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BACKGROUND: Peutz-Jeghers syndrome (PJS) has brought significant physical, psychological and economic burdens on the patients and their families due to its early onset, diagnostic and therapeutic challenges and increased recurrence risk. AIM: To explore the current research status and emerging hotspots of PJS. METHODS: Studies on PJS published during 1994-2023 were gathered based on Web of Science Core Collection. Additionally, a case of PJS-induced intestinal intussusception, successfully treated with endoscopic methods despite three laparotomies, was highlighted. Comprehensive bibliometric and visual analysis were conducted with VOSviewer, R and CiteSpace. RESULTS: Altogether 1760 studies were identified, indicating a steady increase in the publication number. The United States had the highest influence, whereas the University of Helsinki emerged as the leading institution, and Aaltonen LA from the University of Helsinki was the most prolific author. Cancer Research, Oncogene and Endoscopy were the top three journals based on H-index. Keyword burst direction analysis revealed that "cancer risk", "management", "surveillance" and "familial pancreatic cancer" were the potential hotspots for investigation. Additionally, "early detection", "capsule endoscopy", "clinical management", "double-balloon endoscopy", "familial pancreatic cancer" and "molecular genetic basis" were identified as the key clusters of co-cited references. Endoscopic polypectomy remained effective on resolving intestinal intussusception in patients who underwent three previous laparotomies. CONCLUSION: In the last three decades, global publications related to PJS show a steadily increasing trend in number. Endoscopic management is currently a research hotspot.

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OBJECTIVE: To evaluate the diagnostic value of serum alkaline phosphatase (AKP), tumor-supplied growth factor group (TSGF), and lactate dehydrogenase (LDH) for pediatric osteosarcoma. METHODS: A retrospective analysis of clinical data from 81 pediatric osteosarcoma patients (osteosarcoma group) and 63 patients with benign bone tumors (benign bone tumor group) admitted to Yantaishan Hospital from February 2023 to November 2023 was conducted. Basic and clinical data differences between the two groups of children were compared. A multivariate regression model was established to determine predictive factors for pediatric osteosarcoma, and the diagnostic value of identified indicators for pediatric osteosarcoma was evaluated. RESULTS: Osteosarcoma group demonstrated significantly higher serum AKP (375.76±73.47 vs 286.12±76.50 U/L), TSGF (69.01±16.30 vs 53.57±16.37 U/mL), and LDH (269.55±66.96 vs 207.46±59.20 U/L) levels as compared to the benign bone tumor group. Correlation analysis suggested significant positive correlations between AKP (rho=0.505), TSGF (rho=406), LDH (rho=0.449) and pediatric osteosarcoma. Multivariate regression analysis showed serum AKP, TSGF, and LDH were independent predictive factor for pediatric osteosarcoma. The AUC value for AKP was 0.794, with a Youden index of 0.459; the AUC value for TSGF was 0.736, with a Youden index of 0.406; and the AUC value for LDH was 0.761, with a Youden index of 0.462. The combined use of these three biomarkers yielded an AUC of 0.886. CONCLUSION: The combined detection of serum AKP, TSGF, and LDH can enhance the diagnostic accuracy of pediatric osteosarcoma, providing important evidence for clinical treatment.

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Purpose: Healthcare professionals' participation is crucial for the efficient implementation of multidisciplinary team (MDT) collaboration models. We identified the key factors influencing healthcare professionals' preference to participate in MDTs in tertiary hospitals. Methods: To clarify the attributes and levels of the discrete choice experiment (DCE), we conducted a targeted literature review and conducted in-depth interviews with MDT service providers. Following this, a DCE was designed to evaluate healthcare professionals' preferences for MDT participation, and the influence of factors such as salary subsidies, leadership attention, patient participation, quality assessment, working intensity, and case complexity. A conditional logit model estimated the utility of each attribute. Willingness-to-pay estimates were derived by taking the negative ratio of the coefficients of non-economic and economic attributes. A series of policy simulation analyses were conducted. Results: Two hundred healthcare professionals completed the questionnaire, with 180 valid responses used for analysis. All attributes were statistically significant. Leadership attention and working intensity were the primary factors influencing staff willingness to participate in MDTs, followed by quality assessment and salary subsidies. Significant preference differences were observed between respondents; compared with mid-level staff, senior-level healthcare professionals believed patient engagement would be more helpful in boosting participation. The policy simulation showed that changing leadership attention from "neglect" to "emphasis" would increase the probability of staff choosing to participate in MDTs from 24.4% to 66.98%. Conclusion: Leadership attention was the primary concern for healthcare professionals in MDTs. To effectively motivate staff participation in MDTs, policymakers should adopt a holistic approach that considers work motivation and individual backgrounds, including competitive salary packages and a positive work environment. They should concurrently introduce MDT case complexity measurement tools to optimize resource allocation. Addressing staff members' unique needs and career aspirations by creating targeted training programs, pathways for advancement, and personalized career development plans are also crucial.

