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This study applies the Apriori algorithm to analyse patterns, syntactic structures, and thematic clusters in Chinese studies data from various genres. This study aims to identify recurring linguistic elements in order to shed light on the dynamic nature of the Chinese language across different contexts and time periods. The Apriori algorithm is used to identify frequent item sets and establish associations between linguistic constructs in large datasets (over 20 years). This study examines the complexity of the Chinese language by analysing co-occurrence patterns, syntactic tendencies, and thematic categorizations. This study examines the evolution of language, regional word choices, and cultural nuances. Thematic clusters and sensory associations establish the relationship between language and culture. The study of Chinese language patterns and cultural implications utilises data to advance computational linguistics and theory. Computational models prioritize cultural and historical context analysis for more comprehensive language processing. Theoretical implications help researchers understand language evolution and culture, while practical implications improve language technology tools. The conclusion provides support for research in computational linguistics, cultural studies, and linguistic theory-based holistic language analysis and application.

This study aims to track college students' on-task rate during the teaching process and to analyze the influence of instructional strategies on on-task rate through the aspects of observable and internal engagement indicators. Thirty-six undergraduate students at a higher education institution in China participated in the study. Students' behaviors and their EEG signals were recorded from fifty-one learning activities. Analyses have been focused on identifying the determinants of student's engagement levels and revealing the impacts of behavioral sequences and cognitive sequences on student's engagement levels. The results show that: (1) instructional strategies, classroom behaviors, and cognitive states were significant predictors of students' on-task rate; (2) the continuity of classroom behaviors improved the on-task rate; and (3) the standard deviations of attention and cognitive load were positively correlated with the on-task rate. This study describes a case of integrating multimodal data analysis in classroom teaching and discusses practical implications for improving classroom teaching.

Blended learning, integrating online and in-person components, has been increasingly adopted in higher education to enhance students' learning experience and outcomes. While the advantages of blended learning are well-evidenced, research has primarily focused on the online pre-learning component, neglecting the significance of in-class activities. In-class activities play a crucial role in affording active learning opportunities (e.g., discussion, elaboration), necessitating a systemic understanding of their dynamics. The purpose of this study was thus to systemically investigate college students' learning behaviors during in-class activities in a blended course. In-class activities were video-recorded and labelled manually following a coding scheme. By establishing a linear regression model, the study identified listening to the instructor's lecture and taking notes as two predictors of students' learning gains. Additionally, sequential patterns of learning behaviors during in-class activities were examined. The reciprocal interactions between students' behavior of listening to the lecture and their note-taking actions were noted. The findings of this study contributed to a systemic view of blended learning by shedding light on students' learning behaviors and their implications for instructional practice.

The COVID-19 pandemic has caused a wide range of psychological problems among parents and posed significant challenges to their mental health. However, there is a lack of research exploring the antecedents and consequences of parents' psychological distress during the pandemic. This study investigated the familial and individual antecedents and childrearing outcomes of psychological distress (depression, anxiety, worry, and loneliness) among 504 parents of preschool children in Zhengzhou, China. Research Findings: The results showed that both familial (family socioeconomic status, changes in family income during the pandemic, family physical health, and household chaos) and individual (resilience) factors were related to parents' symptoms of psychological distress. Loneliness was negatively related to parents' involvement in children's education, and feelings of worry were positively associated with increases in the parents' time spent engaging with children indoors (e.g. helping children with homework and disciplining children). Practice or Policy: The findings underscore the significance of identifying the risk factors of parents' psychological distress during the pandemic. They also have important implications for the design of parent- and family-based interventions to alleviate the adverse effects of the pandemic on parents' psychological distress and childrearing practices.

Blended learning has been widely integrated in college-level computer science education. Despite evidence about benefits of blended learning, students' in-class activities remain underexplored. To afford effective blended learning experience, supporting students in both modalities is essential. This study thus took an initial step to fill the gap by investigating college students' in-class activities in a blended course from the perspective of attention. Using non-intrusive electroencephalography (EEG) instruments to collect attentional data, this study found students' attention in in-class activities positively correlated with their learning gains. Students' attention also varied across in-class activities, reaching a higher level in group discussions than in pre-tests and lectures. Linear regression analysis indicated students' length of time spent viewing online resources and their pre-test scores significantly predicted their in-class attention. The findings of the study provide insight into course design and facilitation for effective blended computer science courses.

Abstract Hydrogels, provided that they integrate strength and toughness at desired high content of water, promise in load-bearing tissues such as articular cartilage, ligaments, tendons. Many developed strategies impart hydrogels with some mechanical properties akin to natural tissues, but compromise water content. Herein, a strategy deprotonation-complexation-reprotonation is proposed to prepare polyvinyl alcohol hydrogels with water content as high as ~80% and favorable mechanical properties, including tensile strength of 7.4 MPa, elongation of around 1350%, and fracture toughness of 12.4 kJ m−2. The key to water holding yet improved mechanical properties lies in controllable nucleation for refinement of crystalline morphology. With nearly constant water content, mechanical properties of as-prepared hydrogels are successfully tailored by tuning crystal nuclei density via deprotonation degree and their distribution uniformity via complexation temperature. This work provides a nucleation concept to design robust hydrogels with desired water content, holding implications for practical application in tissue engineering.

Abstract Dysnatremia is common in donors and recipients of liver transplantation (LT). However, the influence of dysnatremia on LT prognosis remains controversial. This study aimed to investigate effects of donors’ and recipients’ serum sodium on LT prognosis. We retrospectively reviewed 248 recipients who underwent orthotopic LT at our center between January 2016 and December 2018. Donors and recipients perioperative and 3-year postoperative clinical data were included. Delta serum sodium was defined as the donors’ serum sodium minus the paired recipients’ serum sodium. Donors with serum sodium > 145 mmol/L had significantly higher preoperative blood urea nitrogen (BUN) (P

Research on doping modification of ZnTiO3 ceramics to enhance microwave dielectric properties has been hindered by poor performance, unclear structure-function mechanisms. To expand the applicability of ZnTiO3 ceramics, this study explores Zn1–xLi2xTiO3 (0 ≤ x ≤ 1) ceramics using a phase engineering strategy. Our findings reveal that the introduction of Li+ into the ZnTiO3 system initiates a multiple phase transition, starting at x = 0.1. Initially, ilmenite ZnTiO3 transforms into a cubic ordered spinel phase (space group P4332). Subsequently, a transition to a disordered spinel phase (space group Fd3¯m) occurs at x = 0.5, culminating in the formation of a monoclinic rock salt-structured Li2TiO3 phase. Significantly, two sets of ceramics with near-zero temperature coefficients of resonance frequency (τf) were obtained at x = 0.1 and 0.75. Moreover, the quality factor (Q×f) demonstrated a 4.4-fold increase compared to that of ZnTiO3 ceramics at x = 0.25 (105,013 GHz). Additionally, it was observed that the Ti4+ polarization in Zn1−xLi2xTiO3 ceramics was underestimated by 11.3%–13.3%, causing the measured dielectric constant (εr) exceeding the theoretical dielectric constant (εth). The ionic polarizability of Ti4+ was adjusted to stabilize around 3.29 Å3. Evaluation using multiple methods, including Phillips–van Vechten–Levine (P–V–L) theory, Raman vibrational mode analysis, bond valence, bond energy theory, and octahedral distortion, confirms that the Ti–O bonds within the octahedron predominantly affect εr, the increasing lattice energy (U) contributes to the enhancement of Q×f, and the strengthened Li–O bond energy effectively regulates τf.

