Recent publications
The specialized language and complex concepts in physics pose significant challenges for information extraction through Natural Language Processing (NLP). Central to effective NLP applications is the text embedding model, which converts text into dense vector representations for efficient information retrieval and semantic analysis. In this work, we introduce PhysBERT, the first physics-specific text embedding model. Pre-trained on a curated corpus of 1.2 × 10⁶ arXiv physics papers and fine-tuned with supervised data, PhysBERT outperforms leading general-purpose models on physics-specific tasks, including the effectiveness in fine-tuning for specific physics subdomains.
Quantum sensing has a bright future for applications in need of impeccable sensitivities. The study of periodic fields has resulted in various techniques, which deal with the limited coherence time of the quantum sensor in several ways. However, the periodic signal to measure could include forms of randomness as well, such as changes in phase or in frequency. In such cases, long measurement times required to detect the smallest of field amplitudes hamper the effectiveness of conventional techniques. In this paper, we propose and explore a robust sensing technique to combat this problem. For the technique, instead of measuring the signal amplitude directly, we measure another global property of the signal, in this case the standard deviation. This results in a much-improved sensitivity. We analyze the advantages and limitations of this technique, and we demonstrate the working with a measurement using a nitrogen-vacancy center. This work encourages scouting measurements of alternative statistics.
Proton transfer is essential in virtually all biochemical processes, with enzymes facilitating this transfer by optimizing the proximity and orientation of reactants through site‐specific hydrogen bonds. Proton transfer is also crucial in the rate‐determining step for the ring‐opening polymerization of N‐carboxyanhydrides (NCAs), widely used to prepare various peptidomimetic materials. This study utilizes side chain‐assisted strategy to accelerate the rate of chain propagation by using NCAs with tertiary amine pendants. This moiety enables hydrogen bond formation between the incoming NCA and the polymer amino growing end. The tertiary amine side chain of the NCA forms a proton shuttle, via a less constrained transition state, to facilitate the proton transfer process. Moreover, the tertiary amine side chains enable the precipitation of NCA monomers through in situ protonation during the monomer synthesis. This greatly facilitates the synthesis of these unreported monomers, allowing the direct controlled synthesis of tertiary amine‐pendant polypeptoids. This side chain‐promoted polymerization has rarely been reported. Additionally, the tertiary amine side chains, as widely used functional groups, endow the polymers with unique properties including pH‐ and thermo‐responsiveness, tunable pKas, and siRNA transfection capability. The self‐promoted synthesis, facile monomer preparation, and attractive properties make tertiary amine‐pendant polypeptoids promising materials for various applications.
Background
The cumulative, health system‐wide survival benefit of immune checkpoint inhibitors (ICIs) is unclear, particularly among real‐world patients with limited life expectancies and among subgroups poorly represented on clinical trials. We sought to determine the health system‐wide survival impact of ICIs.
Methods
We identified all patients receiving PD‐1/PD‐L1 or CTLA‐4 inhibitors from 2010 to 2023 in the national Veterans Health Administration (VHA) system (ICI cohort) and all patients who received non‐ICI systemic therapy in the years before ICI approval (historical control). ICI and historical control cohorts were matched on multiple cancer‐related prognostic factors, comorbidities, and demographics. The effect of ICI on overall survival was quantified with Cox regression incorporating matching weights. Cumulative life‐years gained system‐wide were calculated from the difference in adjusted 5‐year restricted mean survival times.
Results
There were 27,322 patients in the ICI cohort and 69,801 patients in the historical control cohort. Among ICI patients, the most common cancer types were NSCLC (46%) and melanoma (10%). ICI demonstrated a large OS benefit in most cancer types with heterogeneity across cancer types (NSCLC: adjusted HR [aHR] 0.56, 95% confidence interval [CI] 0.54–0.58, p < 0.001; urothelial: aHR 0.91, 95% CI 0.83–1.01, p = 0.066). The relative benefit of ICI was stable across patient age, comorbidity, and self‐reported race subgroups. Across VHA, 15,859 life‐years gained were attributable to ICI within 5‐years of treatment, with NSCLC contributing the most life‐years gained.
Conclusion
We demonstrated substantial increase in survival due to ICIs across a national health system, including in patient subgroups poorly represented on clinical trials.
INTRODUCTION
Factors responsible for the deposition of pathological tau in the brain are incompletely understood. This study links macroscale tau deposition in the human brain to cerebrospinal fluid (CSF) flow dynamics using resting‐state functional magnetic resonance imaging (rsfMRI).
