Pain in recessive dystrophic epidermolysis bullosa (RDEB): findings of the Prospective Epidermolysis Bullosa Longitudinal Evaluation Study (PEBLES).

BACKGROUND: Pain is common in the genetic skin fragility disorder epidermolysis bullosa (EB), from skin and mucosal injury and inflammation as well as extra-mucocutaneous sites. Individuals living with EB have identified pain as a priority for better treatments. OBJECTIVES: The Prospective EB Longitudinal Evaluation Study (PEBLES) is a prospective register study exploring the natural history of RDEB across all ages from birth to death. Here, we investigated the characteristics and treatment of pain in different RDEB subtypes. METHODS: Information was collected from individuals with different RDEB subtypes over an 8-year period. Data included visual analogue scale (VAS) ratings of background and procedural pain, its location, intensity and impact on sleep, as well as pain medication. Disease severity scores and quality of life measures were correlated to pain scores. RESULTS: Sixty-one participants (13 children, 48 adults) completed a total of 361 reviews. Pain was common, experienced by 93% of participants at index review, with 80% suffering both background and procedural pain. Across all RDEB patients, the median VAS for background pain was 40 (out of 100) [interquartile range 20,60] and for those having regular dressing changes, median procedural pain was 52 [40,80]. Severe (RDEB-S) and pruriginosa (RDEB-Pru) groups had the greatest increase in procedural compared to background pain of 20 and 22 VAS points, respectively. Correlations between disease severity and quality of life impairment were observed across most groups, particularly RDEB-S. Over half of those studied experienced pain frequently or constantly, and in one third pain disturbed sleep at least 4 nights per week. Skin was the commonest source of pain in all subtypes except inversa RDEB where the mouth was the main site. Despite frequent and severe pain, one third of participants used no medication for pain and, in those that did, pain levels remained high suggesting ineffectiveness of current pain management approaches and a significant unmet need in RDEB. CONCLUSION: The frequency, severity, and impact of pain in all RDEB patients is significant, particularly in RDEB-S and RDEB-Pru. Our findings highlight that current RDEB pain management is poorly effective and that further research is needed to address this symptom.

Using interpretable machine learning to predict bloodstream infection and antimicrobial resistance in patients admitted to ICU: Early alert predictors based on EHR data to guide antimicrobial stewardship.

Nosocomial infections and Antimicrobial Resistance (AMR) stand as formidable healthcare challenges on a global scale. To address these issues, various infection control protocols and personalized treatment strategies, guided by laboratory tests, aim to detect bloodstream infections (BSI) and assess the potential for AMR. In this study, we introduce a machine learning (ML) approach based on Multi-Objective Symbolic Regression (MOSR), an evolutionary approach to create ML models in the form of readable mathematical equations in a multi-objective way to overcome the limitation of standard single-objective approaches. This method leverages readily available clinical data collected upon admission to intensive care units, with the goal of predicting the presence of BSI and AMR. We further assess its performance by comparing it to established ML algorithms using both naturally imbalanced real-world data and data that has been balanced through oversampling techniques. Our findings reveal that traditional ML models exhibit subpar performance across all training scenarios. In contrast, MOSR, specifically configured to minimize false negatives by optimizing also for the F1-Score, outperforms other ML algorithms and consistently delivers reliable results, irrespective of the training set balance with F1-Score.22 and.28 higher than any other alternative. This research signifies a promising path forward in enhancing Antimicrobial Stewardship (AMS) strategies. Notably, the MOSR approach can be readily implemented on a large scale, offering a new ML tool to find solutions to these critical healthcare issues affected by limited data availability.

APOBEC family reshapes the immune microenvironment and therapy sensitivity in clear cell renal cell carcinoma.

