Browse Articles

Continuous flow photosynthesis of methanol from methane by plasmonic charge accumulation

Development of an AI-based magnetic resonance imaging reading support program (AMP) for deep endometriosis diagnosis

Abstract Diagnosis of endometriosis faces significant challenges including diagnostic delay and reliance on invasive procedures. Deep endometriosis (DE) poses additional difficulties in non-invasive diagnosis due to its subtle and complex imaging features. To address these challenges, we developed an AI-based MRI reading support program (AMP) designed to improve diagnostic accuracy and efficiency, with the primary endpoint of demonstrating its potential to enhance radiologists’ reading sensitivity. AMP comprises the following three models: (1) a nnU-Net model for endometriotic nodular lesion (plaque) segmentation, (2) a radiomics-based LightGBM model for adhesion detection, and (3) a nnU-Net model for detection/quantification of ovarian endometriotic cysts (OECs). In cross-validation, AMP achieves mean Dice similarity coefficient of 0.293 for plaque segmentation and 0.580 for OEC segmentation. For adhesion detection, AMP shows high performance for uterine adhesions (F1 scores > 0.6). In a preliminary clinical utility study with three radiologists, AMP improved mean recall for plaque detection from 0.73 to 0.91 demonstrating AMP’s ability to support radiologists in identifying subtle DE lesions and adhesions. Our findings show that AMP is a reliable non-invasive clinical diagnosis tool, that has the potential to minimize diagnostic delays and improve patient outcome.

Rational Engineering of a Pseudaminic Acid Synthase Enzyme Enables Access to a 3‐Fluoro Sugar with Motility Inhibition in Bacterial Pathogens

Abstract We report the rational engineering of a pseudaminic acid synthase (PseI), which enables the first synthesis of a 3‐fluorinated pseudaminic acid sugar (3‐( eq )‐ F ‐Pse5Ac7Ac), potentially establishing a new class of metabolic inhibitors targeting bacterial glycosylation. Pseudaminic acids are ⍺‐keto acid sugars essential for O ‐glycosylation of flagellin in pathogens such as Campylobacter jejuni , where they are critical for motility and virulence. By introducing rational mutations in the PseI active site, we achieve enhanced turnover with unnatural 3‐fluoro‐phosphoenolpyruvate, facilitating a scalable chemoenzymatic synthesis of the fluorinated sugar. Subsequent treatment of C. jejuni with 3‐( eq )‐ F ‐Pse5Ac7Ac resulted in a significant, time‐dependent reduction in motility, and in vitro studies demonstrated bacterial CMP‐pseudaminic acid synthetase enzymes (PseF) can process the fluoro sugar to afford CMP‐3‐( eq )‐ F ‐Pse5Ac7Ac, potentially implicating the fluorinated pseudaminic acid or its glycosyltransferase CMP‐donor as an anti‐motilin in vivo. This study demonstrates, for the first time, that fluorinated pseudaminic acids can impair bacterial motility, paving the way for anti‐virulence strategies in pathogenic bacteria. This anti‐motilin approach offers a promising alternative to traditional antibiotics, addressing the urgent need for novel strategies to combat antimicrobial resistance, and could be extended to other bacterial ⍺‐keto acid sugars.

Molecular‐Rotor‐Engineered Metal–Organic Frameworks with Various Interpenetrated Degrees/Modes Featuring Tunable Porosity/Stability for Binary/Ternary C ₂ H ₂ /CO ₂ /C ₂ H ₄ Separation

Abstract Efficient separation of challenging acetylene/ethylene (C 2 H 2 /C 2 H 4 ) and acetylene/carbon dioxide (C 2 H 2 /CO 2 ) mixtures is crucial for the chemical industry. Interpenetrated metal–organic frameworks (MOFs) hold significant promise for separating complex gas mixtures but often face a trade‐off between porosity and stability. Herein, three different entangled degrees and modes of MOFs, namely Ni‐dcpp‐bpb , Ni‐dcpp‐bpn , and Ni‐dcpp‐bpan , were yielded by the crystal engineering strategy using molecular‐rotor‐based co‐ligands (benzene, naphthalene, and anthracene groups) to systematically modulate their porosity and stability. As expected, the stable Ni‐dcpp‐bpb / Ni‐dcpp‐bpn achieve enhanced porosity (27.2%/32.1%) and improved C 2 H 2 uptake (73.9/75.8 cm 3 g −1 , 298 K, 100 kPa). Interestingly, Ni‐dcpp‐bpan exhibits the unique rotor‐driven gating effect with free bpan ligands, facilitating the pressure‐dependent switching between nonporous (10.8%) and open states at 195 K. Breakthrough experiments confirm excellent C 2 H 2 separation performance from binary/ternary mixtures and achieve one‐step purification of C 2 H 4 (>99.9%) from C 2 H 2 /CO 2 /C 2 H 4 (1/9/90, v/v/v) mixture with a new benchmark productivity of 396.9 L kg −1 ( Ni‐dcpp‐bpb ). Theoretical calculations and in situ IR spectra reveal that C 2 H 2 /C 2 H 4 and C 2 H 2 /CO 2 separation are primarily governed by the abundant C─H⋯O/N and C─H⋯π interactions. This study establishes a molecular‐rotor‐engineered approach to precisely modulate interpenetration in MOFs and offers a robust platform for high‐performance gas purification.

