Decoding the complexity of delayed wound healing following Enterococcus faecalis infection

Wound infections are highly prevalent and can lead to delayed or failed healing, causing significant morbidity and adverse economic impacts. These infections occur in various contexts, including diabetic foot ulcers, burns, and surgical sites. Enterococcus faecalis is often found in persistent non-healing wounds, but its contribution to chronic wounds remains understudied. To address this, we employed single-cell RNA sequencing (scRNA-seq) on infected wounds in comparison to uninfected wounds in a mouse model. Examining over 23,000 cells, we created a comprehensive single-cell atlas that captures the cellular and transcriptomic landscape of these wounds. Our analysis revealed unique transcriptional and metabolic alterations in infected wounds, elucidating the distinct molecular changes associated with bacterial infection compared to the normal wound healing process. We identified dysregulated keratinocyte and fibroblast transcriptomes in response to infection, jointly contributing to an anti-inflammatory environment. Notably, E. faecalis infection prompted a premature, incomplete epithelial-mesenchymal transition in keratinocytes. Additionally, E. faecalis infection modulated M2-like macrophage polarization by inhibiting pro-inflammatory resolution in vitro, in vivo, and in our scRNA-seq atlas. Furthermore, we discovered macrophage crosstalk with neutrophils, which regulates chemokine signaling pathways, while promoting anti-inflammatory interactions with endothelial cells. Overall, our findings offer new insights into the immunosuppressive role of E. faecalis in wound infections.

Comparisons between wrinkles and photo-ageing detected and self-reported by the participant or identified by trained assessors reveal insights from Chinese individuals in the Singapore/Malaysia Cross-sectional Genetics Epidemiology Study (SMCGES) cohort

BACKGROUND

Changes develop on the facial skin as a person ages. Other than chronological time, it has been discovered that gender, ethnicity, air pollution, smoking, nutrition, and sun exposure are notable risk factors that influence the development of skin ageing phenotypes such as wrinkles and photo-ageing. These risk factors can be quantified through epidemiological collection methods. We previously studied wrinkles and photo-ageing in detail using photo-numeric scales. The analysis was performed on the ethnic Chinese skin by three trained assessors. Recent studies have shown that it is possible to use self-reported data to identify skin-related changes including skin colour and skin cancer. In order to investigate the association between risk factors and skin ageing phenotypic outcomes in large-scale epidemiological studies, it would be useful to evaluate whether it is also possible for participants to self-report signs of ageing on their skin.

AIM

We have previously identified several validated photo-numeric scales for wrinkling and photo-ageing to use on ethnic Chinese skin. Using these scales, our trained assessors grade wrinkling and photo-ageing with moderately high inter-assessor concordance and agreement. The main objective of this study involves letting participants grade self-reported wrinkling and photo-ageing using these same scales. We aim to compare the concordance and agreement between signs of skin ageing by the participant and signs of ageing identified by our assessors.

METHOD

Three trained assessors studied facial photo-ageing on 1081 ethnic Chinese young adults from the Singapore/Malaysia Cross-sectional Genetics Epidemiology Study (SMCGES) cohort. Self-reported facial photo-ageing data by the same 1081 participants were also collated and the two sets of data are compared.

RESULTS

Here, we found that self-reported signs of photo-ageing are concordant with photo-ageing detected by our assessors. This finding is consistent whether photo-ageing is evaluated through studying wrinkle variations (Spearman's rank correlation (ρ) value: 0.246-0.329) or through studying dyspigmentation patterns (Spearman's rank correlation (ρ) value 0.203-0.278). When studying individual wrinkles, both participants and assessors often detect the presence of the same wrinkle (Spearman's rank correlation (ρ) value 0.249-0.366). A weak-to-fair level of agreement between both participants and assessors (Cohen's kappa (κ) values: 0.041-0.233) persists and is statistically significant after accounting for agreements due to chance. Both the participant and the assessor are largely consistent in evaluating the extent of photo-ageing (area under curve (AUC) values 0.689-0.769) and in discerning between the presence or absence of a given facial wrinkle (area under curve (AUC) values 0.601-0.856).

CONCLUSION

When we analyse the overall appearance of the face, our results show that signs of photo-ageing identified by the participant are concordant with signs of photo-ageing identified by our assessors. When we focused our analysis on specific areas of the face, we found that participants were more likely to identify and self-report the same wrinkles that our assessors have also detected. Here, we found that self-reported signs of skin ageing provide a satisfactory approximation to the signs of skin ageing identified by our assessors. The ability to use self-reported signs of skin ageing should also be evaluated on scales beyond the ones discussed in this study. Currently, there are not as many photo-numeric scales for quantifying dyspigmentation patterns as there are for quantifying wrinkle variations. As Chinese skin is known to become dyspigmented more easily with age, more photo-numeric scales need to be developed and properly validated.

Refined Sea Salt Markers for Coastal Cities Facilitating Quantification of Aerosol Aging and PM2.5 Apportionment

Sea salt (ss) aerosols in PM2.5 are often quantified through source apportionment by applying sodium (Na+) and chloride (Cl-) as the markers, but both markers can be substantially emitted from anthropogenic sources. In this study, we differentiate ss from nonss (nss) portions of Na+ and Cl- to better apportion PM2.5 in a coastal tropical urban environment. Size-resolved ionic profiles accounting for Cl- depletion of aged ss were applied to 162-day measurements during 2012 and 2018-2019. Results show that the nss (likely anthropogenic) portions, on average, account for 50-80% of total Na+ and Cl- in submicron aerosols (PM1). This corresponds to up to 2.5 μg/m3 of ss in submicron aerosols that can be ∼10 times overestimated if one attributes all Na+ and Cl- in PM1 to ss. Employing the newly speciated ss- and nss-portions of Na+ and Cl- to source apportionment of urban PM2.5 via positive matrix factorization uncovers a new source of transported anthropogenic emissions during the southwest monsoon, contributing to 12-15% of PM2.5. This increases anthropogenic PM2.5 by ≥19% and reduces ss-related PM2.5 by >30%. In addition to demonstrating Cl- depletion (aging) in submicron aerosols and quantifying ssNa+, nssNa+, ssCl-, as well as nssCl- therein, the refined PM2.5 apportionment resolves new insights on PM2.5 of anthropogenic origins in urban environments, useful to facilitate policy making.

In Situ Mitochondrial Biomineralization for Drug-Free Cancer Therapy

The common clinical chemotherapy often brings serious side effects to patients, mainly due to the off-target and leakage of toxic drugs. However, this is fatal for some specific clinical tumors, such as brain tumors and neuroma. This study performs a drug-free approach by encapsulating black phosphorus (BP) and calcium peroxide (CaO2) in liposomes with surface-modified triphenylphosphonium (BCLT) to develop mitochondria targeting calcification for cancer therapy without damaging normal cells. BCLT preferentially accumulates inside tumor mitochondria and then is activated by near-infrared (NIR) laser irradiation to produce abundant PO4 3- and Ca2+ to accelerate in situ mitochondrial mineralization, leading to mitochondrial dysfunction and cancer cell death. More importantly, both PO4 3- and Ca2+ are essential components of metabolism in the body, and random gradient diffusion or premature leakage does not cause damage to adjacent normal cells. This achievement promises to be an alternative to conventional chemotherapy in clinical practice for many specific tumor types.