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This paper explores the evolution of geoscientific inquiry, tracing the progression from traditional physics-based models to modern data-driven approaches facilitated by significant advancements in artificial intelligence (AI) and data collection techniques. Traditional models, which are grounded in physical and numerical frameworks, provide robust explanations by explicitly reconstructing underlying physical processes. However, their limitations in comprehensively capturing Earth's complexities and uncertainties pose challenges in optimization and real-world applicability. In contrast, contemporary data-driven models, particularly those utilizing machine learning (ML) and deep learning (DL), leverage extensive geoscience data to glean insights without requiring exhaustive theoretical knowledge. ML techniques have shown promise in addressing Earth science-related questions. Nevertheless, challenges such as data scarcity, computational demands, data privacy concerns, and the "black-box" nature of AI models hinder their seamless integration into geoscience. The integration of physics-based and data-driven methodologies into hybrid models presents an alternative paradigm. These models, which incorporate domain knowledge to guide AI methodologies, demonstrate enhanced efficiency and performance with reduced training data requirements. This review provides a comprehensive overview of geoscientific research paradigms, emphasizing untapped opportunities at the intersection of advanced AI techniques and geoscience. It examines major methodologies, showcases advances in large-scale models, and discusses the challenges and prospects that will shape the future landscape of AI in geoscience. The paper outlines a dynamic field ripe with possibilities, poised to unlock new understandings of Earth's complexities and further advance geoscience exploration.

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Because of their numerous benefits such as high charge cycle count, low self-discharge rate, low maintenance requirements, and tiny footprint, Li-batteries have been extensively employed in recent times. However, mostly Li-batteries have a limited lifespan of up to three years after production, may catch fire if the separator is damaged, and cannot be recharged when they are fully depleted. Due to the significant heat generation that li-batteries produce while they are operating, the temperature difference inside the battery module rises. This reduces the operating safety of battery and limits its life. Therefore, maintaining safe battery temperatures requires efficient thermal management using both active and passive. Thermal optimization may be achieved battery thermal management system (BTMS) that employs phase change materials (PCMs). However, PCM's shortcomings in secondary heat dissipation and restricted thermal conductivity still require development in the design, structure, and materials used in BTMS. We summarize new methods to control temperature of batteries using Nano-Enhanced Phase Change Materials (NEPCMs), air cooling, metallic fin intensification, and enhanced composite materials using nanoparticles which work well to boost their performance. To the scientific community, the idea of nano-enhancing PCMs is new and very appealing. Hybrid and ternary battery modules are already receiving attention for the li-battery life span enhancement ultimately facilitating their broader adoption across various applications, from portable electronics to electric vehicles and beyond.

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Hydro-meteorological monitoring through satellites in arid and semi-arid regions is constrained by the coarse spatial resolution of precipitation data, which impedes detailed analyses. The objective of this study is to evaluate various machine learning techniques for developing a downscaling framework that generates high spatio-temporal resolution precipitation products. Focusing on the Hai River Basin, we evaluated three machine learning approaches-Extreme Gradient Boosting (XGBoost), Random Forest (RF), and Back Propagation (BP) neural networks. These methods integrate environmental variables including land surface temperature (LST), Normalized Difference Vegetation Index (NDVI), Digital Elevation Model (DEM), Precipitable Water Vapor (PWV), and albedo, to downscale the 0.1° spatial resolution Global Precipitation Measurement (GPM) product to a 1 km resolution. We further refined the results with residual correction and calibration using terrestrial rain gauge data. Subsequently, utilizing the 1 km annual precipitation, we employed the moving average window method to derive monthly and daily precipitation. The results demonstrated that the XGBoost method, calibrated with Geographical Difference Analysis (GDA) and Kriging spatial interpolation, proved to be the most accurate, achieving a Mean Absolute Error (MAE) of 58.40 mm for the annual product, representing a 14 % improvement over the original data. The monthly and daily products achieved MAE values of 11.61 mm and 1.79 mm, respectively, thus enhancing spatial resolution while maintaining accuracy comparable to the original product. In the Hai River Basin, key factors including longitude, latitude, DEM, LST_night, and PWV demonstrated greater importance and stability than other factors, thereby enhancing the model's precipitation prediction capabilities. This study provides a comprehensive assessment of the annual, monthly, and daily high-temporal and high-spatial resolution downscaling processes of precipitation, serving as an important reference for hydrology and related fields.