A qualitative study of bereavement support volunteers’ views and experiences on an online Acceptance and commitment therapy-based (ACT) training programme

Background Grief is a natural process, and many people will adjust in time with support from family and friends. However, evidence suggests that around 40% of bereaved people may benefit from additional assistance, including support from bereavement volunteers. Despite the recognition that bereavement care is a public health priority, availability of bereavement support is inconsistent across the UK and internationally. The continuing expansion of online connectivity offers opportunities to develop digital health interventions to help address the needs of grieving individuals. To improve access to bereavement support, we developed an online intervention based on Acceptance and Commitment therapy-based Training (ACT) ‘My Grief My Way’ and trained volunteers to provide bereavement support in line with ACT-based principles. Aim To describe the views and experiences of bereavement support volunteers who undertook online ACT-based bereavement support training designed to help bereaved individuals cope with grief and improve quality of life. Design Semi-structured interviews and focus groups were conducted with a convenience sample of bereavement support volunteers from two not-for-profit bereavement services in UK. Analysis was guided by the framework approach via NVivo-14. Results A total of 17 participants were recruited; age range 33–76 years, female, n = 15 (88%); ethnicity white, n = 17 (100%). Of these, 15 completed ACT-based My Grief My Way training. Nine participants took part in two focus groups (n = 7) or individual interviews (n = 2), Training was perceived positively, with resulting themes and subthemes indicating there was something to suit everyone’s learning preferences. Participants described the benefits of incorporating ACT-based principles and strategies as valuable additional tools to current practice, underlining the model’s relevance, compatibility and practical application, and was viewed as a good fit irrespective of which therapeutic approach they used with clients. Online ACT-based training and the delivery of ACT-based bereavement support was therefore, perceived as a valuable approach in this context.

Wearable technologies for assisted mobility in the real world

Abstract Mobility impairments from aging, injury, or medical conditions limit independence and social participation. Conventional assistive devices lack adaptability in complex environments. Recent wearable technologies integrating neural sensing, electronics, and co-design offer personalized, responsive mobility support. This perspective focuses on advances in wearable sensing and multimodal fusion for intent recognition, environmental interaction, and adaptive control in exoskeletons, prosthetics, smart wheelchairs, and navigation systems. Emphasizing human-in-the-loop and cognitive–sensorimotor integration, it outlines emerging trends and challenges, promoting intelligent, user-centered solutions to restore function and enhance autonomy, accessibility, and inclusion for individuals with mobility impairments.

Nonlinear flow characteristics of cement grout in fractures with varying geometries

Flight delay prediction: Evaluating machine learning algorithms for enhanced accuracy

Flight delays pose substantial operational and economic challenges for airlines, directly affecting scheduling efficiency, resource allocation, and passenger satisfaction. Accurate prediction of arrival delays is therefore critical for optimizing airline operations and enhancing customer experience. This study systematically evaluates the predictive performance of six machine learning classifiers—Decision Tree, Random Forest, Support Vector Classifier (SVC), Logistic Regression, K-Nearest Neighbors (KNN), and Naive Bayes—on a comprehensive flight dataset, with particular attention to the challenges posed by class imbalance. To mitigate skewed class distributions, resampling techniques including Random Oversampling, Synthetic Minority Oversampling Technique (SMOTE), and Adaptive Synthetic Sampling (ADASYN) were applied to the training data. Model performance was rigorously assessed using stratified 10-fold cross-validation and further validated on a hold-out test set, employing multiple evaluation metrics: Accuracy, F1-score, Matthews Correlation Coefficient (MCC), and ROC-AUC. The results demonstrate that Random Forest combined with Random Oversampling and Decision Tree combined with SMOTE both achieved the highest predictive performance (accuracy 0.90, F1-score 0.90, MCC 0.73, ROC-AUC 0.87. Notably, simpler models such as Naive Bayes exhibited competitive results under balanced conditions, underscoring the continued relevance of probabilistic classifiers in certain operational contexts. These findings highlight the critical role of resampling strategies and rigorous cross-validation in developing reliable, high-performing predictive models for imbalanced flight delay datasets, offering actionable insights for both airline operations and data-driven decision-making.