Overcoming Thermal Quenching in X-ray Scintillators through Multi-Excited State Switching

X-ray scintillators have gained significant attention in medical diagnostics and industrial applications. Despite their widespread utility, scintillator development faces a significant hurdle when exposed to elevated temperatures, as it usually results in reduced scintillation efficiency and diminished luminescence output. Here we report a molecular design strategy based on a hybrid perovskite (TpyBiCl5) that overcomes thermal quenching through multi-excited state switching. The structure of perovskite provides a platform to modulate the luminescence centers. The rigid framework constructed by this perovskite structure stabilized its triplet states, resulting in TpyBiCl5 exhibiting an approximately 12 times higher (45 % vs. 3.8 %) photoluminescence quantum yield of room temperature phosphorescence than that of its organic ligand (Tpy). Most importantly, the interactions between the components of this perovskite enable the mixing of different excited states, which has been revealed by experimental and theoretical investigations. The TpyBiCl5 scintillator exhibits a detection limit of 38.92 nGy s-1 at 213 K and a detection limit of 196.31 nGy s-1 at 353 K through scintillation mode switching between thermally activated delayed fluorescence and phosphorescence. This work opens up the possibility of solving the thermal quenching in X-ray scintillators by tuning different excited states.

Expanded Azahelicenes with Large Dissymmetry Factors

Expanded azahelicenes, as heteroanalogues of helically chiral helicenes, hold significant potential for chiroptical materials. Nevertheless, their investigation and research have remained largely unexplored. Herein, we present the facile synthesis of a series of expanded azahelicenes NHn (n=1-5) consisting of 11, 19, 27, 35, and 43 fused rings, mainly by Suzuki coupling followed by Bi(OTf)3-mediated cyclization of vinyl ethers. The structures of NH2, NH3 and NH4 were confirmed through X-ray crystallography analysis, and their (P)- and (M)- enantiomers were also isolated with chiral high performance liquid chromatography. The enantiomers exhibit large absorption (abs) and luminescence (lum) dissymmetry factors, with |gabs|max=0.044; |glum|max=0.003 for NH2, |gabs|max=0.048; |glum|=0.014 for NH3, and |gabs|max=0.043; |glum|max=0.021 for NH4, which are superior to their respective all-carbon analogues.

Completing and Balancing Database Excerpted Chemical Reactions with a Hybrid Mechanistic-Machine Learning Approach

Computer-aided synthesis planning (CASP) development of reaction routes requires an understanding of complete reaction structures. However, most reactions in the current databases are missing reaction coparticipants. Although reaction prediction and atom mapping tools can predict major reaction participants and trace atom rearrangements in reactions, they fail to identify the missing molecules to complete reactions. This is because these approaches are data-driven models trained on the current reaction databases, which comprise incomplete reactions. In this work, a workflow was developed to tackle the reaction completion challenge. This includes a heuristic-based method to identify balanced reactions from reaction databases and complete some imbalanced reactions by adding candidate molecules. A machine learning masked language model (MLM) was trained to learn from simplified molecular input line entry system (SMILES) sentences of these completed reactions. The model predicted missing molecules for the incomplete reactions, a workflow analogous to predicting missing words in sentences. The model is promising for the prediction of small- and middle-sized missing molecules in incomplete reaction records. The workflow combining both the heuristic and machine learning methods completed more than half of the entire reaction space.

Extraordinary Enhancement of Nonlinear Optical Interaction in NbOBr2 Microcavities

2D materials are burgeoning as promising candidates for investigating nonlinear optical effects due to high nonlinear susceptibilities, broadband optical response, and tunable nonlinearity. However, most 2D materials suffer from poor nonlinear conversion efficiencies, resulting from reduced light-matter interactions and lack of phase matching at atomic thicknesses. Herein, a new 2D nonlinear material, niobium oxide dibromide (NbOBr2) is reported, featuring strong and anisotropic optical nonlinearities with scalable nonlinear intensity. Furthermore, Fabry-Pérot (F-P) microcavities are constructed by coupling NbOBr2 with air holes in silicon. Remarkable enhancement factors of ≈630 times in second harmonic generation (SHG) and 210 times in third harmonic generation (THG) are achieved on cavity at the resonance wavelength of 1500 nm. Notably, the cavity enhancement effect exhibits strong anisotropic feature tunable with pump wavelength, owing to the robust optical birefringence of NbOBr2. The ratio of the enhancement factor along the b- and c-axis of NbOBr2 reaches 2.43 and 5.27 for SHG and THG at 1500 nm pump, respectively, which leads to an extraordinarily high SHG anisotropic ratio of 17.82 and a 10° rotation of THG polarization. The research presents a feasible and practical strategy for developing high-efficiency and low-power-pumped on-chip nonlinear optical devices with tunable anisotropy.

Predicting Antibiotic Resistance and Assessing the Risk Burden from Antibiotics: A Holistic Modeling Framework in a Tropical Reservoir

Predicting the hotspots of antimicrobial resistance (AMR) in aquatics is crucial for managing associated risks. We developed an integrated modeling framework toward predicting the spatiotemporal abundance of antibiotics, indicator bacteria, and their corresponding antibiotic-resistant bacteria (ARB), as well as assessing the potential AMR risks to the aquatic ecosystem in a tropical reservoir. Our focus was on two antibiotics, sulfamethoxazole (SMX) and trimethoprim (TMP), and on Escherichia coli (E. coli) and its variant resistant to sulfamethoxazole-trimethoprim (EC_SXT). We validated the predictive model using withheld data, with all Nash-Sutcliffe efficiency (NSE) values above 0.79, absolute relative difference (ARD) less than 25%, and coefficient of determination (R2) greater than 0.800 for the modeled targets. Predictions indicated concentrations of 1-15 ng/L for SMX, 0.5-5 ng/L for TMP, and 0 to 5 (log10 MPN/100 mL) for E. coli and -1.1 to 3.5 (log10 CFU/100 mL) for EC_SXT. Risk assessment suggested that the predicted TMP could pose a higher risk of AMR development than SMX, but SMX could possess a higher ecological risk. The study lays down a hybrid modeling framework for integrating a statistic model with a process-based model to predict AMR in a holistic manner, thus facilitating the development of a better risk management framework.

Genome-wide analysis to uncover how Pocillopora acuta survives the challenging intertidal environment

Characterisation of genomic variation among corals can help uncover variants underlying trait differences and contribute towards genotype prioritisation in coastal restoration projects. For example, there is growing interest in identifying resilient genotypes for transplantation, and to better understand the genetic processes that allow some individuals to survive in specific conditions better than others. The coral species Pocillopora acuta is known to survive in a wide range of habitats, from reefs artificial coastal defences, suggesting its potential use as a starter species for ecological engineering efforts involving coral transplantation onto intertidal seawalls. However, the intertidal section of coastal armour is a challenging environment for corals, with conditions during periods of emersion being particularly stressful. Here, we scanned the entire genome of P. acuta corals to identify the regions harbouring single nucleotide polymorphisms (SNPs) and copy number variations (CNVs) that separate intertidal colonies (n = 18) from those found in subtidal areas (n = 21). Findings revealed 74,391 high quality SNPs distributed across 386 regions of the P. acuta genome. While the majority of the detected SNPs were in non-coding regions, 12% were identified in exons (i.e. coding regions). Functional SNPs that were significantly associated with intertidal colonies were found in overrepresented genomic regions linked to cellular homeostasis, metabolism, and signalling processes, which may represent local environmental adaptation in the intertidal. Interestingly, regions that exhibited CNVs were also associated with metabolic and signalling processes, suggesting P. acuta corals living in the intertidal have a high capacity to perform biological functions critical for survival in extreme environments.