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New energy vehicles (NEVs) are considered a crucial means of reducing travel costs, enhancing consumer experiences, and innovating services. This paper aims to categorize the functional experiences of NEVs into two types: intelligent experience and eco-friendly experience, using a dual-path model. By analyzing 118,648 text data from automotive information and service platforms, the relevant factors influencing consumer satisfaction are explored. The research findings reveal that intelligent experience has a significantly positive impact on consumer satisfaction, whereas eco-friendly experience has a significantly negative impact on consumer satisfaction. This suggests that new energy vehicle companies need technological innovation in infrastructure and range to enhance consumer satisfaction. Furthermore, the research confirms that, when facing the intelligent experience of new energy vehicles, consumers' "rational" thinking plays a dominant role, and efficacy is an intermediate variable to enhance consumer satisfaction. On the other hand, when facing the eco-friendly experience of new energy vehicles, consumers' "emotional" thinking predominates, and identity is an intermediate variable to enhance consumer satisfaction. Additionally, the moderating effect of perceived usability is examined. When faced with the intelligent experience of NEVs, consumers with high perceived usability are more likely to generate a sense of efficiency. In the case of the eco-friendly experience of NEVs, consumers with low perceived usability are more likely to experience a sense of identity.

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BACKGROUND: Postoperative delirium (POD) is a serious and common complication. The aim of present study is to investigate the diurnal variation of POD and the effects of esketamine in elderly patients. METHODS: A randomized, double-blind, placebo-controlled clinical trial with factorial design was conducted. Patients (aged 65 to 85 years) with normal Mini-Mental State Examination (MMSE) score were stratified by age (≤70 vs. >70) and American Society of Anesthesiologists physical status classification (Ⅱ vs. Ⅲ), then randomly assigned to either morning (08:00-12:00) or afternoon (14:00-18:00) noncardiac operation under general anesthesia with or without esketamine administration (0.2 mg/kg). The primary outcome was the incidence of POD (3-Minute Diagnostic Interview for Confusion Assessment Method-defined Delirium, 3D-CAM) on postoperative days 1, 3, and 7. The secondary outcomes were the scores of MMSE and Hospital Anxiety and Depression Scale. The intention-to-treat analysis of the outcomes were performed by generalized estimating equation. RESULTS: Six patients who did not receive an intervention because of canceled operation were excluded after randomization. The datasets containing 426 cases were analyzed following the intention-to-treat principle after handling missing data via multiple imputation method. The incidence of POD declined from about 55% on postoperative day 1 to 31 and 18% on postoperative days 3 and 7, respectively. Afternoon operation [B=-0.583, OR (95% CI) 0.558 (0.319-0.976); P=0.041], but not esketamine, significantly decreased the incidence of POD. Both esketamine and operation time failed to significantly affect MMSE, HAD, and NRS score. There was no interaction among operation time, esketamine, and follow up time. CONCLUSION: Elderly patients undergoing elective noncardiac surgery in the afternoon displayed lower POD incidence than those operated in the morning. A single low-dose of esketamine before general anesthesia induction failed to significantly decrease the risk of POD but decrease the risk of intraoperative hypotension and emergence agitation.