Publisher Correction: Light patterning semiconductor nanoparticles by modulating surface charges

Pearson correlation-based clustering with collaborative task allocation in 5G Industrial Internet of Things divergent health networks

A Photoswitchable HaloTag for Spatiotemporal Control of Fluorescence in Living Cells

Abstract Photosensitive fluorophores, whose emission can be controlled using light, are essential for advanced biological imaging, enabling precise spatiotemporal tracking of molecular features and facilitating super‐resolution microscopy techniques. Although irreversibly photoactivatable fluorophores are well established, reversible reporters that can be reactivated multiple times remain scarce, and only a few have been applied in living cells using generalizable protein labeling methods. To address these limitations, we introduce chemigenetic photoswitchable fluorophores, leveraging the self‐labeling HaloTag protein with fluorogenic rhodamine dye ligands. By incorporating a light‐responsive protein domain into HaloTag, we engineer a tunable, photoswitchable HaloTag (psHaloTag), which can reversibly modulate the fluorescence of a bound dye‐ligand via a light‐induced conformational change. Our best performing psHaloTag variants show excellent performance in living cells, with large, reversible, deep‐red fluorescence turn‐on upon 450 nm illumination across various biomolecular targets and SMLM compatibility. Together, this work establishes the chemigenetic approach as a versatile platform for the design of photoswitchable reporters, tunable through both genetic and synthetic modifications, with promising applications for dynamic imaging.

3D-MRI evaluation of cartilage thickness changes and their location in the patellofemoral joint after open wedge high tibial osteotomy for knee osteoarthritis: A retrospective cohort study

Background Open wedge high tibial osteotomy (OWHTO) has been widely established as a safe surgical procedure for medial compartmental knee osteoarthritis. However, concerns remain regarding the progression of patellofemoral (PF) osteoarthritis following surgery. Recent advances in 3D-MRI analysis have enabled quantitative cartilage thickness measurement. We hypothesized that OWHTO would result in measurable decreases in the PF joint cartilage thickness, predominantly medially and detectable using quantitative 3D-MRI. This study evaluated the clinical utility of quantitative 3D-MRI for assessing PF joint cartilage changes before and after OWHTO. Methods Patients were included if they had undergone OWHTO without lateral retinacular release for medial osteoarthritis and had both the preoperative and post–hardware-removal 3D-MRI datasets required for this analysis. Radiographic evaluations were performed before and after OWHTO. Trochlear and patellar cartilage thicknesses were measured from 3D-MRI images at both time points. Changes exceeding 0.1 mm (the validated measurement precision threshold) were considered significant. To assess cartilage loss location, each 3D image was divided into medial, central, and lateral thirds. Superimposed images were observed to determine spatial correspondence of the cartilage defects. Results In total, 13 knees from 13 patients (median age 55 [32–74] years) were evaluated. Postoperatively, patellar height and lateral tilt significantly decreased (p < 0.001 for both). Of these 13 cases, 7 (54%) showed thickness reductions exceeding 0.1 mm in the trochlear cartilage, and 7 cases showed reductions in the patellar cartilage, with 4 cases showing reductions in both. All cases demonstrated predominantly medial thickness decreases (p = 0.008). Of the 3 cases with patellar cartilage defects, 2 cases showed spatial correspondence with trochlear defects. Conclusions Quantitative 3D-MRI analysis revealed significant cartilage thickness decreases after OWHTO, predominantly in the medial aspect of the PF joint. This method proved useful for evaluating postoperative PF joint changes and detecting cartilage defect locations.

