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In this work, a series of cationic luminogens (designated as PSMP isomers) were developed based on the cyano positional isomerism strategy. The isomerism of the cyano substituent on the molecular skeleton can finely regulate the optical behaviour, the type of photoinduced reactive oxygen species (ROS), and mitochondria-targeted capability of isomers. Interestingly, PSMP-4, with the cyano group installed at an appropriate location, exhibits a special aggregation-induced emission effect and potent O2˙− generation efficacy through the type I photochemistry pathway. Notably, PSMP-4 can accumulate in mitochondria with high specificity. Taking advantage of its excellent photostability, PSMP-4 realizes in situ mitochondria imaging in a washing-free manner and sensitive response to the change of mitochondrial membrane potential. The integration of comprehensive photophysical properties and mitochondrial specificity enable PSMP-4 to successfully trigger the death of cancer cells through an efficient type I photodynamic therapy process both in vitro and in multicellular tumor spheroid models. [ABSTRACT FROM AUTHOR]

Background: Bioterrorism is an important topic in the field of biosecurity. Nurses, the largest group of healthcare workers, play a critical role in addressing the threat of bioterrorism. This study aimed to examine the present level of bioterrorism knowledge, attitudes, and practices among nurses. It also explored the relationships among bioterrorism knowledge, attitudes, and practices, as well as demographic variables that influence the scores of each dimension. Methods: A descriptive correlational research design was conducted using a convenience sample of 429 nurses in five tertiary general hospitals in Tianjin. Registered nurses with six months or more of work experience, currently still working in hospitals, and volunteering to participate in the study are included; otherwise, they are excluded. A structured questionnaire with four components was used: sociodemographic characteristics, knowledge of bioterrorism, attitudes toward bioterrorism, and practices related to bioterrorism. The acquired data were analyzed using the Mann‒Whitney test, Kruskal‒Wallis test, Spearman correlation analysis, and multiple linear regression. This study followed the STROBE guidelines. Results: The study ultimately included 429 valid surveys. The mean score for bioterrorism knowledge was satisfactory (33.06 ± 4.87), the mean score for bioterrorism attitudes was good (23.83 ± 5.23), and the mean score for bioterrorism practices was poor (10.94 ± 6.51). There was a significant negative correlation between bioterrorism knowledge and attitudes (r=-0.38, p < 0.01), knowledge and practices (r=-0.42, p < 0.01). Bioterrorism practices were significantly positively correlated with attitudes (r = 0.21, p < 0.01). Educational level (β = 0.17, p < 0.001), years of experience (β = 0.26, p < 0.001), and previous bioterrorism education (β = 0.19, p < 0.001) influenced the bioterrorism knowledge score. Gender (β=-0.21, p < 0.001), educational level (β = 0.10, p < 0.05), and previous bioterrorism education (β = 0.22, p < 0.001) affected the bioterrorism attitude score. Years of experience (β=-0.28, p < 0.001) and previous bioterrorism education (β = 0.13, p < 0.01) had an impact on the practice score. Conclusions: Knowledge of bioterrorism was significantly negatively correlated with attitudes and practices, which could be attributed to the specificity of bioterrorism itself. To improve nurses' bioterrorism preparedness, continuing medical education efforts must be strengthened, as well as regular delivery of bioterrorism-specific training and drills. [ABSTRACT FROM AUTHOR]

The device performance of deep‐blue perovskite light‐emitting diodes (PeLEDs) is primarily constrained by low external quantum efficiency (EQE) especially poor operational stability. Herein, we develop a facile strategy to improve deep‐blue emission through rational interface engineering. We innovatively reported the novel electron transport material, 4,6‐Tris(4‐(diphenylphosphoryl)phenyl)‐1,3,5‐triazine (P‐POT2T), and utilized a sequential wet‐dry deposition method to form the homogenic gradient interface between electron transport layer (ETL) and perovskite surface. Unlike previous reports that achieved carrier injection balance by inserting new interlayers, our strategy not only passivated uncoordinated Pb2+ in the perovskite via P=O functional groups but also reduced interfacial carrier recombination without introducing new interfaces. Additionally, this strategy enhanced the interface contact between the perovskite and ETL, significantly boosting device stability. Consequently, the fabricated deep‐blue PeLEDs delivered an EQE exceeding 5 % (@ 460 nm) with an exceptional halftime extended to 31.3 minutes. This straightforward approach offers a new strategy to realize highly efficient especially stable PeLEDs. [ABSTRACT FROM AUTHOR]

The device performance of deep‐blue perovskite light‐emitting diodes (PeLEDs) is primarily constrained by low external quantum efficiency (EQE) especially poor operational stability. Herein, we develop a facile strategy to improve deep‐blue emission through rational interface engineering. We innovatively reported the novel electron transport material, 4,6‐Tris(4‐(diphenylphosphoryl)phenyl)‐1,3,5‐triazine (P‐POT2T), and utilized a sequential wet‐dry deposition method to form the homogenic gradient interface between electron transport layer (ETL) and perovskite surface. Unlike previous reports that achieved carrier injection balance by inserting new interlayers, our strategy not only passivated uncoordinated Pb2+ in the perovskite via P=O functional groups but also reduced interfacial carrier recombination without introducing new interfaces. Additionally, this strategy enhanced the interface contact between the perovskite and ETL, significantly boosting device stability. Consequently, the fabricated deep‐blue PeLEDs delivered an EQE exceeding 5 % (@ 460 nm) with an exceptional halftime extended to 31.3 minutes. This straightforward approach offers a new strategy to realize highly efficient especially stable PeLEDs. [ABSTRACT FROM AUTHOR]

Background: Clinical observations have recently shown that Abelmoschus manihot (L.) in the form of Huangkui capsule (HKC) and in combination with irbesartan (EB) is an effective therapy for diabetic nephropathy (DN) in patients with type 2 diabetes (T2D). The present study aims to explore the mechanisms underlying the therapeutic efficacies of HKC and its combination with EB in DN via the gut-kidney axis. Methods: HKC, EB, and their combination or vehicle were administered in db/db mice, which is an animal model for the study of T2D and DN. Comparative analyses of the gut microbiota, serum metabolites, and kidney transcriptomics before and after drug administration were performed. Results: After treatment with HKC, EB, and their combination for 4 weeks, the urinary albumin-to-creatinine ratios decreased significantly in the db/db mice with DN. In terms of the gut microbiota, the abundances of Faecalitalea, Blautia, and Streptococcus increased but those of Bacteroidetes, Firmicutes, Enterobacteriaceae, and Desulfovibrio decreased. Parallelly, serum metabolites, mainly including quercetin 3′-glucuronide and L-dopa, were elevated while cortisol and cytochalasin B were reduced. Furthermore, the S100a8 , S100a9 , Trem1 , and Mmp7 genes in the kidneys were downregulated. These altered elements were associated with proteinuria/albuminuria reduction. However, EB had no effects on the changes in blood pressure and specific differentially expressed genes in the kidneys. Conclusion: The present study provides experimental evidence that HKC regulates the gut microbiota, circulating metabolites, and renal gene activities, which are useful for better understanding of the action mechanisms of A. manihot in the treatment of DN through the gut-kidney axis. [ABSTRACT FROM AUTHOR]