Mitigating the Overheat of Stretchable Electronic Devices Via High-Enthalpy Thermal Dissipation of Hydrogel Encapsulation

The practical application of flexible and stretchable electronics is significantly influenced by their thermal and chemical stability. Elastomer substrates and encapsulation, due to their soft polymer chains and high surface-area-to-volume ratio, are particularly susceptible to high temperatures and flame. Excessive heat poses a severe threat of damage and decomposition to these elastomers. By leveraging water as a high enthalpy dissipating agent, here, a hydrogel encapsulation strategy is proposed to enhance the flame retardancy and thermal stability of stretchable electronics. The hydrogel-based encapsulation provides thermal protection against flames for more than 10 s through the evaporation of water. Further, the stretchability and functions automatically recover by absorbing air moisture. The incorporation of hydrogel encapsulation enables stretchable electronics to maintain their functions and perform complex tasks, such as fire saving in soft robotics and integrated electronics sensing. With high enthalpy heat dissipation, encapsulated soft electronic devices are effectively shielded and retain their full functionality. This strategy offers a universal method for flame retardant encapsulation of stretchable electronic devices.

Modulating the Electronic Structure of Cobalt in Molecular Catalysts via Coordination Environment Regulation for Highly Efficient Heterogeneous Nitrate Reduction

Ammonia (NH3) is pivotal in modern industry and represents a promising next-generation carbon-free energy carrier. Electrocatalytic nitrate reduction reaction (eNO3RR) presents viable solutions for NH3 production and removal of ambient nitrate pollutants. However, the development of eNO3RR is hindered by lacking the efficient electrocatalysts. To address this challenge, we synthesized a series of macrocyclic molecular catalysts for the heterogeneous eNO3RR. These materials possess different coordination environments around metal centers by surrounding subunits. Consequently, electronic structures of the active centers can be altered, enabling tunable activity towards eNO3RR. Our investigation reveals that metal center with an N2(pyrrole)-N2(pyridine) configuration demonstrates superior activity over the others and achieves a high NH3 Faradaic efficiency (FE) of over 90 % within the tested range, where the highest FE of approximately 94 % is obtained. Furthermore, it achieves a production rate of 11.28 mg mgcat -1 h-1, and a turnover frequency of up to 3.28 s-1. Further tests disclose that these molecular catalysts with diverse coordination environments showed different magnetic moments. Theoretical calculation results indicate that variated coordination environments can result in a d-band center variation which eventually affects rate-determining step energy and calculated magnetic moments, thus establishing a correlation between electronic structure, experimental activity, and computational parameters.

Observing Proton-Electron Mixed Conductivity in Graphdiyne

Mixed conducting materials with both ionic and electronic conductivities have gained prominence in emerging applications. However, exploring material with on-demand ionic and electronic conductivities remains challenging, primarily due to the lack of correlating macroscopic conductivity with atom-scale structure. Here, the correlation of proton-electron conductivity and atom-scale structure in graphdiyne is explored. Precisely adjusting the conjugated diynes and oxygenic functional groups in graphdiyne yields a tunable proton-electron conductivity on the order of 103. In addition, a wet-chemistry lithography technique for uniform preparation of graphdiyne on flexible substrates is provided. Utilizing the proton-electron conductivity and mechanical tolerance of graphdiyne, bimodal flexible devices serving as capacitive switches and resistive sensors are created. As a proof-of-concept, a breath-machine interface for sentence-based communication and self-nursing tasks with an accuracy of 98% is designed. This work represents an important step toward understanding the atom-scale structure-conductivity relationship and extending the applications of mixed conducting materials to assistive technology.

Activable Nano-Immunomodulator Assembled from π-Extended Naphthalenediimide for Precision Photothermal Immunotherapy

A nano-immunomodulator (R-NPT NP) comprising a tumor microenvironment (TME) activable resiquimod (R848) and a π-extended NIR-absorbing naphthophenanthrolinetetraone (NPT) has been engineered for spatiotemporal controlled photothermal immunotherapy. R-NPT NP demonstrated excellent photostability, while R848 promoted synergistic immunity as a toll-like receptor 7/8 (TLR7/8) agonist. Upon accumulation at the tumor site, R-NPT NP released R848 in response to redox metabolite glutathione (GSH), triggering dendritic cell (DC) activation. The photothermal effect endowed by R-NPT NP can ablate tumors directly and trigger immunogenic cell death to augment immunity after photoirradiation. The synergistic effect of GSH-liable TLR7/8 agonist and released immunogenic factors leads to a robust evocation of systematic immunity through promoted DC maturation and T cell infiltration. Thus, R-NPT NP with photoirradiation achieved 99.3 % and 98.2 % growth inhibition against primary and distal tumors, respectively.

Engineering cell-free systems by chemoproteomic-assisted phenotypic screening

Phenotypic screening is a valuable tool to both understand and engineer complex biological systems. We demonstrate the functionality of this approach in the development of cell-free protein synthesis (CFPS) technology. Phenotypic screening identified numerous compounds that enhanced protein production in yeast lysate CFPS reactions. Notably, many of these were competitive ATP kinase inhibitors, with the exploitation of their inherent substrate promiscuity redirecting ATP flux towards heterologous protein expression. Chemoproteomic-guided strain engineering partially phenocopied drug effects, with a 30% increase in protein yield observed upon deletion of the ATP-consuming SSA1 component of the HSP70 chaperone. Moreover, drug-mediated metabolic rewiring coupled with template optimization generated the highest protein yields in yeast CFPS to date using a hitherto less efficient, but more cost-effective glucose energy regeneration system. Our approach highlights the utility of target-agnostic phenotypic screening and target identification to deconvolute cell-lysate complexity, adding to the expanding repertoire of strategies for improving CFPS.

Creating 3D Nanoparticle Structural Space via Data Augmentation to Bidirectionally Predict Nanoparticle Mixture's Purity, Size, and Shape from Extinction Spectra

Nanoparticle (NP) characterization is essential because diverse shapes, sizes, and morphologies inevitably occur in as-synthesized NP mixtures, profoundly impacting their properties and applications. Currently, the only technique to concurrently determine these structural parameters is electron microscopy, but it is time-intensive and tedious. Here, we create a three-dimensional (3D) NP structural space to concurrently determine the purity, size, and shape of 1000 sets of as-synthesized Ag nanocubes mixtures containing interfering nanospheres and nanowires from their extinction spectra, attaining low predictive errors at 2.7-7.9 %. We first use plasmonically-driven feature enrichment to extract localized surface plasmon resonance attributes from spectra and establish a lasso regressor (LR) model to predict purity, size, and shape. Leveraging the learned LR, we artificially generate 425,592 augmented extinction spectra to overcome data scarcity and create a comprehensive NP structural space to bidirectionally predict extinction spectra from structural parameters with <4 % error. Our interpretable NP structural space further elucidates the two higher-order combined electric dipole, quadrupole, and magnetic dipole as the critical structural parameter predictors. By incorporating other NP shapes and mixtures' extinction spectra, we anticipate our approach, especially the data augmentation, can create a fully generalizable NP structural space to drive on-demand, autonomous synthesis-characterization platforms.

Genome-wide profiling of piggyBac transposon insertion mutants reveals loss of the F1F0 ATPase complex causes fluconazole resistance in Candida glabrata

Invasive candidiasis caused by non-albicans species has been on the rise, with Candida glabrata emerging as the second most common etiological agent. Candida glabrata possesses an intrinsically lower susceptibility to azoles and an alarming propensity to rapidly develop high-level azole resistance during treatment. In this study, we have developed an efficient piggyBac (PB) transposon-mediated mutagenesis system in C. glabrata to conduct genome-wide genetic screens and applied it to profile genes that contribute to azole resistance. When challenged with the antifungal drug fluconazole, PB insertion into 270 genes led to significant resistance. A large subset of these genes has a role in the mitochondria, including almost all genes encoding the subunits of the F1F0 ATPase complex. We show that deleting ATP3 or ATP22 results in increased azole resistance but does not affect susceptibility to polyenes and echinocandins. The increased azole resistance is due to increased expression of PDR1 that encodes a transcription factor known to promote drug efflux pump expression. Deleting PDR1 in the atp3Δ or atp22Δ mutant resulted in hypersensitivity to fluconazole. Our results shed light on the mechanisms contributing to azole resistance in C. glabrata. This PB transposon-mediated mutagenesis system can significantly facilitate future genome-wide genetic screens.

