Search

This paper presents an innovative approach for predicting the relative populations of protein conformations using AlphaFold 2, an AI-powered method that has revolutionized biology by enabling the accurate prediction of protein structures. While AlphaFold 2 has shown exceptional accuracy and speed, it is designed to predict proteins' ground state conformations and is limited in its ability to predict conformational landscapes. Here, we demonstrate how AlphaFold 2 can directly predict the relative populations of different protein conformations by subsampling multiple sequence alignments. We tested our method against nuclear magnetic resonance experiments on two proteins with drastically different amounts of available sequence data, Abl1 kinase and the granulocyte-macrophage colony-stimulating factor, and predicted changes in their relative state populations with more than 80% accuracy. Our subsampling approach worked best when used to qualitatively predict the effects of mutations or evolution on the conformational landscape and well-populated states of proteins. It thus offers a fast and cost-effective way to predict the relative populations of protein conformations at even single-point mutation resolution, making it a useful tool for pharmacology, analysis of experimental results, and predicting evolution. Protein dynamics, crucial for life, are difficult and expensive to predict. This study shows that AI-based structure prediction methods can be modified for rapidly predicting the conformational landscapes of proteins, with strong correlations with experimentally-measured relative state populations. [ABSTRACT FROM AUTHOR]

Many surveys ask participants to retrospectively record their location of birth. This paper examines the accuracy of such data in the UK Biobank using a sample of full siblings. Comparison of reported birth locations for siblings with different age gaps allows us to estimate the probabilities of household moves and of misreported birth locations. Our first contribution is to show that there are inaccuracies in retrospective birth location data, showing a sizeable probability of misreporting, with 28% of birth coordinates, 16% of local districts and 6% of counties of birth being incorrectly reported. Our second contribution is to show that such error can lead to substantial attenuation bias when investigating the impacts of location-based exposures, especially when there is little spatial correlation and limited time variation in the exposure variable. Sibling fixed effect models are shown to be particularly vulnerable to the attenuation bias. Our third contribution is to highlight possible solutions to the attenuation bias and sensitivity analyses to the reporting error. Many surveys ask participants to retrospectively record their location of birth. Here, the authors find misreporting in retrospective birth location data in UK Biobank using data from siblings, which can lead to bias in estimates of the impact of location-based exposures. [ABSTRACT FROM AUTHOR]

Restoring tree cover changes albedo, which is the fraction of sunlight reflected from the Earth's surface. In most locations, these changes in albedo offset or even negate the carbon removal benefits with the latter leading to global warming. Previous efforts to quantify the global climate mitigation benefit of restoring tree cover have not accounted robustly for albedo given a lack of spatially explicit data. Here we produce maps that show that carbon-only estimates may be up to 81% too high. While dryland and boreal settings have especially severe albedo offsets, it is possible to find places that provide net-positive climate mitigation benefits in all biomes. We further find that on-the-ground projects are concentrated in these more climate-positive locations, but that the majority still face at least a 20% albedo offset. Thus, strategically deploying restoration of tree cover for maximum climate benefit requires accounting for albedo change and we provide the tools to do so. Restoring tree cover is a prominent climate solution but can cause global warming due to changes in albedo. This paper maps albedo and carbon changes from restoring tree cover to highlight where the greatest net climate benefits can be achieved. [ABSTRACT FROM AUTHOR]

The rise of antibiotic resistance is a critical public health concern, requiring an understanding of mechanisms that enable bacteria to tolerate antimicrobial agents. Bacteria use diverse strategies, including the amplification of drugresistance genes. In this paper, we showed that multicopy plasmids, often carrying antibiotic resistance genes in clinical bacteria, can rapidly amplify genes, leading to plasmid-mediated phenotypic noise and transient antibiotic resistance. By combining stochastic simulations of a computational model with high-throughput single-cell measurements of blaTEM-1 expression in Escherichia coli MG1655, we showed that plasmid copy number variability stably maintains populations composed of cells with both low and high plasmid copy numbers. This diversity in plasmid copy number enhances the probability of bacterial survival in the presence of antibiotics, while also rapidly reducing the burden of carrying multiple plasmids in drug-free environments. Our results further support the tenet that multicopy plasmids not only act as vehicles for the horizontal transfer of genetic information between cells but also as drivers of bacterial adaptation, enabling rapid modulation of gene copy numbers. Understanding the role of multicopy plasmids in antibiotic resistance is critical, and our study provides insights into how bacteria can transiently survive lethal concentrations of antibiotics. [ABSTRACT FROM AUTHOR]

Identifying sex differences in outcomes and toxicity between males and females in oncology clinical trials is important and has also been mandated by National Institutes of Health policies. Here we analyze the Trialtrove database, finding that, strikingly, only 472/89,221 oncology clinical trials (0.5%) had curated post-treatment sex comparisons. Among 288 trials with comparisons of survival, outcome, or response, 16% report males having statistically significant better survival outcome or response, while 42% reported significantly better survival outcome or response for females. The strongest differences are in trials of EGFR inhibitors in lung cancer and rituximab in non-Hodgkin's lymphoma (both favoring females). Among 44 trials with side effect comparisons, more trials report significantly lesser side effects in males (N = 22) than in females (N = 13). Thus, while statistical comparisons between sexes in oncology trials are rarely reported, important differences in outcome and toxicity exist. These considerable outcome and toxicity differences highlight the need for reporting sex differences more thoroughly going forward. The role of sex differences in response to cancer therapy remains unclear but this could be improved by reporting sex comparisons of outcomes in clinical trials. Here, the authors characterise the sex outcome comparisons in 89,221 interventional trials, finding that while comparisons were rare, important insights could be obtained. [ABSTRACT FROM AUTHOR]