Abstract Objective To evaluate the clinical effectiveness of antibiotic bone cement combined with the lobulated perforator flap based on the descending branch of the lateral circumflex femoral artery (d-LCFA) in the treatment of infected traumatic tissue defects in the foot, in accordance with the Enhanced Recovery after Surgery (ERAS) concept. Methods From December 2019 to November 2022, 10 patients with infected traumatic tissue defects of the foot were treated with antibiotic bone cement combined with the d-LCFA lobulated perforator flap. The cohort comprised 6 males and 4 females, aged 21 to 67 years. Initial infection control was achieved through debridement and coverage with antibiotic bone cement, requiring one debridement in nine cases and two debridements in one case. Following infection control, the tissue defects were reconstructed utilizing the d-LCFA lobulated perforator flap, with the donor site closed primarily. The flap area ranged from 12 cm×6 cm to 31 cm×7 cm. Postoperative follow-up included evaluation of flap survival, donor site healing, and ambulatory function of the foot. Results The follow-up period ranged from 7 to 24 months, averaging 14 months. Infection control was achieved successfully in all cases. The flaps exhibited excellent survival rates and the donor site healed by first intention. Based on the American Orthopaedic Foot and Ankle Society (AOFAS) ankle-hindfoot scale, pain and function were evaluated as excellent in 3 cases, good in 5 cases, and moderate in 2 cases. Conclusion The application of antibiotic bone cement combined with the d-LCFA lobulated perforator flap is an effective treatment for infected traumatic tissue defects of the foot with the advantages of simplicity, high repeatability, and precise curative effects. The application of the d-LCFA lobulated perforator flap in wound repair causes minimal damage to the donor site, shortens hospital stays, lowers medical expenses, and accelerates patient rehabilitation, aligning with the ERAS concept. Therefore, it is a practice worth promoting in clinical use.

Abstract High myopia (HM) is a leading cause of blindness worldwide with currently no effective interventions available. A major hurdle lies in its often isolated perception as a purely ocular morbidity, disregarding potential systemic implications. Recent evidence suggests the existence of a gut-eye axis; however, the role of gut microbiota in the pathogenesis of HM remains largely unexplored. Herein, we provide a potential crosstalk among HM’s gut dysbiosis, microbial metabolites, and scleral remodeling. Utilizing 16S rRNA gene sequencing, we observed an altered gut microbiota profile in HM patients with a significant reduction in probiotic abundance compared with healthy controls. Subsequent targeted metabolic profiling revealed a notable decrease in plasma levels of the gut microbiota-derived metabolite indole-3-acetic acid (3-IAA) among HM patients, which is closely associated with the reduced probiotics, both negatively correlated with HM severity. Genetic analyses determined that gut microbiota are causally associated with myopia risk. Importantly, when mice subjected to HM modeling receive fecal microbiota transplantation from healthy donors, there is an increase in 3-IAA plasma levels and simultaneous retardation of HM progression along with better maintenance of collagen type I alpha 1 (COL1A1) expression in the sclera. Furthermore, 3-IAA gavage achieves similar effects. Mechanistic investigations confirm the transcriptional activation of COL1A1 by 3-IAA via promoting the enrichment of SP1 to its promoter. Together, our findings provide novel insights into the gut microbiota-eye axis in the pathogenesis of HM and propose new strategies for HM intervention by remodeling the gut microbiota and indole supplementation.

Abstract Characterizing the nature of hydrodynamical transport properties in quantum dynamics provides valuable insights into the fundamental understanding of exotic non-equilibrium phases of matter. Experimentally simulating infinite-temperature transport on large-scale complex quantum systems is of considerable interest. Here, using a controllable and coherent superconducting quantum simulator, we experimentally realize the analog quantum circuit, which can efficiently prepare the Haar-random states, and probe spin transport at infinite temperature. We observe diffusive spin transport during the unitary evolution of the ladder-type quantum simulator with ergodic dynamics. Moreover, we explore the transport properties of the systems subjected to strong disorder or a tilted potential, revealing signatures of anomalous subdiffusion in accompany with the breakdown of thermalization. Our work demonstrates a scalable method of probing infinite-temperature spin transport on analog quantum simulators, which paves the way to study other intriguing out-of-equilibrium phenomena from the perspective of transport.

ObjectiveTo optimize the energy capture efficiency of a rocker-type wave energy converter, the effects of the platform pillar wave diversion scheme and shape of finned floats on energy capture are studied.MethodsFirst, a hydrodynamic model of float motion is established. Next, the hydrodynamic characteristics of different finned floats are calculated using AQWA software and analyzed under different platform pillar wave diversion schemes, different frequency domain parameters such as added mass, radiation damping, wave excitation force and response amplitude operator (RAO), and different time domain parameters such as displacement, velocity, acceleration and excitation force. Finally, the energy-capture width ratios of different finned floats under different platform pillar wave diversion schemes are investigated.ResultsThe results show that different platform pillar wave diversion schemes have little effect on the frequency domain parameters of the finned floats or the float motion displacement of time domain parameters, but a large effect on the motion period. Energy capture is optimal at a fin angle of 100° under the double-pillar wave diversion scheme.ConclusionsBased on the proposed numerical simulation model, the hydrodynamic response of multi-degree-of-freedom finned floats in wave motion can be simulated accurately, providing useful references for the optimized design of the float shape for oscillating float-type wave energy generation platforms.