Ferroics in Hybrid Organic-Inorganic Perovskites: Fundamentals, Design Strategies, and Implementation

Hybrid organic-inorganic perovskites (HOIPs) afford highly versatile structure design and lattice dimensionalities; thus, they are actively researched as material platforms for the tailoring of ferroic behaviors. Unlike single-phase organic or inorganic materials, the interlayer coupling between organic and inorganic components in HOIPs allows the modification of strain and symmetry by chirality transfer or lattice distortion, thereby enabling the coexistence of ferroic orders. This review focuses on the principles for engineering one or multiple ferroic orders in HOIPs, and the conditions for achieving multiferroicity and magnetoelectric properties. The prospects of multilevel ferroic modulation, chiral spin textures, and spin orbitronics in HOIPs are also presented.

Self-Healable and 4D Printable Hydrogel for Stretchable Electronics

Materials with high stretchability and conductivity are used to fabricate stretchable electronics. Self-healing capability and four-dimensional (4D) printability are becoming increasingly important for these materials to facilitate their recovery from damage and endow them with stimuli-response properties. However, it remains challenging to design a single material that combines these four strengths. Here, a dually crosslinked hydrogel is developed by combining a covalently crosslinked acrylic acid (AAC) network and Fe3+ ions through dynamic and reversible ionically crosslinked coordination. The remarkable electrical sensitivity (a gauge factor of 3.93 under a strain of 1500%), superior stretchability (a fracture strain up to 1700%), self-healing ability (a healing efficiency of 88% and 97% for the mechanical and electrical properties, respectively), and 4D printability of the hydrogel are demonstrated by constructing a strain sensor, a two-dimensional touch panel, and shape-morphing structures with water-responsive behavior. The hydrogel demonstrates vast potential for applications in stretchable electronics.

Large language models approach expert-level clinical knowledge and reasoning in ophthalmology: A head-to-head cross-sectional study

Large language models (LLMs) underlie remarkable recent advanced in natural language processing, and they are beginning to be applied in clinical contexts. We aimed to evaluate the clinical potential of state-of-the-art LLMs in ophthalmology using a more robust benchmark than raw examination scores. We trialled GPT-3.5 and GPT-4 on 347 ophthalmology questions before GPT-3.5, GPT-4, PaLM 2, LLaMA, expert ophthalmologists, and doctors in training were trialled on a mock examination of 87 questions. Performance was analysed with respect to question subject and type (first order recall and higher order reasoning). Masked ophthalmologists graded the accuracy, relevance, and overall preference of GPT-3.5 and GPT-4 responses to the same questions. The performance of GPT-4 (69%) was superior to GPT-3.5 (48%), LLaMA (32%), and PaLM 2 (56%). GPT-4 compared favourably with expert ophthalmologists (median 76%, range 64-90%), ophthalmology trainees (median 59%, range 57-63%), and unspecialised junior doctors (median 43%, range 41-44%). Low agreement between LLMs and doctors reflected idiosyncratic differences in knowledge and reasoning with overall consistency across subjects and types (p>0.05). All ophthalmologists preferred GPT-4 responses over GPT-3.5 and rated the accuracy and relevance of GPT-4 as higher (p<0.05). LLMs are approaching expert-level knowledge and reasoning skills in ophthalmology. In view of the comparable or superior performance to trainee-grade ophthalmologists and unspecialised junior doctors, state-of-the-art LLMs such as GPT-4 may provide useful medical advice and assistance where access to expert ophthalmologists is limited. Clinical benchmarks provide useful assays of LLM capabilities in healthcare before clinical trials can be designed and conducted.

Schrödinger's Red Beyond 65,000 Pixel-Per-Inch by Multipolar Interaction in Freeform Meta-Atom through Efficient Neural Optimizer

Freeform nanostructures have the potential to support complex resonances and their interactions, which are crucial for achieving desired spectral responses. However, the design optimization of such structures is nontrivial and computationally intensive. Furthermore, the current "black box" design approaches for freeform nanostructures often neglect the underlying physics. Here, a hybrid data-efficient neural optimizer for resonant nanostructures by combining a reinforcement learning algorithm and Powell's local optimization technique is presented. As a case study, silicon nanostructures with a highly-saturated red color are designed and experimentally demonstrated. Specifically, color coordinates of (0.677, 0.304) in the International Commission on Illumination (CIE) chromaticity diagram - close to the ideal Schrödinger's red, with polarization independence, high reflectance (>85%), and a large viewing angle (i.e., up to ± 25°) is achieved. The remarkable performance is attributed to underlying generalized multipolar interferences within each nanostructure rather than the collective array effects. Based on that, pixel size down to ≈400 nm, corresponding to a printing resolution of 65000 pixels per inch is demonstrated. Moreover, the proposed design model requires only ≈300 iterations to effectively search a thirteen-dimensional (13D) design space - an order of magnitude more efficient than the previously reported approaches. The work significantly extends the free-form optical design toolbox for high-performance flat-optical components and metadevices.

Deshielding Anions Enable Solvation Chemistry Control of LiPF6-Based Electrolyte toward Low-Temperature Lithium-Ion Batteries

Severe capacity decay under subzero temperatures remains a significant challenge for lithium-ion batteries (LIBs) due to the sluggish interfacial kinetics. Current efforts to mitigate this deteriorating interfacial behavior rely on high-solubility lithium salts (e.g., Lithium bis(trifluoromethanesulfonyl)imide (LiTFSI), Lithium bis(fluorosulfonyl)imide (LiFSI))-based electrolytes to construct anion participated solvation structures. However, such electrolytes bring issues of corrosion on the current collector and increased costs. Herein, the most commonly used Lithium hexafluorophosphate (LiPF6) instead, to establish a peculiar solvation structure with a high ratio of ion pairs and aggregates by introducing a deshielding NO3 - additive for low-temperature LIBs is utilized. The deshielding anion significantly reduces the energy barrier for interfacial behavior at low temperatures. Benefiting from this, the graphite (Gr) anode retains a high capacity of ≈72.3% at -20 °C, which is far superior to the 32.3% and 19.4% capacity retention of counterpart electrolytes. Moreover, the LiCoO2/Gr full cell exhibits a stable cycling performance of 100 cycles at -20 °C due to the inhibited lithium plating. This work heralds a new paradigm in LiPF6-based electrolyte design for LIBs operating at subzero temperatures.

Leveraging Text-to-Text Pretrained Language Models for Question Answering in Chemistry

In this study, we present a question answering (QA) system for chemistry, named Marie, with the use of a text-to-text pretrained language model to attain accurate data retrieval. The underlying data store is "The World Avatar" (TWA), a general world model consisting of a knowledge graph that evolves over time. TWA includes information about chemical species such as their chemical and physical properties, applications, and chemical classifications. Building upon our previous work on KGQA for chemistry, this advanced version of Marie leverages a fine-tuned Flan-T5 model to seamlessly translate natural language questions into SPARQL queries with no separate components for entity and relation linking. The developed QA system demonstrates competence in providing accurate results for complex queries that involve many relation hops as well as showcasing the ability to balance correctness and speed for real-world usage. This new approach offers significant advantages over the prior implementation that relied on knowledge graph embedding. Specifically, the updated system boasts high accuracy and great flexibility in accommodating changes and evolution of the data stored in the knowledge graph without necessitating retraining. Our evaluation results underscore the efficacy of the improved system, highlighting its superior accuracy and the ability in answering complex questions compared to its predecessor.