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BACKGROUND: F-627 (efbemalenograstim alfa) is a novel long acting granulocyte colony-stimulating factor (G-CSF) that contains two human G-CSF fused to a human immunoglobulin G2 (hIgG2) -Fc fragment with a peptide linker. This studyevaluated the efficacy and safety of F-627, also known as efbemalenograstim alfa (Ryzneuta®) in reducing neutropenia compared with filgrastim (GRAN®). METHODS: This was a multicenter, randomized, open-label, active-controlled non-inferiority study. Two hundred thirty nine (239) patients were enrolled in thirteen centers and received the chemotherapy with epirubicin (100 mg/m2) and cyclophosphamide (600 mg/m2) on day 1 of each cycle for a maximum of four cycles. Patients were randomized to receive either a single 20 mg subcutaneous (s.c.) injection of F-627 on day 3 of each cycle or daily s.c. injection of filgrastim 5 µg/kg/d starting from day 3 of each cycle. The primary endpoint was the duration of grade 3 or 4 neutropenia in cycle 1. The safety profile was also evaluated. RESULTS: The mean (SD) duration of grade 3 or 4 neutropenia in cycle 1 was 0.68 (1.10) and 0.71 (0.95) days for the F-627 and the filgrastim groups, respectively. The Hodges-Lehmann estimate of the between-group median difference (F-627 vs filgrastim) in the duration of grade 3 or 4 neutropenia in cycle 1 was 0 day and the upper limit of the one-sided 97.5% CI was 0 day, which was within the prespecified non-inferiority margin of 1-day. Results for all efficacy endpoints in cycles 2 - 4 were consistent with the results in cycle 1, however a trend towards a lower incidence and a shorter duration of grade 3 or 4 neutropenia and grade 4 neutropenia was observed in the F-627 group compared with the filgrastim group. The ANC nadir in the F-627 group was significantly higher than that in the filgrastim group in each cycle. A single fixed dose of F-627 was well tolerated and as safe as standard daily filgrastim. CONCLUSIONS: A single fixed dose of 20 mg of F-627 in each cycle was as safe and effective as a daily dose of filgrastim 5 µg/kg/d in reducing neutropenia and its complications in patients who received four cycles of EC. TRIAL REGISTRATION: ClinicalTrials.gov: NCT04174599, on 22/11/2019.

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As a protein extracted from soybeans, soy protein isolate (SPI) may undergo the Maillard reaction (MR) with co-existing saccharides during the processing of soy-containing foods, potentially altering its structural and functional properties. This work aimed to investigate the effect of mono- and polysaccharides on the structure and functional properties of SPI during MR. The study found that compared to oat ß-glucan, the reaction rate between SPI and D-galactose was faster, leading to a higher degree of glycosylation in the SPI-galactose conjugate. D-galactose and oat ß-glucan showed different influences on the secondary structure of SPI and the microenvironment of its hydrophobic amino acids. These structural variations subsequently impact a variety of the properties of the SPI conjugates. The SPI-galactose conjugate exhibited superior solubility, surface hydrophobicity, and viscosity. Meanwhile, the SPI-galactose conjugate possessed better emulsifying stability, capability to produce foam, and stability of foam than the SPI-ß-glucan conjugate. Interestingly, the SPI-ß-glucan conjugate, despite its lower viscosity, showed stronger hypoglycemic activity, potentially due to the inherent activity of oat ß-glucan. The SPI-galactose conjugate exhibited superior antioxidant properties due to its higher content of hydroxyl groups on its molecules. These results showed that the type of saccharides had significant influences on the SPI during MR.

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By integrating the thermal characteristics from thermal-infrared remote sensing with the physiological and structural information of vegetation revealed by multispectral remote sensing, a more comprehensive assessment of the crop soil-moisture-status response can be achieved. In this study, multispectral and thermal-infrared remote-sensing data, along with soil-moisture-content (SMC) samples (0~20 cm, 20~40 cm, and 40~60 cm soil layers), were collected during the flowering stage of soybean. Data sources included vegetation indices, texture features, texture indices, and thermal-infrared vegetation indices. Spectral parameters with a significant correlation level (p < 0.01) were selected and input into the model as single- and fuse-input variables. Three machine learning methods, eXtreme Gradient Boosting (XGBoost), Random Forest (RF), and Genetic Algorithm-optimized Backpropagation Neural Network (GA-BP), were utilized to construct prediction models for soybean SMC based on the fusion of UAV multispectral and thermal-infrared remote-sensing information. The results indicated that among the single-input variables, the vegetation indices (VIs) derived from multispectral sensors had the optimal accuracy for monitoring SMC in different soil layers under soybean cultivation. The prediction accuracy was the lowest when using single-texture information, while the combination of texture feature values into new texture indices significantly improved the performance of estimating SMC. The fusion of vegetation indices (VIs), texture indices (TIs), and thermal-infrared vegetation indices (TVIs) provided a better prediction of soybean SMC. The optimal prediction model for SMC in different soil layers under soybean cultivation was constructed based on the input combination of VIs + TIs + TVIs, and XGBoost was identified as the preferred method for soybean SMC monitoring and modeling, with its R2 = 0.780, RMSE = 0.437%, and MRE = 1.667% in predicting 0~20 cm SMC. In summary, the fusion of UAV multispectral and thermal-infrared remote-sensing information has good application value in predicting SMC in different soil layers under soybean cultivation. This study can provide technical support for precise management of soybean soil moisture status using the UAV platform.