Abstract Nitrous acid (HONO), a key precursor of hydroxyl radicals (OH), is one of the factors affecting atmospheric chemistry and air quality. Currently, the proposed sources of HONO are not able to fully explain observed HONO concentrations. In this study, a comprehensive field observation of HONO was conducted in the autumn of 2021 in urban Beijing. The box model using a default Master Chemical Mechanism (MCM) was unable to reproduce the observed HONO concentrations with a normalized mean bias (NMB) of −92.8%. The NMB improved to −46.1% after the inclusion of seven additional HONO formation pathways. Several factors like vehicle emission factor (1.23%) and nocturnal NO2 heterogeneous uptake coefficient on the ground surface (8.25 × 10−6) were calculated based on observational data. The enhancement factor for nocturnal NO2 heterogeneous conversion was established as a function of relative humidity (RH) and incorporated into the model, which compensated for the missing nocturnal HONO sources and well-reproduced the observed HONO concentrations, with an NMB of −5.1%. The major source of HONO at night was found to be the heterogeneous reaction of NO2 on the ground surface, contributing up to 85.6%. During the daytime, it was the homogeneous reaction of NO with OH, accounting for 41.8%. The daytime primary source of OH was mainly the photolysis of HONO, which constituted 73.6% and therefore promoted the formation of secondary pollutants and exacerbated haze events.

Abstract A set of nine unique tobacco extract samples was analyzed using a self-developed electronic nose (E-nose) system, a commercial E-nose, and gas chromatography-mass spectrometry (GC–MS). The evaluation employed principal component analysis, statistical quality control, and soft independent modeling of class analogies (SIMCA). These multifaceted statistical methods scrutinized the collected data. Subsequently, a quality control model was devised to assess the stability of the sample quality. The results showed that the custom E-nose system could successfully distinguish between tobacco extracts with similar odors. After further training and the development of a quality control model for accepted tobacco extracts, it was possible to identify samples with normal and abnormal quality. To further validate our E-nose and extend its use within the tobacco industry, we collected and accurately classified the flavors of different tobacco leaf positions, with a remarkable accuracy rate of 0.9744. This finding facilitates the practical application of our E-nose system for the efficient identification of tobacco leaf positions.

Abstract Objectives Acute ischemic stroke (AIS) is caused by cerebral ischemia due to thrombosis in the blood vessel. The purpose of this study is to identify key genes related to metabolism to aid in the mechanism research and management of AIS. Materials and Methods Gene expression data were downloaded from the Gene Expression Omnibus database. Weighted gene co‐expression network analysis, Gene Ontology and kyoto encyclopedia of genes and genomes analysis were used to identify metabolism‐related genes that may be involved in the regulation of AIS. A protein protein interaction network was mapped using Cytoscape based on the STRING database. Subsequently, hub metabolism‐related genes were identified based on Cytoscape‐CytoNCA and Cytoscape‐MCODE plug‐ins. Least absolute shrinkage and selection operator algorithm and differential expression analysis. In addition, drug prediction, molecular docking, ceRNA network construction, and correlation analysis with immune cell infiltration were performed to explore their potential molecular mechanisms of action in AIS. Finally, the expression of hub gene was verified by real‐time PCR. Results Metabolism‐related genes FBL, HEATR1, HSPA8, MTMR4, NDUFC1, NDUFS8 and SNU13 were identified. The AUC values of FBL, HEATR1, HSPA8, MTMR4, NDUFS8 and SNU13 were all greater than 0.8, suggesting that they had good diagnostic accuracy. Correlation analysis found that their expression levels were also related to the infiltration levels of multiple immune cells, such as Activated.CD8.T.cell and Activated.dendritic.cell. It was found that only HSPA8 was successfully matched to drugs with literature support, and these drugs were acetaminophen, bupivacaine, dexamethasone, gentamicin, tretinoin and cisplatin. Moreover, it was also identified that the ENSG000000218510‐hsa‐miR‐330‐3p‐HEATR1 axis may be involved in regulating AIS. Conclusions The identification of FBL, HEATR1, HSPA8, MTMR4, NDUFC1, NDUFS8 and SNU13 provides a new research direction for exploring the molecular mechanisms of AIS, which can help in clinical management and diagnosis.

Abstract Background Dietary diversity has been suggested as a potential preventive measure against frailty in older adults, but the effect of changes in dietary diversity on frailty is unclear. This study was conducted to examine the association between the dietary diversity score (DDS) and frailty among older Chinese adults. Methods A total of 12,457 adults aged 65 years or older were enrolled from three consecutive and nonoverlapping cohorts from the Chinese Longitudinal Healthy Longevity Survey (the 2002 cohort, the 2005 cohort, and the 2008 cohort). DDS was calculated based on nine predefined food groups, and DDS changes were assessed by comparing scores at baseline and the first follow-up survey. We used 39 self-reported health items to assess frailty. Cox proportional hazard models were performed to examine the association between DDS change patterns and frailty. Results Participants with low-to-low DDS had the highest frailty incidence (111.1/1000 person-years), while high-to-high DDS had the lowest (41.1/1000 person-years). Compared to the high-to-high group of overall DDS pattern, participants in other DDS change patterns had a higher risk of frailty (HRs ranged from 1.25 to 2.15). Similar associations were observed for plant-based and animal-based DDS. Compared to stable DDS changes, participants with an extreme decline in DDS had an increased risk of frailty, with HRs of 1.38 (1.24, 1.53), 1.31 (1.19, 1.44), and 1.29 (1.16, 1.43) for overall, plant-based, and animal-based DDS, respectively. Conclusions Maintaining a lower DDS or having a large reduction in DDS was associated with a higher risk of frailty among Chinese older adults. These findings highlight the importance of improving a diverse diet across old age for preventing frailty in later life.

Abstract As the burgeoning field of Artificial Intelligence (AI) continues to permeate the fabric of healthcare, particularly in the realms of patient surveillance and telemedicine, a transformative era beckons. This manuscript endeavors to unravel the intricacies of recent AI advancements and their profound implications for reconceptualizing the delivery of medical care. Through the introduction of innovative instruments such as virtual assistant chatbots, wearable monitoring devices, predictive analytic models, personalized treatment regimens, and automated appointment systems, AI is not only amplifying the quality of care but also empowering patients and fostering a more interactive dynamic between the patient and the healthcare provider. Yet, this progressive infiltration of AI into the healthcare sphere grapples with a plethora of challenges hitherto unseen. The exigent issues of data security and privacy, the specter of algorithmic bias, the requisite adaptability of regulatory frameworks, and the matter of patient acceptance and trust in AI solutions demand immediate and thoughtful resolution .The importance of establishing stringent and far-reaching policies, ensuring technological impartiality, and cultivating patient confidence is paramount to ensure that AI-driven enhancements in healthcare service provision remain both ethically sound and efficient. In conclusion, we advocate for an expansion of research efforts aimed at navigating the ethical complexities inherent to a technology-evolving landscape, catalyzing policy innovation, and devising AI applications that are not only clinically effective but also earn the trust of the patient populace. By melding expertise across disciplines, we stand at the threshold of an era wherein AI's role in healthcare is both ethically unimpeachable and conducive to elevating the global health quotient.