Emerging evidence suggests that the APOBEC family is implicated in multiple cancers and might be utilized as a new target for cancer detection and treatment. However, the dysregulation and clinical implication of the APOBEC family in clear cell renal cell cancer (ccRCC) remain elusive. TCGA multiomics data facilitated a comprehensive exploration of the APOBEC family across cancers, including ccRCC. Remodeling analysis classified ccRCC patients into two distinct subgroups: APOBEC family pattern cancer subtype 1 (APCS1) and subtype 2 (APCS2). The study investigated differences in clinical parameters, tumor immune microenvironment, therapeutic responsiveness, and genomic mutation landscapes between these subtypes. An APOBEC family-related risk model was developed and validated for predicting ccRCC patient prognosis, demonstrating good sensitivity and specificity. Finally, the overview of APOBEC3B function was investigated in multiple cancers and verified in clinical samples. APCS1 and APCS2 demonstrated considerably distinct clinical features and biological processes in ccRCC. APCS1, an aggressive subtype, has advanced clinical stage and a poor prognosis. APCS1 exhibited an oncogenic and metabolically active phenotype. APCS1 also exhibited a greater tumor mutation load and immunocompromised condition, resulting in immunological dysfunction and immune checkpoint treatment resistance. The genomic copy number variation of APCS1, including arm gain and loss, was much more than that of APCS2, which may help explain the tired immune system. Furthermore, the two subtypes have distinct drug sensitivity patterns in clinical specimens and matching cell lines. Finally, we developed a predictive risk model based on subtype biomarkers that performed well for ccRCC patients and validated the clinical impact of APOBEC3B. Aberrant APOBEC family expression patterns might modify the tumor immune microenvironment by increasing the genome mutation frequency, thus inducing an immune-exhausted phenotype. APOBEC family-based molecular subtypes could strengthen the understanding of ccRCC characterization and guide clinical treatment. Targeting APOBEC3B may be regarded as a new therapeutic target for ccRCC.

Long COVID demographic and secondary care referral characteristics in primary care: analysis of anonymised primary care data from a multiethnic, deprived urban area in the UK.

Once the nature and number of patients with Long COVID was more fully understood, UK secondary care developed services to investigate, treat and support these patients. We aimed to identify evidence for demographic health inequalities based on general practitioner (GP) Long COVID referrals to available secondary care services. Despite Long COVID demographics broadly reflecting the multiethnic and socially disadvantaged profile of the study population, we found that secondary care referral was mainly focussed on older age patients and those born in the UK with co-morbid anxiety; although co-morbid diabetes was associated with reduced referrals.

Largescale multicenter study of a serum metabolite biomarker panel for the diagnosis of breast cancer.

Breast cancer (BC) is currently the most prevalent malignancy worldwide, and finding effective non-invasive biomarkers for routine clinical detection of BC remains a significant challenge. Here, we performed non-targeted and targeted metabolomics analysis on the screening, training and validation cohorts of serum samples from 1,947 participants. A metabolite biomarker model including glutamate, erythronate, docosahexaenoate, propionylcarnitine, and patient's age was established for detecting BC. This model demonstrated better diagnostic performance than carbohydrate antigen 15-3 (CA15-3) and carcinoembryonic antigen (CEA) alone in discriminating BC from healthy controls both in the training and validation cohorts [area under the curve (AUC), 0.954; sensitivity, 87.1% and specificity, 93.5% for the training cohort and 0.834, 68.3%, and 85.2%, respectively, for the validation cohort 1]. This study has established a noninvasive approach for the detection of BC, which shows potential as a suitable supplement to the clinical screening methods currently employed for BC.

Covalent versus noncovalent attachments of [FeFe]­hydrogenase models onto carbon nanotubes for aqueous hydrogen evolution reaction.