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Numerous plants evolve ingeniously microcantilever-based hairs to ultra-sensitively detect out-of-plane quasi-static tactile loads, providing a natural blueprint for upgrading the industrial static mode microcantilever sensors, but how do the biological sensory hairs work mechanically? Here, the action potential-producing trigger hairs of carnivorous Venus flytraps (Dionaea muscipula) are investigated in detail from biomechanical perspective. Under tiny mechanical stimulation, the deformable trigger hair, composed of distal stiff lever and proximal flexible podium, will lead to rapid trap closure and prey capture. The multiple features determining the sensitivity such as conical morphology, multi-scale functional structures, kidney-shaped sensory cells, and combined deformation under tiny mechanical stimulation are comprehensively researched. Based on materials mechanics, finite element simulation, and bio-inspired original artificial sensors, it is verified that the omnidirectional ultra-sensitivity of trigger hair is attributed to the stiff-flexible coupling of material, the double stress concentration, the circular distribution of sensory cells, and the positive local buckling. Also, the balance strategy of slender hair between sensitivity and structural stability (i.e., avoiding disastrous collapse) is detailed revealed. The unique basic biomechanical mechanism underlying trigger hairs is essential for significantly enhancing the performance of the traditional industrial static mode microcantilever sensors, and ensure the stability of arbitrary load perception.

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AIM: The study objective was to evaluate the primary feasibility of endoscopic submucosal resection (ESD) and endoscopic full-thickness resection (EFTR) via balloon-assisted enteroscopy (BAE) to treat small bowel subepithelial lesions (SELs). METHOD: A retrospective case series study was performed. The first fifteen consecutive patients who underwent ESD (n = 10) and EFTR (n = 5) via BAE to remove small bowel SELs from November 2016 to December 2023 were included. The main outcome measures were the technique success rate, operative time and complication rate. RESULTS: This research focused on 15 cases of jejunoileal SELs, four cases of lipomyoma, three cases of ectopic pancreas, two cases of NETs, three cases of benign fibrous tumours and three cases of angioma. The overall technique success rate was 86.7%, with 100% (10/10) and 60% (3/5) for BAE-ESD and BAE-EFTR, respectively, in removing small bowel SELs. Two cases of EFTR failed, as the BAE operation was unsuitable for tumour resection and suture repair of a perforated wound. No serious bleeding or any postoperative complications occurred. The median time of endoscopic resection via BAE for SELs was 44 min (range 22-68 min). CONCLUSION: ESD and EFTR via BAE might be alternative choices for treating small SELs in the small bowel, with the advantages of clear and accurate positioning and minimal invasiveness. However, its superiority over surgery still needs to be further investigated.

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Hydrogel-based 3D cell cultures are extensively utilized to create biomimetic cellular microstructures. However, there is still lack of effective method for both evaluation of the complex interaction of cells with hydrogel and the functionality of the resulting micro-structures. This limitation impedes the further application of these microstructures as microphysiological models (microPMs) for the screening of potential culture condition combinations to enhance the skeletal muscle regeneration. This paper introduces a two-probe micromanipulation method for the large-scale assessment of viscoelasticity and contractile force (CF) of skeletal muscle microPMs, which are produced in high-throughput via microfluidic spinning and 96-well culture. The collected data demonstrate that viscoelasticity parameters (E* and tanδ) and CF both measured in a solution environment are indicative of the formation of cellular structures without hydrogel residue and the subsequent generation of myotubes, respectively. This study have developed screening criterias that integrate E*, tanδ, and CF to examine the effects of multifactorial interactions on muscle fiber repair under hypoxic conditions and within bioprinted bipennate muscle structures. This approach has improved the quality of hypoxic threshold evaluation and aligned cell growth in 3D. The proposed method is useful in exploring the role of different factors in muscle tissue regeneration with limited resources.

