Browse Articles

A tough soft–hard interface in the human knee joint driven by multiscale toughening mechanisms

Joining heterogeneous materials in engineered structures remains a significant challenge due to stress concentration at interfaces, which often leads to unexpected failures. Investigating the complex, multiscale-graded structures found in animal tissue provides valuable insights that can help address this challenge. The human meniscus root–bone interface is an exemplary model, renowned for its exceptional fatigue resistance, toughness, and interfacial adhesion properties throughout its lifespan. Here, we investigated the multiscale graded mineralization structure and their strengthening mechanisms within the 30-micron soft–hard interface at the root–bone junction. This graded interface, featuring interdigitated structures and an exponential increase in modulus, undergoes a phase transition from amorphous calcium phosphate (ACP) to gradually matured hydroxyapatite (HAP) crystals, regulated by location-specific distributed biomolecules. In coordination with collagen fibril deformation and reorientation, the in situ tensile mechanical experiments and molecular dynamic simulations revealed that immature ACP particles debond from the collagenous matrix and translocate to dissipate energy, while the progressively matured HAP crystals with high stiffness pins propagating cracks, thereby enhancing both the toughness and fatigue resistance of the interface. To further validate our findings, we built biomimetic soft–hard interfaces with phase-transforming mineralization which exhibited boosted strength, toughness, and interface adhesion. This interface model is generalizable to other material joints and provides a blueprint for developing robust soft–hard composites across various applications.

The disparities and development trajectories of nations in achieving the sustainable development goals

Abstract The Sustainable Development Goals (SDGs) provide a comprehensive framework for societal progress and planetary health. However, it remains unclear whether universal patterns exist in how nations pursue these goals and whether key development areas are being overlooked. Here, we apply the product space methodology, widely used in development economics, to construct an ‘SDG space of nations’. The SDG space models the relative performance and specialization patterns of 166 countries across 96 SDG indicators from 2000 to 2022. Our SDG space reveals a polarized global landscape, characterized by distinct groups of nations, each specializing in specific development indicators. Furthermore, we find that as countries improve their overall SDG scores, they tend to modify their sustainable development trajectories, pursuing different development objectives. Additionally, we identify orphaned SDG indicators — areas where certain country groups remain under-specialized. These patterns, and the SDG space more broadly, provide a high-resolution tool to understand and evaluate the progress and disparities of countries towards achieving the SDGs.

Towards automated recipe genre classification using semi-supervised learning

Sharing cooking recipes is a great way to exchange culinary ideas and provide instructions for food preparation. However, categorizing raw recipes found online into appropriate food genres can be challenging due to a lack of adequate labeled data. In this study, we present a dataset named the “Assorted, Archetypal, and Annotated Two Million Extended (3A2M+) Cooking Recipe Dataset” that contains two million culinary recipes labeled in respective categories with extended named entities extracted from recipe descriptions. This collection of data includes various features such as title, NER, directions, and extended NER, as well as nine different labels representing genres including bakery, drinks, non-veg, vegetables, fast food, cereals, meals, sides, and fusions. The proposed pipeline named 3A2M+ extends the size of the Named Entity Recognition (NER) list to address missing named entities like heat, time or process from the recipe directions using two NER extraction tools. 3A2M+ dataset provides a comprehensive solution to the various challenging recipe-related tasks, including classification, named entity recognition, and recipe generation. Furthermore, we have demonstrated traditional machine learning, deep learning and pre-trained language models to classify the recipes into their corresponding genre and achieved an overall accuracy of 98.6%. Our investigation indicates that the title feature played a more significant role in classifying the genre.

Antiviral Mx proteins have an ancient origin and widespread distribution among eukaryotes

Mx proteins, first identified in mammals, encode potent antiviral activity against a wide range of viruses. Mx proteins arose within the Dynamin superfamily of proteins (DSP), which mediate critical cellular processes, such as endocytosis and mitochondrial, plastid, and peroxisomal dynamics. Despite their crucial role, the evolutionary origins of Mx proteins are poorly understood. Through comprehensive phylogenomic analyses with progressively expanded taxonomic sampling, we demonstrate that Mx proteins predate the interferon signaling system in vertebrates. Our analyses find an ancient monophyletic DSP lineage in eukaryotes that groups vertebrate and invertebrate Mx proteins with fungal MxF proteins, the largely uncharacterized plant and algal Dynamin 4A/4C proteins, and representatives from several other eukaryotic lineages, suggesting that Mx-like proteins date back close to the origin of Eukarya. Our phylogenetic analyses also find host-encoded and nucleocytoplasmic large DNA viruses-encoded DSPs interspersed in four distinct DSP lineages, indicating recurrent viral theft of host DSPs. Our analyses thus reveal an ancient history of viral and antiviral functions encoded by the Dynamin superfamily in eukaryotes.