METHODS
Low‐frequency (< 0.1 Hz) resting‐state global brain activity is coupled with CSF flow and potentially reflects CSF dynamics‐related clearance. We examined the correlation between rsfMRI measures of CSF inflow and global activity (gBOLD–CSF coupling) as a predictor, interacting with amyloid beta (Aβ), of tau and cortical thickness (dependent variables) across Alzheimer's Disease Neuroimaging Initiative (ADNI) participants from cognitively unimpaired through mild cognitive impairment (MCI) and Alzheimer's disease (AD).
RESULTS
Tau deposition in Aβ+ participants, accompanied by cortical thinning and cognitive decline, is associated with decreased gBOLD–CSF coupling. Tau mediates the relationship between coupling and thickness.
DISCUSSION
Findings suggest that resting‐state global brain activity and CSF movements comodulate Alzheimer's tau deposition, presumably related to CSF clearance.
Highlights
A non‐invasive functional magnetic resonance imaging (fMRI) assessment of a CSF clearance‐related process is carried out.
Global brain activity is coupled with CSF inflow in human fMRI during resting state.
Global fMRI–CSF coupling is correlated with tau in Alzheimer's disease (AD).
This coupling measure is also associated with cortical thickness, mediated by tau.
The exotic polarization configurations of topologically protected dipolar textures have opened new avenues for realizing novel phenomena absent in traditional ferroelectric systems. While multiple recent studies have revealed a diverse array of emergent properties in such polar topologies, the details of their atomic and mesoscale structures remain incomplete. Through atomic‐ and meso‐scale imaging techniques, the emergence of a macroscopic ferroelectric polarization along both principal axes of the vortex lattice while performing phase‐field modeling to probe the atomic scale origins of these distinct polarization components is demonstrated. Additionally, due to the anisotropic epitaxial strain, the polarization switching behavior perpendicular and parallel to the vortices is highly anisotropic, with switching along the vortex axes occurring over numerous decades in field‐pulse width. This slow switching process allows for the deterministic control of the polarization state, enabling a non‐volatile, multi‐state memory with excellent distinguishability and long retention times.
The enantioselective reduction of prochiral ketones catalyzed by horse liver alcohol dehydrogenase (HLADH), was investigated via a hybrid computational approach, for molecular reactions involved in chiral synthesis of S‐alcohols, when the natural co‐factor, 1,4‐dihyronicotinamide adenine dinucleotide, 1,4‐NADH, was replaced with biomimetic co‐factor, N‐benzyl‐1,4‐dihydronicotinamide, 1. We surmised that different hydride and proton transfer mechanisms were involved using co‐factor, 1. An alternative mechanism, where the hydride transfer step occurred, via an η¹‐keto‐S‐η²‐5,6‐1,4‐dihydronicotinamide‐Zn(II) complex, was previously investigated with a model of the HLADH−Zn(II) catalytic site (J. Organometal. Chem. 2021, 943, 121810). Presently, we studied canonical and alternative mechanisms compared to models of the entire enzyme structure. We disproved the η²‐Zn(II) complex, and discovered a canonical hydride transfer from biomimetic 1,4‐NADH, 1, to the Zn(II) bound prochiral ketone substrate, followed by a new proton relay, consisting of a water chain connecting His51 to Ser48 that accomplished the S‐alkoxy anion's protonation to yield the final S‐alcohol product. The HLADH catalysis, with biomimetic co‐factor, 1, that replaced the ribose group, the 5′‐diphosphate groups, and the adenine nucleotide with a N‐benzyl group, has provided a new paradigm for the design of other structures of 1,4‐NADH biomimetic co‐factors, including their economic value in biocatalysis reactions.
Metal–organic frameworks (MOFs) have been widely studied due to their versatile applications and easily tunable structures. However, heteroatom‐metal coordination dominates the MOFs community, and the rational synthesis of carbon–metal coordination‐based MOFs remains a significant challenge. Herein, two‐dimensional (2D) MOFs based on silver–carbon linkages are synthesized through the coordination between silver(I) salt and isocyanide‐based monomers at ambient condition. The as‐synthesized 2D MOFs possess well‐defined crystalline structures and a staggered AB stacking mode. Most interestingly, these 2D MOFs, without π–π stacking between layers, exhibit narrow band gaps down to 1.42 eV. As electrochemical catalysts for converting CO2 to CO, such 2D MOFs demonstrate Faradaic efficiency over 92 %. Surprisingly, the CO2 reduction catalyzed by these MOFs indicates favorable adsorption of CO2 and *COOH on the active carbon sites of the isocyanide groups rather than on silver sites. This is attributed to the critical σ donor role of isocyanides and the corresponding ligand‐to‐metal charge–transfer effect. This work not only paves the way toward a new family of MOFs based on metal–isocyanide coordination but also offers a rare platform for understanding the electrocatalysis processes on strongly polarized carbon species.