Designing Efficient Single Metal Atom Biocatalysts at the Atomic Structure Level

Various nanomaterials as biocatalysts could be custom-designed and modified to precisely match the specific microenvironment of diseases, showing a promise in achieving effective therapy outcomes. Compared to conventional biocatalysts, single metal atom catalysts (SMACs) with maximized atom utilization through well-defined structures offer enhanced catalytic activity and selectivity. Currently, there is still a gap in a comprehensive overview of the connection between structures and biocatalytic mechanisms of SMACs. Therefore, it is crucial to deeply investigate the role of SMACs in biocatalysis from the atomic structure level and to elucidate their potential mechanisms in biocatalytic processes. In this minireview, we summarize catalysis regulation methods of SMACs at the atomic structure level, focusing on the optimization of catalytic active sites, coordination environment, and active site-support interactions, and briefly discuss biocatalytic mechanisms for biomedical applications.

Origin of Oxygen in Graphene Oxide Revealed by 17O and 18O Isotopic Labeling

Wet-chemical oxidation of graphite in a mixture of sulfuric acid with a strong oxidizer, such as potassium permanganate, leads to the formation of graphene oxide with hydroxyl and epoxide groups as the major functional groups. Nevertheless, the reaction mechanism remains unclear and the source of oxygen is a subject of debate. It could theoretically originate from the oxidizer, water, or sulfuric acid. In this study, we employed 18O and 17O labeled reagents to experimentally elucidate the reaction mechanism and, thus, determine the origin of oxo-functional groups. Our findings reveal the multifaceted roles of sulfuric acid, acting as a dispersion medium, a dehydrating agent for potassium permanganate, and an intercalant. Additionally, it significantly acts as a source of oxygen next to manganese oxides. Through 17O solid-state magic-angle spinning (MAS) NMR experiments, we exclude water as a direct reaction partner during oxygenation. With labeling experiments, we conclude on mechanistic insights, which may be exploited for the synthesis of novel graphene derivatives.

WWP2 Regulates Renal Fibrosis and the Metabolic Reprogramming of Profibrotic Myofibroblasts

Key Points

Background

Renal fibrosis is a common pathologic end point in CKD that is challenging to reverse, and myofibroblasts are responsible for the accumulation of a fibrillar collagen–rich extracellular matrix. Recent studies have unveiled myofibroblasts' diversity in proliferative and fibrotic characteristics, which are linked to different metabolic states. We previously demonstrated the regulation of extracellular matrix genes and tissue fibrosis by WWP2, a multifunctional E3 ubiquitin–protein ligase. Here, we investigate WWP2 in renal fibrosis and in the metabolic reprograming of myofibroblasts in CKD.

Methods

We used kidney samples from patients with CKD and WWP2-null kidney disease mice models and leveraged single-cell RNA sequencing analysis to detail the cell-specific regulation of WWP2 in fibrotic kidneys. Experiments in primary cultured myofibroblasts by bulk-RNA sequencing, chromatin immunoprecipitation sequencing, metabolomics, and cellular metabolism assays were used to study the metabolic regulation of WWP2 and its downstream signaling.

Results

The tubulointerstitial expression of WWP2 was associated with fibrotic progression in patients with CKD and in murine kidney disease models. WWP2 deficiency promoted myofibroblast proliferation and halted profibrotic activation, reducing the severity of renal fibrosis in vivo. In renal myofibroblasts, WWP2 deficiency increased fatty acid oxidation and activated the pentose phosphate pathway, boosting mitochondrial respiration at the expense of glycolysis. WWP2 suppressed the transcription of peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC-1α), a metabolic mediator of fibrotic response, and pharmacologic inhibition of PGC-1α partially abrogated the protective effects of WWP2 deficiency on myofibroblasts.

Conclusions

WWP2 regulates the metabolic reprogramming of profibrotic myofibroblasts by a WWP2-PGC-1α axis, and WWP2 deficiency protects against renal fibrosis in CKD.

Hygroscopic Solutes Enable Non-van der Waals Electrolytes for Fire-Tolerant Dual-Air Batteries

Thermal safety issues of batteries have hindered their large-scale applications. Nonflammable electrolytes improved safety but solvent evaporation above 100 °C limited thermal tolerance, lacking reliability. Herein, fire-tolerant metal-air batteries were realized by introducing solute-in-air electrolytes whose hygroscopic solutes could spontaneously reabsorb the evaporated water solvent. Using Zn/CaCl2 -in-air/carbon batteries as a proof-of-concept, they failed upon burning at 631.8 °C but self-recovered then by reabsorbing water from the air at room temperature. Different from conventional aqueous electrolytes whose irreversible thermal transformation is determined by the boiling points of solvents, solute-in-air electrolytes make this transformation determined by the much higher decomposition temperature of solutes. It was found that stronger intramolecular bonds instead of intermolecular (van der Waals) interactions were strongly correlated to ultra-high tolerance temperatures of our solute-in-air electrolytes, inspiring a concept of non-van der Waals electrolytes. Our study would improve the understanding of the thermal properties of electrolytes, guide the design of solute-in-air electrolytes, and enhance battery safety.

Geophysical survey based on hybrid gravimetry using relative measurements and an atomic gravimeter as an absolute reference

Gravimetry is a versatile metrological approach in geophysics to accurately map subterranean mass and density anomalies. There is a broad diversification regarding the working principle of gravimeters, wherein atomic gravimeters are one of the most technologically progressive class of gravimeters which can monitor gravity at an absolute scale with a high-repetition without exhibiting drift. Despite the apparent utility for geophysical surveys, atomic gravimeters are (currently) laboratory-bound devices due to the vexatious task of transportation. Here, we demonstrated the utility of an atomic gravimeter on-site during a gravity survey, where the issue of immobility was circumvented with a relative spring gravimeter. The atomic gravimeter served as a means to map the relative data from the spring gravimeter to an absolute measurement with an effective precision of 7.7 μ Gal. Absolute measurements provide a robust and feasible method to define and control gravity data taken at different sites, or a later date, which is critical to analyze underground geological units, in particular when it is combined with other geophysical approaches.

Joint modeling of association networks and longitudinal biomarkers: An application to childhood obesity

The prevalence of chronic non-communicable diseases such as obesity has noticeably increased in the last decade. The study of these diseases in early life is of paramount importance in determining their course in adult life and in supporting clinical interventions. Recently, attention has been drawn to approaches that study the alteration of metabolic pathways in obese children. In this work, we propose a novel joint modeling approach for the analysis of growth biomarkers and metabolite associations, to unveil metabolic pathways related to childhood obesity. Within a Bayesian framework, we flexibly model the temporal evolution of growth trajectories and metabolic associations through the specification of a joint nonparametric random effect distribution, with the main goal of clustering subjects, thus identifying risk sub-groups. Growth profiles as well as patterns of metabolic associations determine the clustering structure. Inclusion of risk factors is straightforward through the specification of a regression term. We demonstrate the proposed approach on data from the Growing Up in Singapore Towards healthy Outcomes cohort study, based in Singapore. Posterior inference is obtained via a tailored MCMC algorithm, involving a nonparametric prior with mixed support. Our analysis has identified potential key pathways in obese children that allow for the exploration of possible molecular mechanisms associated with childhood obesity.