Structure and function of a near fully-activated intermediate GPCR-Gαβγ complex

Abstract Unraveling the signaling roles of intermediate complexes is pivotal for G protein-coupled receptor (GPCR) drug development. Despite hundreds of GPCR-Gαβγ structures, these snapshots primarily capture the fully activated complex. Consequently, the functions of intermediate GPCR-G protein complexes remain elusive. Guided by a conformational landscape visualized via 19 F quantitative NMR and molecular dynamics (MD) simulations, we determined the structure of an intermediate GPCR-mini-Gα s βγ complex at 2.6 Å using cryo-EM, by blocking its transition to the fully activated complex. Furthermore, we present direct evidence that the complex at this intermediate state initiates a rate-limited nucleotide exchange before transitioning to the fully activated complex. In this state, BODIPY-GDP/GTP based nucleotide exchange assays further indicated the α-helical domain of the Gα is partially open, allowing it to grasp a nucleotide at a non-canonical binding site, distinct from the canonical nucleotide-binding site. These advances bridge a significant gap in our understanding of the complexity of GPCR signaling.

Prevalence of depression, anxiety, stress, and suicide tendency among individual with long-COVID and determinants: A systematic review and meta-analysis

Background While mental health alterations during active COVID-19 infection have been documented, the prevalence of long-term mental health consequences remains unclear. This study aimed to determine the prevalence of mental health symptoms—depression, anxiety, stress, and suicidal tendencies—and to identify their trends and associated risk factors in individuals with long-COVID. Methods We conducted a systematic literature search of databases including PubMed, EMBASE, Scopus, CINAHL, Cochrane Library, Web of Science, and PsycINFO up to August 2024, targeting observational studies published in English. Study quality was assessed using structured standard tools. The primary outcome was the pooled prevalence of depression, anxiety, stress, and suicidal tendencies in individuals with long-COVID. Secondary outcomes included trends in these mental health problems over time and identification of associated determinants. Results A total of 94 eligible studies were included in the analysis. The pooled prevalence estimates, regardless of follow up times duration, were as follows: depression, 25% (95%CI:22–28%; PI:1–59%); anxiety (adjusted via trim and fill method), 23%(95%CI:21–25%;PI:2–35%); composite outcomes of depression and/or anxiety, 25% (95%CI:23–27%;PI:2–51%); stress, 26%(95%CI:13–39%;PI:1–69%); and suicidality, 19%(95%CI:15–22%;PI:13–25%). The results of meta-regression analyses revealed a statistically significant trend showing a gradual decrease in the prevalence of the composite outcome of anxiety and/or depression over time (RD = -0.004,P = 0.022). Meta-regression results indicated that being female and younger age were significantly associated with a higher prevalence of mental health symptoms. Study design and study setting did not contribute to heterogeneity. Conclusion One-fourth of individual with long-COVID experience mental health symptoms, including depression, anxiety, and stress, which remain prevalent even two years post-infection despite a slight decreasing trend. Factors such as female gender and younger age were linked to higher rates of anxiety and depression. These findings indicate the need for ongoing mental health screening and early interventions to mitigate long-term psychological distress in long-COVID patients.

Structure-guided engineering of a mutation-tolerant inhibitor peptide against variable SARS-CoV-2 spikes

Pathogen mutations present an inevitable and challenging problem for therapeutics and the development of mutation-tolerant anti-infective drugs to strengthen global health and combat evolving pathogens is urgently needed. While spike proteins on viral surfaces are attractive targets for preventing viral entry, they mutate frequently, making it difficult to develop effective therapeutics. Here, we used a structure-guided strategy to engineer an inhibitor peptide against the SARS-CoV-2 spike, called CeSPIACE, with mutation-tolerant and potent binding ability against all variants to enhance affinity for the invariant architecture of the receptor-binding domain (RBD). High-resolution structures of the peptide complexed with mutant RBDs revealed a mechanism of mutation-tolerant inhibition. CeSPIACE bound major mutant RBDs with picomolar affinity and inhibited infection by SARS-CoV-2 variants in VeroE6/TMPRSS2 cells (IC 50 4 pM to 13 nM) and demonstrated potent in vivo efficacy by inhalation administration in hamsters. Mutagenesis analyses to address mutation risks confirmed tolerance against existing and/or potential future mutations of the RBD. Our strategy of engineering mutation-tolerant inhibitors may be applicable to other infectious diseases.