Inertial Measurement Unit-based methods have great potential in capturing motion in large-scale and complex environments with many people. Sparse Inertial Measurement Unit-based methods have more research value due to their simplicity and flexibility. However, improving the computational efficiency and reducing latency in such methods are challenging. In this paper, we propose Fast Inertial Poser, which is a full body motion estimation deep neural network based on 6 inertial measurement units considering body parameters. We design a network architecture based on recurrent neural networks according to the kinematics tree. This method introduces human body shape information by the causality of observations and eliminates the dependence on future frames. During the estimation of joint positions, the upper body and lower body are estimated using separate network modules independently. Then the joint rotation is obtained through a well-designed single-frame kinematics inverse solver. Experiments show that the method can greatly improve the inference speed and reduce the latency while ensuring the reconstruction accuracy compared with previous methods. Fast Inertial Poser runs at 65 fps with 15 ms latency on an embedded computer, demonstrating the efficiency of the model.Inertial Measurement Units-based motion capture effective application in large scale and complex environments depends on improved efficiency and reduced latency. Here, authors propose a full body motion estimation deep neural network based on 6 IMUs, which runs at 65 fps with 15 ms latency on an embedded computer. [ABSTRACT FROM AUTHOR]

Ion trapping has been found to be responsible for the performance degradation in electrochromic oxide thin films, and a detrapping procedure was proved to be effective to rejuvenate the degraded films. Despite of the studies on ion trapping and detrapping, its dynamics remain largely unknown. Moreover, coloration mechanisms of electrochromic oxides are also far from clear, limiting the development of superior devices. Here, we visualize ion trapping and detrapping dynamics in a model electrochromic material, amorphous WO3. Specifically, formation of orthorhombic Li2WO4 during long-term cycling accounts for the origin of shallow traps. Deep traps are multiple-step-determined, composed of mixed W4+-Li2WO4, amorphous Li2WO4 and W4+-Li2O. The non-decomposable W4+-Li2WO4 couple is the origin of the irreversible traps. Furthermore, we demonstrate that, besides the typical small polaron hopping between W5+ ↔ W6+ sites, bipolaron hopping between W4+ ↔ W6+ sites gives rise to optical absorption in the short-wavelength region. Overall, we provide a general picture of electrochromism based on polaron hopping. Ion trapping and detrapping were demonstrated to also prevail in other cathodic electrochromic oxides. This work not only provides the ion trapping and detrapping dynamics of WO3, but also open avenues to study other cathodic electrochromic oxides and develop superior electrochromic devices with great durability. Ion trapping has been found to be responsible for the performance degradation in electrochromic oxide thin films. This paper visualizes ion trapping and detrapping dynamics, and provides a general picture of electrochromism in amorphous WO3. [ABSTRACT FROM AUTHOR]

In May 2022, individuals infected with the monkeypox virus were detected in the UK without clear travel links to endemic areas. Understanding the clinical characteristics and infection severity of mpox is necessary for effective public health policy. The study period of this paper, from the 1st June 2022 to 30th September 2022, included 3,375 individuals that tested positive for the monkeypox virus. The posterior mean times from infection to hospital admission and length of hospital stay were 14.89 days (95% Credible Intervals (CrI): 13.60, 16.32) and 7.07 days (95% CrI: 6.07, 8.23), respectively. We estimated the modelled Infection Hospitalisation Risk to be 4.13% (95% CrI: 3.04, 5.02), compared to the overall sample Case Hospitalisation Risk (CHR) of 5.10% (95% CrI: 4.38, 5.86). The overall sample CHR was estimated to be 17.86% (95% CrI: 6.06, 33.11) for females and 4.99% (95% CrI: 4.27, 5.75) for males. A notable difference was observed between the CHRs that were estimated for each sex, which may be indicative of increased infection severity in females or a considerably lower infection ascertainment rate. It was estimated that 74.65% (95% CrI: 55.78, 86.85) of infections with the monkeypox virus in the UK were captured over the outbreak.Mpox cases without known travel links to endemic countries began to be detected in the UK in mid-2022. In this study, the authors characterise the severity of mpox cases in the UK and estimate the overall infection hospitalisation risk at ~4%. [ABSTRACT FROM AUTHOR]

Although ImmuneCells.Sig was not developed in the validation datasets, the reported predictive error on each validation dataset in the original paper is actually the training error from classification models trained on the same dataset. Based on this finding, they further identified a gene expression signature named ImmuneCells.Sig from the scRNA-seq datasets and a bulk gene expression dataset GSE78220[2] for the purpose of predicting response to immunotherapy. Comparisons with AUC values of 12 previously reported ICT response signatures show that ImmuneCells.Sig predicts the ICT outcomes of melanoma patients more accurately across the above four gene expression datasets of melanoma. Testing with random gene sets shows the effect of overfitting The ImmuneCells.Sig signature was discovered from the scRNA-seq datasets[9] and a bulk gene expression dataset GSE78220[2]. [Extracted from the article]

