environmental surveillance revealedS. aureuson surfaces; 3 of these isolates were also identified in colonizing and invasive clusters, suggesting potential environmental reservoirs. Remarkably, transmission clusters with both colonizing and invasive isolates were associated with higher rates of transmission, suggesting that specific transmission clusters pose a significantly higher risk for invasive infections in the NICU.InterpretationsGenomic temporal-spatial epidemiologic analyses revealed high levels ofS. aureustransmission in the NICU with multiple transmission clusters that persisted over long periods of time. Our findings demonstrate a strong association amongst colonization, transmission, and the development of invasive infections, underscoring the importance of targeted measures to preventS. aureusinfections in the NICU setting.FundingThis work was supported by the Center for Microbial Medicine, Microbial Archive and Cryocollection and the Research Institute (CLABSI Innovation and OMICS Initiative) at CHOP.
SEEDNet: Covariate-free multi-country settlement-level epidemiological estimates datasets for network analysis
Authors: Darooneh Amir Hossein , Kortenaar Jean-Luc , Goulart Céline M. , McLaughlin Katie , Cornelius Sean P. , Bassani Diego G. 
Published: February 2025

ABSTRACTThe study of population health through network science holds high promise, but data sources that allow complete representation of populations are limited in low-and middle-income countries. Large national health surveys designed to gather nationally representative health and development data are promising data sources but are not designed to produce small-area estimates of health indicators. Methods for producing these from national surveys tend to rely on varied covariate data sources and are computationally demanding, limiting their use for network representations of populations. To reduce the sources of measurement error and allow efficient multi-country representation of populations as networks of human settlements here, we present SEEDNet (Settlement-level Epidemiological Estimates Datasets for Network Analysis)1, a data library of multi-country representations of population health across human settlements. Our covariate-free method uses georeferenced national surveys to produce SAEs of health indicators through local inverse-distance weighted interpolation and includes an algorithm for the comprehensive identification of population settlements of all sizes across the globe. Our estimates are cross-validated against those obtained using a Bayesian Geostatistical Model. The method is fully automated, requiring a single standard georeferenced survey data source for mapping populations, eliminating the need for indicator or country-specific covariate selection by investigators. Computational efficiency is achieved by restricting computation to human-occupied areas and by adopting a logical aggregation of estimates into the complete range of settlement sizes. Standardized georeferenced settlement-level datasets for 15 indicators and 10 countries were validated in this paper, as well as the novel method to identify settlements. SEEDNet1is a specialized library of nodes that can serve as a basis for network representations of population health in low-and middle-income countries.
Enhancing Brain Age Estimation Under Uncertainty: A Spectral-normalized Neural Gaussian Process Approach Utilizing 2.5D Slicing
Authors: Linli Zeqiang , Liang Xingcheng , Zhang Zhenhua , Hu Kang , Guo Shuixia 
Published: February 2025

AbstractBrain age gap, the difference between estimated brain age and chronological age via magnetic resonance imaging, has emerged as a pivotal biomarker in the detection of brain abnormalities. While deep learning is accurate in estimating brain age, the absence of uncertainty estimation may pose risks in clinical use. Moreover, current 3D brain age models are intricate, and using 2D slices hinders comprehensive dimensional data integration. Here, we introduced Spectral-normalized Neural Gaussian Process (SNGP) accompanied by 2.5D slice approach for seamless uncertainty integration in a single network with low computational expenses, and extra dimensional data integration without added model complexity. Subsequently, we compared different deep learning methods for estimating brain age uncertainty via the Pearson correlation coefficient, a metric that helps circumvent systematic underestimation of uncertainty during training. SNGP shows excellent uncertainty estimation and generalization on a dataset of 11 public datasets (N=6327), with competitive predictive performance (MAE=2.95). Besides, SNGP demonstrates superior generalization performance (MAE=3.47) on an independent validation set (N=301). Additionally, we conducted five controlled experiments to validate our method. Firstly, uncertainty adjustment in brain age estimation improved the detection of accelerated brain aging in adolescents with ADHD, with a 38% increase in effect size after adjustment. Secondly, the SNGP model exhibited OOD detection capabilities, showing significant differences in uncertainty across Asian and non-Asian datasets. Thirdly, the performance of DenseNet as a backbone for SNGP was slightly better than ResNeXt, attributed to DenseNet’s feature reuse capability, with robust generalization on an independent validation set. Fourthly, site effect harmonization led to a decline in model performance, consistent with previous studies. Finally, the 2.5D slice approach significantly outperformed 2D methods, improving model performance without increasing network complexity. In conclusion, we present a cost-effective method for estimating brain age with uncertainty, utilizing 2.5D slicing for enhanced performance, showcasing promise for clinical applications.
A Genomic Analysis of Usher Syndrome: Population-Scale Prevalence and Therapeutic Targets
Authors: Redfield Shelby E. , Mauriac Stephanie A. , Géléoc Gwenaëlle S. , Shearer A. Eliot 
Published: February 2025