Monitoring rapid degradation of NANOG reveals UTP15 maintains pluripotency by regulating nascent transcripts

Simulation-assisted multimodal deep learning (Sim-MDL) fusion models for the evaluation of thermal barrier coatings using infrared thermography and Terahertz imaging

Abstract Thermal Barrier Coatings (TBCs) are critical for high-temperature applications, such as gas turbines and aerospace engines, protecting metallic substrates from extreme thermal stress and degradation. Accurate evaluation of TBCs is essential to improve operational efficiency, optimize predictive maintenance strategies, and extend component life. Conventional non-destructive evaluation (NDE) techniques such as infrared thermography (IRT) and terahertz (THz) imaging have been widely used for TBC inspection with limitations when used independently, including sensitivity to surface conditions, limited penetration depth mainly in multi-layer coatings. This study proposes a novel framework called simulation-assisted multimodal deep learning (Sim-MDL) that combines IRT and THz data for a comprehensive evaluation of TBCs. To generalize the study to varying thermophysical properties of TBCs, the study uses simulation-generated data along with experimental data for training deep learning models. Two deep learning frameworks based on a 1D convolutional neural networks (CNN) and a long short-term memory (LSTM) with attention were developed for the multimodal feature fusion. The IR-THz fused frameworks enable simultaneous prediction of key TBC topcoat properties including thermal conductivity, heat capacity, topcoat thickness and refractive index. Experiments were conducted on four newly coated samples topcoat thicknesses ranging from 24 to 120 μm. An attention-based LSTM model trained on both simulation and experimental data shows high prediction accuracy with MAPE values ranging from 2.06% to 4.43% for thermal conductivity, 2.05% to 3.57% for heat capacity, 11.53% to 1.75% for topcoat thickness, and 0.27% to 1.05% for refractive index, respectively, for the topcoat layers of four samples. The proposed Sim-MDL framework outperformed single-modality and conventional parameter estimation methods in accuracy and robustness, highlighting the potential of multimodal data for automated analysis of TBC in industrial settings.

Contribution of xpert MTB/RIF assay and Urine LF-LAM for the diagnosis of tuberculosis in children aged 5 – 14 years, at selected health facilities in Ethiopia, 2016 – 2019

Background Childhood tuberculosis (TB) remains under-reported and undiagnosed. A full complement of diagnostic tests is oftentimes unavailable in resource limited country like Ethiopia. This study assesses the contribution of Xpert MTB/RIF assay and urine LF-LAM for childhood TB diagnosis using sputum and urine samples. Method A facility based cross-sectional study was conducted in children between 5 and 14 years of age. Sputum and urine samples were collected from children with presumptive TB. The samples were tested for TB using LF-LAM, Xpert MTB/RIF assay, concentrated smear microscopy, and culture. Diagnostic performance of Xpert MTB/RIF assay was analyzed and compared against culture, which was used as the gold standard. Urine LF-LAM test result was compared to a composite reference standard. Result Of 576 participants with presumptive TB enrolled in the study, 519 (90.1%) had complete clinical data and bacteriological laboratory test results. Active TB was diagnosed in 14.1% (73/519), and bacteriological confirmation was made in 10.1% (52/515) of children with presumptive TB. The odds of being diagnosed with a bacteriologically confirmed TB are significantly higher in children who have household contact history with TB patient (aOR 2.27, P = 0.03) and age above 10 years (aOR 3.67, P < 0.001). Xpert MTB/RIF test had sensitivity of 79% using culture as the gold standard. Compared to smear microscopy, the sensitivity of the Xpert MTB/RIF assay increased by 50% for children aged 5–9 years and by 40% for children and adolescents living with HIV (C/ALHIV). All bacteriologically confirmed (n = 2) and clinically diagnosed TB children (n = 2) who live with HIV were tested positive for urine LF-LAM. The overall sensitivity of urine LF-LAM was 27.6% when using the composite reference standard, compared to 17.9% when the bacteriological reference standard was applied. Conclusions Pulmonary TB diagnosis was greatly improved with the use of Xpert MTB/RIF assay, particularly in children aged 5–9 years and C/ALHIV who typically have difficulty producing good quality sputum. Urine LF-LAM performed well in children/adolescents who tested positive for HIV, but it performed poorly in the other variables, which suggests that urine LF-LAM testing did not play a critical role in TB diagnosis in children with negative HIV status.