Locomotor activities can enhance learning, but the underlying circuit and synaptic mechanisms are largely unknown. Here we show that locomotion facilitates aversive olfactory learning in C. elegans by activating mechanoreceptors in motor neurons, and transmitting the proprioceptive information thus generated to locomotion interneurons through antidromic-rectifying gap junctions. The proprioceptive information serves to regulate experience-dependent activities and functional coupling of interneurons that process olfactory sensory information to produce the learning behavior. Genetic destruction of either the mechanoreceptors in motor neurons, the rectifying gap junctions between the motor neurons and locomotion interneurons, or specific inhibitory synapses among the interneurons impairs the aversive olfactory learning. We have thus uncovered an unexpected role of proprioception in a specific learning behavior as well as the circuit, synaptic, and gene bases for this function. Locomotion affects learning with unknown neural mechanisms. Here, authors show that locomotion enhances olfactory learning in C. elegans by transmitting proprioceptive information from mechanosensitive motor neurons to higher-order interneurons. [ABSTRACT FROM AUTHOR]

One well established HIF functional target from mammalian studies is pyruvate dehydrogenase kinase (PDK1), as upregulation of PDK1 by HIF reduces flux through the tricarboxylic acid cycle (TCA) and promotes anaerobic ATP generation by glycolysis[3]. B replying to b R. Comas-Ghierra et al. I Nature Communications i https://doi.org/10.1038/s41467-023-39510-5 (2023) In a recent paper, we showed that the hypoxia response (HR) pathway promotes gluconeogenesis in I Caenorhabditis elegans i through upregulation of PCK-1, a phosphoenolpyruvate carboxykinase (PEPCK)[1]. In summary, we agree with Comas-Ghierra et al. that malate dismutation is an additional important adaptation to hypoxia, but we want to highlight that the specific environmental and developmental context of HIF activation dictates the specific hypoxia response. Malate dehydrogenase, which is also upregulated by HIF-1, converts oxaloacetate into malate, which can enter the mitochondria to be converted to fumarate in the first step of malate dismutation. [Extracted from the article]

Despite persistent efforts in understanding the creativity of scientists over different career stages, little is known about the underlying dynamics of research topic switching that drives innovation. Here, we analyze the publication records of individual scientists, aiming to quantify their topic switching dynamics and its influence. We find that the co-citing network of papers of a scientist exhibits a clear community structure where each major community represents a research topic. Our analysis suggests that scientists have a narrow distribution of number of topics. However, researchers nowadays switch more frequently between topics than those in the early days. We also find that high switching probability in early career is associated with low overall productivity, yet with high overall productivity in latter career. Interestingly, the average citation per paper, however, is in all career stages negatively correlated with the switching probability. We propose a model that can explain the main observed features. How does a scientist's tendency to explore a variety of topics affect their career? Here, the authors analyze scientific publication data to understand how often scientists switch topics, how topic switching has changed over time, and how it relates to research productivity. [ABSTRACT FROM AUTHOR]

A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-21448-1 [ABSTRACT FROM AUTHOR]

This paper explores the behaviour of the ubiquitous twisted pairs at high frequencies and wideband excitation of twisted pairs up to 12 GHz. Higher carrier frequencies on twisted pairs can enable the data rates required by the future communication networks; hence, the existing copper infrastructure can be utilised on the last mile complementing the fibre networks. In this paper, we show a fundamental limit on the operating frequency of twisted pairs beyond which twisted pairs start to radiate and behave like an antenna. To validate our theoretical derivations through measurements, we designed a microstrip balun to excite the differential mode on the twisted pairs. At the end, we demonstrate that the standard twisted pairs used in the UK can be used up to 5 GHz carrier frequency without any radiation effect and this upper-bound can be moved to higher frequencies by decreasing the twist lengths. This paper establishes a physical limit on the ability of the ubiquitous twisted pairs to support high speed internet. This limit due to radiation from the wire is theoretically explained as well as numerically simulated and experimentally measured. [ABSTRACT FROM AUTHOR]

Chemical bonds, including covalent and ionic bonds, endow semiconductors with stable electronic configurations but also impose constraints on their synthesis and lattice-mismatched heteroepitaxy. Here, the unique multi-scale van der Waals (vdWs) interactions are explored in one-dimensional tellurium (Te) systems to overcome these restrictions, enabled by the vdWs bonds between Te atomic chains and the spontaneous misfit relaxation at quasi-vdWs interfaces. Wafer-scale Te vdWs nanomeshes composed of self-welding Te nanowires are laterally vapor grown on arbitrary surfaces at a low temperature of 100 °C, bringing greater integration freedoms for enhanced device functionality and broad applicability. The prepared Te vdWs nanomeshes can be patterned at the microscale and exhibit high field-effect hole mobility of 145 cm2/Vs, ultrafast photoresponse below 3 μs in paper-based infrared photodetectors, as well as controllable electronic structure in mixed-dimensional heterojunctions. All these device metrics of Te vdWs nanomesh electronics are promising to meet emerging technological demands. The limited scalability of 1D semiconductors has restricted their large-area optoelectronic applications so far. Here, the authors report the low-temperature synthesis of wafer-scale van der Waals nanomeshes composed of self-welding Te nanowires on various substrates, showing improved transport and photoelectric properties. [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via a link at the top of the paper. [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via a link at the top of the paper. [ABSTRACT FROM AUTHOR]