Abstract Background Renal cell carcinoma (RCC) is a type of cancer that can develop at any point in adulthood, spanning the range of age-related changes that occur in the body. However, the specific molecular mechanisms underlying the connections between age and genetic mutations in RCC have not been extensively investigated. Methods Clinical and genetic data from patients diagnosed with RCC were collected from two prominent medical centers in China as well as the TCGA dataset. The patients were categorized into two groups based on their prognosticated age: young adults (YAs) and older adults (OAs). Univariate and multivariate analysis were employed to evaluate the relationships between age and genetic mutations. Furthermore, a mediation analysis was conducted to assess the association between age and overall survival, with genetic disparities serving as a mediator. Results Our analysis revealed significant differences in clinical presentation between YAs and OAs with RCC, including histopathological types, histopathological tumor stage, and sarcomatoid differentiation. YAs were found to have lower mutation burden and significantly mutated genes (SMGs) of RCC. However, we did not observe any significant differences between the two groups in terms of 10 canonical oncogenic signaling pathways-related genes mutation, telomerase-related genes (TRGs) mutation, copy number changes, and genetic mutations associated with clinically actionable targeted drugs. Importantly, we demonstrate superior survival outcomes in YAs, and we confirmed the mediating effect of genetic disparities on these survival outcome differences between YAs and OAs. Conclusion Our findings reveal previously unrecognized associations between age and the molecular underpinnings of RCC. These associations may serve as valuable insights to guide precision diagnostics and treatments for RCC.

Abstract Mechanochemistry studies the effect of mechanical force on chemical bonds, bringing opportunities for synthesizing alloys, ceramics, organics, polymers, and biomaterials. A vital issue of applying macro-scale mechanical force to manipulate crystal structures is finding ways to precisely adjust the force directions to break micro-scale target chemical bonds. Inspired by a common technique of driving a wedge into the wood to make wood chopping much easier, a wedging strategy of splitting three-dimensional structured crystalline frameworks and then converting them to nanosheets was proposed, where specific molecules were wedged into crystalline frameworks to drive the directional transmission of mechanical force to break chemical bonds. As a result, various crystalline framework nanosheets including metal−organic framework nanosheets, covalent organic framework nanosheets, and coordination polymer nanosheets were fabricated. This wedging crystal strategy exhibits advantages of operability, flexibility and designability, and furthermore, it is expected to expand mechanochemistry applications in material preparation.

Abstract The COVID-19 pandemic has imposed significant challenges on global health, emphasizing the persistent threat of large-scale infectious diseases in the future. This study addresses the need to enhance pooled testing efficiency for large populations. The common approach in pooled testing involves consolidating multiple test samples into a single tube to efficiently detect positivity at a lower cost. However, what is the optimal number of samples to be grouped together in order to minimize costs? i.e. allocating ten individuals per group may not be the most cost-effective strategy. In response, this paper introduces the hierarchical quotient space, an extension of fuzzy equivalence relations, as a method to optimize group allocations. In this study, we propose a cost-sensitive multi-granularity intelligent decision model to further minimize testing costs. This model considers both testing and collection costs, aiming to achieve the lowest total cost through optimal grouping at a single layer. Building upon this foundation, two multi-granularity models are proposed, exploring hierarchical group optimization. The experimental simulations were conducted using MATLAB R2022a on a desktop with Intel i5-10500 CPU and 8G RAM, considering scenarios with a fixed number of individuals and fixed positive probability. The main findings from our simulations demonstrate that the proposed models significantly enhance the efficiency and reduce the overall costs associated with pooled testing. For example, testing costs were reduced by nearly half when the optimal grouping strategy was applied, compared to the traditional method of grouping ten individuals. Additionally, the multi-granularity approach further optimized the hierarchical groupings, leading to substantial cost savings and improved testing efficiency.

Abstract Background Recently, the oral oncobacterium Fusobacterium nucleatum (F. nucleatum), has been linked with ulcerative colitis (UC). Here, we aim to investigate whether Fecal Microbiota Transplantation (FMT) can alleviate UC by restoring gut microbiota and eliminating oral-derived F. nucleatum and virulence factor fadA. Method C57BL/6J mice were randomly divided into a healthy control group (HC), Dextran Sulfate Sodium group (DSS), oral inoculation group (OR), upper FMT group (UFMT), and lower FMT group (LFMT). Disease activity index, body weight, survival rate, and histopathological scores were used to measure the severity of colitis. The function of the intestinal mucosal barrier was evaluated by performing immunohistochemical staining of the tight junction protein Occludin. Real-time PCR was used to assess the relative abundance of the nusG gene and the virulence gene fadA. Cytokine levels were detected by ELISA. Full-length sequencing of 16S rRNA was used to analyze the changes and composition of gut microbiota. Findings Oral incubation of F. nucleatum further exacerbated the severity of colitis and gut dysbiosis. Peptostreptococcaceae, Enterococcaceae, and Escherichia coli were significantly enriched in OR mice. However, LFMT mice showed an obvious decrease in disease activity and were more effective in restoring gut microbiota and eliminating F. nucleatum than UFMT mice. Bacteroidota, Lachnospiraceae, and Prevotellaceae were mainly enriched bacteria in LFMT mice. In addition, Genera such as Lactobacillus, Allobaculum, and Bacteroidales were found negative correlation with TNF-α, IL-1β, and IL-6. Genera like Romboutsia, Escherichia Shigella, Enterococcus, and Clostridium were found positively correlated with TNF-α, IL-1β, and IL-6. Conclusions Oral incubation of F. nucleatum further exacerbates the severity and dysbiosis in DSS-induced colitis mice. Besides, lower tract FMT can ameliorate colitis by restoring the gut microbiota diversity and eliminating F. nucleatum and virulence factor fadA.

Abstract Superparaelectrics are considered promising candidate materials for achieving superior energy storage capabilities. However, due to the complicated local structural design, simultaneously achieving high recoverable energy density (W rec) and energy storage efficiency (η) under high electric fields remains a challenge in bulk superparaelectrics. Here, we propose utilizing entropy engineering to disrupt long-range ferroic orders into local polymorphic distortion disorder with multiple BO6 tilt types and diverse heterogeneous polarization configurations. This strategy reduces the switching barriers, thereby facilitating the emergence of superparaelectric behaviors with ideal polarization forms. Furthermore, it enables high polarization response, negligible remnant polarization, delayed polarization saturation, and enhanced breakdown electric fields (E b) in high-entropy superparaelectrics. Consequently, an extraordinary W rec of 15.48 J cm–3 and an ultrahigh η of 90.02% are achieved at a high E b of 710 kV cm–1, surpassing the comprehensive energy storage performance of previously reported bulk superparaelectrics. This work demonstrates that entropy engineering is a viable strategy for designing high-performance superparaelectrics.