HTRA1/lncRNA HTRA1-AS1 dominates in age-related macular degeneration reticular pseudodrusen genetic risk with no complement involvement

Coal matrix response to CO2 adsorption and emission: implications for sustainable mining and carbon sequestration

Breaking Diffusion Limit in Ester‐Flame‐Proof Na‐Ion Electrolytes Through Solvent Coordination Chemistry

Abstract Traditional electrolyte systems are struggle to meet practical needs for high performance of sodium‐ion batteries (SIBs) due to their limited functionality. The design of electrolytes today relies largely on expensive trial‐and‐error methodologies and intricate solvent–structure engineering, in which various additives and solvents are arbitrarily used without any reasonable selection rules. Motivated by this, we herein establish a descriptor‐guided framework centered on solvent oxidative stability and Na + ‐solvent coordination chemistry to identify intrinsically flame‐proof, ester‐based electrolytes that overcome conventional diffusion limits. By screening a number of fluorinated phosphate and cyclic carbonate candidates, the electrolytes with the comprehensive properties, including the electrolyte desolvation processes, oxidation resistance, and flame retardancy, were successfully designed and synthesized, thereby realizing intrinsic flameproofing with fast‐charging capability. Impressively, our optimized electrolytes sustain over 98% capacity retention for 350 cycles at 1.0 C with a Coulombic efficiency of nearly 100% when deployed in Na 3 V 2 (PO 4 ) 3 (NVP) cells, whereas benchmark carbonate systems fail within a few tens of cycles. By linking the explicit performance descriptors of solvent electronic structure and ion–solvent coordination, this work delivers a rational pathway to flame‐proof and high‐rate SIB electrolytes, breaking the long‐standing diffusion limit and brute‐force screening.

Judging the unseen: The impact of onset controllability in shaping perceptions of defendants with traumatic brain injury

Traumatic brain injury (TBI) has been associated with increased risk of criminality, yet very little is known about how individuals with TBI may intersect with the adjudication phase of the criminal justice system. Therefore, the aim of this study was to conduct the first empirical investigation of how individuals with TBI are perceived within the context of a UK magistrates’ court, and how the perceived controllability of the onset of injury may influence perceptions and sentencing-related recommendations. 174 participants (60.35% female, mean age = 34.86 years) from a general population sample, reflecting diverse employment and education backgrounds, read a fictional transcript of a magistrate sentencing a defendant for an assault charge. Participants were randomly allocated to a single condition (Onset Controllable, Onset Uncontrollable, or no-TBI control), where the onset controllability of the injury was experimentally manipulated. Participants were asked to make sentence related recommendations and to rate the defendant’s level of risk and dangerousness, behavioural tendencies, and the extent to which they felt empathy/sympathy towards them. Additionally, their proximity to, knowledge of, and attitudes towards brain injury were assessed. The perceived onset controllability of the TBI was not found to influence perceptions and sentencing-related recommendations. Instead, participants reported feeling more empathetic towards the defendant and rated their behavioural tendencies more favourably if they were described as having sustained a TBI, irrespective of its onset controllability. This suggests that the presence of TBI might evoke strong empathic responses that counteract the tendency to assign blame based on controllability and may also lead to more favourable behavioural perceptions, but that such evaluations are not strong enough to exert an influence on sentencing related recommendations. Consequently, it is possible that the invisible nature of TBI-related disability, coupled with poor public understanding, may mean that information about a defendant’s brain injury is overlooked and/or not taken into full account in sentencing related recommendations.

CiFi: accurate long-read chromosome conformation capture with low-input requirements

Abstract Hi-C characterizes three-dimensional chromatin organization, facilitates haplotype phasing, and enables genome-assembly scaffolding, but encounters difficulties across complex regions. By coupling chromosome conformation capture (3 C ) with PacBio H iFi long-read sequencing, here we develop a method (CiFi) that enables analysis of genomic interactions across repetitive regions. Starting with as little as 60,000 cells (sub-microgram DNA), the method produces multi-kilobasepair HiFi reads that contain multiple interacting, concatenated segments (~350 bp to 2 kbp). This multiplicity and increase in segment length versus standard short-read-based Hi-C improves read-mapping efficiency and coverage in repetitive regions and enhances haplotype phasing. CiFi pairwise interactions are largely concordant with Hi-C from a human lymphoblastoid cell line, with gains in assigning topologically associating domains across centromeres, segmental duplications, and human disease-associated genomic hotspots. As CiFi requires less input versus established methods, we apply the approach to characterize single small insects: assaying chromatin interactions across the genome from an Anopheles coluzzii mosquito and producing a chromosome-scale scaffolded assembly from a Ceratitis capitata Mediterranean fruit fly. Together, CiFi enables assessment of chromosome-scale interactions of previously recalcitrant low-complexity loci, low-input samples, and small organisms.