Background: Follicular atresia significantly impairs female fertility and hastens reproductive senescence. Apoptosis of granulosa cells is the primary cause of follicular atresia. Pyroptosis and necroptosis, as additional forms of programmed cell death, have been reported in mammalian cells. However, the understanding of pyroptosis and necroptosis pathways in granulosa cells during follicular atresia remains unclear. This study explored the effects of programmed cell death in granulosa cells on follicular atresia and the underlying mechanisms. Results: The results revealed that granulosa cells undergo programmed cell death including apoptosis, pyroptosis, and necroptosis during follicular atresia. For the first time, we identified the formation of a PANoptosome complex in porcine granulosa cells. This complex was initially identified as being composed of ZBP1, RIPK3, and RIPK1, and is recruited through the RHIM domain. Additionally, we demonstrated that caspase-6 is activated and cleaved, interacting with RIPK3 as a component of the PANoptosome. Heat stress may exacerbate the activation of the PANoptosome, leading to programmed cell death in granulosa cells. Conclusions: Our data identified the formation of a PANoptosome complex that promoted programmed cell death in granulosa cells during the process of follicular atresia. These findings provide new insights into the molecular mechanisms underlying follicular atresia. [ABSTRACT FROM AUTHOR]

Introduction: Effective management of epilepsy in working-age patients is essential to reduce the burden on individuals, families, and communities. This study aimed to assess the long-term efficacy of phenobarbital (PB) in working-age patients with epilepsy in rural Northeast China and identify the risk factors for seizures during treatment. Methods: Patients aged 18–65 years diagnosed with convulsive epilepsy in rural areas of Jilin Province between 2010 and 2024 were included, and demographic and clinical data were recorded. Seizure frequency, self-efficacy, adherence, and adverse events (AEs) were assessed monthly. Results: Of the 3,568 participants, 288 (8.1%) withdrew from the study and 159 (4.5%) died. During the first year of treatment, 75.2% of patients experienced a ≥50% reduction in seizure frequency compared with baseline (considered as treatment effectiveness); 53.7% of patients were seizure-free. By the tenth year, 97.7% of patients showed treatment effectiveness, and 89.6% were seizure-free. Self-efficacy was improved in 37.8% of patients in the first year and in 72% of patients by the tenth year. The independent risk factors for seizures during treatment were higher baseline seizure frequency [odds ratio (OR) = 1.431, 95% confidence interval (CI): 1.122–1.824], presence of multiple seizure types (OR = 1.367, 95% CI: 1.023–1.826), and poor adherence (OR = 14.806, 95% CI: 3.495–62.725), with significant differences observed in the first, third, and fifth years. The most commonly reported AEs were drowsiness (43.3%), dizziness (25.0%), and headaches (17.0%), most of which were mild and decreased over time. Age at enrollment was the only factor influencing withdrawal (hazard ratio = 0.984, 95% CI: 0.973–0.996, p = 0.010), with a substantial number of patients who withdrew (32.6%) relocating for work. Cardiovascular disease was the primary cause of death, and age at enrollment was the only risk factor (hazard ratio = 1.026, 95% CI: 1.009–1.043, p = 0.002). Discussion: Working-age adults with epilepsy demonstrated a favorable response and tolerability to PB monotherapy. Baseline seizure frequency, seizure type, and adherence consistently predicted prognosis throughout the treatment period. Withdrawal was mainly explained by work-related pressures in this age group. Therefore, it is essential to implement interventions that support patient adherence to therapy and maintain stable regimens. [ABSTRACT FROM AUTHOR]

The intersection of environmental communication and visual arts has emerged as a burgeoning area of scholarly interest, holding promise for both theoretical advancement and innovative applied research. This review collects publications pertaining to art-based environmental communication from multiple disciplines and underscores the roles of self-reflection, audience characteristics, and artwork attributes in shaping cognitive, emotional, and behavioral outcomes. We not only highlight insights from current literature but also outline directions for future research, shedding light on the evolving and dynamic landscape of this field. [ABSTRACT FROM AUTHOR]

Biosurfactants represent a promising choice for the development of environmentally friendly and gentle personal care cleansers. Building viscosity is one of the major challenges to apply biosurfactants. In this study, sodium lauroyl sarcosinate (LS) and sodium lauroamphoacetate (LA) were used as bases to build wormlike micelles, and subsequently rhamnolipids were introduced to build mild surfactant systems. The LS‐LA mixture had the highest viscosity at the mass ratio of 1:5 and pH 6.0. After adding 1 wt% and less rhamnolipid, relatively high viscosity can be maintained. The viscosity of LS‐LA‐rhamnolipid can be increased by adding NaCl and more significantly by the addition of carrageenan due to its synergistic interactions with the surfactant mixture. In addition, the foaming properties of the systems are characterized with different amounts of rhamnolipid and carrageenan, which are correlated with the bulk viscosity and interfacial elasticity of the diluted solution used for the foaming test. Rhamnolipids have both high mildness and cleaning efficacy and adding rhamnolipids can significantly increase the mildness of the system. This study offers practical solutions for the incorporation of rhamnolipids or other biosurfactants in the formulation of personal care cleansers. [ABSTRACT FROM AUTHOR]

Objectives: The aim of this study was to determine the performance of radionuclide-labeled fibroblast activation protein inhibitors (Al18F-NOTA-FAPI-04) PET/CT in patients with autoimmune rheumatic diseases (ARDs) and compare it with fluorine-18 (18F) labeled fluorodeoxyglucose (FDG) imaging. Methods: Fifty-eight participants with ARDs were prospectively enrolled from April 2022 to February 2024 and underwent dual-tracer PET/CT imaging. For both 18F-FDG and Al18F-NOTA-FAPI-04 PET/CT, imaging findings were interpreted and compared. The clinical significance was compared between18F-FDG PET/CT and Al18F-NOTA-FAPI-04 PET/CT imaging. Results: 18F-FDG imaging was positive in 53 out of 58 cases (91.4%) while Al18F-NOTA-FAPI-04 imaging was positive in 55 out of 58 cases (94.8%). Overall positive rate of Al18F-NOTA-FAPI-04 imaging was as high as 18F-FDG imaging (P = 0.625). 18F-FDG imaging detected more lesions in lymph node, spleen, and bone marrow. Al18F-NOTA-FAPI-04 imaging detected more lesions in the lung, muscle, and tendon/ligament. There was no statistical difference of composing ratio of grades of clinical significance between two imaging modalities (χ2 = 2.875, P = 0.238). The superior rate of Al18F-NOTA-FAPI-04 PET/CT imaging was higher than 18F-FDG imaging (P = 0.020). In subgroup of adult-onset Still's disease, 18F-FDG imaging showed better performance than Al18F-NOTA-FAPI-04 imaging. In most of the other subgroup of ARDs, Al18F-NOTA-FAPI-04 PET/CT imaging overperformed 18F-FDG imaging. Conclusion: Both 18F-FDG and Al18F-NOTA-FAPI-04 PET/CT imaging have excellent sensitivity in ARDs. The detection capabilities of two tracers varied according to the involving organs of ARDs. In most of ARDs except adult-onset Still's disease, Al18F-NOTA-FAPI-04 PET/CT imaging overperformed 18F-FDG imaging. Key Points • 18F-FDG and Al18F-NOTA-FAPI-04 PET/CT imaging have excellent sensitivity in diagnosing of ARDs. • 18F-FDG PET/CT imaging detected more lesions in lymph node, spleen, and bone marrow. • 18F-NOTA-FAPI-04 PET/CT imaging detected more lesions in the lung, muscle, and tendon/ligament. • 18F-NOTA-FAPI-04 PET/CT imaging overperformed18F-FDG in most subgroups of ARDs. [ABSTRACT FROM AUTHOR]