Abstract Background The triglyceride-glucose (TyG) index is linked to both the development and progression of diabetes, while obesity remains a significant risk factor for this disease. However, the relationship between the TyG index and overweight or obese diabetes remains unclear. Methods This study was a cross-sectional analysis of data from 40,633 participants with body mass index (BMI) ≥ 24 kg/m2 who were screened from January 2018 to December 2023 at Henan Provincial People’s Hospital. Participants were divided into groups of overweight or obese individuals with diabetes and those without diabetes according to the diabetes diagnostic criteria. The TyG index, the dependent variable, was determined using the equation ln [fasting triglycerides (mg/dL) × fasting glucose (mg/dL)/2]. We explored the association between TyG index and diabetes in overweight or obese individuals through multivariate logistic regression, subgroup analysis, generalized additive models, smoothed curve fitting, and analysis of threshold effects. Results Patients who were overweight or obese and had diabetes had higher TyG index levels than those without diabetes. After adjusting for confounders, our findings indicated a significant association between the TyG index and the risk of diabetes in overweight or obese individuals [odds ratio (OR) = 7.38, 95% confidence interval (CI): 6.98–7.81]. There was a J-shaped nonlinear association between TyG index and diabetes. When TyG index was > 4.46, the risk of diabetes increased sharply. Notably, a high baseline TyG index (Q4 group) correlated with a notably greater risk of diabetes than did the Q1 group, with an OR of 22.72 (95% CI: 20.52–25.16). Subgroup analysis revealed that the association between TyG and diabetes was stronger in females than in males (OR = 7.57, 95% CI: 6.76–8.48,), more significant in individuals with a BMI of 24–28 kg/m2 than in those with a BMI ≥ 28 kg/m2 (OR = 8.40, 95% CI: 7.83–9.02), and increased with age (OR = 8.15, 95% CI: 7.25–9.17) (all P for interaction 4.46. Furthermore, factors such as sex, age, and BMI significantly influence the risk of diabetes in overweight or obese individuals. Specifically, older women with a BMI of 24–28 kg/m2 are at a greater risk of diabetes under similar TyG index conditions.

Abstract The E‐proteinoid 3 receptor (PTGER3), a member of the prostaglandin E2 (PGE2) subtype receptor, belongs to the G‐protein‐coupled superfamily of receptors. Animal studies have demonstrated its involvement in salt sensitivity by regulating sodium reabsorption. This study aimed to investigate the association between genetic variants of PTGER3 and salt sensitivity, longitudinal blood pressure (BP) changes, and the incidence of hypertension in Chinese adults. A chronic salt intake intervention was conducted involving 514 adults from 124 families in the 2004 Baoji Salt‐Sensitivity Study Cohort in northern China. These participants followed a 3‐day regular baseline diet, followed by a 7‐day low‐salt diet (3.0 g/d) and a 7‐day high‐salt diet (18 g/d), and were subsequently followed for 14 years. The findings revealed a significant relationship between the single nucleotide polymorphism (SNP) rs17482751 of PTGER3 and diastolic blood pressure (DBP) response to high salt intervention. Additionally, SNPs rs11209733, rs3765894, and rs2268062 were significantly associated with longitudinal changes in systolic blood pressure (SBP), DBP, and mean arterial pressure (MAP) during the 14‐year follow‐up period. SNP rs6424414 was significantly associated with longitudinal changes in DBP over 14 years. Finally, SNP rs17482751 showed a significant correlation with the incidence of hypertension over 14 years. These results emphasize the significant role of PTGER3 gene polymorphism in salt sensitivity, longitudinal BP changes, and the development of hypertension in the Chinese population.

Abstract Sharply increased reactive oxygen species (ROS) are thought to induce oxidative stress, damage cell structure and cause cell death; however, its role in prostate cancer remains unclear. Enzalutamide is a widely used anti-prostate cancer drug that antagonizes androgen binding with its receptor. Further exploration of the mechanism and potential application strategies of enzalutamide is crucial for the treatment of prostate cancer. Here, we confirmed PEX10 can be induced by ROS activators while reduce ROS level in prostate cancer cells, which weakened the anti-tumor effect of ROS activators. The androgen receptor (AR) can promote the expression of PEX10 by acting as an enhancer in cooperation with FOXA1. The anti-tumor drug enzalutamide inhibits PEX10 by inhibiting the function of AR, and synergize with ROS activators ML210 or RSL3 to produce a stronger anti-tumor effect, thereby sensitizing cells to ROS activators. This study reveals a previously unrecognized function of enzalutamide and AR by regulating PEX10 and suggests a new strategy of enzalutamide application in prostate cancer treatment.

The Linxing gas field on the northeastern edge of Ordos Basin is mainly composed of multi-thin interbedded tight sandstone reservoirs. These reservoirs feature complex lithologies and low permeability, and are affected by multiple factors with unclear mechanisms, leading to difficulties in hydraulic fracturing operations and significant variability in operation outcomes. Therefore, this study designed and conducted a series of large-scale three-dimensional (3D) physical simulation experiments of hydraulic fracturing under different geological conditions, focusing on different rock components, clay contents, particle sizes, sedimentary cycles, and planar and longitudinal heterogeneities of the tight sandstone reservoirs in the Linxing gas field. According to the similarity criteria, the basic parameters of the experiments were determined by referencing the triaxial geostress, rock strength, wellbore structural parameters, and on-site fracturing operational parameters of the Permian Shihezi Formation. Based on the characteristics of the main reservoirs in typical wells of the Linxing gas field, 15 cubic rock cores were produced to account for different rock components, clay contents, particle sizes, sedimentary cycle combinations, and planar and longitudinal heterogeneity combinations. Fifteen sets of hydraulic fracturing simulation experiments were conducted, and the main controlling factors affecting the propagation of hydraulic fractures were summarized by analyzing the injection pressure curves and observing the fracture surfaces of rock samples. The results indicate that rock minerals, particle sizes, sedimentary cycles, and planar and longitudinal heterogeneities have a significant impact on fracture propagation patterns in tight reservoirs. The fracture surfaces are more prone to buckling with larger sandstone particle sizes, weaker cementation, higher clay content, and stronger planar heterogeneity, increasing the expansion pressure and difficulty in sand addition. Sedimentary cycles facilitate hydraulic fractures to propagate along the cycle planes, resulting in horizontal fractures. The difficulty of breaking through in retrograde cycle interfaces is greater than in prograde cycles. Interfaces between sand and mud layers, sand and coal layers, and natural weak sandstone surfaces are easily activated, leading to "工" or "T" shaped fractures. A combination of "工", "T", and "十" shaped fractures may occur in sand-mud multi-thin interlayers. This experimental study reveals the propagation patterns of hydraulic fractures under different geological conditions, providing insights for research in similar blocks.