In an effort to develop the biomimetic chemistry of [FeFe]­hydrogenases for catalytic hydrogen evolution reaction (HER) in aqueous environment, we herein report the integrations of diiron dithiolate complexes into carbon nanotubes (CNTs) through three different strategies and compare the electrochemical HER performances of the as-resulted 2Fe2S/CNT hybrids in neutral aqueous medium. That is, three new diiron dithiolate complexes [{(µ-SCH2)2N(C6H4CH2C(O)R)}Fe2(CO)6] (R = N-oxylphthalimide (1), NHCH2pyrene (2), and NHCH2Ph (3)) were prepared and could be further grafted covalently to CNTs via an amide bond (this 2Fe2S/CNT hybrid is labeled as H1) as well as immobilized noncovalently to CNTs via π-π stacking interaction (H2) or via simple physisorption (H3). Meanwhile, the molecular structures of 1-3 are determined by elemental analysis and spectroscopic as well as crystallographic techniques, whereas the structures and morphologies of H1-H3 are characterized by various spectroscopies and scanning electronic microscopy. Further, the electrocatalytic HER activity trend of H1 > H2 ≈ H3 is observed in 0.1 M phosphate buffer solution (pH = 7) through different electrochemical measurements, whereas the degradation processes of H1-H3 lead to their electrocatalytic deactivation in the long-term electrolysis as proposed by post operando analysis. Thus, this work is significant to extend the potential application of carbon electrode materials engineered with diiron molecular complexes as heterogeneous HER electrocatalysts for water splitting to hydrogen.

Diagnostic accuracy of deep learning using speech samples in depression: a systematic review and meta-analysis.

OBJECTIVE: This study aims to conduct a systematic review and meta-analysis of the diagnostic accuracy of deep learning (DL) using speech samples in depression. MATERIALS AND METHODS: This review included studies reporting diagnostic results of DL algorithms in depression using speech data, published from inception to January 31, 2024, on PubMed, Medline, Embase, PsycINFO, Scopus, IEEE, and Web of Science databases. Pooled accuracy, sensitivity, and specificity were obtained by random-effect models. The diagnostic Precision Study Quality Assessment Tool (QUADAS-2) was used to assess the risk of bias. RESULTS: A total of 25 studies met the inclusion criteria and 8 of them were used in the meta-analysis. The pooled estimates of accuracy, specificity, and sensitivity for depression detection models were 0.87 (95% CI, 0.81-0.93), 0.85 (95% CI, 0.78-0.91), and 0.82 (95% CI, 0.71-0.94), respectively. When stratified by model structure, the highest pooled diagnostic accuracy was 0.89 (95% CI, 0.81-0.97) in the handcrafted group. DISCUSSION: To our knowledge, our study is the first meta-analysis on the diagnostic performance of DL for depression detection from speech samples. All studies included in the meta-analysis used convolutional neural network (CNN) models, posing problems in deciphering the performance of other DL algorithms. The handcrafted model performed better than the end-to-end model in speech depression detection. CONCLUSIONS: The application of DL in speech provided a useful tool for depression detection. CNN models with handcrafted acoustic features could help to improve the diagnostic performance. PROTOCOL REGISTRATION: The study protocol was registered on PROSPERO (CRD42023423603).

Modulation of morphology and electronic structure of cobalt thiophenedicarboxylic coordination polymer via ligand exchange for high-performance oxygen evolution reaction and supercapacitor.

Rationally designing metal organic frameworks (MOFs) as an ideal dual-function material for water electrolysis and supercapacitors is of great significance for energy storage and conversion. Herein, we successfully synthesized the nanoneedle-like structure CoNi-MOF by partially replacing 2, 5-thiophenedicarboxylic acid (TDA) with 1, 1'-Ferrocenedicarboxylate (Fc). The exchange of Fc ligand can modulate the morphology and electronic structure of CoNi-TDA, thus exposing the abundant active sites and improving the electrical conductivity. The as-prepared CoNi-TDA/0.2Fc exhibited a low overpotential of 236 mV at 10 mA cm-2 for oxygen evolution reaction (OER) and a low Tafel slope of 40.44 mV dec-1. Additionally, CoNi-TDA/0.2Fc demonstrated a notable specific capacitance of 1409 F g-1 at 1 A/g and excellent stability, maintaining a capacitance retention of 96.54 % after 20,000 cycles. The study proposes a new strategy to modulate the morphology and electronic structure of MOFs via the ligand exchange for high-performance energy storage and conversion device.