Flexible capacitive pressure sensors have garnered significant attention in research areas such as electronic skin, wearable devices, medical diagnosis, physical health detection, and artificial intelligence due to their advantageous characteristics, including high sensitivity, flexibility, lightness, and easy integration. Over the past few years, the field of flexible capacitive pressure sensors has experienced notable advancements in materials, structural design, fabrication processes, and applications. This review aims to examine the different materials employed for sensor electrodes and dielectric layers, as well as the structural design of these sensors. Additionally, we delve into the diverse fabrication processes and techniques utilised, including electrode and dielectric layer fabrication, as well as weaving technology. Lastly, we explore the various applications of flexible capacitive pressure sensors, encompassing electronic skin, health monitoring device, electronic textiles, and structural health monitoring. [ABSTRACT FROM AUTHOR]

Background: Research investigating the potential link between gingival microvascular blood flow and inflammatory status is scarce. This study aims to assess color doppler flow imaging (CDFI) and micro-flow imaging (MFI) as tools for the assessment of gingival papilla blood flow (GPBF) and to examine their diagnostic utility as a noninvasive means of detecting gingival bleeding. Methods: CDFI and MFI were used to assess the GPBF grade (0–4) of 140 anterior gingival papilla sites in advanced periodontitis patients. Correlations between GPBF grades and periodontal characteristics were examined, and diagnostic performance as a means of predicting bleeding on probing (BOP) was examined using receiver operating characteristic curves. Results: GPBF grades 0 and 1 assessed by the MFI were 14.29% and 15.71% respectively, lower than the 28.57% and 24.29% assessed by the CDFI. In contrast, MFI detected a higher frequency of GPBF grade 2 sites (40.71%) relative to CDFI (22.14%). The CDFI and MFI provided consistent results in 62.14% of the sites, while the MFI demonstrated higher ratings in rest 37.86% of the sites. A significant positive correlation was detected between GPBF grade and the modified gingival index (MGI), bleeding index (BI), BOP, and probing depth (PD). It showed high accuracy for CDFI or MFI to diagnosing BOP with a sensitivity of 80.51% and 96.43% and a specificity of 77.27% and 57.14%, respectively. Area under the receiver operator characteristic curve values when predicting BOP based on the GPBF grade determined using CDFI and MFI approaches 0.887 (95% CI 0.833–0.942) and 0.917 (95% CI 0.862–0.972), respectively, and there were no significant differences between these values (Z = − 1.502, p = 0.133). Conclusions: Both MFI and CDFI can be employed for the evaluation of GPBF, and MFI is better suited to detecting mild inflammation. Trial registration ChiCTR2200066021 (Date of registration: 22/11/2022). [ABSTRACT FROM AUTHOR]

Mechanics-related tasks often present unique challenges in achieving accurate geometric and physical representations, particularly for non-uniform structures. Graph neural networks (GNNs) have emerged as a promising tool to tackle these challenges by adeptly learning from graph data with irregular underlying structures. Consequently, recent years have witnessed a surge in complex mechanics-related applications inspired by the advancements of GNNs. Despite this process, there is a notable absence of a systematic review addressing the recent advancement of GNNs in solving mechanics-related tasks. To bridge this gap, this review article aims to provide an in-depth overview of the GNN applications in mechanics-related domains while identifying key challenges and outlining potential future research directions. In this review article, we begin by introducing the fundamental algorithms of GNNs that are widely employed in mechanics-related applications. We provide a concise explanation of their underlying principles to establish a solid understanding that will serve as a basis for exploring the applications of GNNs in mechanics-related domains. The scope of this paper is intended to cover the categorisation of literature into solid mechanics, fluid mechanics, and interdisciplinary mechanics-related domains, providing a comprehensive summary of graph representation methodologies, GNN architectures, and further discussions in their respective subdomains. Additionally, open data and source codes relevant to these applications are summarised for the convenience of future researchers. This article promotes an interdisciplinary integration of GNNs and mechanics and provides a guide for researchers interested in applying GNNs to solve complex mechanics-related tasks. [ABSTRACT FROM AUTHOR]

Due to the popularization of high-speed rail (HSR), there have been increasing concerns of passengers about the thermal comfort of HSR air conditioning. The corrected predicted mean vote (CPMV) model considering the impact of solar radiation on indoor thermal comfort has been previously proposed and validated for accuracy in office buildings. To verify the accuracy of the CPMV model in evaluating the thermal comfort of passengers inside HSR carriages, the field study on HSR in the Yangtze River Delta region of China was conducted in winter and summer. The results indicate thermal sensation vote values obtained from passengers fit well with CPMV values. When the temperature is high in summer and low in winter, the CPMV model ignores people's ability to adapt and tolerate harsh environments. In addition, the thermal preference temperature of passengers in summer is 0.57°C higher than the neutral temperature, indicating that there is an overcooling situation in summer. The study recommends to lower the set temperature of summer air conditioning in HSR. This study contributes to the promotion of the CPMV model on HSR and provides technical support for the design of air-conditioning systems for HSR carriages from the perspective of thermal comfort of passengers. [ABSTRACT FROM AUTHOR]

At present, the problem of global warming is becoming increasingly serious, and one of the main culprits is the increasing amount of carbon dioxide emissions. Although the traditional carbon capture technologies can reduce the concentration of CO2 in the atmosphere, it has a series of problems such as high energy consumption, high cost, low efficiency or unfriendly environment. Hydrate-based carbon dioxide separation are considered to be a technology with great application and development prospects. Compared with the traditional method of carbon dioxide separation, the hydrate method has the advantages of simple process, low energy consumption and environmental friendliness. This review introduces the advantages of hydrate method compared with traditional carbon capture technologies, expounds the theory of carbon dioxide capture by hydrate, and the strengthening and improvement techniques of hydrate method, including thermodynamic promoter, kinetic promoter and mechanical reinforcement, and introduces the practical application of hydrate method in various fields. [ABSTRACT FROM AUTHOR]