Quantum interference between reaction pathways around a conical intersection (CI) is an ultrasensitive probe of detailed chemical reaction dynamics. Yet, for the hydrogen exchange reaction, the difference between contributions of the two reaction pathways increases substantially as the energy decreases, making the experimental observation of interference features at low energy exceedingly challenging. We report in this paper a combined experimental and theoretical study on the H + HD → H2 + D reaction at the collision energy of 1.72 eV. Although the roaming insertion pathway constitutes only a small fraction (0.088%) of the overall contribution, angular oscillatory patterns arising from the interference of reaction pathways were clearly observed in the backward scattering direction, providing direct evidence of the geometric phase effect at an energy of 0.81 eV below the CI. Furthermore, theoretical analysis reveals that the backward interference patterns are mainly contributed by two distinct groups of partial waves (J ~ 10 and J ~ 19). The well-separated partial waves and the geometric phase collectively influence the quantum reaction dynamics. In a combined experimental and theoretical study of the H + HD → H2 + D reaction at low collision energy (1.72 eV), the authors obtain detailed information on the quantum reaction dynamics surrounding a conical intersection. [ABSTRACT FROM AUTHOR]

Tunable generation of vortex beams holds relevance in various fields, including communications and sensing. In this paper, we demonstrate the feasibility of nonlinear spin-orbit interactions in thin films of materials with second-order nonlinear susceptibility. Remarkably, the nonlinear tensor can mix the longitudinal and transverse components of the pump field. We observe experimentally our theoretical predictions in the process of second-harmonic generation from a thin film of aluminum gallium arsenide, a material platform widely spread for its role in the advancement of active, nonlinear, and quantum photonic devices. In particular, we prove that a nonlinear thin film can be used to produce vector vortex beams of second-harmonic light when excited by circularly-polarized Gaussian beams.Spin-orbit interaction, and the associated phenomena, is commonly observed in crystalline structure pumped with circularly polarised beam. Here, the authors showed that this is not the case, and used nonlinear thin film to produce vortex beams of second-harmonic light. [ABSTRACT FROM AUTHOR]

Multimode fiber (MMF) which supports parallel transmission of spatially distributed information is a promising platform for remote imaging and capacity-enhanced optical communication. However, the variability of the scattering MMF channel poses a challenge for achieving long-term accurate transmission over long distances, of which static optical propagation modeling with calibrated transmission matrix or data-driven learning will inevitably degenerate. In this paper, we present a self-supervised dynamic learning approach that achieves long-term, high-fidelity transmission of arbitrary optical fields through unstabilized MMFs. Multiple networks carrying both long- and short-term memory of the propagation model variations are adaptively updated and ensembled to achieve robust image recovery. We demonstrate >99.9% accuracy in the transmission of 1024 spatial degree-of-freedom over 1 km length MMFs lasting over 1000 seconds. The long-term high-fidelity capability enables compressive encoded transfer of high-resolution video with orders of throughput enhancement, offering insights for artificial intelligence promoted diffusive spatial transmission in practical applications. This work introduces a cutting-edge technique to overcome dynamic scattering challenges in long-distance multimode fiber transmission, achieving >99.9% accuracy for 1024 modes over 1 km, hence promises applications in diverse scattering scenarios. [ABSTRACT FROM AUTHOR]

Capturing fine spatial, spectral, and temporal information of the scene is highly desirable in many applications. However, recording data of such high dimensionality requires significant transmission bandwidth. Current computational imaging methods can partially address this challenge but are still limited in reducing input data throughput. In this paper, we report a video-rate hyperspectral imager based on a single-pixel photodetector which can achieve high-throughput hyperspectral video recording at a low bandwidth. We leverage the insight that 4-dimensional (4D) hyperspectral videos are considerably more compressible than 2D grayscale images. We propose a joint spatial-spectral capturing scheme encoding the scene into highly compressed measurements and obtaining temporal correlation at the same time. Furthermore, we propose a reconstruction method relying on a signal sparsity model in 4D space and a deep learning reconstruction approach greatly accelerating reconstruction. We demonstrate reconstruction of 128 × 128 hyperspectral images with 64 spectral bands at more than 4 frames per second offering a 900× data throughput compared to conventional imaging, which we believe is a first-of-its kind of a single-pixel-based hyperspectral imager. The authors showcase a video-rate hyperspectral imager based on a single-pixel photodetector that can achieve high-throughput hyperspectral video recording at a low bandwidth. Specifically, they propose a joint spatial-spectral encoding scheme which can encode the scene into highly compressed single-pixel measurements and obtain temporal correlation at the same time. [ABSTRACT FROM AUTHOR]

Extracting structured knowledge from scientific text remains a challenging task for machine learning models. Here, we present a simple approach to joint named entity recognition and relation extraction and demonstrate how pretrained large language models (GPT-3, Llama-2) can be fine-tuned to extract useful records of complex scientific knowledge. We test three representative tasks in materials chemistry: linking dopants and host materials, cataloging metal-organic frameworks, and general composition/phase/morphology/application information extraction. Records are extracted from single sentences or entire paragraphs, and the output can be returned as simple English sentences or a more structured format such as a list of JSON objects. This approach represents a simple, accessible, and highly flexible route to obtaining large databases of structured specialized scientific knowledge extracted from research papers. Extracting scientific data from published research is a complex task required specialised tools. Here the authors present a scheme based on large language models to automatise the retrieval of information from text in a flexible and accessible manner. [ABSTRACT FROM AUTHOR]