Global Burden of Ischemic Heart Disease from 2022 to 2050: Projections of Incidence, Prevalence, Deaths, and Disability-Adjusted Life Years.

AIMS: Ischemic heart disease (IHD) has been a significant public health issue worldwide. This study aims to predict the global burden of IHD in a timely and comprehensive manner. METHODS AND RESULTS: Incidence, prevalence, deaths, and disability-adjusted life years (DALYs) for IHD from 1990 to 2021 were derived from the Global Burden of Disease 2021 database and three models (linear, exponential, and Poisson regression) were used to estimate their trends over time at the global, regional, and national levels by age, sex, and country groups, with the gross domestic product per capita was applied to adjust the model. The model results revealed that the global burden of IHD is expected to increase continuously by 2050. By 2050, global IHD incidence, prevalence, deaths, and DALYs are projected to reach 67.3 million, 510 million, 16 million, and 302 million, respectively, which represents an increase of 116%, 106%, 80%, and 62% from 2021. Moreover, the results showed that regions with lower socio-demographic index (SDI) bore a greater burden of IHD than those with higher SDI, with men having a higher burden of IHD than women. People over 70 years old account for a major part of the burden of IHD, and premature death of IHD is also becoming more serious. CONCLUSION: The global burden of IHD will increase further by 2050, potentially due to population aging and economic disparities. Hence, it is necessary to strengthen the prevention of IHD and formulate targeted strategies according to different SDI regions and special populations.

The Dynamic Comprehensive Evaluation of the Importance of Cutting Parameters in the Side Milling TC4 Process Using an Integrated End Mill.

In the cutting process, there are many parameters that affect the cutting effect, and the same parameter has different degrees of influence on different performance indicators, which makes it difficult to select key parameters for parameter optimization and parameter combination evaluation while considering multiple performance indicators at the same time. The process of titanium alloy milling with an integrated end mill is studied herein. The values of cutting tool flank face wear and material removal rates are obtained with experimental and analytical methods. Numerical characteristics and causes of the cutting tool flank face wear at different stages are also analyzed. The dynamic, comprehensive evaluation method based on the double incentives model is used to evaluate the dynamic, comprehensive importance of cutting parameters in view of the problem of considering multiple performance indicators and the characteristics of the dynamic change in performance indicators in the cutting process. According to the result of a dynamic, comprehensive evaluation, the cutting parameters with the highest comprehensive importance are selected. Finally, the radar map is used to plot the comprehensive importance of the cutting parameters. The overall comprehensive importance of each cutting parameter is intuitively displayed as well. As a result of the research, the dynamic, comprehensive evaluation method based on the double incentives model has a good application value in the evaluation of tool performance in the cutting process and can quickly select the best tool performance parameter combination; it is established that the most comprehensive parameter is the cutting speed, and the cutting width is the second most important. In turn, the comprehensive importance of the cutting depth is the lowest.

Microdroplets initiate organic-inorganic interactions and mass transfer in thermal hydrous geosystems.

Organic-inorganic interactions regulate the dynamics of hydrocarbons, water, minerals, CO2, and H2 in thermal rocks, yet their initiation remains debated. To address this, we conducted isotope-tagged and in-situ visual thermal experiments. Isotope-tagged studies revealed extensive H/O transfers in hydrous n-C20H42-H2O-feldspar systems. Visual experiments observed water microdroplets forming at 150-165 °C in oil phases near the water-oil interface without surfactants, persisting until complete miscibility above 350 °C. Electron paramagnetic resonance (EPR) detected hydroxyl free radicals concurrent with microdroplet formation. Here we propose a two-fold mechanism: water-derived and n-C20H42-derived free radicals drive interactions with organic species, while water-derived and mineral-derived ions trigger mineral interactions. These processes, facilitated by microdroplets and bulk water, blur boundaries between organic and inorganic species, enabling extensive interactions and mass transfer. Our findings redefine microscopic interplays between organic and inorganic components, offering insights into diagenetic and hydrous-metamorphic processes, and mass transfer cycles in deep basins and subduction zones.