High field science relies on ultrashort pulse lasers with multi-joule pulse energies for studying light–matter interactions under extreme conditions and for driving particle accelerators and secondary radiation sources of x rays, gamma rays, neutrons, positrons, muons, and protons. Next-generation laser drivers will require a 10 3 − 10 4 times increase in pulse repetition rates, producing multi-joule energies at multi-kilowatt average powers to enable practical applications in nuclear engineering, advanced materials, medicine, biology, homeland security, and high-energy physics. Spatially coherently combined femtosecond fiber lasers are recognized as a pathway to these next-generation drivers, with significant practical advantages including high efficiency and the possibility of compact integration. However, chirped pulse amplification in fibers is capable of extracting only a small fraction (usually ∼ 1 % ) of the maximum stored energy. Here we demonstrate near-complete maximum stored energy extraction with low accumulated nonlinearity from a large-core fiber amplifier using coherent pulse stacking amplification. We have amplified a 81-pulse stacking burst in a 85 µm core chirally coupled core Yb-doped fiber, extracting up to 9.5 mJ ( ∼ 90 % of stored energy) with < 4.5 radians of accumulated nonlinear phase, temporally combined this burst into a single pulse, and achieved 4.2 mJ pulses of 313 fs bandwidth-limited duration after compression. This represents, to our knowledge, the highest energy extracted and compressed into a femtosecond pulse from a single fiber amplifier, enabling approximately two orders of magnitude size reduction of future high-energy coherently spatially combined fiber laser arrays.
In Finland, the frequency of isolated cleft palate (CP) is higher than that of isolated cleft lip with or without cleft palate (CL/P). This trend contrasts to that in other European countries but its genetic underpinnings are unknown. We conducted a genome-wide association study in the Finnish population and identified rs570516915, a single nucleotide polymorphism highly enriched in Finns, as strongly associated with CP (P = 5.25 × 10⁻³⁴, OR = 8.65, 95% CI 6.11–12.25), but not with CL/P (P = 7.2 × 10⁻⁵), with genome-wide significance. The risk allele frequency of rs570516915 parallels the regional variation of CP prevalence in Finland, and the association was replicated in independent cohorts of CP cases from Finland (P = 8.82 × 10⁻²⁸) and Estonia (P = 1.25 × 10⁻⁵). The risk allele of rs570516915 alters a conserved binding site for the transcription factor IRF6 within an enhancer (MCS-9.7) upstream of the IRF6 gene and diminishes the enhancer activity. Oral epithelial cells derived from CRISPR-Cas9 edited induced pluripotent stem cells demonstrate that the CP-associated allele of rs570516915 concomitantly decreases the binding of IRF6 and the expression level of IRF6, suggesting impaired IRF6 autoregulation as a molecular mechanism underlying the risk for CP.
The brain represents the world through the activity of neural populations; however, whether the computational goal of sensory coding is to support discrimination of sensory stimuli or to generate an internal model of the sensory world is unclear. Correlated variability across a neural population (noise correlations) is commonly observed experimentally, and many studies demonstrate that correlated variability improves discriminative sensory coding compared to a null model with no correlations. However, such results do not address whether correlated variability is for discriminative sensory coding. If the computational goal of sensory coding is discriminative, then correlated variability should be optimized to support that goal. We assessed optimality of noise correlations for discriminative sensory coding in diverse datasets by developing two novel null models, each with a biological interpretation. Across datasets, we found correlated variability in neural populations leads to highly suboptimal discriminative sensory coding according to both null models. Furthermore, biological constraints prevent many subsets of the neural populations from achieving optimality, and subselecting based on biological criteria leaves discriminative coding performance suboptimal. Finally, we show that optimal subpopulation are exponentially small as the population size grows. Together, these results demonstrate that the geometry of correlated variability leads to highly suboptimal discriminative sensory coding.