This paper presents our findings on the recursive band gap engineering of chiral fermions in bilayer graphene doubly aligned with hBN. Using two interfering moiré potentials, we generate a supermoiré pattern that renormalizes the electronic bands of the pristine bilayer graphene, resulting in higher order fractal gaps even at very low energies. These Bragg gaps can be mapped using a unique linear combination of periodic areas within the system. To validate our findings, we use electronic transport measurements to identify the position of these gaps as a function of the carrier density. We establish their agreement with the predicted carrier densities and corresponding quantum numbers obtained using the continuum model. Our study provides strong evidence of the quantization of the momentum-space area of quasi-Brillouin zones in a minimally incommensurate lattice. It fills important gaps in the understanding of band structure engineering of Dirac fermions with a doubly periodic superlattice spinor potential.In moiré superlattices, a multitude of higher order Bragg gaps and van Hove singularities emerges as the band structure renormalizes. Here, the authors map these gaps uniquely to the recently predicted topological Bragg indices of the underlying supermoiré lattice. [ABSTRACT FROM AUTHOR]

Accurate estimation of protein–ligand binding affinity is the cornerstone of computer-aided drug design. We present a universal physics-based scoring function, named SQM2.20, addressing key terms of binding free energy using semiempirical quantum-mechanical computational methods. SQM2.20 incorporates the latest methodological advances while remaining computationally efficient even for systems with thousands of atoms. To validate it rigorously, we have compiled and made available the PL-REX benchmark dataset consisting of high-resolution crystal structures and reliable experimental affinities for ten diverse protein targets. Comparative assessments demonstrate that SQM2.20 outperforms other scoring methods and reaches a level of accuracy similar to much more expensive DFT calculations. In the PL-REX dataset, it achieves excellent correlation with experimental data (average R2 = 0.69) and exhibits consistent performance across all targets. In contrast to DFT, SQM2.20 provides affinity predictions in minutes, making it suitable for practical applications in hit identification or lead optimization. The paper presents the universal QM-based scoring function that accurately and rapidly predicts protein-ligand binding affinities, outperforming current computational tools. This is demonstrated on the PL-REX experimental benchmark dataset. [ABSTRACT FROM AUTHOR]

Domain boundaries have been intensively investigated in bulk ferroelectric materials and two-dimensional materials. Many methods such as electrical, mechanical and optical approaches have been utilized to probe and manipulate domain boundaries. So far most research focuses on the initial and final states of domain boundaries before and after manipulation, while the microscopic understanding of the evolution of domain boundaries remains elusive. In this paper, we report controllable manipulation of the domain boundaries in two-dimensional ferroelectric In2Se3 with atomic precision using scanning tunneling microscopy. We show that the movements of the domain boundaries can be driven by the electric field from a scanning tunneling microscope tip and proceed by the collective shifting of atoms at the domain boundaries. Our density functional theory calculations reveal the energy path and evolution of the domain boundary movement. The results provide deep insight into domain boundaries in two-dimensional ferroelectric materials and will inspire inventive applications of these materials. Here, the authors realize controllable manipulation of polar domain boundaries in a two-dimensional ferroelectric material In2Se3. It reveals the origin of distinct behaviors for different domain boundaries in combination with density functional theory calculations. [ABSTRACT FROM AUTHOR]

During 2022, extreme rainfall occurred across southeast Australia, making it the wettest year on record. The oceanic impact of extreme rainfall events in normally ‘dry’ regions is not well understood, as their effects are challenging to observe. Here, we use unique multi-platform timeseries and spatial data from 36 autonomous ocean glider missions over 13 years, and we define an extreme salinity threshold inshore of the East Australian Current. We show that the freshwater plume extended fivefold further than previously thought. The compound effect of multiple large rainfall events resulted in a newly observed stratification (‘double-stacking’) dynamic, with the stratification being largely controlled by salinity. Extreme salinity events are known to be important for species composition of local fisheries as well as detrimental for coastal water quality. Such events and their impacts may become more common as extreme rainfall events are projected to become more frequent in a changing climate. Hence, comprehensive observing strategies facilitating identification of salinity extremes are essential.In 2022, record rainfall in Australia impacted coastal salinity and circulation. In this paper, the authors used ocean gliders to track extreme low salinity conditions that lasted months and extended over 70 km offshore. [ABSTRACT FROM AUTHOR]

Frogs are an ecologically diverse and phylogenetically ancient group of anuran amphibians that include important vertebrate cell and developmental model systems, notably the genus Xenopus. Here we report a high-quality reference genome sequence for the western clawed frog, Xenopus tropicalis, along with draft chromosome-scale sequences of three distantly related emerging model frog species, Eleutherodactylus coqui, Engystomops pustulosus, and Hymenochirus boettgeri. Frog chromosomes have remained remarkably stable since the Mesozoic Era, with limited Robertsonian (i.e., arm-preserving) translocations and end-to-end fusions found among the smaller chromosomes. Conservation of synteny includes conservation of centromere locations, marked by centromeric tandem repeats associated with Cenp-a binding surrounded by pericentromeric LINE/L1 elements. This work explores the structure of chromosomes across frogs, using a dense meiotic linkage map for X. tropicalis and chromatin conformation capture (Hi-C) data for all species. Abundant satellite repeats occupy the unusually long (~20 megabase) terminal regions of each chromosome that coincide with high rates of recombination. Both embryonic and differentiated cells show reproducible associations of centromeric chromatin and of telomeres, reflecting a Rabl-like configuration. Our comparative analyses reveal 13 conserved ancestral anuran chromosomes from which contemporary frog genomes were constructed. Frogs are an ancient and ecologically diverse group of amphibians that include important model systems. This paper reports genome sequences of multiple frog species, revealing remarkable stability of frog chromosomes and centromeres, along with highly recombinogenic extended subtelomeres. [ABSTRACT FROM AUTHOR]