Stereotactic radiotherapy for neovascular age-related macular degeneration (STAR): a pivotal, randomised, double-masked, sham-controlled device trial.

BACKGROUND: Neovascular age-related macular degeneration (nAMD) is a leading cause of blindness. The first-line therapy is anti-vascular endothelial growth factor (anti-VEGF) agents delivered by intravitreal injection. Ionising radiation mitigates key pathogenic processes underlying nAMD, and therefore has therapeutic potential. STAR aimed to assess whether stereotactic radiotherapy (SRT) reduces the number of anti-VEGF injections required, without sacrificing visual acuity. METHODS: This pivotal, randomised, double-masked, sham-controlled trial enrolled participants with pretreated chronic active nAMD from 30 UK hospitals. Participants were randomly allocated in a 2:1 ratio to 16-Gray (Gy) SRT delivered using a robotically controlled device or sham SRT, stratified by treatment centre. Eligible participants were aged 50 years or older and had chronic active nAMD, with at least three previous anti-VEGF injections, including at least one in the last 4 months. Participants and all trial and image reading centre staff were masked to treatment allocation, except one unmasked statistician. The primary outcome was the number of intravitreal ranibizumab injections required over 2 years, tested for superiority (fewer injections). The main secondary outcome was Early Treatment Diabetic Retinopathy Study visual acuity at two years, tested for non-inferiority (five-letter margin). The primary analysis used the intention-to-treat principle, and safety was analysed per-protocol on participants with available data. The study is registered with ClinicalTrials.gov (NCT02243878) and is closed for recruitment. FINDINGS: 411 participants enrolled between Jan 1, 2015, and Dec 27, 2019, and 274 were randomly allocated to the 16-Gy SRT group and 137 to the sham SRT group. 240 (58%) of all participants were female, and 171 (42%) of all participants were male. 241 participants in the 16-Gy SRT group and 118 participants in the sham group were included in the final analysis, and 409 patients were treated and formed the safety population, of whom two patients allocated to sham treatment erroneously received 16-Gy SRT. The SRT group received a mean of 10·7 injections (SD 6·3) over 2 years versus 13·3 injections (5·8) with sham, a reduction of 2·9 injections after adjusting for treatment centre (95% CI -4·2 to -1·6, p<0·0001). The SRT group best-corrected visual acuity change was non-inferior to sham (adjusted mean letter loss difference between groups, -1·7 letters [95% CI -4·2 to 0·8]). Adverse event rates were similar across groups, but reading centre-detected microvascular abnormalities occurred in 77 SRT-treated eyes (35%) and 13 (12%) sham-treated eyes. Overall, eyes with microvascular abnormalities tended to have better best-corrected visual acuity than those without. Fewer ranibizumab injections offset the cost of SRT, saving a mean of £565 per participant (95% CI -332 to 1483). INTERPRETATION: SRT can reduce ranibizumab treatment burden without compromising vision. FUNDING: Medical Research Council and National Institute for Health and Care Research Efficacy and Mechanism Evaluation Programme.

Missense mutation of ISL1 (E283D) is associated with the development of type 2 diabetes.