Efficient O- and S-glycosylation with ortho-2,2-dimethoxycarbonylcyclopropylbenzyl thioglycoside donors by catalytic strain-release

We herein present a strain-release glycosylation method employing a rationally designed ortho-2,2-dimethoxycarbonylcyclopropylbenzyl (CCPB) thioglycoside donor. The donor is activated through the nucleophilic ring-opening of a remotely activable donor-acceptor cyclopropane (DAC) catalyzed by mild Sc(OTf)3. Our new glycosylation method efficiently synthesizes O-, N-, and S-glycosides, providing facile chemical access to the challenging S-glycosides. Because the activation conditions of conventional glycosyl donors and our CCPB thioglycoside are orthogonal, our novel donor is amenable to controlled one-pot glycosylation reactions with conventional donors for expeditious access to complex glycans. The strain-release glycosylation is applied to the assembly of a tetrasaccharide of O-polysaccharide of Escherichia coli O-33 in one pot and the synthesis of a 1,1'-S-linked glycoside oral galectin-3 (Gal-3) inhibitor, TD139, to demonstrate the versatility and effectiveness of the novel method for constructing both O- and S-glycosides.

Detecting radioactive particles in complex environmental samples using real-time autoradiography

Radioactive particles often contain very high radioactivity concentrations and are widespread. They pose a potential risk to human health and the environment. Their detection, quantification, and characterization are crucial if we are to understand their impact. Here, we present the use of a real-time autoradiography gaseous detector (using parallel ionization multiplier) to expedite and improve the accuracy of radioactive particle screening in complex environmental samples. First, standard particles were used to assess the detector capabilities (spatial resolution, spectrometry, and artefact contributions), then, we applied the technique to more complex and environmentally relevant samples. The real-time autoradiography technique provides data with a spatial resolution (≲100 µm) suitable for particle analysis in complex samples. Further, it can differentiate between particles predominantly emitting alpha and beta radiation. Here, the technique is applied to radioactive cesium-rich microparticles collected from the Fukushima Daiichi nuclear exclusion zone, showing their accurate detection, and demonstrating the viability of real-time autoradiography in environmental scenarios. Indeed, for more complex samples (radioactive particles in a less radioactive heterogeneous background mix of minerals), the technique permits relatively high selectivity for radioactive particle screening (up to 61.2% success rate) with low false positive percentages (~ 1%).

3D Printing of Self-Healing Materials

This review article presents a comprehensive overview of the latest advances in the field of 3D printable structures with self-healing properties. Three-dimensional printing (3DP) is a versatile technology that enables the rapid manufacturing of complex geometric structures with precision and functionality not previously attainable. However, the application of 3DP technology is still limited by the availability of materials with customizable properties specifically designed for additive manufacturing. The addition of self-healing properties within 3D printed objects is of high interest as it can improve the performance and lifespan of structural components, and even enable the mimicking of living tissues for biomedical applications, such as organs printing. The review will discuss and analyze the most relevant results reported in recent years in the development of self-healing polymeric materials that can be processed via 3D printing. After introducing the chemical and physical self-healing mechanism that can be exploited, the literature review here reported will focus in particular on printability and repairing performances. At last, actual perspective and possible development field will be critically discussed.

Poor personal protective equipment practices were associated with heat-related symptoms among Asian healthcare workers: a large-scale multi-national questionnaire survey

BACKGROUND

It is pertinent to understand the perceptions of healthcare workers (HCWs) with their associated personal protective equipment (PPE) usage and heat strain symptoms experienced to effectively combat the negative effects of heat stress during treatment and care activities.

METHODS

We evaluated the associated heat stress perceived by HCWs across Asia and validated a questionnaire on perceptions of heat stress, associated PPE usage, and heat strain symptoms experienced. The questionnaire was administered to 3,082 HCWs in six Asian regions. Factor analyses, including Cronbach's alpha, assessed the questionnaire's validity and reliability. Structural equation modelling analysed the effects of knowledge, attitudes and practices, and heat strain symptoms.

RESULTS

The questionnaire was found to be reliable in assessing HCWs' knowledge, and attitudes and practices towards heat stress and PPE usage (both Cronbach's alpha = 0.9), but not heat strain symptoms (Cronbach's alpha = 0.6). Despite knowledge of heat stress, HCWs had negative attitudes and practices regarding PPE usage (β1 = 0.6, p < 0.001). Knowledge (path coefficient = 0.2, p < 0.001), and negative attitudes and practices (path coefficient = 0.2, p < 0.001) of HCWs towards heat stress and PPE usage adversely affected symptoms experienced.

CONCLUSIONS

The questionnaire was not reliable in assessing symptoms. HCWs should, nevertheless, still self-assess their symptoms for early detection of heat strain. To effectively attenuate heat strain, understanding HCWs' attitudes and practices towards PPE usage should guide policymakers in implementing targeted heat management strategies.

Functionalized MXene Films with Substantially Improved Low-Voltage Actuation

Ti3 C2 Tx MXene film is promising for low-voltage electrochemical actuators (ECAs) due to its excellent electrical conductivity, volumetric capacitance, and mechanical properties. However, its in-plane actuation is limited to little intralayer strain of MXene sheets under polarization. Here it is demonstrated that a simple tetrabutylammonium (TBA) functionalization of MXene improves the in-plane actuation strain by 337% and also enhances the mechanical property and stability in air and the electrolyte. Various in situ characterizations reveal that the improved actuation is ascribed to the co-insertion/desertion of TBA and Li ions into/from MXene interlayer galleries and inter-edge gaps that causes a large in-plane sliding of MXene sheets under negative/positive polarizations. The assembled bending actuator has a high strength and modulus and generates a peak-to-peak strain difference of 0.771% and a blocking force up to 51.5 times its own weight under 1 V. The designed soft robotic tweezer can grasp an object under 1 V and hold it firmly under 0 V. The novel sheet sliding mechanism resembling the filament sliding theory in skeletal muscles may inspire the design of high-performance actuators with other nanomaterials.

Preparation of Block Copolymer Self-Assemblies via Pisa in a Non-Polar Medium Based on RCMP

Polymerization-induced self-assembly (PISA) is conducted in a non-polar medium (n-dodecane) via reversible complexation-mediated polymerization (RCMP). Stearyl methacrylate (SMA) is used to synthesize a macroinitiator, and subsequent block polymerization of benzyl methacrylate (BzMA) from the macroinitiator in n-dodecane afforded a PSMA-PBzMA block copolymer, where PSMA is poly(stearyl methacrylate) and PBzMA is poly(benzyl methacrylate). Because PSMA is soluble but PBzMA is insoluble in n-dodecane, the block copolymer formed a self-assembly during the block polymerization (PISA). Spherical micelles, worms, and vesicles are obtained, depending on the degrees of polymerization of PSMA and PBzMA. "One-pot" PISA is also attained; namely, BzMA is directly added to the reaction mixture of the macroinitiator synthesis, and PISA is conducted in the same pot without purification of the macroinitiator. The spherical micelle and vesicle structures are also fixed using a crosslinkable monomer during PISA. RCMP-PISA is highly attractive as it is odorless and metal-free. The "one-pot" synthesis does not require the purification of the macroinitiator. RCMP-PISA can provide a practical approach to synthesize self-assemblies in non-polar media.

Prospective analysis of pre and postoperative laboratory parameters associated with thrombosis in patients with ovarian cancer

Patients with ovarian cancer have a high risk of developing thrombosis. We aimed to investigate pre and post operative biomarkers associated with thrombosis including deep vein thrombosis and pulmonary thromboembolism in patients treated for ovarian cancer. We collected pre and post operative blood samples from 133 patients undergoing surgery for ovarian cancer between December 2021 and August 2022. The measured parameters were white blood cell count, hemoglobin, platelets, monocytes, serum glucose, CA125, D-dimer, fibrinogen, prothrombin time, activated partial thromboplastin time, fibrinogen degradation products, antithrombin III, protein C, protein S, plasminogen, plasminogen activator inhibitor 1, homocysteine, N-terminal pro-brain natriuretic peptide, interleukin 6, thrombopoietin, soluble P-selectin and granulocyte stimulating factor. Body mass index of patients were collected. Differences between patients who developed thrombosis and those without were compared with Wilcoxon rank-sum test and we analyzed the continuous variables using logistic regression. Twenty-one (15.8%) patients developed thrombosis ranging from 6 to 146 days (median 15 days) after surgery. Pre operative values of homocysteine (p = 0.033) and IL-6 (p = 0.043) were significantly increased and post operative aPTT (p = 0.022) was prolonged and plasminogen (p = 0.041) was decreased in patients with thrombosis. It is important to find novel biomarkers for thrombosis to carefully manage patients who are prone to develop thrombosis despite preventive measures were applied.