Human mitochondrial tRNAs (mt-tRNAs), critical for mitochondrial biogenesis, are frequently associated with pathogenic mutations. These mt-tRNAs have unusual sequence motifs and require post-transcriptional modifications to stabilize their fragile structures. However, whether a modification that stabilizes a wild-type (WT) mt-tRNA would also stabilize its pathogenic variants is unknown. Here we show that the N1-methylation of guanosine at position 9 (m1G9) of mt-Leu(UAA), while stabilizing the WT tRNA, has a destabilizing effect on variants associated with MELAS (mitochondrial myopathy, encephalopathy, lactic acidosis, and stroke-like episodes). This differential effect is further demonstrated, as removal of the m1G9 methylation, while damaging to the WT tRNA, is beneficial to the major pathogenic variant, improving the structure and activity of the variant. These results have therapeutic implications, suggesting that the N1-methylation of mt-tRNAs at position 9 is a determinant of pathogenicity and that controlling the methylation level is an important modulator of mt-tRNA-associated diseases. Here the authors show that the m1G9 post-transcriptional methylation differentially regulates the stability of the native and the MELAS variants of human mt-Leu(UAA) tRNA, contributing to mitochondrial pathology. [ABSTRACT FROM AUTHOR]

Background/Objectives: This study aimed to assess the effect of aerobic exercise on capillary density and vascular smooth muscle cell (VSMC) phenotype in the visceral and subcutaneous adipose tissue of high-fat-diet (HFD) mice in order to understand the mechanisms underlying improvements in insulin resistance (IR) and chronic inflammation in adipose tissue (AT). Methods: Male C57BL/6J mice were divided into HFD and normal diet groups for 12 weeks and then further split into sedentary and aerobic exercise subgroups for an additional 8 weeks. Various parameters including body weight, fat weight, blood glucose, lipid profile, insulin levels, glucose tolerance, and inflammatory cytokines were evaluated. Results: Aerobic exercise reduced HFD-induced weight gain, IR, and improved lipid profiles. HFD had a minimal effect on inflammatory cytokines except in visceral adipose tissue (VAT). IR was associated with capillary density in subcutaneous adipose tissue (SAT) and VSMC phenotype in VAT. Aerobic exercise promoted anti-inflammatory responses in VAT, correlating with VSMC phenotype in this tissue. Conclusions: Aerobic exercise can alleviate HFD-induced IR and inflammation through the modulation of VSMC phenotype in AT. [ABSTRACT FROM AUTHOR]

Growth hormone secretagogue receptor 1a (GHS-R1a), also known as the ghrelin receptor, is an important nutrient sensor and metabolic regulator in both humans and rodents. Increased GHS-R1a expression is observed in the hippocampus of both Alzheimer's disease (AD) patients and AD model mice. However, the causal relationship between GHS-R1a elevation in the hippocampus and AD memory deficits remains uncertain. Here, we find that increasing GHS-R1a expression in dCA1 pyramidal neurons impairs hippocampus-dependent memory formation, which is abolished by local administration of the endogenous antagonist LEAP2. GHS-R1a elevation in dCA1 pyramidal neurons suppresses excitability and blocks memory allocation in these neurons. Chemogenetic activation of those high GHS-R1a neurons during training rescues GHS-R1a overexpression-induced memory impairment. Moreover, we demonstrate that increasing GHS-R1a expression in dCA1 pyramidal neurons hampers these neurons' ability to encode spatial memory and reduces engram size in the dCA1 region. Finally, we show that GHS-R1a deletion mitigates spatial memory deficits in APP/PS1 mice with increased GHS-R1a expression in the hippocampus. Our findings reveal a negative, causal relationship between hippocampal GHS-R1a expression and memory encoding, and suggest that blocking the abnormal increase in GHS-R1a activity/expression may be a promising approach to improve memory and treat cognitive decline in AD. Mechanistic modeling reveals that increased GHS-R1a expression in hippocampal neurons impairs memory formation, suggesting that targeting GHS-R1a activity could improve memory and mitigate cognitive decline in AD. [ABSTRACT FROM AUTHOR]

Among all cancers occurring in the head and neck region, oral squamous cell carcinoma (OSCC) is the most common oral malignant tumours characterized by its aggressiveness and metastasis. The development of transcriptomics technology has greatly facilitated the diagnosis of various cancers. However, identifying genetic biomarkers is limited by data from a single batch of OSCC samples, and integrating analysis across different platforms remains a great challenge. In this study, we integrated five OSCC transcriptome datasets using an innovative strategy capable of mitigating batch effect, and extracting information from different datasets based on changes in the relative expression of gene pairs. By leveraging a machine learning method, we developed a prediction model including 27 differential gene pairs (DGPs) to discriminate OSCC from control samples, achieving an area under the receiver operating characteristic curve (AUC) of 0.8987 for the training set. Moreover, the model demonstrated commendable performance in four external validation sets, with AUCs of 0.9926, 0.9688, 0.8052 and 0.8565, respectively. Subsequently, a prognostic model was constructed based on six key gene pairs through univariate and multivariate Cox regression analysis. The AUCs of the model at 1‐year and 3‐year overall survival time prediction were 0.717 and 0.779 in an independent dataset. Our result demonstrates the effectiveness of this new method of integrating data and identifying DGPs. Using DGPs can significantly improve the performance of both diagnostic and prognostic models. [ABSTRACT FROM AUTHOR]

Neuropathic pain is a debilitating chronic condition that lacks effective treatment. The role of cytokine- and chemokine-mediated neuroinflammation in its pathogenesis has been well documented. Follistatin (FST) is a secreted protein known to antagonize the biological activity of cytokines in the transforming growth factor–β (TGF-β) superfamily. The involvement of FST in neuropathic pain and the underlying mechanism remain largely unknown. Here, we report that FST was up-regulated in A-fiber sensory neurons after spinal nerve ligation (SNL) in mice. Inhibition or deletion of FST alleviated neuropathic pain and reduced the nociceptive neuron hyperexcitability induced by SNL. Conversely, intrathecal or intraplantar injection of recombinant FST, or overexpression of FST in the dorsal root ganglion (DRG) neurons, induced pain hypersensitivity. Furthermore, exogenous FST increased neuronal excitability in nociceptive neurons. The biolayer interferometry (BLI) assay and coimmunoprecipitation (co-IP) demonstrated direct binding of FST to the insulin-like growth factor–1 receptor (IGF1R), and IGF1R inhibition reduced FST-induced activation of extracellular signal–regulated kinase (ERK) and protein kinase B (AKT), as well as neuronal hyperexcitability. Further co-IP analysis revealed that the N-terminal domain of FST exhibits the highest affinity for IGF1R, and blocking this interaction with a peptide derived from FST attenuated Nav1.7-mediated neuronal hyperexcitability and neuropathic pain after SNL. In addition, FST enhanced neuronal excitability in human DRG neurons through IGF1R. Collectively, our findings suggest that FST, released from A-fiber neurons, enhances Nav1.7-mediated hyperexcitability of nociceptive neurons by binding to IGF1R, making it a potential target for neuropathic pain treatment. Editor's summary: Neuroinflammation contributes to the pathogenesis of neuropathic pain. The characterization of signaling pathways involved could help to identify new therapeutic targets. Here, Jiang et al. used a mouse model to show that the glycoprotein follistatin (FST) was up-regulated in sensory neurons in the dorsal root ganglia (DRG) after spinal nerve ligation. FST injections were sufficient to drive mechanical hypersensitivity and excitability of DRG neurons. FST interacted with insulin-like growth factor–1 receptor, and a peptide that blocked these interactions could alleviate neuropathic pain–related behaviors and FST-mediated voltage-gated sodium channel currents, highlighting a potential therapeutic strategy that warrants further examination. —Daniela Neuhofer [ABSTRACT FROM AUTHOR]