AIMS/HYPOTHESIS: Mutations in Isl1, encoding the insulin enhancer-binding protein islet-1 (ISL1), may contribute to attenuated insulin secretion in type 2 diabetes mellitus. We made an Isl1E283D mouse model to investigate the disease-causing mechanism of diabetes mellitus. METHODS: The ISL1E283D mutation (c. 849A>T) was identified by whole exome sequencing on an early-onset type 2 diabetes family and then the Isl1E283D knockin (KI) mouse model was created and an IPGTT and IPITT were conducted. Glucose-stimulated insulin secretion (GSIS), expression of Ins2 and other ISL1 target genes and interacting proteins were evaluated in isolated pancreas islets. Transcriptional activity of Isl1E283D was evaluated by cell-based luciferase reporter assay and electrophoretic mobility shift assay, and the expression levels of Ins2 driven by Isl1 wild-type (Isl1WT) and Isl1E283D mutation in rat INS-1 cells were determined by RT-PCR and western blotting. RESULTS: Impaired GSIS and elevated glucose level were observed in Isl1E283D KI mice while expression of Ins2 and other ISL1 target genes Mafa, Pdx1, Slc2a2 and the interacting protein NeuroD1 were downregulated in isolated islets. Transcriptional activity of the Isl1E283D mutation for Ins2 was reduced by 59.3%, and resulted in a marked downregulation of Ins2 expression when it was overexpressed in INS-1 cells, while overexpression of Isl1WT led to an upregulation of Ins2 expression. CONCLUSIONS/INTERPRETATION: Isl1E283D mutation reduces insulin expression and secretion by regulating insulin and other target genes, as well as its interacting proteins such as NeuroD1, leading to the development of glucose intolerance in the KI mice, which recapitulated the human diabetic phenotype. This study identified and highlighted the Isl1E283D mutation as a novel causative factor for type 2 diabetes, and suggested that targeting transcription factor ISL1 could offer an innovative avenue for the precise treatment of human type 2 diabetes.

Natural history of depression up to 18 years after stroke: a population-based South London Stroke Register study.

Background: Current evidence on the long-term natural history of post-stroke depression (PSD) is limited. We aim to determine the prevalence, incidence, duration and recurrence rates of depression to 18-years after stroke and assess differences by onset-time and depression severity. Methods: Data were from the South London Stroke Register (1995-2019, N = 6641 at registration). Depression was defined using the Hospital Anxiety and Depression scale (scores > 7 = depression) at 3-months, then annually to 18-years after stroke. We compared early- (3-months post-stroke) vs late-onset depression (1-year) and initial mild (HADS scores > 7) vs severe depression (scores > 10). Findings: 3864 patients were assessed for depression at any time-points during the follow-up (male:55.4% (2141), median age: 68.0 (20.4)), with the number ranging from 2293 at 1-year to 145 at 18-years after stroke. Prevalence of PSD ranged from 31.3% (28.9-33.8) to 41.5% (33.6-49.3). The cumulative incidence of depression was 59.4% (95% CI 57.8-60.9), of which 87.9% (86.5-89.2) occurred within 5-years after stroke. Of patients with incident PSD at 3-months after stroke, 46.6% (42.1-51.2) recovered after 1 year. Among those recovered, 66.7% (58.0-74.5) experienced recurrent depression and 94.4% (87.5-98.2) of recurrences occurred within 5-years since recovery. Similar estimates were observed in patients with PSD at 1-year. 34.3% (27.9-41.1) of patients with severe depression had recovered at the next time-point, compared to 56.7% (50.5-62.8) with mild depression. Recurrence rate at 1-year after recovery was higher in patients with severe depression (52.9% (35.1-70.2)) compared to mild depression (23.5% (14.1-35.4)) (difference: 29.4% (7.6-51.2), p = 0.003). Interpretation: Long-term depressive status may be established by 5-years post-onset. Early- and late-onset depression presented similar natural history, while severe depression had a longer duration and quicker recurrence than mild depression. These estimates were limited to alive patients completing the depression assessment, who tended to have less severe stroke than excluded patients, so may be underestimated and not generalizable to all stroke survivors. Funding: National Institute for Health and Care Research (NIHR202339).

Synthesis of self-supported NiCoFe(OH)x via fenton-like effect corrosion for highly efficient water oxidation.