While federated learning (FL) is promising for efficient collaborative learning without revealing local data, it remains vulnerable to white-box privacy attacks, suffers from high communication overhead, and struggles to adapt to heterogeneous models. Federated distillation (FD) emerges as an alternative paradigm to tackle these challenges, which transfers knowledge among clients instead of model parameters. Nevertheless, challenges arise due to variations in local data distributions and the absence of a well-trained teacher model, which leads to misleading and ambiguous knowledge sharing that significantly degrades model performance. To address these issues, this paper proposes a selective knowledge sharing mechanism for FD, termed Selective-FD, to identify accurate and precise knowledge from local and ensemble predictions, respectively. Empirical studies, backed by theoretical insights, demonstrate that our approach enhances the generalization capabilities of the FD framework and consistently outperforms baseline methods. We anticipate our study to enable a privacy-preserving, communication-efficient, and heterogeneity-adaptive federated training framework. While federated learning is promising for efficient collaborative learning without revealing local data, it remains vulnerable to white-box privacy attacks, suffers from high communication overhead, and struggles to adapt to heterogeneous models. Here, the authors show a federated distillation method to tackle these challenges, which leverages the strengths of knowledge distillation in a federated learning setting. [ABSTRACT FROM AUTHOR]

Researchers in many fields use networks to represent interactions between entities in complex systems. To study the large-scale behavior of complex systems, it is useful to examine mesoscale structures in networks as building blocks that influence such behavior. In this paper, we present an approach to describe low-rank mesoscale structures in networks. We find that many real-world networks possess a small set of latent motifs that effectively approximate most subgraphs at a fixed mesoscale. Such low-rank mesoscale structures allow one to reconstruct networks by approximating subgraphs of a network using combinations of latent motifs. Employing subgraph sampling and nonnegative matrix factorization enables the discovery of these latent motifs. The ability to encode and reconstruct networks using a small set of latent motifs has many applications in network analysis, including network comparison, network denoising, and edge inference. Network structures can be examined at different scales, and subnetworks in the form of motifs can provide insights into global network properties. The authors propose an approach to decompose a network into a set of latent motifs, which can be used for network comparison, network denoising, and edge inference. [ABSTRACT FROM AUTHOR]

Studies of the Venusian mesosphere provide important information about the current state of the entire Venusian atmosphere. This includes information about the dense cloud structure, its vertical thermal profile, temperature fields, and the resulting dynamical and meteorological processes that contribute to a deeper understanding of the climatologically different evolutionary paths of Earth and Venus. However, the last measurements were acquired in 1983 during Venera-15 mission. In this paper, results of mid-infrared spectral measurements of the Venusian atmosphere are presented. Here we show Mercury Radiometer and Thermal Infrared Spectrometer (MERTIS) measurements of the Venusian atmosphere during the second flyby of BepiColombo mission on its way to Mercury. Our Venus measurements provide reliable retrievals of mesospheric temperature profiles and cloud parameters between 60 and 75 km altitude, although MERTIS was only designed to operate in Mercury environment. Our results are in good agreement with the Venera-15 mission findings. This indicates the stability of the Venusian atmosphere on time scales of decades. On its way to Mercury, BepiColombo spacecraft made two flybys of Venus. Here, the authors show spectrally resolved measurements of Venus' atmosphere during BepiColombo's second flyby and reveal that Venusian atmosphere has been stable since 1980s. [ABSTRACT FROM AUTHOR]

Tricomb spectroscopy unveils a new dimension to standard linear and nonlinear spectroscopic analysis, offering the possibility to reveal the almost real-time evolution of complex systems with unprecedented accuracy. Current triple comb configurations are based on the use of mode-locked lasers, which impose constraints on the comb parameters, and require complex electronic synchronization, thus limiting potential applications. In this paper, we present the experimental demonstration of a new type of all-fiber, self-phase-locked, frequency-agile tri-comb light source. It is based on the nonlinear spectral broadening of three electro-optic modulator-based frequency combs in a three-core fiber. The exploitation of spatial multiplexing of light in optical fibers offers new possibilities to generate broadband-frequency combs that are highly coherent with each other. After characterizing the stability of the source and performing several dual-comb test measurements, we revealed the high mutual coherence between the three combs through the demonstration of a 2-D pump-probe four-wave mixing spectroscopy experiment. The authors introduce an agile, all-fiber laser source with three frequency combs. Three EOM combs from a single laser are expanded in a tri-core nonlinear fiber, maintaining high mutual coherence. This system's performance is showcased through a 2D four-wave mixing spectroscopy experiment. [ABSTRACT FROM AUTHOR]