Half of land use carbon emissions in Southeast Asia can be mitigated through peat swamp forest and mangrove conservation and restoration

Experience modulates gaze behavior and the effectiveness of information pickup to overcome the inversion effect in biological motion perception

The inversion effect in biological motion suggests that presenting a point-light display (PLD) in an inverted orientation impairs the observer’s ability to perceive the movement, likely due to the observer’s unfamiliarity with the dynamic characteristics of inverted motion. Vertical dancers (VDs), accustomed to performing and perceiving others to perform dance movements in an inverted orientation while being suspended in the air, offer a unique perspective on this phenomenon. A previous study showed that VDs were more sensitive to the artificial inversion of PLDs depicting dance movements when compared to typical and non-dancers if given sufficient dynamic information. The current study compared the gaze behaviors of non-dancers, typical dancers, and VDs when observing PLDs of upright and inverted dance movements (either on the ground or in the air) to determine if the PLDs were artificially inverted. Behavioral results replicated the previous study, showing that VDs were more sensitive in detecting inverted movements. Eye-tracking data revealed that VDs had longer fixations, primarily directed at the depicted dancer’s pelvic area. When performing movements in the air, the depicted dancer was suspended via a harness around their pelvis, providing unique dynamic information that specified the movement’s canonical orientation. In contrast, although typical dancers also attended to the pelvic area, their lack of experience with perceiving and performing vertical dance movements limited their ability to interpret the dynamic information effectively. These findings highlight the role of specialized visuomotor experience in enhancing biological motion perception and have implications for training techniques that leverage visual strategies to improve performance in complex or unfamiliar movement contexts.

Life sets off a cascade of machines

Life is invasive, occupying all physically accessible scales, stretching between almost nothing (protons, electrons, and photons) and almost everything (the whole biosphere). Motivated by seventeenth-century insights into this infinity, this paper proposes a language to discuss life as an infinite double cascade of machines making machines. Using this simplified language, we first discuss the micro-cascade proposed by Leibniz, which describes how the self-reproducing machine of the cell is built of smaller submachines down to the atomic scale. In the other direction, we propose that a macro-cascade builds from cells larger, organizational machines, up to the scale of the biosphere. The two cascades meet at the critical point of 10 3 s in time and 1 micron in length, the scales of a microbial cell. We speculate on how this double cascade evolved once a self-replicating machine emerged in the salty water of prebiotic earth.

Water-mediated ion transport in an anion exchange membrane

Abstract Water is a critical component in polyelectrolyte anion exchange membranes (AEMs). It plays a central role in ion transport in electrochemical systems. Gaining a better understanding of molecular transport and conductivity in AEMs has been challenged by the lack of a general methodology capable of capturing and connecting water dynamics, water structure, and ionic transport over time and length scales ranging from those associated with individual bond vibrations and molecular reorientations to those pertaining to macroscopic AEM performance. In this work, we use two-dimensional infrared spectroscopy and semiclassical simulations to examine how water molecules are arranged into successive solvation shells, and we explain how that structure influences the dynamics of bromide ion transport processes in polynorbornene-based materials. We find that the transition to the faster transport mechanism occurs when the reorientation of water molecules in the second solvation shell is fast, allowing a robust hydrogen bond network to form. Our findings provide molecular-level insights into AEMs with inherent transport of halide ions, and help pave the way towards a comprehensive understanding of hydroxide ion transport in AEMs.