Observation of a Higher-Order End Topological Insulator in a Real Projective Lattice

The modern theory of quantized polarization has recently extended from 1D dipole moment to multipole moment, leading to the development from conventional topological insulators (TIs) to higher-order TIs, i.e., from the bulk polarization as primary topological index, to the fractional corner charge as secondary topological index. The authors here extend this development by theoretically discovering a higher-order end TI (HOETI) in a real projective lattice and experimentally verifying the prediction using topolectric circuits. A HOETI realizes a dipole-symmetry-protected phase in a higher-dimensional space (conventionally in one dimension), which manifests as 0D topologically protected end states and a fractional end charge. The discovered bulk-end correspondence reveals that the fractional end charge, which is proportional to the bulk topological invariant, can serve as a generic bulk probe of higher-order topology. The authors identify the HOETI experimentally by the presence of localized end states and a fractional end charge. The results demonstrate the existence of fractional charges in non-Euclidean manifolds and open new avenues for understanding the interplay between topological obstructions in real and momentum space.

Full-parameter omnidirectional transformation optical devices

Transformation optics (TO) provides an unprecedented technique to control electromagnetic (EM) waves by engineering the constitutive parameters of the surrounding medium through a proper spatial transformation. In general, ideal transformation optical devices require simultaneous electric and magnetic responses along all three dimensions. To ease the practical implementation, previous studies usually made use of reduced parameters or other simplified approaches, which inevitably introduce extra reflection or unwanted phase shift. Up to today, experimental realizations of full-parameter transformation optical devices in free space are still quite limited. Here, a general design strategy is proposed to solve this problem. As a specific example, a full-parameter spatial-compression TO medium with constitutive parameters taking the diagonal form diag(a, a, 1/a) for the TM wave incidence was designed and realized experimentally. Such spatial-compression TO media were then applied to the implementation of an ideal omnidirectional invisibility cloak capable of concealing a large-scale object over a wide range of illumination angles. Both the simulation and experiment confirm that the cloak allows for nearly unity transmission of EM waves in the forward direction without introducing extra scattering or phase shift. This work constitutes an important stepping stone for future practical implementation of arbitrary full-parameter omnidirectional transformation optical devices.

Assigning the unassigned: A signature-based classification of rDNA metabarcodes reveals new deep-sea diversity

Environmental DNA metabarcoding reveals a vast genetic diversity of marine eukaryotes. Yet, most of the metabarcoding data remain unassigned due to the paucity of reference databases. This is particularly true for the deep-sea meiofauna and eukaryotic microbiota, whose hidden diversity is largely unexplored. Here, we tackle this issue by using unique DNA signatures to classify unknown metabarcodes assigned to deep-sea foraminifera. We analyzed metabarcoding data obtained from 311 deep-sea sediment samples collected in the Clarion-Clipperton Fracture Zone, an area of potential polymetallic nodule exploitation in the Eastern Pacific Ocean. Using the signatures designed in the 37F hypervariable region of the 18S rRNA gene, we were able to classify 802 unassigned metabarcodes into 61 novel lineages, which have been placed in 27 phylogenetic clades. The comparison of new lineages with other foraminiferal datasets shows that most novel lineages are widely distributed in the deep sea. Five lineages are also present in the shallow-water datasets; however, phylogenetic analysis of these lineages separates deep-sea and shallow-water metabarcodes except in one case. While the signature-based classification does not solve the problem of gaps in reference databases, this taxonomy-free approach provides insight into the distribution and ecology of deep-sea species represented by unassigned metabarcodes, which could be useful in future applications of metabarcoding for environmental monitoring.

Towards a validated glossary of usability attributes for the evaluation of wearable robotic devices

BACKGROUND

Despite technical advances in the field of wearable robotic devices (WRD), there is still limited user acceptance of these technologies. While usability often comes as a key factor influencing acceptance, there is a scattered landscape of definitions and scopes for the term. To advance usability evaluation, and to integrate usability features as design requirements during technology development, there is a need for benchmarks and shared terminology. These should be easily accessible and implementable by developers.

METHODS

An initial set of usability attributes (UA) was extracted from a literature survey on usability evaluation in WRD. The initial set of attributes was enriched and locally validated with seven developers of WRD through an online survey and a focus group. The locally validated glossary was then externally validated through a globally distributed online survey.

RESULTS

The result is the Robotics Usability Glossary (RUG), a comprehensive glossary of 41 UA validated by 70 WRD developers from 17 countries, ensuring its generalizability. 31 of the UA had high agreement scores among respondents and 27 were considered highly relevant in the field, but only 11 of them had been included as design criteria by the respondents.

CONCLUSIONS

Multiple UA ought to be considered for a comprehensive usability assessment. Usability remains inadequately incorporated into device development, indicating a need for increased awareness and end-user perspective. The RUG can be readily accessed through an online platform, the Interactive Usability Toolbox (IUT), developed to provide context-specific outcome measures and usability evaluation methods. Overall, this effort is an important step towards improving and promoting usability evaluation practices within WRD. It has the potential to pave the way for establishing usability evaluation benchmarks that further endorse the acceptance of WRD.

Skin-Inspired Multi-Modal Mechanoreceptors for Dynamic Haptic Exploration

Active sensing is a fundamental aspect of human and animal interactions with the environment, providing essential information about the hardness, texture, and tackiness of objects. This ability stems from the presence of diverse mechanoreceptors in the skin, capable of detecting a wide range of stimuli and from the sensorimotor control of biological mechanisms. In contrast, existing tactile sensors for robotic applications typically excel in identifying only limited types of information, lacking the versatility of biological mechanoreceptors and the requisite sensing strategies to extract tactile information proactively. Here, inspired by human haptic perception, a skin-inspired artificial 3D mechanoreceptor (SENS) capable of detecting multiple mechanical stimuli is developed to bridge sensing and action in a closed-loop sensorimotor system for dynamic haptic exploration. A tensor-based non-linear theoretical model is established to characterize the 3D deformation (e.g., tensile, compressive, and shear deformation) of SENS, providing guidance for the design and optimization of multimode sensing properties with high fidelity. Based on SENS, a closed-loop robotic system capable of recognizing objects with improved accuracy (≈96%) is further demonstrated. This dynamic haptic exploration approach shows promise for a wide range of applications such as autonomous learning, healthcare, and space and deep-sea exploration.

Expanding the DNA editing toolbox: Novel lambda integrase variants targeting microalgal and human genome sequences

Recombinase enzymes are extremely efficient at integrating very large DNA fragments into target genomes. However, intrinsic sequence specificities curtail their use to DNA sequences with sufficient homology to endogenous target motifs. Extensive engineering is therefore required to broaden applicability and robustness. Here, we describe the directed evolution of novel lambda integrase variants capable of editing exogenous target sequences identified in the diatom Phaeodactylum tricornutum and the algae Nannochloropsis oceanica. These microorganisms hold great promise as conduits for green biomanufacturing and carbon sequestration. The evolved enzyme variants show >1000-fold switch in specificity towards the non-natural target sites when assayed in vitro. A single-copy target motif in the human genome with homology to the Nannochloropsis oceanica site can also be efficiently targeted using an engineered integrase, both in vitro and in human cells. The developed integrase variants represent useful additions to the DNA editing toolbox, with particular application for targeted genomic insertion of large DNA cargos.