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This study investigated the toxicological effects and mechanisms of cadmium (Cd) (5 and 50 µg/L) and selenium (Se) (3 and 30 µg/L) at environmentally relevant concentrations on the gills and digestive glands of clams Ruditapes philippinarum. Results indicated that Cd and Se could tissue-specifically impact osmoregulation, energy metabolism, and synaptic transmission in the gills and digestive glands of clams. After exposure to 50 µg/L Cd, the digestive glands of clams up-regulated the expression of methionine-gamma-lyase and metallothionein for detoxification. Clam digestive glands exposed to 3 µg/L Se up-regulated the expression of catalase and glutathione peroxidase to alleviate oxidative stress, and down-regulated the expression of selenide-water dikinase to reduce the conversion of inorganic Se. Additionally, the interaction mode between Cd and Se largely depended on their molar ratio, with a ratio of 11.71 (50 µg/L Cd + 3 µg/L Se) demonstrated to be particularly harmful, as manifested by significantly more lesions, oxidative stress, and detoxification demand in clams than those exposed to Cd or Se alone. Collectively, this study revealed the complex interaction patterns and mechanisms of Cd and Se on clams, providing a reference for exploring their single and combined toxicity.

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BACKGROUND: The American Heart Association recently introduced a novel cardiovascular health (CVH) metric, Life's Essential 8 (LE8), for health promotion. However, the relationship between LE8 and cancer mortality risk remains uncertain. METHODS: We investigated 17,076 participants from US National Health and Nutrition Examination Survey (US NHANES) and 272,727 participants from UK Biobank, all free of cancer at baseline. The CVH score, based on LE8 metrics, incorporates four health behaviors (diet, physical activity, smoking, and sleep) and four health factors (body mass index, lipid, blood glucose, and blood pressure). Self-reported questionnaires assessed health behaviors. Primary outcomes were mortality rates for total cancer and its subtypes. The association between CVH score (continuous and categorical variable) and outcomes was examined using Cox model with adjustments. Cancer subtypes-related polygenic risk score (PRS) was constructed to evaluate its interactions with CVH on cancer death risk. RESULTS: Over 141,526 person-years in US NHANES, 424 cancer-related deaths occurred, and in UK Biobank, 8,872 cancer deaths were documented during 3,690,893 person-years. High CVH was associated with reduced overall cancer mortality compared to low CVH (HR 0.58, 95% CI 0.37-0.91 in US NHANES; 0.51, 0.46-0.57 in UK Biobank). Each one-standard deviation increase in CVH score was linked to a 19% decrease in cancer mortality (HR: 0.81; 95% CI: 0.73-0.91) in US NHANES and a 19% decrease (HR: 0.81; 95% CI: 0.79-0.83) in UK Biobank. Adhering to ideal CVH was linearly associated with decreased risks of death from lung, bladder, liver, kidney, esophageal, breast, colorectal, pancreatic, and gastric cancers in UK Biobank. Furthermore, integrating genetic data revealed individuals with low PRS and high CVH exhibited the lowest mortality from eight cancers (HRs ranged from 0.36 to 0.57) compared to those with high PRS and low CVH. No significant modification of the association between CVH and mortality risk for eight cancers by genetic predisposition was observed. Subgroup analyses showed a more pronounced protective association for overall cancer mortality among younger participants and those with lower socio-economic status. CONCLUSIONS: Maintaining optimal CVH is associated with a substantial reduction in the risk of overall cancer mortality. Adherence to ideal CVH correlates linearly with decreased mortality risk across multiple cancer subtypes. Individuals with both ideal CVH and high genetic predisposition demonstrated significant health benefits. These findings support adopting ideal CVH as an intervention strategy to mitigate cancer mortality risk and promote healthy aging.