Does opting in or out affect the take up of incentives in a long running population-based cohort study: A nested randomised trial in ALSPAC

Background Financial incentives may be important for improving response rates to data collection activities and for retaining participants in longitudinal studies. However, for large studies, this introduces significant additional costs. We sought to determine whether an opt-in or an opt-out option for receiving financial incentives when completing questionnaires offers any cost saving measures. Methods The Avon Longitudinal Study of Parents and Children has been ongoing for more than 30 years. It has offered a £10 incentive for returning a partly or fully completed annual questionnaire for >10 years, this is provided by default unless a participant chooses to opt out. For questionnaires completed in 2020 by the original parents recruited to the study and by their offspring, we randomised eligible participants to either opt-out or to opt-in to receiving their vouchers. Logistic regressions determined whether opt-out or opt-in made any difference to the proportion of respondents receiving their vouchers. Results Respondents are less likely to choose to receive a thank you for their time in the form of a £10 shopping voucher if they are asked to opt in compared to if they are asked to opt out. The odds ratio, adjusted for baseline characteristics was 3.94 (95% Confidence Interval: 3.49, 4.45). There was no difference in response rates according to whether respondents were randomised to the opt-in or opt-out group. Conclusions ALSPAC now employs an opt-in procedure for respondents receiving their financial incentive when completing a questionnaire. We recommend similar studies that rely on volunteers consider this option if they want to introduce some cost savings without harming overall response rates.

Lipid-induced condensate formation from the Alzheimer’s Aβ peptide triggers amyloid aggregation

The onset and development of Alzheimer’s disease is linked to the accumulation of pathological aggregates formed from the normally monomeric amyloid-β peptide within the central nervous system. These Aβ aggregates are increasingly successfully targeted with clinical therapies at later stages of the disease, but the fundamental molecular steps in early stage disease that trigger the initial nucleation event leading to the conversion of monomeric Aβ peptide into pathological aggregates remain unknown. Here, we show that the Aβ peptide can form biomolecular condensates on lipid bilayers both in molecular assays and in living cells. Our results reveal that these Aβ condensates can significantly accelerate the primary nucleation step in the amyloid conversion cascade that leads to the formation of amyloid aggregates. We show that Aβ condensates contain phospholipids, are intrinsically heterogeneous, and are prone to undergo a liquid-to-solid transition leading to the formation of amyloid fibrils. These findings uncover the liquid–liquid phase separation behavior of the Aβ peptide and reveal a molecular step very early in the amyloid-β aggregation process.

Assembly of Genetically Engineered Ionizable Protein Nanocage-based Nanozymes for Intracellular Superoxide Scavenging

Obstacles to emergency medical consultation in cases of conflict-related sexual violence

Background Despite the availability of a well-developed holistic care model for victims of conflict-related sexual violence, little is known about the factors that determine late presentation for care post-sexual violence care. Drawing from data from the Democratic Republic of the Congo, this study aimed to determine obstacles to accessing emergency medical care within 72-hours of sexual violence (SV). Methods We retrospectively analyzed data from 4048 victims of SV treated at Panzi Hospital (PH) in Bukavu city between 2015 and 2018. The factors of access to care within 72h were analyzed using logistic regression. Results 88% of the victims consulted after 72h post sexual violence. Several sociodemographic factors were found to limit access to the medical care post-sexual violence including the victim’s age (p = 0,022), place of residence (p = 0,000) and education level (p = 0,039). Clinical discomfort from pain during urination (p = 0,002) and fear of pregnancy (p = 0,000) were also associated with late assessment of care. Conclusion Seeking medical care within 72 hours after sexual violence within the critical 72-hours timeframe is crucial to avoid several medical complications stemming from SV. Improvement will be achieved by integrating the post-exposure prophylaxis protocol into primary health care, as well as by increasing community awareness of the relevance of timely consultation after sexual abuse.

Co-option of mitochondrial nucleic acid–sensing pathways by HSV-1 UL12.5 for reactivation from latent infection

Although viruses subvert innate immune pathways for their replication, there is evidence they can also co-opt antiviral responses for their benefit. The ubiquitous human pathogen, Herpes simplex virus-1 (HSV-1), encodes a protein (UL12.5) that induces the release of mitochondrial nucleic acid into the cytosol, which activates immune-sensing pathways and reduces productive replication in nonneuronal cells. HSV-1 establishes latency in neurons and can reactivate to cause disease. We found that UL12.5 is required for HSV-1 reactivation in neurons and acts to directly promote viral lytic gene expression during initial exit from latency. Further, the direct activation of innate immune-sensing pathways triggered HSV-1 reactivation and compensated for a lack of UL12.5. Finally, we found that the induction of HSV-1 lytic genes during reactivation required intact RNA- and DNA-sensing pathways, demonstrating that HSV-1 can respond to and active antiviral nucleic acid–sensing pathways to reactivate from a latent infection.