Steranes preserved in sedimentary rocks serve as molecular fossils, which are thought to record the expansion of eukaryote life through the Neoproterozoic Era (~ 1000-541 Ma). Scientists hypothesize that ancient C27 steranes originated from cholesterol, the major sterol produced by living red algae and animals. Similarly, C28 and C29 steranes are thought to be derived from the sterols of prehistoric fungi, green algae, and other microbial eukaryotes. However, recent work on annelid worms–an advanced group of eumetazoan animals–shows that they are also capable of producing C28 and C29 sterols. In this paper, we explore the evolutionary history of the 24-C sterol methyltransferase (smt) gene in animals, which is required to make C28+ sterols. We find evidence that the smt gene was vertically inherited through animals, suggesting early eumetazoans were capable of C28+ sterol synthesis. Our molecular clock of the animal smt gene demonstrates that its diversification coincides with the rise of C28 and C29 steranes in the Neoproterozoic. This study supports the hypothesis that early eumetazoans were capable of making C28+ sterols and that many animal lineages independently abandoned its biosynthesis around the end-Neoproterozoic, coinciding with the rise of abundant eukaryotic prey. Sterane molecular fossils are used to compliment evidence from the fossil record. Here, the authors use a molecular clock to explore the origins of the smt gene, tracing the loss of sterol synthesis to dietary shifts in animals at the end-Neoproterozoic. [ABSTRACT FROM AUTHOR]

Forming a hetero-interface is a materials-design strategy that can access an astronomically large phase space. However, the immense phase space necessitates a high-throughput approach for an optimal interface design. Here we introduce a high-throughput computational framework, InterMatch, for efficiently predicting charge transfer, strain, and superlattice structure of an interface by leveraging the databases of individual bulk materials. Specifically, the algorithm reads in the lattice vectors, density of states, and the stiffness tensors for each material in their isolated form from the Materials Project. From these bulk properties, InterMatch estimates the interfacial properties. We benchmark InterMatch predictions for the charge transfer against experimental measurements and supercell density-functional theory calculations. We then use InterMatch to predict promising interface candidates for doping transition metal dichalcogenide MoSe2. Finally, we explain experimental observation of factor of 10 variation in the supercell periodicity within a few microns in graphene/α-RuCl3 by exploring low energy superlattice structures as a function of twist angle using InterMatch. We anticipate our open-source InterMatch algorithm accelerating and guiding ever-growing interfacial design efforts. Moreover, the interface database resulting from the InterMatch searches presented in this paper can be readily accessed online. Predicting properties at the interface of materials is crucial for advanced materials design. Here, the authors introduce a high-throughput computational framework, InterMatch, for predicting several properties of an interface by using the databases of individual bulk materials. [ABSTRACT FROM AUTHOR]

HP's Multi Jet Fusion is a powder bed fusion 3D printing technology that utilizes a carbon-based radiation absorber in combination with a near infrared (NIR) light source to facilitate the fusion of polymer powder in a layer-by-layer fashion to generate 3D parts. Most available carbon-based and NIR radiation absorbers have an intrinsic dark color, which as a result will only produce black/gray and dark colored parts. However, there are many applications that require variable color, including prosthetics, medical models, and indicators, among others. To create white, bright colored, and translucent parts with MJF, a visibly transparent and colorless radiation absorber is required. In this paper, we designed an activating fusing agent (AFA) that contains a red, strong NIR absorbing dye that turns colorless after harvesting irradiation energy during the MJF 3D printing process and provide a bright colored part when working with other color agents. Most NIR radiation absorbers used in multi jet fusion 3D printing have an intrinsic dark color which prevents printing parts with variable colors. Here, the authors design an activating fusing agent containing a strong NIR absorbing dye that turns colorless after harvesting irradiation energy during the 3D printing process and provide a bright colored part when working with other color agents. [ABSTRACT FROM AUTHOR]

Electroreductive coupling of biomass-derived benzaldehyde offers a sustainable approach to producing value-added hydrobenzoin. The low efficiency of the reaction mainly ascribes to the mismatch of initial formation and subsequent dimerization of ketyl intermediates (Ph-CH = O → Ph-C·-OH → Ph-C(OH)-C(OH)-Ph). This paper describes a strategy to balance the active sites for the generation and dimerization of ketyl intermediates by constructing bimetallic Pd/Cu electrocatalysts with tunable surface coverage of Pd. A Faradaic efficiency of 63.2% and a hydrobenzoin production rate of up to 1.27 mmol mg−1 h−1 (0.43 mmol cm−2 h−1) are achieved at −0.40 V vs. reversible hydrogen electrode. Experimental results and theoretical calculations reveal that Pd promotes the generation of the ketyl intermediate, and Cu enhances their dimerization. Moreover, the balance between these two sites facilitates the coupling of benzaldehyde towards hydrobenzoin. This work offers a rational strategy to design efficient electrocatalysts for complex reactions through the optimization of specified active sites for different reaction steps.Electroreductive coupling of benzaldehyde is mainly hindered by the mismatch between initial formation and subsequent dimerization of the ketyl intermediates. Here the authors report a strategy to balance the active sites for the generation and dimerization of the ketyl intermediates, leading to promoted production rate of hydrobenzoin. [ABSTRACT FROM AUTHOR]

Flapping wings produce lift and thrust in bio-inspired aerial robots, leading to quiet, safe and efficient flight. However, to extend their application scope, these robots must perch and land, a feat widely demonstrated by birds. Despite recent progress, flapping-wing vehicles, or ornithopters, are to this day unable to stop their flight. In this paper, we present a process to autonomously land an ornithopter on a branch. This method describes the joint operation of a pitch-yaw-altitude flapping flight controller, an optical close-range correction system and a bistable claw appendage design that can grasp a branch within 25 milliseconds and re-open. We validate this method with a 700 g robot and demonstrate the first autonomous perching flight of a flapping-wing robot on a branch, a result replicated with a second robot. This work paves the way towards the application of flapping-wing robots for long-range missions, bird observation, manipulation, and outdoor flight. Bird-like, flapping-wing robots can fly safely, quietly and with high agility. The authors propose a method to extend flapping-wing robots capability with autonomous perching, and is demonstrated with a 700 g robot flying and perching onto a branch. [ABSTRACT FROM AUTHOR]

