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Learning how to effectively respond to ethical dilemma can affect nurses’ physical and mental health, which is not conducive to developing a nursing career. Nursing students’ ethical behavior warrants attention as professionals about to begin clinical work. We aim to understand the current situation and influencing factors of Chinese nursing students’ ethical behavior. A cross-sectional descriptive study was conducted. Descriptive statistics and multiple linear regression were used to analyze the data. Full-time nursing students were recruited from an undergraduate medical university in Jinan through convenient sampling from November to December 2021. Research ethics approval (No. 2022-0018) was obtained from the Ethics Committee of Affiliated Hospital of Shandong University of Traditional Chinese Medicine. Informed consent was also received from participants. The EBT scores of the nursing students were 95.14 ± 11.37, which was not high compared with the total score. Gender, year level, and professional values had a significant impact on participants’ ethical behavior. A positive correlation was found between nursing professional values and ethical behavior. A gap still exists between the moral development and maturity of undergraduate nursing students. To further cultivate their ethical behavior and improve their confidence and ability to respond to ethical dilemmas, more innovative methods must be employed in teaching ethics courses, and continuity in the ethics education system must be maintained. For male and third- and fourth-year nursing students who showed lower ethical behavior scores, nursing educators can develop their ethical behaviors by helping them establish positive professional values. Plain Language Summary Ethical behavior refers to the actions taken by individuals when they encounter ethical dilemmas, which can either benefit or harm others and society. The occurrence of clinical ethical dilemmas is unavoidable, which often causes pressure to nurses and threatens the physical and mental health of nurses. Nursing students are valuable assets to the nursing profession, and their demonstration of positive ethical behavior can significantly boost their confidence and competence in resolving ethical dilemmas, which is conducive to the development of nursing work and career. This study aimed to investigate the current situation and influencing factors of nursing students’ ethical behavior in China. A total of 921 nursing students from a medical college in Shandong Province were surveyed using the Chinese version of the Ethical Behavior Test (EBT) and Revised Nursing Professional Values Scale (NPVS-R). The results of this study showed that ethical behavior of Chinese nursing students was relatively immature. Female nursing students, first- and second-year nursing students and nursing students who agree with the nursing professional view have more mature ethical behavior and they can deal with ethical dilemmas more effectively. We should focus on those students who have difficulties in adopting positive ethical behavior to solve ethical dilemmas and find powerful measures to improve the current situation of ethical behavior. This study is limited by a single sample source and limited exploration variables. Future research should expand the sample sources at more universities, explore other influencing factors, and take intervention measures to improve the moral behavior of nursing students.

Magic-angle twisted trilayer graphene (MATTG) exhibits a range of strongly correlated electronic phases that spontaneously break its underlying symmetries 1 , 2 . Here we investigate the correlated phases of MATTG using scanning tunnelling microscopy and identify marked signatures of interaction-driven spatial symmetry breaking. In low-strain samples, over a filling range of about two to three electrons or holes per moiré unit cell, we observe atomic-scale reconstruction of the graphene lattice that accompanies a correlated gap in the tunnelling spectrum. This short-scale restructuring appears as a Kekulé supercell—implying spontaneous inter-valley coherence between electrons—and persists in a wide range of magnetic fields and temperatures that coincide with the development of the gap. Large-scale maps covering several moiré unit cells further reveal a slow evolution of the Kekulé pattern, indicating that atomic-scale reconstruction coexists with translation symmetry breaking at a much longer moiré scale. We use auto-correlation and Fourier analyses to extract the intrinsic periodicity of these phases and find that they are consistent with the theoretically proposed incommensurate Kekulé spiral order 3 , 4 . Moreover, we find that the wavelength characterizing moiré-scale modulations monotonically decreases with hole doping away from half-filling of the bands and depends weakly on the magnetic field. Our results provide essential insights into the nature of the correlated phases of MATTG in the presence of strain and indicate that superconductivity can emerge from an inter-valley coherent parent state. Scanning tunnelling microscopy imaging of the correlated phases of magic-angle twisted trilayer graphene shows marked signatures of interaction-driven spatial symmetry breaking.

Acute kidney injury (AKI) is a frequent clinical complication in critically ill patients, and it rapidly develops into renal failure with high morbidity and mortality. However, other than dialysis, no effective therapeutic interventions can offer reliable treatment to limit renal injury and improve survival. Here, we firstly reported that remdesivir (RDV, GS-5734), a broad-spectrum antiviral nucleotide prodrug, alleviated AKI by specifically inhibiting NOD-, LRR-, and pyrin domain-containing protein 3 (NLRP3) inflammasome activation in macrophages. Mechanically, RDV effectively suppressed the activities of nuclear transcription factor (NF)-κB, mitogen-activated protein kinase (MAPK), which further led to the reduction of the inflammasome genes of NLRP3 transcription, limiting the activation of NLRP3 inflammasome in vivo and in vitro . RDV also inhibited other pro-inflammatory genes including tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), IL-12, IL-1β, and interferon–β (IFN-β), leading to the reduction of inflammatory factors release. Thus, RDV can ameliorate AKI via modulating macrophage inflammasome activation and inflammatory immune responses and may have a therapeutic potential for patients with AKI in clinical application.