ABSTRACTUsher syndrome (USH), the most common form of deaf-blindness, displays extensive genetic, allelic, and phenotypic heterogeneity. The dual sensory impairment associated with this disorder makes Usher syndrome an important target for gene therapy, with dozens of published preclinical studies targeting multiple USH genes and using multiple gene therapy strategies. Nine genes have been conclusively linked to Usher syndrome; however, data on prevalence and contribution of specific genetic variants is lacking. Such information is essential to choosing a favorable target gene or therapeutic approach during clinical trial design. Here, we used large genomic databases to systematically evaluate the genomics of Usher syndrome. We ascertained pathogenic USH variants from three clinical databases and determined the occurrence of these pathogenic USH variants within: (1) a publicly available dataset including worldwide populations (GnomAD), (2) a cohort of 3,888 children without hearing loss, and (3) 637 children with hearing loss. Results show significant variability in the frequency of USH variants by gene and genetic ancestry. 1% of control subjects carry a pathogenic USH variant. Pathogenic variants inUSH2Aare the most prevalent, at 1 in 150 individuals (0.0062). Calculated general population prevalence for all USH subtypes is 1 in ∼29,000, indicating that 30,405 individuals in the United States and 721,769 individuals worldwide are affected. We estimate that 324 babies in the United States and 12,090 worldwide are born with Usher syndrome each year. We identify key targets for genetic therapy based on population-level prevalence including a focus on alternatives to gene replacement therapies, specifically forUSH2A.
Living dangerously with decoupled first and second generation scalars: SUSY prospects at the LHC
Authors: Baer Howard , Barger Vernon , Zhang Kairui 
Published: February 2025

The string landscape statistical draw to large scalar soft masses leads to a mixed quasidegeneracy/decoupling solution to the supersymmetry (SUSY) flavor and CP problems where first/second generation matter scalars lie in the 20–40 TeV range. With increasing first/second generation scalars, SUSY models actually become more natural due to two-loop renormalization group (RG) effects that suppress the corresponding third generation soft masses. This can also lead to substantial parameter space regions that are forbidden by the presence of charge and/or color breaking minima of the scalar potential. We outline the allowed SUSY parameter space for the gravity-mediated three extra-parameter-nonuniversal Higgs model NUHM3. The natural regions with mh∼125  GeV, ΔEW≲30 and decoupled first/second generation scalar are characterized by rather heavy gluinos and EW gauginos, but with rather small μ and top squarks not far beyond LHC Run 2 limits. This scenario also explains why SUSY has so far eluded discovery at LHC in that the parameter space with small scalar and gaugino masses is all excluded by the presence of charge and/or color breaking minima.

Published by the American Physical Society
2025
Angle-resolved spin noise spectroscopy in semiconductors: Two-state theory and experiments
Authors: Gribakin B. F. , Cronenberger S. , Boukari H. , Scalbert D. 
Published: February 2025

Traditional spin noise spectroscopy generally does not address spatial spin correlations, which are in fact crucial for an in-depth understanding of spin relaxation. In semiconductors, one requires spin noise measurements at substantial angles from the incident beam to study spatial correlations on the relevant submicron scale. Recording electron spin noise over a wide range of angles via goniometric homodyne detection enables us to recover the spatiotemporal spectra of electron spin fluctuations with virtually no losses in spin noise power in reciprocal space. Applied to a series of insulating n-doped CdTe samples, the technique permits the separation of various spin motion mechanisms in reciprocal space. We show that cross correlations between localized and delocalized spins are crucial in explaining the observed long-distance spin jumps between neutral donors, and they have a profound impact on the spin relaxation of localized electrons even at temperatures that are low compared to the activation energy. We develop a theoretical two-state model based on Bloch equations that take these cross correlations into account via a release-and-trapping spin transport mechanism. The model is in quantitative agreement with the entire body of our experimental data, where spatiotemporal electron spin noise spectra are measured as functions of temperature, donor density, and magnetic field.

Published by the American Physical Society
2025
Classical Simulability of Quantum Circuits with Shallow Magic Depth
Authors: Zhang Yifan , Zhang Yuxuan 
Published: February 2025

Quantum magic is a necessary resource for quantum computers to be not efficiently simulable by classical computers. Previous results have linked the of quantum magic, characterized by the number of T gates or the stabilizer rank, to classical simulability. However, the effect of the of quantum magic on the hardness of simulating a quantum circuit remains open. In this work, we investigate the classical simulability of quantum circuits with alternating Clifford and T layers across three tasks: amplitude estimation, sampling, and evaluating Pauli observables. In the case in which all T gates are distributed in a single layer, performing amplitude estimation and sampling to multiplicative error are already classically intractable under reasonable assumptions, but Pauli observables are easy to evaluate. Surprisingly, with the addition of just one T-gate layer or merely replacing all T gates with T1/2, the Pauli evaluation task reveals a sharp complexity transition from being in P to being GapP-complete. Nevertheless, when the precision requirement is relaxed to 1/poly(n) additive error, we are able to give a polynomial-time classical algorithm to compute amplitudes, Pauli observables, and sampling from log﻿(n)-sized marginal distributions for any magic-depth-1 circuit that is decomposable into a product of diagonal gates. This rules out certain forms of quantum advantage in these circuits. Our research provides new techniques to simulate highly magical circuits while shedding light on their complexity and their significant dependence on the magic depth.

Published by the American Physical Society
2025