Probing strongly coupled quasiparticle excitations at their intrinsic length scales offers unique insights into their properties and facilitates the design of devices with novel functionalities. In this work, we investigate the formation and emission characteristics of plexcitons, arising from the interaction between surface plasmons in narrow gold nanotrenches and excitons in monolayer WSe2. We study this strong plasmon–exciton coupling in both the far-field and the near-field. Specifically, we observe a Rabi splitting in the far-field reflection spectra of about 80 meV under ambient conditions, consistent with our theoretical modeling. Using a custom-designed near-field probe, we find that plexciton emission originates predominantly from the lower-frequency branch, which we can directly probe and map its local field distribution. We precisely determine the plexcitonʼs spatial extension, similar to the trench width, with nanometric precision by collecting spectra at controlled probe locations. Our work opens exciting prospects for nanoscale mapping and engineering of plexcitons in complex nanostructures with potential applications in nanophotonic devices, optoelectronics, and quantum electrodynamics in nanoscale cavities.
We report the metagenome-assembled genome of an ammonia-oxidizing archaeon that is closely related to Nitrosopumilus adriaticus NF5 but shows distinct genomic features compared to strain NF5.
The cation-independent mannose 6-phosphate receptor (CI-MPR) is clinically significant in the treatment of patients with lysosomal storage diseases because it functions in the biogenesis of lysosomes by transporting mannose 6-phosphate (M6P)-containing lysosomal enzymes to endosomal compartments. CI-MPR is multifunctional and modulates embryonic growth and fetal size by downregulating circulating levels of the peptide hormone insulin-like growth factor 2 (IGF2). The extracellular region of CI-MPR comprises 15 homologous domains with binding sites for M6P-containing ligands located in domains 3, 5, 9, and 15, whereas IGF2 interacts with residues in domain 11. How a particular ligand affects the receptor’s conformation or its ability to bind other ligands remains poorly understood. To address these questions, we purified a soluble form of the receptor from newborn calf serum, carried out glycoproteomics to define the N-glycans at its 19 potential glycosylation sites, probed its ability to bind lysosomal enzymes in the presence and absence of IGF2 using surface plasmon resonance, and assessed its conformation in the presence and absence of IGF2 by negative-staining electron microscopy and hydroxyl radical protein footprinting studies. Together, our findings support the hypothesis that IGF2 acts as an allosteric inhibitor of lysosomal enzyme binding by inducing global conformational changes of CI-MPR.
Iridium oxide (IrO2) is recognized as a state-of-art catalyst for anodes of low-temperature polymer-electrolyte membrane water electrolyzers (PEMWE), one of the promising clean energy technologies to produce hydrogen, a critical energy carrier for decarbonization. However, typical IrO2 ink formulations are challenging to process in liquid-film coating processes because of their poor stability against gravitational settling and low viscosities. Here we report on time evolution of the microstructure of concentrated IrO2 inks in a water-rich dispersion medium, probed using a combination of rheology and X-ray scattering for up to four days. The inks progressively evolve from a predominantly liquid-like to a gel-like material with increasing aging time that can be leveraged as a formulation strategy to enhance their stability against sedimentation, and processability during electrode fabrication. We also elucidate the aging behavior by investigating the effects of ink formulation composition - ionomer concentration and solvent composition - and using the extended-DLVO theory. The implications of aging on electrode fabrication, including via direct coating onto membranes and porous transport layers, and membrane-electrode-assembly performance has also been examined. Our findings offer not only a facile but also an environmentally benign formulation strategy to enhance ink processibility, expand practical fabrication approaches, and advance PEMWE manufacturing.
A fundamental question in biology, central to our understanding of cancer and other pathologies, is determining how different cell types coordinate to form and maintain tissues. Recognizing the distinct features and capabilities of the cells that compose these tissues is critical. Unfortunately, the complexity of tissues often hinders our ability to distinguish between neighboring cell types and, in turn, scrutinize their transcriptomes and generate reliable and tractable cell models for studying their inherently different biologies. We have recently introduced a novel method that permits the identification and purification of the 12 cell types that compose the human breast—nearly all of which could be reliably propagated in the laboratory. Here, we explore the nature of these cell types. We sequence mRNAs from each purified population and investigate transcriptional patterns that reveal their distinguishing features. We describe the differentially expressed genes and enriched biological pathways that capture the essence of each cell type, and we highlight transcripts that display intriguing expression patterns. These data, analytic tools, and transcriptional analyses form a rich resource whose exploration provides remarkable insights into the inner workings of the cell types composing the breast, thus furthering our understanding of the rules governing normal cell and tissue function.
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