Enantioselective reductive cross-couplings to forge C(sp2)–C(sp3) bonds by merging electrochemistry with nickel catalysis

Abstract Motivated by the inherent benefits of synergistically combining electrochemical methodologies with nickel catalysis, we present here a Ni-catalyzed enantioselective electroreductive cross-coupling of benzyl chlorides with aryl halides, yielding chiral 1,1-diaryl compounds with good to excellent enantioselectivity. This catalytic reaction can not only be applied to aryl chlorides/bromides, which are challenging to access by other means, but also to benzyl chlorides containing silicon groups. Additionally, the absence of a sacrificial anode lays a foundation for scalability. The combination of cyclic voltammetry analysis with electrode potential studies suggests that NiI species activate aryl halides via oxidative addition and alkyl chlorides via single electron transfer.

Numerical analysis of sodium diffusion in aluminum electrolysis cathode carbon blocks based on a microstructure multi-factor corrected model

Current researches on sodium penetration in electrolytic aluminum cathode carbon blocks primarily measure cathode expansion curves, showing mostly macroscopic characteristics. However, the microscopic structure is often underexplored. As a porous medium, the diffusion performance of cathode carbon blocks is closely tied to their internal pore structure. Viewing the cathode carbon block as a multiphase composite material, this study examines the sodium diffusion process from a microstructural perspective. A prediction model for sodium diffusion, considering factors like porosity, temperature, binding effects, current density, and molecular ratio, was developed. A random aggregate model was implemented in Python and imported into finite element software to simulate sodium diffusion using Fick’s second law. Results indicate that increased porosity, higher temperatures, reduced binding effects, increased current density, and higher molecular ratios enhance sodium infiltration, reducing diffusion resistance and increasing the diffusion coefficient. The simulation aligns well with experimental results, confirming its accuracy and reliability.

Assessing the influence of the modifiable areal unit problem on Bayesian disease mapping in Queensland, Australia

Background Spatial data are often aggregated by area to protect the confidentiality of individuals and aid the calculation of pertinent risks and rates. However, the analysis of spatially aggregated data is susceptible to the modifiable areal unit problem (MAUP), which arises when inference varies with boundary or aggregation changes. While the impact of the MAUP has been examined previously, typically these studies have focused on well-populated areas. Understanding how the MAUP behaves when data are sparse is particularly important for countries with less populated areas, such as Australia. This study aims to assess different geographical regions’ vulnerability to the MAUP when data are relatively sparse to inform researchers’ choice of aggregation level for fitting spatial models. Methods To understand the impact of the MAUP in Queensland, Australia, the present study investigates inference from simulated lung cancer incidence data using the five levels of spatial aggregation defined by the Australian Statistical Geography Standard. To this end, Bayesian spatial BYM models with and without covariates were fitted. Results and conclusion The MAUP impacted inference in the analysis of cancer counts for data aggregated to coarsest areal structures. However, area structures with moderate resolution were not greatly impacted by the MAUP, and offer advantages in terms of data sparsity, computational intensity and availability of data sets.

Life history is a key driver of temporal fluctuations in tropical tree abundances

The question of what mechanisms maintain tropical biodiversity is a critical frontier in ecology, intensified by the heightened risk of biodiversity loss faced in tropical regions. Ecological theory has shed light on multiple mechanisms that could lead to the high levels of biodiversity in tropical forests. But variation in species abundances over time may be just as important as overall biodiversity, with a more immediate connection to the risk of extirpation and biodiversity loss. Despite the urgency, our understanding of the primary mechanisms driving fluctuations in species abundances has not been clearly established. Here, we introduce a theoretical framework based around life history; the schedule of birth, growth, and mortality over a lifespan, and its systematic variation across species. We develop a mean field model to predict expected fluctuations in abundance for a focal species in a larger community, and we quantify empirical life history variation among 90 tropical forest species in a 50 ha plot in Panama. Putting theory and data together, we show that life history provides a critical piece of this puzzle, allowing us to explain patterns of abundance fluctuations more accurately than previous models incorporating demographic stochasticity without life history variation, and without introducing unobserved couplings between species and their environment. This framework provides a starting point for more general models that incorporate multiple factors in addition to life history variation, and suggests the potential for a fine-grained assessment of extirpation risk based on the impacts of anthropogenic change on demographic rates across life stages.