This study aimed to create Pickering emulsions with varying oil fractions and assess the impact of ultrasonic treatment on the properties of Whey Protein Isolates (WPIs). At 640 W for 30 min, ultrasound reduced WPI aggregate size, raised zeta potential, and improved foaming, emulsifying, and water-holding capacities. FTIR analysis showed structural changes, while fluorescence and hydrophobicity increased, indicating tertiary structure alterations. This suggests that sonication efficiently modifies WPI functionality. Under ideal conditions, φ = 80 emulsions were most stable, with no foaming or phase separation. Laser scanning revealed well-organized emulsions at φ = 80. This study provides a reference for modifying and utilizing WPI. [ABSTRACT FROM AUTHOR]

In this work, we investigated the effects of alloying elements on plastic deformation and microstructure evolution in polycrystalline copper (Cu) and Cu alloyed with 1 wt. % lead (Cu-1 % Pb). These materials were selected due to the size mismatch between Cu and Pb, with the latter forming precipitates at grain boundaries. Multi-modal characterization techniques, including neutron diffraction, electron backscatter diffraction (EBSD), and transmission electron microscopy (TEM), along with finite element simulations were employed to study the deformation behavior across multiple length scales. While both Cu and Cu-1 % Pb exhibited similar macroscale response and final deformation textures, both dislocation line profile analysis and TEM revealed increased dislocation density in deformed Cu-1 % Pb specimens. The presence of lead precipitates also significantly affected local plastic deformation during compression, with their influence diminishing with increasing strain. These results demonstrate the complex relationships between alloying elements, plastic deformation, microstructural evolution, and material behavior under load. The insights gained from this multi-scale and multi-technique approach contribute to the fundamental understanding of microstructural evolution in immiscible alloys and are valuable for tailoring the properties of structural materials for specific engineering applications. [ABSTRACT FROM AUTHOR]

To tackle the clinical challenge of noninvasively assessing immunotherapy efficacy in patients, here we used positron emission tomography (PET) with 68Ga-grazytracer, which targets granzyme B, a crucial effector molecule secreted by activated CD8+ T cells. In this phase 1/2 clinical trial (NCT05000372) involving a diverse cohort of 24 patients with solid tumors and lymphomas who received immunotherapies, including immune checkpoint inhibitors (either alone or with chemotherapies) and chimeric antigen receptor-T cell therapy, we examined the in vivo behaviors of 68Ga-grazytracer. Primary endpoints were safety, biodistribution, granzyme B specificity, and the predictive utility of 68Ga-grazytracer, while secondary endpoint was the relationship between 68Ga-grazytracer uptake and tumor immune phenotype. 68Ga-grazytracer exhibited a safe profile and specifically targeted granzyme B in patients. 68Ga-grazytracer PET showed superior predictive value for short-term prognosis and progression-free survival than those of conventional assessment criteria, including RECIST 1.1 and PERCIST. Moreover, the uptake of 68Ga-grazytracer in tumors was significantly higher in those with a "non-desert" immune phenotype than those with an immune "desert" phenotype, thereby meeting the primary and secondary endpoints of this trial. Collectively, we successfully visualized CD8+ T cell effector function in humans using 68Ga-grazytracer PET, offering insights for enhancing immunotherapy assessment, patient stratification and treatment planning. Several approaches based on positron emission tomography (PET) are currently used to evaluate cancer response to immunotherapy. Here the authors report the results of a phase 1/2 trial evaluating a PET radiotracer, 68Ga-grazytracer, for the imaging of granzyme B expression in patients treated with immune checkpoint inhibitors or CAR-T cell therapy. [ABSTRACT FROM AUTHOR]

Background: Over the last 2 decades, various education and training programmes have been launched by the European School of Urology (ESU) on behalf of the European Association of Urology (EAU) Education Office. These include e-learning platforms, in-person meetings, courses, podcasts, webinars, sub-specialisation meetings and the European Urology Resident Education Programme (EUREP), all of which aim to achieve standardisation in urological education (SISE) and training at the highest level. Methods: Data from the last 2 decades of all ESU activities were collected by the EAU/ESU office and analyzed for attendance, geographical, gender and age trends. Demographic data on registrations and attendances at EUREP were also monitored and analysed. A descriptive analysis of participation and trends is provided. Results: A total of 4750 participants have completed ESU courses (including guideline courses, specialization courses and webinar courses). Similarly, a total of 5958 trainees attended the EUREP from 2004 to 2022 of which the male: female ratio was 3.75:1. However, the proportion of females increased 3.5-fold from 10.7% in 2004 to 37.1% in 2022(p < 0.001). There is a growing interest in the meeting, with increasing registrations over this time (353 in 2004 to 599 in 2023, p < 0.001). The mean age of participants is constantly decreasing (32.6 years in 2004 to 31.54 in 2022), with a mean yearly decrease of -0.18% (p < 0.001). Conclusion: ESU courses have had increasing interest and participation from young urologists worldwide. During EUREP, while the trainee age has decreased, there has been a surge in the proportion of female trainees. ESU is providing all modes of education and training across the world with both virtual and in-person meetings and courses, which would help in the development and preparation of urologists of the future and provide the best patient care. [ABSTRACT FROM AUTHOR]

Background: Over the last 2 decades, various education and training programmes have been launched by the European School of Urology (ESU) on behalf of the European Association of Urology (EAU) Education Office. These include e-learning platforms, in-person meetings, courses, podcasts, webinars, sub-specialisation meetings and the European Urology Resident Education Programme (EUREP), all of which aim to achieve standardisation in urological education (SISE) and training at the highest level. Methods: Data from the last 2 decades of all ESU activities were collected by the EAU/ESU office and analyzed for attendance, geographical, gender and age trends. Demographic data on registrations and attendances at EUREP were also monitored and analysed. A descriptive analysis of participation and trends is provided. Results: A total of 4750 participants have completed ESU courses (including guideline courses, specialization courses and webinar courses). Similarly, a total of 5958 trainees attended the EUREP from 2004 to 2022 of which the male: female ratio was 3.75:1. However, the proportion of females increased 3.5-fold from 10.7% in 2004 to 37.1% in 2022(p < 0.001). There is a growing interest in the meeting, with increasing registrations over this time (353 in 2004 to 599 in 2023, p < 0.001). The mean age of participants is constantly decreasing (32.6 years in 2004 to 31.54 in 2022), with a mean yearly decrease of -0.18% (p < 0.001). Conclusion: ESU courses have had increasing interest and participation from young urologists worldwide. During EUREP, while the trainee age has decreased, there has been a surge in the proportion of female trainees. ESU is providing all modes of education and training across the world with both virtual and in-person meetings and courses, which would help in the development and preparation of urologists of the future and provide the best patient care. [ABSTRACT FROM AUTHOR]