Efficientandinexpensiveoxygenevolutionreaction(OER)catalysts are essential for the electrochemical splitting of water into hydrogen fuel. Herein, we have successfully synthesized NiCoFe(OH)x nanosheets on Ni-Fe foam (NFF) by exploiting the Fenton-like effect of Co2+ and S2O82- to corrode the NFF foam. The as-prepared NiCoFe(OH)x/NFF exhibits the porous structure with the interconnected nanosheets that are firmly bonded to the conductive substrate of NFF, thereby enhancing ions and charge transfer kinetics. The unique structure and composition of NiCoFe(OH)x/NFF result in the low overpotentials of 200 and 262 mV at current densities of 10 and 100 mA cm-2, respectively, as well as a low Tafel slope of 53.25 mV dec-1. In addition, NiCoFe(OH)x/NFF displays low overpotentials of 267 and 294 mV at a high current density of 100 mA cm-2 in simulated and real seawater, respectively. Furthermore, the assembled NiCoFe(OH)x//Pt/C water electrolysis cell has achieved a current density of 10 mA cm-2 at a low voltage of 1.49 V, and displayed the good stability with slight attenuation for 110 h. The high OER performance of NiCoFe(OH)x is attributed to the co-catalytic effect of the three metal ions and the interconnected porous nanosheet structure.

The ARIA trial protocol: a randomised controlled trial to assess the clinical, technical, and cost-effectiveness of a cloud-based, ARtificially Intelligent image fusion system in comparison to standard treatment to guide endovascular Aortic aneurysm repair.

BACKGROUND: Endovascular repair of aortic aneurysmal disease is established due to perceived advantages in patient survival, reduced postoperative complications, and shorter hospital lengths of stay. High spatial and contrast resolution 3D CT angiography images are used to plan the procedures and inform device selection and manufacture, but in standard care, the surgery is performed using image-guidance from 2D X-ray fluoroscopy with injection of nephrotoxic contrast material to visualise the blood vessels. This study aims to assess the benefit to patients, practitioners, and the health service of a novel image fusion medical device (Cydar EV), which allows this high-resolution 3D information to be available to operators at the time of surgery. METHODS: The trial is a multi-centre, open label, two-armed randomised controlled clinical trial of 340 patient, randomised 1:1 to either standard treatment in endovascular aneurysm repair or treatment using Cydar EV, a CE-marked medical device comprising of cloud computing, augmented intelligence, and computer vision. The primary outcome is procedural time, with secondary outcomes of procedural efficiency, technical effectiveness, patient outcomes, and cost-effectiveness. Patients with a clinical diagnosis of AAA or TAAA suitable for endovascular repair and able to provide written informed consent will be invited to participate. DISCUSSION: This trial is the first randomised controlled trial evaluating advanced image fusion technology in endovascular aortic surgery and is well placed to evaluate the effect of this technology on patient outcomes and cost to the NHS. TRIAL REGISTRATION: ISRCTN13832085. Dec. 3, 2021.

Development and Validation of a Deep-Learning Network for Detecting Congenital Heart Disease from Multi-View Multi-Modal Transthoracic Echocardiograms.

Early detection and treatment of congenital heart disease (CHD) can significantly improve the prognosis of children. However, inexperienced sonographers often face difficulties in recognizing CHD through transthoracic echocardiogram (TTE) images. In this study, 2-dimensional (2D) and Doppler TTEs of children collected from 2 clinical groups from Beijing Children's Hospital between 2018 and 2022 were analyzed, including views of apical 4 chamber, subxiphoid long-axis view of 2 atria, parasternal long-axis view of the left ventricle, parasternal short-axis view of aorta, and suprasternal long-axis view. A deep learning (DL) framework was developed to identify cardiac views, integrate information from various views and modalities, visualize the high-risk region, and predict the probability of the subject being normal or having an atrial septal defect (ASD) or a ventricular septaldefect (VSD). A total of 1,932 children (1,255 healthy controls, 292 ASDs, and 385 VSDs) were collected from 2 clinical groups. For view classification, the DL model reached a mean [SD] accuracy of 0.989 [0.001]. For CHD screening, the model using both 2D and Doppler TTEs with 5 views achieved a mean [SD] area under the receiver operating characteristic curve (AUC) of 0.996 [0.000] and an accuracy of 0.994 [0.002] for within-center evaluation while reaching a mean [SD] AUC of 0.990 [0.003] and an accuracy of 0.993 [0.001] for cross-center test set. For the classification of healthy, ASD, and VSD, the model reached the mean [SD] accuracy of 0.991 [0.002] and 0.986 [0.001] for within- and cross-center evaluation, respectively. The DL models aggregating TTEs with more modalities and scanning views attained superior performance to approximate that of experienced sonographers. The incorporation of multiple views and modalities of TTEs in the model enables accurate identification of children with CHD in a noninvasive manner, suggesting the potential to enhance CHD detection performance and simplify the screening process.