Abstract Rock strength is imperative for the design and stability analysis of engineering structures. The Mohr–Coulomb (M-C) criterion holds significant prominence in geotechnical engineering. However, the M-C criterion fails to accurately capture the nonlinear strength response and neglects the critical state of rocks, potentially leading to inaccuracies in the design phase of deep engineering projects. This study introduces an innovative stress-dependent friction angle and cohesion (SFC) for the M-C criterion to capture the nonlinear strength responses of intact rocks, spanning from non-critical to critical states (brittle to ductile regions). A novel method for determining these stress-dependent parameters at each corresponding $$\sigma_{3}$$ σ 3 is initially introduced. Subsequently, an examination of the confinement dependency of the friction angle and cohesion is conducted, leading to the derivation of the SFC model. The SFC-enhanced M-C criterion, utilizing parameters obtained from triaxial tests under lower $$\sigma_{3}$$ σ 3 , demonstrates the capability to delineate the complete non-linear strength envelope from brittle to ductile regions. Validation through triaxial test data confirms that the predictions of the SFC-enhanced M-C criterion accurately correspond to the strength characteristics of the tested rocks.

Abstract Skillful subseasonal forecasts are crucial for various sectors of society but pose a grand scientific challenge. Recently, machine learning-based weather forecasting models outperform the most successful numerical weather predictions generated by the European Centre for Medium-Range Weather Forecasts (ECMWF), but have not yet surpassed conventional models at subseasonal timescales. This paper introduces FuXi Subseasonal-to-Seasonal (FuXi-S2S), a machine learning model that provides global daily mean forecasts up to 42 days, encompassing five upper-air atmospheric variables at 13 pressure levels and 11 surface variables. FuXi-S2S, trained on 72 years of daily statistics from ECMWF ERA5 reanalysis data, outperforms the ECMWF’s state-of-the-art Subseasonal-to-Seasonal model in ensemble mean and ensemble forecasts for total precipitation and outgoing longwave radiation, notably enhancing global precipitation forecast. The improved performance of FuXi-S2S can be primarily attributed to its superior capability to capture forecast uncertainty and accurately predict the Madden-Julian Oscillation (MJO), extending the skillful MJO prediction from 30 days to 36 days. Moreover, FuXi-S2S not only captures realistic teleconnections associated with the MJO but also emerges as a valuable tool for discovering precursor signals, offering researchers insights and potentially establishing a new paradigm in Earth system science research.

Abstract Background Atherogenic index of plasma (AIP), a marker of atherosclerosis and cardiovascular disease (CVD). However, few studies have investigated association between AIP and all-cause mortality and specific-mortality in the general population. Methods This study included data from 14,063 American adults. The exposure variable was the AIP, which was defined as log10 (triglycerides/high-density lipoprotein cholesterol). The outcome variables included all-cause mortality and specific-mortality. Survey-weighted cox regressions were performed to evaluate the relation between AIP and all-cause mortality and specific-mortality. Weighted restricted cubic spline was conducted to examin the non-linear relationship. Results During 10 years of follow-up, we documented 2,077, 262, 854, and 476 cases of all-cause mortality, diabetes mortality, CVD mortality and cancer mortality, respectively. After adjustment for potential confounders, we found that atherogenic index of plasma (AIP) was significantly associated with an increased risk of diabetes mortality when comparing the highest to the lowest quantile of AIP in female (p for trend = 0.001) or participants older than 65 years (p for trend = 0.002). AIP was not significantly associated with all-cause mortality, CVD mortality and cancer mortality (p > 0.05). Moreover, a non-linear association was observed between AIP and all-cause mortality in a U-shape (p for non-linear = 0.0011), while a linear relationship was observed with diabetes mortality and non-diabetes mortality (p for linear

Abstract Limited studies have focused on the prognostic factors of esophageal respiratory fistula (ERF) associated with radiotherapy in patients with unresectable esophageal squamous cell carcinoma (ESCC). Between January 1st, 2014 and January 1st, 2021, we included patients who were initially diagnosed with unresectable ESCC and underwent radiotherapy. All patients were followed up for a period of 2 years after completing their radiotherapy treatment. The primary outcomes of the study were defined as death or severe adverse events. The survival curves of ERF were calculated using the Kaplan–Meier method. Cox proportional hazards model was employed to calculated the prognostic factors. A cohort of 232 patients underwent radiotherapy, of whom 32 patients experienced ERF. The median period from initial diagnosis of ESCC to ERF was 5.75 months, and the median period from ERF to the primary outcome was 4.6 weeks. Neck + upper chest location (odds ratio [OR] 3.305), high T stage (OR 1.765), esophageal stenosis (OR 1.073), high neutrophil to lymphocyte ratio (NLR) (OR 1.384) and platelet to lymphocyte ratio (PLR) (OR 1.765) were risk factors for the occurrence of ERF. Cox regression analysis suggested that tumor location (hazards ratio [HR] 3.572, 95% confidence interval [CI] 2.467–5.1), high T stage (HR 4.050, 95% CI 2.812–5.831), esophageal stenosis (HR 2.643, 95% CI 1.753–3.983), high PLR (HR 2.541, 95% CI 1.868–3.177) were independent prognostic factors for poor survival. Esophageal stenosis, neck + upper chest tumor location, high T stage and PLR predicted the prognosis of ERF in ESCC patients undergoing radiotherapy.

Abstract Calculus equations serve as fundamental frameworks in mathematics, enabling describing an extensive range of natural phenomena and scientific principles, such as thermodynamics and electromagnetics. Analog computing with electromagnetic waves presents an intriguing opportunity to solve calculus equations with unparalleled speed, while facing an inevitable tradeoff in computing density and equation reconfigurability. Here, we propose a reconfigurable metamaterial processing unit (MPU) that solves arbitrary linear calculus equations at a very fast speed. Subwavelength kernels based on inverse-designed pixel metamaterials are used to perform calculus operations on time-domain signals. In addition, feedback mechanisms and reconfigurable components are used to formulate and solve calculus equations with different orders and coefficients. A prototype of this MPU with a compact planar size of 0.93λ0×0.93λ0 (λ0 is the free-space wavelength) is constructed and evaluated in microwave frequencies. Experimental results demonstrate the MPU’s ability to successfully solve arbitrary linear calculus equations. With the merits of compactness, easy integration, reconfigurability, and reusability, the proposed MPU provides a potential route for integrated analog computing with high speed of signal processing.