Simple Summary: We explored the role of exercise in promoting hippocampal neurogenesis and memory function in T2DM mice through the Irisin/TLR4/MyD88/NF-κB signaling pathway. Ten weeks of exercise training significantly reduced inflammation in the DG region caused by T2DM and promoted hippocampal neurogenesis and memory function. However, these positive effects could be reversed by treatment with Cyclo RGDyk, which blocks irisin receptor signaling. The results suggest that exercise may be an effective strategy for alleviating cognitive decline caused by diabetes by activating the irisin signaling pathway. Neuroinflammation is a major feature of type 2 diabetic mellitus (T2DM), adversely affecting hippocampal neurogenesis. However, the precise mechanism is not fully understood, and therapeutic approaches are currently lacking. Therefore, we determined the effects of exercise on neuroinflammation and hippocampal neurogenesis in T2DM mice, with a specific focus on understanding the role of the irisin and related cascade pathways in modulating the beneficial effects of exercise in these processes. Ten-week exercise significantly decreased T2DM-induced inflammation levels and markedly promoted hippocampal neurogenesis and memory function. However, these positive effects were reversed by 10 weeks of treatment with cyclo RGDyk, an inhibitor of irisin receptor signaling. Additionally, exercise helped reduce the M1 phenotype polarization of hippocampal microglia in diabetic mice; this effect could be reversed with cyclo RGDyk treatment. Moreover, exercise markedly increased the levels of fibronectin type III domain-containing protein 5 (FNDC5)/irisin protein while decreasing the expression of Toll-like receptor 4 (TLR4), myeloid differential protein-88 (MyD88), and nuclear factor kappa-B (NF-κB) in the hippocampus of T2DM mice. However, blocking irisin receptor signaling counteracted the down-regulation of TLR4/MyD88/NF-κB in diabetic mice undergoing exercise intervention. Conclusively, exercise appears to be effective in reducing neuroinflammation and enhancing hippocampal neurogenesis and memory in diabetes mice. The positive effects are involved in the participation of the irisin/TLR4/MyD88/NF-κB signaling pathway, highlighting the potential of exercise in the management of diabetic-induced cognitive decline. [ABSTRACT FROM AUTHOR]

Due to the lack of real-time planning for fire escape routes in large buildings, the current route planning methods fail to adequately consider factors related to the fire situation. This study introduces a real-time fire monitoring and dynamic path planning system based on an improved ant colony algorithm, comprising a hierarchical arrangement of upper and lower computing units. The lower unit employs an array of sensors to collect environmental data in real time, which is subsequently transmitted to an upper-level computer equipped with LabVIEW. Following a comprehensive data analysis, pertinent visualizations are presented. Capitalizing on the acquired fire situational awareness, a propagation model for fire spreading is developed. An enhanced ant colony algorithm is then deployed to calculate and plan escape routes by introducing a fire spread model to enhance the accuracy of escape route planning and incorporating the A* algorithm to improve the convergence speed of the ant colony algorithm. In response to potential anomalies in sensor data under elevated temperature conditions, a correction model for data integrity is proposed. The real-time depiction of escape routes is facilitated through the integration of LabVIEW2018 and MATLAB2023a, ensuring the dependability and safety of the path planning process. Empirical results demonstrate the system's capability to perform real-time fire surveillance coupled with efficient escape route planning. When benchmarked against the traditional ant colony algorithm, the refined version exhibits expedited convergence, augmented real-time performance, and effectuates an average reduction of 17.1% in the length of the escape trajectory. Such advancements contribute significantly to enhancing evacuation efficiency and minimizing potential casualties. [ABSTRACT FROM AUTHOR]

Harmful algal blooms (HABs) often occur in estuaries due to their unique environmental heterogeneity, posing significant environmental and human health risks. However, there is limited understanding of the community composition and community‐level change points (thresholds) of harmful microalgae in subtropical estuaries. This study explored harmful microalgae community structure and thresholds in the Dafengjiang River estuary using a metabarcoding approach. The results revealed 63 harmful microalgae species, and major species included Guinardia flaccida, Prorocentrum cordatum, Thalassiosira punctigera, Pseudo‐nitzschia galaxiae and T. gravida. Nonparametric change‐point analysis and threshold indicator taxa analysis (TITAN) showed threshold responses of harmful microalgae community structure to ammonium (57.5–60 μg·L−1), total phosphorus (27.8–28.5 μg·L−1) and dissolved inorganic phosphorus (14.5–28 μg·L−1) along the salinity gradient. Wider environmental thresholds were also found in hypersaline areas. Additionally, Pyrodinium bahamense, Pfiesteria piscicida, Skeletonema tropicum and T. punctigera were sensitive to environmental changes and thus could be used as bioindicators. Overall, our study unveiled diverse abrupt transitions of harmful microalgal communities, providing a risk assessment for human health and ecological safety in subtropical estuary ecosystems. [ABSTRACT FROM AUTHOR]

Accurate monitoring of soil moisture and the development of timely interventions are important to reduce the social and economic losses caused by drought. Compared to short-wave infrared (SWIR) and thermal infrared (TIR), near-infrared (NIR) and visible bands are widely used in almost all optical satellites. Drought monitoring using NIR and visible bands is therefore more relevant for optical satellites. Among the visible bands, the red band is often used in combination with the NIR band for drought monitoring due to its sensitivity to vegetation. However, current drought indexes based on the NIR and the red band applied to areas of high vegetation suffer from insufficient accuracy or tedious calculations. In this study, the ratio drought index (RDI) was developed after constructing a new feature space by examining the spectral properties of soil and vegetation at different water levels in the NIR and red bands. The accuracy of soil moisture inversion under two types of bare soil and vegetation was evaluated using in situ data from Tai'an City, Shandong Province. The perpendicular drought index (PDI) and modified perpendicular drought index (MPDI) were also used to compare for the RDI. The results showed that the RDI correlation coefficients (R2) of 0.653 and 0.641 were better than the MPDI of 0.616 and 0.594 and the PDI of 0.602 and 0.546 for soil moisture measurements from vegetation and bare soil cover. The RDI attenuates the effect of vegetation on soil moisture inversion, as its root mean square error (RMSE) in vegetated areas is lower than that of the PDI and MPDI. The RDI calculation can be used as a theoretical guide for large-scale soil moisture estimation because it is fast, accurate and does not require additional quantitative remote sensing inversion factors. [ABSTRACT FROM AUTHOR]