Repurposing of Zika virus live-attenuated vaccine (ZIKV-LAV) strains as oncolytic viruses targeting human glioblastoma multiforme cells

Glioblastoma multiforme (GBM) is the most common malignant primary brain cancer affecting the adult population. Median overall survival for GBM patients is poor (15 months), primarily due to high rates of tumour recurrence and the paucity of treatment options. Oncolytic virotherapy is a promising treatment alternative for GBM patients, where engineered viruses selectively infect and eradicate cancer cells by inducing cell lysis and eliciting robust anti-tumour immune response. In this study, we evaluated the oncolytic potency of live-attenuated vaccine strains of Zika virus (ZIKV-LAV) against human GBM cells in vitro. Our findings revealed that Axl and integrin αvβ5 function as cellular receptors mediating ZIKV-LAV infection in GBM cells. ZIKV-LAV strains productively infected and lysed human GBM cells but not primary endothelia and terminally differentiated neurons. Upon infection, ZIKV-LAV mediated GBM cell death via apoptosis and pyroptosis. This is the first in-depth molecular dissection of how oncolytic ZIKV infects and induces death in tumour cells.

The SingHealth Perioperative and Anesthesia Subject Area Registry (PASAR), a large-scale perioperative data mart and registry

BACKGROUND

To enhance perioperative outcomes, a perioperative registry that integrates high-quality real-world data throughout the perioperative period is essential. Singapore General Hospital established the Perioperative and Anesthesia Subject Area Registry (PASAR) to unify data from the preoperative, intraoperative, and postoperative stages. This study presents the methodology employed to create this database.

METHODS

Since 2016, data from surgical patients have been collected from the hospital electronic medical record systems, de-identified, and stored securely in compliance with privacy and data protection laws. As a representative sample, data from initiation in 2016 to December 2022 were collected.

RESULTS

As of December 2022, PASAR data comprise 26 tables, encompassing 153,312 patient admissions and 168,977 operation sessions. For this period, the median age of the patients was 60.0 years, sex distribution was balanced, and the majority were Chinese. Hypertension and cardiovascular comorbidities were also prevalent. Information including operation type and time, intensive care unit (ICU) length of stay, and 30-day and 1-year mortality rates were collected. Emergency surgeries resulted in longer ICU stays, but shorter operation times than elective surgeries.

CONCLUSIONS

The PASAR provides a comprehensive and automated approach to gathering high-quality perioperative patient data.

Thermal Rectification in Modularly Designed Bulk Metamaterials

Thermal rectification is a phenomenon of great practical importance where heat transfer is preferential in one direction. Programmable control of heat transfer in 3D space is key to enable thermal rectification at the macroscale but is rarely realized in natural materials or in current existing devices that are constructed at the nano and microscales with high system complexity. Here, modularly designed bulk metamaterials that can break the symmetry of heat transfer from one direction to the other are created, leading to thermal rectification in convergent or divergent states by tuning the metamaterial microstructural design. These thermal metamaterials are microstructured composites made using one material composition, however, they offer sufficient microstructural design freedom to allow tunable local thermal properties for unusual macroscopic heat transfer. The strategy and performance achieved are promising for next-generation thermal management.

Accelerating Sulfur Redox Kinetics by Electronic Modulation and Drifting Effects of Pre-Lithiation Electrocatalysts

Efficient catalyst design is crucial for addressing the sluggish multi-step sulfur redox reaction (SRR) in lithium-sulfur batteries (LiSBs), which are among the promising candidates for the next-generation high-energy-density storage systems. However, the limited understanding of the underlying catalytic kinetic mechanisms and the lack of precise control over catalyst structures pose challenges in designing highly efficient catalysts, which hinder the LiSBs' practical application. Here, drawing inspiration from the theoretical calculations, the concept of precisely controlled pre-lithiation SRR electrocatalysts is proposed. The dual roles of channel and surface lithium in pre-lithiated 1T'-MoS2 are revealed, referred to as the "electronic modulation effect" and "drifting effect", respectively, both of which contribute to accelerating the SRR kinetics. As a result, the thus-designed 1T'-Lix MoS2 /CS cathode obtained by epitaxial growth of pre-lithiated 1T'-MoS2 on cubic Co9 S8 exhibits impressive performance with a high initial specific capacity of 1049.8 mAh g-1 , excellent rate-capability, and remarkable long-term cycling stability with a decay rate of only 0.019% per cycle over 1000 cycles at 3 C. This work highlights the importance of precise control in pre-lithiation parameters and the synergistic effects of channel and surface lithium, providing new valuable insights into the design and optimization of SRR electrocatalysts for high-performance LiSBs.

A Gate-Tunable Ambipolar Quantum Phase Transition in a Topological Excitonic Insulator

Coulomb interactions among electrons and holes in 2D semimetals with overlapping valence and conduction bands can give rise to a correlated insulating ground state via exciton formation and condensation. One candidate material in which such excitonic state uniquely combines with non-trivial band topology are atomic monolayers of tungsten ditelluride (WTe2 ), in which a 2D topological excitonic insulator (2D TEI) forms. However, the detailed mechanism of the 2D bulk gap formation in WTe2 , in particular with regard to the role of Coulomb interactions, has remained a subject of ongoing debate. Here, it shows that WTe2 is susceptible to a gate-tunable quantum phase transition, evident from an abrupt collapse of its 2D bulk energy gap upon ambipolar field-effect doping. Such gate tunability of a 2D TEI, into either n- and p-type semimetals, promises novel handles of control over non-trivial 2D superconductivity with excitonic pairing.

Targeted Depletion of Individual Pathogen by Bacteria-Templated Polymer

Selective and targeted removal of individual species or strains of bacteria from complex communities can be desirable over traditional and broadly acting antibiotics in several conditions. However, strategies that can detect and ablate bacteria with high specificity are emerging in recent years. Herein, a platform is reported that uses bacteria as a template to synthesize polymers containing guanidinium groups for self-selective depletion of specific pathogenic bacteria without disturbing microbial communities. Different from conventional antibiotics, repeated treatment of bacteria with the templated polymers does not evolve drug resistance mutants after 20 days of serial passaging. Especially, high in vivo therapeutic effectiveness of the templated polymers is achieved in E. coli- and P. aeruginosa-induced microbial peritonitis. The templated polymers have shown high selectivity in in vivo antimicrobial activity, which has excellent potential as systemic antimicrobials against bacterial infections.

Microbial community-based protein from soybean-processing wastewater as a sustainable alternative fish feed ingredient

As the global demand for food increases, aquaculture plays a key role as the fastest growing animal protein sector. However, existing aquafeeds contain protein ingredients that are not sustainable under current production systems. We evaluated the use of microbial community-based single cell protein (SCP), produced from soybean processing wastewater, as a partial fishmeal protein substitute in juvenile Asian seabass (Lates calcarifer). A 24-day feeding trial was conducted with a control fishmeal diet and a 50% fishmeal replacement with microbial community-based SCP as an experimental group, in triplicate tanks containing 20 fish each. Both diets met the protein, essential amino acids (except for lysine), and fat requirements for juvenile Asian sea bass. The microbial composition of the SCP was dominated by the genera Acidipropionibacterium and Propioniciclava, which have potential as probiotics and producers of valuable metabolites. The growth performance in terms of percent weight gain, feed conversion ratio (FCR), specific growth rate (SGR), and survival were not significantly different between groups after 24 days. The experimental group had less variability in terms of weight gain and FCR than the control group. Overall, microbial community-based protein produced from soybean processing wastewater has potential as a value-added feed ingredient for sustainable aquaculture feeds.