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BACKGROUND: With the development of percutaneous coronary intervention (PCI), the number of interventional procedures without implantation, such as bioresorbable stents (BRS) and drug-coated balloons, has increased annually. Metal drug-eluting stent unloading is one of the most common clinical complications. Comparatively, BRS detachment is more concealed and harmful, but has yet to be reported in clinical research. In this study, we report a case of BRS unloading and successful rescue. CASE SUMMARY: This is a case of a 59-year-old male with the following medical history: "Type 2 diabetes mellitus" for 2 years, maintained with metformin extended-release tablets, 1 g PO BID; "hypertension" for 20 years, with long-term use of metoprolol sustained-release tablets, 47.5 mg PO QD; "hyperlipidemia" for 20 years, without regular medication. He was admitted to the emergency department of our hospital due to intermittent chest pain lasting 18 hours, on February 20, 2022 at 15: 35. Electrocardiogram results showed sinus rhythm, ST-segment elevation in leads I and avL, and poor R-wave progression in leads V1-3. High-sensitivity troponin I level was 4.59 ng/mL, indicating an acute high lateral wall myocardial infarction. The patient's family requested treatment with BRS, without implantation. During PCI, the BRS became unloaded but was successfully rescued. The patient was followed up for 2 years; he had no episodes of angina pectoris and was in generally good condition. CONCLUSION: We describe a case of a 59-year-old male experienced BRS unloading and successful rescue. By analyzing images, the causes of BRS unloading and the treatment plan are discussed to provide insights for BRS release operations. We discuss preventive measures for BRS unloading.

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Extracellular protein coronas (exPCs), which have been identified in various biofluids, are recognized for their pivotal role in mediating the interaction between nanoparticles and the cytomembrane. However, it is still unclear whether various exPCs can induce different levels of intracellular proteostasis, which is of utmost importance in preserving cellular function, and eliciting distinct intracellular biological behaviors. To investigate this, two types of exPC-coated iron oxide nanoparticles (IONPs) are prepared and used to investigate the influence of exPCs on extracellular and intracellular biological outcomes. The results demonstrate that the formation of exPCs promotes the colloidal stability of IONPs, and the discrepancies in the components of the two exPCs, including opsonin, dysopsonin, and lipoprotein, are responsible for the disparities in cellular uptake and endocytic pathways. Moreover, the differential evolution of the two exPCs during cellular internalization leads to distinct autophagy and glycolysis activities, which can be attributed to the altered depletion of angiopoietin 1 during the formation of intracellular protein coronas, which ultimately impacts the PI3K/AKT-mTOR signaling. These findings offer valuable insights into the dynamic characteristics of exPCs during cellular internalization, and their consequential implications for cellular internalization and intracellular metabolism activity, which may facilitate the comprehension of PCs on biological effects of NPs and expedite the design and application of biomedical nanoparticles.

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Glucocorticoid-induced osteoporosis (GIOP) commonly accelerates bone loss, increasing the risk of fractures and osteonecrosis more significantly than traditional menopausal osteoporosis. The extracellular environment influenced by glucocorticoids heightens fracture and osteonecrosis risks. Fraxin (Fra), a key component of the traditional Chinese herbal remedy Cortex Fraxini, is known for its wide-ranging pharmacological effects, but its impact on GIOP remains unexplored. This investigation aims to delineate the effects and underlying mechanisms of Fra in combating dexamethasone (Dex)-induced ferroptosis and GIOP. We established a mouse model of GIOP via intraperitoneal injections of Dex and cultured osteoblasts with Dex treatment for in vitro analysis. We evaluated the impact of Fra on Dex-treated osteoblasts through assays such as C11-BODIPY and FerroOrange staining, mitochondrial functionality tests, and protein expression analyses via Western blot and immunofluorescence. The influence of Fra on bone microarchitecture of GIOP in mice was assessed using microcomputerized tomography, hematoxylin and eosin staining, double-labeling with Calcein-Alizarin Red S, and immunohistochemistry at imaging and histological levels. Based on our data, Fra prevented Dex-induced ferroptosis and bone loss. In vitro, glutathione levels increased and malondialdehyde, lipid peroxidation, and mitochondrial reactive oxygen species decreased. Fra treatment also increases nuclear factor erythroid 2-related factor 2 (Nrf2), glutathione peroxidase 4 (GPX4), and COL1A1 expression and promotes bone formation. To delve deeper into the mechanism, the findings revealed that Fra triggered the activation of Nrf2/GPX4 signaling. Moreover, the use of siRNA-Nrf2 blocked the beneficial effect of Fra in osteoblasts cultivated with Dex. Fra effectively combats GIOP by activating the Nrf2/GPX4 signaling pathway to inhibit ferroptosis.