Long-duration energy storage (LDES) is a key resource in enabling zero-emissions electricity grids but its role within different types of grids is not well understood. Using the Switch capacity expansion model, we model a zero-emissions Western Interconnect with high geographical resolution to understand the value of LDES under 39 scenarios with different generation mixes, transmission expansion, storage costs, and storage mandates. We find that a) LDES is particularly valuable in majority wind-powered regions and regions with diminishing hydropower generation, b) seasonal operation of storage becomes cost-effective if storage capital costs fall below US$5 kWh−1, and c) mandating the installation of enough LDES to enable year-long storage cycles would reduce electricity prices during times of high demand by over 70%. Given the asset and resource diversity of the Western Interconnect, our results can provide grid planners in many regions with guidance on how LDES impacts and is impacted by energy storage mandates, investments in LDES research and development, and generation mix and transmission expansion decisions. This study models a zero-emissions Western North American grid to provide guidelines and understand the value of long-duration storage as a function of different generation mixes, transmission expansion decisions, storage costs, and storage mandates. [ABSTRACT FROM AUTHOR]

The Challenger Deep (CD) is the deepest known hadal trench in the world. Due to challenges in data sampling at extreme ocean depths, the Lower Circumpolar Deep Water (LCDW) transport and ocean circulation structure in the CD remain unclear. By analyzing data from an extra-deep current meter mooring array, here we find a three-layer circulation in the CD, transitioning downward from westward LCDW flow (about −1.866 ± 2.953 Sv, 1 Sv = 106 m3/s) to cyclonic circulation, and then to anticyclonic circulation. The westward flow reverses its direction during summer, giving evidence for bidirectional connectivity of deep-sea basins, while the cyclonic-anticyclonic circulation is relatively steady. The LCDW intrusion, local topography and turbulent mixing are crucial for modulating the three-layer circulation. Turbulent mixing plays a key role in driving the anticyclonic circulation. Our findings provide insights for understanding the hydrodynamic environment in the ocean's deepest areas. The study presents data from moorings in the Challenger Deep, the deepest known hadal trench in the world, showing a three-layer circulation structure, modulated by deep-water intrusion, topography and turbulent mixing. [ABSTRACT FROM AUTHOR]

This document is a reply to a study on twinning in humans. The authors analyzed a large dataset of birth records from Northern and Central Europe to understand the relationship between twinning and fertility. They found a negative relationship between the probability of a mother having multiple offspring per birth and her total number of births, challenging the idea that mothers who are more fertile are more likely to have twins. The authors argue that the differences between their study and the previous study are due to the demographic transition and that both studies support the conclusion that the heterogeneity/maternal capacity hypothesis is not supported. They caution against removing specific births from the data and encourage further exploration of complex scenarios using their statistical framework. [Extracted from the article]

This document is a reply to a previous article by Brandani et al. regarding diffusion anomalies in nanopores. The authors of this reply provide a comprehensive response to the points raised by Brandani et al. They discuss the limitations of the dual-resistance model (DRM) in decoupling surface barriers and intracrystalline diffusion based on theoretical analysis. The authors also present their own experimental data and calculations to support their findings. They acknowledge the challenges in comparing experimental results with molecular dynamics simulations and express gratitude for the funding and support received for their work. [Extracted from the article]

The publication of a paper on mentorship, now retracted, led us to reflect on our editorial processes and strengthened our determination in supporting diversity, equity and inclusion in research. [ABSTRACT FROM AUTHOR]

Abstract Advanced design strategies are essential to realize the full potential of engineered living materials, including their biodegradability, manufacturability, sustainability, and ability to tailor functional properties. Toward these goals, we present mechanically engineered living material with compostability, healability, and scalability – a material that integrates these features in the form of a stretchable plastic that is simultaneously flushable, compostable, and exhibits the characteristics of paper. This plastic/paper-like material is produced in scalable quantities (0.5–1 g L−1), directly from cultured bacterial biomass (40%) containing engineered curli protein nanofibers. The elongation at break (1–160%) and Young’s modulus (6-450 MPa) is tuned to more than two orders of magnitude. By genetically encoded covalent crosslinking of curli nanofibers, we increase the Young’s modulus by two times. The designed engineered living materials biodegrade completely in 15–75 days, while its mechanical properties are comparable to petrochemical plastics and thus may find use as compostable materials for primary packaging.

We examined the long-term impact of coauthorship with established, highly-cited scientists on the careers of junior researchers in four scientific disciplines. Here, using matched pair analysis, we find that junior researchers who coauthor work with top scientists enjoy a persistent competitive advantage throughout the rest of their careers, compared to peers with similar early career profiles but without top coauthors. Such early coauthorship predicts a higher probability of repeatedly coauthoring work with top-cited scientists, and, ultimately, a higher probability of becoming one. Junior researchers affiliated with less prestigious institutions show the most benefits from coauthorship with a top scientist. As a consequence, we argue that such institutions may hold vast amounts of untapped potential, which may be realised by improving access to top scientists. By examining publication records of scientists from four disciplines, the authors show that coauthoring a paper with a top-cited scientist early in one's career predicts lasting increases in career success, especially for researchers affiliated with less prestigious institutions. [ABSTRACT FROM AUTHOR]