Real-time service (RTS) products are an important guarantee for real-time precise point positioning (RT-PPP), and the RTS outages caused by loss of network connection are a concern. In this paper, a multivariate CNN-LSTM model is proposed for short-term BDS satellite clock offset prediction during the discontinuity in receiving RTS clock offsets, which utilizes the superior feature of convolution neural network (CNN) and long short-term memory (LSTM) for simultaneous prediction of multiple satellite clock offsets by considering the inter-satellite correlation. First, the correlation between satellite clock offsets was analyzed to identify satellites suitable for parallel prediction. Then, to preserve the sequential structure of the features extracted from multiple parallel satellite clock offsets, remove the pooling layer of traditional CNN, and use the convolution layer to learn the relationships and dependencies between clock offsets of different satellites and the LSTM layer to model the temporal dependencies in satellite clock offsets. The experiment results show that the computational efficiency of the proposed model is significantly better than that of autoregressive integrated moving average (ARIMA), wavelet neural network (WNN), and LSTM models. Compared with the linear polynomial (LP), quadratic polynomial model (QP), ARIMA, WNN, and the LSTM models, the prediction accuracy of the multivariate CNN-LSTM model for 5 min, 15 min, 30 min, and 1 h is improved by approximately (84.0, 76.6, 1.5, 8.3, 8.3)%, (72.0, 62.6, 6.0, 15.3, 18.7)%, (57.1, 48.5, 11.3, 18.4, 23.3)%, and (34.9, 35.1, 27.3, 21.8, 26.3)%, respectively. [ABSTRACT FROM AUTHOR]

The limited oxidation stability of ether solvents has posed significant challenges for their applications in high‐voltage lithium metal batteries (LMBs). To tackle this issue, the prevailing strategy either adopts a high concentration of fluorinated salts or relies on highly fluorinated solvents, which will significantly increase the manufacturing cost and create severe environmental hazards. Herein, an alternative and sustainable salt engineering approach is proposed to enable the utilization of dilute electrolytes consisting of fluorine (F)‐free ethers in high‐voltage LMBs. The proposed 0.8 M electrolyte supports stable lithium plating‐stripping with a high Coulombic efficiency of 99.47 % and effectively mitigates the metal dissolution, phase transition, and gas release issues of the LiNi0.8Co0.1Mn0.1O2 (NCM811) cathode upon charging to high voltages. Consequently, the 4.5 V high‐loading Li||NCM 811 cell shows a capacity retention of 75.2 % after 300 cycles. Multimodal experimental characterizations coupled with theoretical investigations demonstrate that the boron‐containing salt plays a pivotal role in forming the passivation layers on both anode and cathode. The present simple and cost‐effective electrolyte design strategy offers a promising and alternative avenue for using commercially mature, environmentally benign, and low‐cost F‐free ethers in high‐voltage LMBs. [ABSTRACT FROM AUTHOR]

As the scale of the power grid rapidly expands, its operation becomes increasingly complex, with higher demands on personnel proficiency, grid stability, equipment safety, and operational efficiency. In this study, a novel power insulator defect detection method based on convolutional neural networks (CNNs) is proposed. This method innovatively combines the feature extraction advantages of deep learning to build an efficient binary classification model capable of accurately detecting defects in power insulators in complex backgrounds. To avoid the impact of a small dataset on model performance, transfer learning was employed during model training to enhance the model's generalization ability. A combination of Grid Search and Random Search was used for hyperparameter tuning, and the Early Stopping strategy was introduced to effectively prevent the model from overfitting to the training set, ensuring generalization performance on the validation set. Experimental results show that the proposed method achieves an average accuracy of 98.6%, a recall of 96.8%, and an F1 score of 97.7% on the test set. Compared to traditional Faster RCNN and PCA-SVM methods, the proposed CNN model significantly improves detection accuracy and computational efficiency in complex backgrounds, exhibiting superior recognition precision and model generalization ability for efficiently and accurately identifying defective insulators. [ABSTRACT FROM AUTHOR]

With people's concern for health and the development of medical technology, medical products for children are gradually appearing in pharmacies and online stores. However, the appearance of most children's household medical products tends to meet the needs of adults, which leads to low acceptance of medical products. This study aimed to explore 10- to 16-year-old children's visual and tactile perception of different materials by researching the relationship between the psychological quantities of visual and tactile perception and the physical quantities of the material surface. Based on the theory of kansei engineering, we measured the physical quantities of nine materials used in insulin syringe products and administered a perceptual questionnaire test for children. By correlating subjective perceptions with the physical attributes of the materials' surfaces, we determined a strong correlation between the visual and tactile psychological properties and the properties of the materials' surfaces. Children clearly perceive materials, and materials with lower roughness can elicit calmness, while materials with higher gloss elicit negative emotions. This paper establishes an evaluation model and provides a scientific selection method for surface materials in different children's household medical products. [ABSTRACT FROM AUTHOR]

The development of marine oil and gas resources is currently an important global increment. The thermal insulation effect of intumescent fireproof coatings is excellent, and the construction is limited by the geometric shape of the structure. It is widely used in the marine oil and gas industry. Large oil and gas processing skids that require passive fire protection on offshore platforms have the characteristics of compact structure and inconvenient coating construction. This article takes the passive fire prevention and painting process of high-pressure gas injection compressor skids for natural gas processing equipment as an example, systematically elaborates fire hazards and evaluation, selection of fire resistant coatings, coating system design, coating construction, fire extension and film thickness measurement, etc., providing reference for the passive fire prevention design and construction of skids. By means of complete design at the source, trial assembly on the skid, and precise reservation and positioning, the integrated coating of the skid block is achieved, ensuring coating quality and reducing painting loss. [ABSTRACT FROM AUTHOR]

The limited oxidation stability of ether solvents has posed significant challenges for their applications in high‐voltage lithium metal batteries (LMBs). To tackle this issue, the prevailing strategy either adopts a high concentration of fluorinated salts or relies on highly fluorinated solvents, which will significantly increase the manufacturing cost and create severe environmental hazards. Herein, an alternative and sustainable salt engineering approach is proposed to enable the utilization of dilute electrolytes consisting of fluorine (F)‐free ethers in high‐voltage LMBs. The proposed 0.8 M electrolyte supports stable lithium plating‐stripping with a high Coulombic efficiency of 99.47 % and effectively mitigates the metal dissolution, phase transition, and gas release issues of the LiNi0.8Co0.1Mn0.1O2 (NCM811) cathode upon charging to high voltages. Consequently, the 4.5 V high‐loading Li||NCM 811 cell shows a capacity retention of 75.2 % after 300 cycles. Multimodal experimental characterizations coupled with theoretical investigations demonstrate that the boron‐containing salt plays a pivotal role in forming the passivation layers on both anode and cathode. The present simple and cost‐effective electrolyte design strategy offers a promising and alternative avenue for using commercially mature, environmentally benign, and low‐cost F‐free ethers in high‐voltage LMBs. [ABSTRACT FROM AUTHOR]