Cation-induced Ti3C2Tx MXene@melamine sponge aerogels with large layer spacing and high strength for high-performance supercapacitors.

The self-assembled aerogels are considered as an efficient strategy to address the aggregation and restacking of Ti3C2Tx MXene nanosheets for high-performance supercapacitors. However, the low mechanical strength of the MXene aerogel results in the structural collapse of the self-standing supercapacitor electrode materials. Herein, a low-cost melamine sponge (MS) absorbed different cations (H+, K+, Mg2+, Fe2+, Co2+, Ni2+ and Al3+), serves as a carrier and crosslinker for loading MXene hydrogel induced by the absorbed cations on the skeleton surface and the pores of MS, resulting in the high loading mass MXene aerogels with high mechanical strength. The experimental results show that the Mg-Ti3C2Tx@MS aerogel exhibits the maximum area capacitance of 702.22 mF cm-2 at 3 mA cm-2, and the area capacitance is still 603.12 mF cm-2 even at 100 mA cm-2, indicating the high rate capability with a capacitance retention of 85.89 %. It is worth noting that the constructed asymmetric supercapacitor with activated carbon achieves high energy densities of 104.53 µWh cm-2 and 93.87 µWh cm-2 at 800 µW cm-2 and 7999 µW cm-2, respectively. Furthermore, the asymmetric supercapacitor shows the high cycling stability with 90.2 % capacity retention after 10,000 cycles. This work provides a feasible strategy to prepare Ti3C2Tx MXene aerogels with large layer spacing and high strength for high-performance supercapacitors.

Facile synthesis of amorphous/crystalline Ni-Fe thiophenedicarboxylate coordination polymer nanobelts for efficient water oxidation.

The oxygen evolution reaction (OER) is a complex four-electron transfer process that poses a significant challenge to the efficient production of hydrogen through water splitting. However, developing non-noble metal electrocatalyst with excellent OER performance is still a big challenge. Herein, we propose a new strategy for the in-situ growth of two-dimensional amorphous/crystalline thiophene-based Ni-Fe metal-organic frameworks (MOFs) using Ni-Fe foam (NFF) as metal source and current collector, and thiophene-2,5-dicarboxylic acid (TDC) as corrosion agent and ligand. TDC was ionized at high temperature to produce H+ ions that etch NFF to release Ni2+ and Fe2+ ions, which were coordinated with TDC to in situ synthesize two-dimensional Ni-Fe thiophenedicarboxylate coordination polymer (NiFe-TDC) nanobelts on NFF. The unique structure and synergistic effect of Ni and Fe ions of NiFe-TDC0.05 result in the excellent OER performance with an overpotential of 224 and 256 mV at current densities of 10 and 100 mA cm-2, respectively, and it can run stably for 100 h at a current density of 100 mA cm-2, indicating the outstanding stability. Furthermore, NiFe-TDC0.05 remains the excellent OER performance with an extremely low potential of 196 and 271 mV at current densities of 10 and 100 mA cm-2 in seawater with 1 mol L-1 (M) KOH, respectively. The assembled NiFe-TDC0.05 || Pt/C water electrolysis cell achieves a current density of 100 mA cm-2 at a low voltage of 1.78 V. The work provides a new method to prepare two dimensional MOFs for efficient water oxidation.