Abstract Head and neck squamous carcinoma (HNSC) is a prevalent malignant disease, with the majority of patients being diagnosed at an advanced stage. Endoplasmic reticulum stress (ERS) is considered to be a process that promotes tumorigenesis and impacts the tumor microenvironment (TME) in various cancers. The study aims to investigate the predictive value of ERS in HNSC and explore the correlation between ERS-related genes and TME. A series of bioinformatics analyses were carried out based on mRNA and scRNA-seq data from the TCGA and GEO databases. We conducted RT-qPCR and western blot to validate the signature, and performed cell functional experiments to investigate the in vitro biological functions of the gene. We identified 63 ERS-related genes that were associated with outcome and stage in HNSC. A three-gene signature (ATF6, TRIB3, and UBXN6) was developed, which presents predictive value in the prognosis and immunotherapy response of HNSC patients. The high-risk group exhibited a worse prognosis but may benefit from immunotherapy. Furthermore, there was a significant correlation between the signature and immune infiltration. In the high-risk group, fibroblasts were more active in intercellular communication, and more T cells were observed at the end of the sequential phase. The genes in the ERS-related signature were overexpressed in HNSC cells, and the knockdown of TRIB3 significantly inhibited cell proliferation and migration. This study established a novel ERS-related signature that has potential implications for HNSC therapy and the understanding of TME.

Abstract The proficient handling of diabetic wounds, a rising issue coinciding with the global escalation of diabetes cases, poses significant clinical difficulties. A range of biofunctional dressings have been engineered and produced to expedite the healing process of diabetic wounds. This study proposes a multifunctional hydrogel dressing for diabetic wound healing, which is composed of Polyvinyl Alcohol (PVA) and N1-(4-boronobenzyl)-N3-(4-boronophenyl)-N1, N1, N3, N3-teramethylpropane-1, 3-diaminium (TSPBA), and a dual-drug loaded Gelatin methacryloyl (GM) microgel. The GM microgel is loaded with sodium fusidate (SF) and nanoliposomes (LP) that contain metformin hydrochloride (MH). Notably, adhesive and self-healing properties the hydrogel enhance their therapeutic potential and ease of application. In vitro assessments indicate that SF-infused hydrogel can eliminate more than 98% of bacteria within 24 h and maintain a sustained release over 15 days. Additionally, MH incorporated within the hydrogel has demonstrated effective glucose level regulation for a duration exceeding 15 days. The hydrogel demonstrates a sustained ability to neutralize ROS throughout the entire healing process, predominantly by electron donation and sequestration. This multifunctional hydrogel dressing, which integrated biological functions of efficient bactericidal activity against both MSSA and MRSA strains, blood glucose modulation, and control of active oxygen levels, has successfully promoted the healing of diabetic wounds in rats in 14 days. The hydrogel dressing exhibited significant effectiveness in facilitating the healing process of diabetic wounds, highlighting its considerable promise for clinical translation. Graphical Abstract

Abstract Hydrogen sulfide (H2S) has emerged as a novel endogenous gas signaling molecule, joining the ranks of nitric oxide (NO) and carbon monoxide (CO). Recent research has highlighted its involvement in various physiological processes, such as promoting root organogenesis, regulating stomatal movement and photosynthesis, and enhancing plant growth, development, and stress resistance. Tobacco, a significant cash crop crucial for farmers’ economic income, relies heavily on root development to affect leaf growth, disease resistance, chemical composition, and yield. Despite its importance, there remains a scarcity of studies investigating the role of H2S in promoting tobacco growth. This study exposed tobacco seedlings to different concentrations of NaHS (an exogenous H2S donor) − 0, 200, 400, 600, and 800 mg/L. Results indicated a positive correlation between NaHS concentration and root length, wet weight, root activity, and antioxidant enzymatic activities (CAT, SOD, and POD) in tobacco roots. Transcriptomic and metabolomic analyses revealed that treatment with 600 mg/L NaHS significantly effected 162 key genes, 44 key enzymes, and two metabolic pathways (brassinosteroid synthesis and aspartate biosynthesis) in tobacco seedlings. The addition of exogenous NaHS not only promoted tobacco root development but also potentially reduced pesticide usage, contributing to a more sustainable ecological environment. Overall, this study sheds light on the primary metabolic pathways involved in tobacco root response to NaHS, offering new genetic insights for future investigations into plant root development.

Abstract Steroid-induced osteonecrosis of the femoral head (SONFH) is the predominant cause of non-traumatic osteonecrosis of the femoral head (ONFH). Impaired blood supply and reduced osteogenic activity of the femoral head are the key pathogenic mechanisms of SONFH. Fibroblast growth factor 23 (FGF23) levels are not only a biomarker for early vascular lesions caused by abnormal mineral metabolism, but can also act directly on the peripheral vascular system, leading to vascular pathology. The aim of this study was to observe the role of FGF23 on bone microarchitecture and vascular endothelium, and to investigate activation of pyroptosis in SONFH. Lipopolysaccharide (LPS) combined with methylprednisolone (MPS) was applied for SONFH mouse models, and adenovirus was used to increase or decrease the level of FGF23. Micro-CT and histopathological staining were used to observe the structure of the femoral head, and immunohistochemical staining was used to observe the vascular density. The cells were further cultured in vitro and placed in a hypoxic environment for 12 h to simulate the microenvironment of vascular injury during SONFH. The effect of FGF23 on osteogenic differentiation was evaluated using alkaline phosphatase staining, alizarin red S staining and expression of bone formation-related proteins. Matrigel tube formation assay in vitro and immunofluorescence were used to detect the ability of FGF23 to affect endothelial cell angiogenesis. Steroids activated the pyroptosis signaling pathway, promoted the secretion of inflammatory factors in SONFH models, led to vascular endothelial dysfunction and damaged the femoral head structure. In addition, FGF23 inhibited the HUVECs angiogenesis and BMSCs osteogenic differentiation. FGF23 silencing attenuated steroid-induced osteonecrosis of the femoral head by inhibiting the pyroptosis signaling pathway, and promoting osteogenic differentiation of BMSCs and angiogenesis of HUVECs in vitro.

Abstract Cancer is rarely the straightforward consequence of an abnormality in a single gene, but rather reflects a complex interplay of many genes, represented as gene modules. Here, we leverage the recent advances of model-agnostic interpretation approach and develop CGMega, an explainable and graph attention-based deep learning framework to perform cancer gene module dissection. CGMega outperforms current approaches in cancer gene prediction, and it provides a promising approach to integrate multi-omics information. We apply CGMega to breast cancer cell line and acute myeloid leukemia (AML) patients, and we uncover the high-order gene module formed by ErbB family and tumor factors NRG1, PPM1A and DLG2. We identify 396 candidate AML genes, and observe the enrichment of either known AML genes or candidate AML genes in a single gene module. We also identify patient-specific AML genes and associated gene modules. Together, these results indicate that CGMega can be used to dissect cancer gene modules, and provide high-order mechanistic insights into cancer development and heterogeneity.