Purpose: To establish an explainable 18F-FDG PET/CT-derived prediction model to identify EGFR mutation status and subtypes (EGFR wild, EGFR-E19, and EGFR-E21) in lung adenocarcinoma (LUAD). Methods: Baseline 18F-FDG PET/CT images of 478 patients with LUAD from 2 hospitals were collected. Data from hospital A (n = 390) was randomly split into a training group (n = 312) and an internal test group (n = 78), with data from hospital B (n = 88) utilized for external test. Further, a total of 4,760 handcrafted radiomics features (HRFs) were extracted from PET/CT scans. Candidates for the prediction model were constructed by cross-combinations of 11 feature selection methods and 7 classifiers. The optimal model was determined by combining the results of cross-center data validation and model visualization (Yellowbrick). The predictive performance was assessed via receiver operating characteristic curve, confusion matrix and classification report. Four explainable artificial intelligence technologies were used for optimal model interpretation. Results: Sex and SUVmax were selected as clinical risk factors, which were then combined with 8 robust PET/CT HRFs to establish the models. The optimal performance was obtained by combining a light gradient boosting machine classifier with random forest feature selection method achieving an optimal performance with a macro-average AUC of 0.75 in the internal test group and 0.81 in the external test group. Conclusion: The explainable EGFR mutation status prediction model have certain clinical practicability and good generalization performance, which may help in the timely selection of treatment options and prognosis prediction in patients with LUAD. [ABSTRACT FROM AUTHOR]

The manufactured capital, usually denoted as material stocks from an industrial ecology perspective, has thus far received wide attention in sustainability and circularity science. Sustainable resource management should be rooted in detailed knowledge of manufactured capital accumulation in society at a high spatial resolution. Previous studies demonstrated that night‐time light (NTL) data provide a great opportunity for monitoring material stocks dynamics at a higher spatial resolution on the regional and global scale. However, the potential of historical–geographical refined material stocks has not been fully analyzed and explored because of the inconsistency of NTL images detected by the different satellites. In this study, based on a new set of material stocks data in China and harmonized NTL images (1992–2018), we map the national stocks of 13 bulk materials (including cement, gravel, wood, brick, sand, asphalt, glass, lime, plastic, rubber, copper, aluminum, and steel) at a 1 × 1 km resolution from 1992 to 2018. The results find that the total material stocks increased from 190,000 to 460,000 t/km2 between 1992 and 2018. Among the five end‐use sectors, buildings have the highest density of 430,000 t/km2, while domestic appliances have the lowest density of 140 t/km2. Four manufactured capital clusters, including the Yangtze River Delta, Pearl River Delta, Beijing–Tianjin–Hebei, and Chengdu–Chongqing agglomerations, possess 38% of the national total stocks in 2018, revealing an unbalanced distributed pattern of manufactured capital across China. Our results provide valuable support for policymakers and business decision‐makers on efficient resource management and urban mining. [ABSTRACT FROM AUTHOR]

Rising costs, complex supply chain management, and stringent regulations have created significant financial burdens on business sustainability, calling for new and rapid strategies to help enterprises transform. Supply chain digitalization (SCD) has emerged as a promising approach in the context of digitalization and globalization, with the potential to reduce an enterprise's debt costs. Developing a strategic framework for SCD that effectively reduces the cost of debt (CoD) has become a key academic challenge, critical for ensuring business sustainability. To this end, under the perspective of four flows, SCD is deconstructed into four distinct features: logistics flow digitalization (LFD), product flow digitalization (PFD), information flow digitalization (IFD), and capital flow digitalization (CFD). To precisely measure the four SCD features and the dependent variable, COD, publicly available data from Chinese listed manufacturing enterprises such as annual report texts and financial statement data are collected, and various data mining technologies are also used to conduct data measurement and data processing. To comprehensively investigate the impact pattern of SCD on CoD, we employed the explainable machine learning methodology for data analysis. This methodology involved in-depth data discussions, cross-validation utilizing a series of machine learning models, and the utilization of Shapley additive explanations (SHAP) to explain the results generated by the models. To conduct sensitivity analysis, permutation feature importance (PFI) and partial dependence plots (PDPs) were also incorporated as supplementary explanatory methods, providing additional insights into the model's explainability. Through the aforementioned research processes, the following findings are obtained: SCD can play a role in reducing CoD, but the effects of different SCD features are not exactly the same. Among the four SCD features, LFD, PFD, and IFD have the potential to significantly reduce CoD, with PFD having the most substantial impact, followed by LFD and IFD. In contrast, CFD has a relatively weak impact, and its role is challenging to discern. These findings provide significant guidance for enterprises in furthering their digitalization and supply chain development, helping them optimize SCD strategies more accurately to reduce CoD. [ABSTRACT FROM AUTHOR]

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Monopolar spindle kinase 1 (MPS1, also called TTK) is an attractive target for the treatment of cancers. Five MPS1 inhibitors have entered the clinical trials, but four of them were discontinued; thus, it is necessary to develop MPS1 inhibitors with novel scaffolds. In the present work, several computational tools were built to design MPS1 inhibitors. The deep recurrent neural network was used for generating potential highly active MPS1 inhibitors. The deep neural network was used to build a ligand-based consensus model for distinguishing the highly and weakly active MPS1 inhibitors. Five co-crystal structures were used to develop the consensus docking score for distinguishing actives and decoys. The ligand-based consensus model and the consensus docking score were used to evaluate the generated molecules, and finally, two scaffolds, which were less reported as MPS1 inhibitors previously, were selected. A total of 15 compounds with the two scaffolds were synthesized and tested by in vitro enzymatic inhibition assays. Five compounds had sub-micromolar to low micromolar in vitro potencies, and the most active compound was 10 with an IC50 of 556 nM. The binding modes of the new compounds were revealed by molecular dynamic simulations. We believe that the computational strategies in the present work were helpful for discovering new potential scaffolds. [ABSTRACT FROM AUTHOR]

The aim of this study was to explore the role of NADH:ubiquinone oxidoreductase subunit B3 (NDUFB3) in human gynecological malignancies and to screen potential natural compounds targeting it. GEPIA and HPA databases were used to study the expression characteristics of NDUFB3. GO and KEGG enrichment analyses were performed using the R software clusterProfiler package. GSEA for NDUFB3 was performed using the LinkedOmics database. Natural compounds targeting NDUFB3 were screened by virtual screening and molecular docking. After NDUFB3 was depleted or wedelolactone treatment, cell proliferation was detected by CCK‐8 assay. The production of reactive oxide species (ROS) in tumor cells was detected by dihydroethidium fluorescent probe. The cell cycle and apoptosis were evaluated by flow cytometry. It was revealed that NDUFB3 was highly expressed in ovarian cancer (OV), uterine corpus endometrial carcinoma (UCEC), and cervical squamous cell carcinoma (CESC). NDUFB3 expression was associated with multiple immunomodulators in CESC, OV, and UCEC. NDUFB3 was predicted to modulate MAPK signaling pathways in CESC, OV, and UCEC. Knocking down NDUFB3 inhibited the proliferation of CESC, OV, and UCEC cells, increased intracellular ROS production, and induced cell cycle arrest and apoptosis. Wedelolactone was a potential small molecule with a strong ability to bind with the active pocket of NDUFB3, and wedelolactone could kill CESC, OV, and UCEC cells partly via NDUFB3. In conclusion, NDUFB3 may be a potential biomarker and a new target for gynecological tumors, and wedelolactone may exert antitumor activity via targeting NDUFB3. [ABSTRACT FROM AUTHOR]