Abstract Background To explore and compare the values of 3.0T magnetic resonance imaging (MRI) T2 mapping in evaluating the degree of acetabular cartilage degeneration in hip replacement surgery. Methods A total of 26 elderly patients with femoral neck fractures who were scanned in 3.0T MRI T2 mapping quantification technique were included. Basing on MRI images, the degree of acetabular cartilage degeneration was classified into Grade 0, 1, 2, 3 and 4, according to the International Cartilage Repair Society (ICRS) scores. In addition, 8 healthy volunteers were included for control group. Results By comparison with health population, T2 relaxation values in the anterior, superior, and posterior regions of acetabular cartilage in patients with femoral neck fracture were obviously increased (P 0.05). Importantly, acetabular cartilage degeneration can be detected through signal changes of T2 mapping pseudo-color images. Conclusion 3.0T MRI T2 mapping technology can be used to determine the degree of acetabular cartilage degeneration, which can effectively monitor the disease course.

Abstract All-solid-state batteries (ASSBs) are promising alternatives to conventional lithium-ion batteries. ASSBs consist of solid-fast-ion-conducting electrolytes and electrodes that offer improved energy density, battery safety, specific power, and fast-charging capability. Despite decades of intensive research, only a few have high ionic conductivity at ambient temperature. Developing fast ion-conducting materials requires both synthesis of high-conducting materials and a fundamental understanding of ion transport mechanisms. However, this is challenging due to wide variations of the ionic conductivity, even within the same class of materials, indicating the strong influence of structural modifications on ion transport. This Review discusses three selected material classes, namely layered oxides, polyhedral connections, and cluster anion types, as promising fast ion conductors. Emphasis is placed on the inherent challenges and the role of the framework structure on mobile ion conduction. We elucidate strategies to address these challenges by leveraging theoretical frameworks and insights from materials science.

Abstract The oversized TE11 mode bend is able to make the transmission direction of electromagnetic wave to turn 90°, and it is one of the key components in the high‐power microwave system. The mode coupling characteristics between the TE11 and parasitic modes under two different polarisations in the bending waveguide are analysed, and it is found that the TE11 suffers less interferences from parasitic modes when its polarisation direction is perpendicular to the bending plane, and the corresponding 90° TE11 bend is easier to realise high performance. To verify this analysis, an oversized 90° TE11 bend waveguide working at 10 GHz is designed, and its structural length is only 7.5 times the central working wavelength. Simulated results indicate that its relative bandwidth is 15.6% when the transmission efficiency is over 98%, and its maximum power handling capacity reaches 5.6 GW at short microwave pulse duration (less than 100 ns). The S‐parameters indicate that its S21 is about −0.1 dB from 9.5 to 10.5 GHz, and its S11 is under −25 dB in the same frequency range. Meanwhile, the high power test indicates that the bend works stably when the injected power is 3 GW.

Abstract Background Clinical imaging tools to probe aggressiveness of renal masses are lacking, and T2-weighted imaging as an integral part of magnetic resonance imaging protocol only provides qualitative information. We developed high-resolution and accelerated T2 mapping methods based on echo merging and using k-t undersampling and reduced flip angles (TEMPURA) and tested their potential to quantify differences between renal tumour subtypes and grades. Methods Twenty-four patients with treatment-naïve renal tumours were imaged: seven renal oncocytomas (RO); one eosinophilic/oncocytic renal cell carcinoma; two chromophobe RCCs (chRCC); three papillary RCCs (pRCC); and twelve clear cell RCCs (ccRCC). Median, kurtosis, and skewness of T2 were quantified in tumours and in the normal-adjacent kidney cortex and were compared across renal tumour subtypes and between ccRCC grades. Results High-resolution TEMPURA depicted the tumour structure at improved resolution compared to conventional T2-weighted imaging. The lowest median T2 values were present in pRCC (high-resolution, 51 ms; accelerated, 45 ms), which was significantly lower than RO (high-resolution; accelerated, p = 0.012) and ccRCC (high-resolution, p = 0.019; accelerated, p = 0.008). ROs showed the lowest kurtosis (high-resolution, 3.4; accelerated, 4.0), suggestive of low intratumoural heterogeneity. Lower T2 values were observed in higher compared to lower grade ccRCCs (grades 2, 3 and 4 on high-resolution, 209 ms, 151 ms, and 106 ms; on accelerated, 172 ms, 160 ms, and 102 ms, respectively), with accelerated TEMPURA showing statistical significance in comparison (p = 0.037). Conclusions Both high-resolution and accelerated TEMPURA showed marked potential to quantify differences across renal tumour subtypes and between ccRCC grades. Trial registration ClinicalTrials.gov, NCT03741426 . Registered on 13 November 2018. Relevance statement The newly developed T2 mapping methods have improved resolution, shorter acquisition times, and promising quantifiable readouts to characterise incidental renal masses. Graphical Abstract

Abstract We previously identified that serum EFNA1 and MMP13 were potential biomarker for early detection of esophageal squamous cell carcinoma. In this study, our aim is to explore the diagnostic value of serum EFNA1 and MMP13 for gastric cancer. We used enzyme-linked immunosorbent assay (ELISA) to detect the expression levels of serum EFNA1 and MMP13 in 210 GCs and 223 normal controls. The diagnostic value of EFNA1 and MMP13 was evaluated in an independent cohorts of GC patients and normal controls (n = 238 and 195, respectively). Receiver operating characteristics were used to calculate diagnostic accuracy. In training and validation cohorts, serum EFNA1 and MMP13 levels in the GC groups were significantly higher than those in the normal controls (P

Abstract Electrochemical urea oxidation offers a sustainable avenue for H2 production and wastewater denitrification within the water-energy nexus; however, its wide application is limited by detrimental cyanate or nitrite production instead of innocuous N2. Herein we demonstrate that atomically isolated asymmetric Ni–O–Ti sites on Ti foam anode achieve a N2 selectivity of 99%, surpassing the connected symmetric Ni–O–Ni counterparts in documented Ni-based electrocatalysts with N2 selectivity below 55%, and also deliver a H2 evolution rate of 22.0 mL h–1 when coupled to a Pt counter cathode under 213 mA cm–2 at 1.40 VRHE. These asymmetric sites, featuring oxygenophilic Ti adjacent to Ni, favor interaction with the carbonyl over amino groups in urea, thus preventing premature resonant C⎓N bond breakage before intramolecular N–N coupling towards N2 evolution. A prototype device powered by a commercial Si photovoltaic cell is further developed for solar-powered on-site urine processing and decentralized H2 production.