Chronic pancreatitis (CP) is characterized by irreversible fibrotic destruction and impaired pancreatic function. CP disrupts lipid metabolism and causes the imbalance of gut microbiota which in turn exacerbates pancreatic fibrosis. Statins alter gut microbiota and exert anti-inflammatory effects, but its role in CP has not been fully elucidated. Here, we found that statins-associated higher abundance of Lactobacillus intestinalis ( L.intestinalis ) maintained gut homeostasis that restrained bacteria translocation from gut to the pancreas, which eventually aggravated pancreatic fibrosis through inhibiting CD8 + T cells-dependent immunity. Fecal microbiota transplantation (FMT) or L.intestinalis administration inhibited the infiltration of CD8 + T cells and macrophages that delayed CP progression. L.intestinalis restrained the recruitment of M1 macrophages and limited the release of Ccl2/7 in the colon, which prevented epithelial damage and epithelial barrier dysfunction through blocking Ccl2/7-Ccr1 signaling. Our findings elucidate that the utilization of statin therapy or supplementation of L.intestinalis can be potential approach for the therapies of CP.

The decreased reconstruction potential of aging bone marrow mesenchymal stem cells (BMMSCs) fails to resist compromised bone healing, and strategies to remodel the regeneration capacity of senescent BMMSCs are urgently needed. A depletion of ARG1+ macrophages in aging murine exacerbates the impaired reconstructive functionality of BMMSCs, eventually becomes a critical obstacle for aged osteointegration. Herein, we fabricated a niche-like multiscale porous Titanium (p-Ti) implant using a vapor-phase-assisted alloying-dealloying strategy for in-situ manipulating the regenerative repair potential of BMMSCs while alleviating immunosenescence during bone reconstruction. This versatile method can be used to fabricate a porous surface layer on commercial implants with complex geometries. As benchmarked with commercial Ti, the in vitro and in vivo results of rabbits and rats show our niche-like p-Ti efficiently promotes BMMSCs to engender an osteogenic phenotype and attune the areas of bone defect. Moreover, niche-like multiscale porous structure yields rejuvenated ARG1+ macrophages in tandem with BMMSCs osteogenic differentiation at the bone-implant interface, modulating the immunosenescence, and synergistically promoting the osteointegration. Our findings establish that the macrophage can be re-engineered to be youthful for maintaining immune homeostasis, thereby providing a reversible treatment strategy for bone reconstruction of old people with broad applications in other senescence-related diseases. The declined reconstruction potential of aging BMMSCs fails to antagonize compromised bone healing. Our vapor-phase-assisted alloying-dealloying-customized niche-like multiscale porous p-Ti efficiently manipulates the regenerative repair potential of BMMSCs to engender an osteogenic phenotypic and attune the balance of immunosenecence. Moreover, multiscale structure with niche-like pores yields rejuvenated ARG1+ macrophages enlists the regenerative capacity of resident BMMSCs and restoration youthful structure and functional features to the aged bone. [Display omitted] •Niche-like porous Ti (p-Ti) can be fabricated through vapor phase dealloying.•P-Ti manipulates BMMSCs osteogenesis in tandem with macrophages rejuvenation.•P-Ti revolutionizes the treatment in senescence-related diseases.

Objective. To investigate the preventive effects of Ilex cornuta aqueous extract (ICAE) on high-fat diet (HFD)-induced fatty liver of mice and its mechanisms. Materials and Methods. Twenty-six male KM (Kunming) mice were divided into 3 groups, including the control group (n = 9), fed with normal diet; HFD group (n = 9), fed with HFD; ICAE + HFD group (n = 8), fed with HFD and administered with ICAE (3 g·kg−1·d−1) at the same time for 10 weeks. Body weight, liver weight, intra-abdominal and subcutaneous fat weight, serum triglyceride (TG), total cholesterol (TC), and blood glucose were determined to evaluate the preventive effects of ICAE on obesity. The average 24 h food consumption of the mice was monitored for 5 times in the 9th week of the experiment to investigate the effects of ICAE on food intake. Serum alanine transaminase (ALT) and aspartate aminotransferase (AST) were assayed to observe the influences of HFD and ICAE on liver function. HE staining was adopted to observe the influence of ICAE on the morphology of adipose tissue and liver tissue. Hepatic TG and TC content assay and oil red O staining were used to evaluate the influences of ICAE on HFD-induced fatty liver, and the protein expression of peroxisome proliferator-activated receptors γ (PPARγ) and adipose differentiation-related protein (ADRP) in liver were examined by immunoblotting. Results. ICAE treatment significantly reduced the increase of body weight, intra-abdominal, and subcutaneous fat and liver weight induced by HFD (P<0.001), but has no influence on food intake; ICAE treatment attenuated the elevation of serum TG, TC, and glucose, as well as serum ALT and AST (P<0.01, P<0.05, P<0.001) and dramatically decreased the content of TG in liver (P<0.01), but has no influence on hepatic TC content. HE staining and oil red O staining showed that ICAE significantly reduced HFD-induced white adipocyte hypertrophy and significantly inhibited lipid accumulation in liver. Immunoblotting showed that the protein levels of PPARγ and ADRP were significantly increased by HFD induction, which can be dramatically reduced by ICAE treatment (P<0.05, P<0.0001). Conclusion. ICAE has preventive effects on HFD-induced obesity and fatty liver in mice, exerted beneficial effects upon HFD-induced hepatic injury. The preventive effects of ICAE on fatty liver are concerned with the downregulation of PPARγ and ADRP protein expression in liver.

Magic-angle twisted trilayer graphene (MATTG) exhibits a range of strongly correlated electronic phases that spontaneously break its underlying symmetries. The microscopic nature of these phases and their residual symmetries stands as a key outstanding puzzle whose resolution promises to shed light on the origin of superconductivity in twisted materials. Here we investigate correlated phases of MATTG using scanning tunneling microscopy and identify striking signatures of interaction-driven spatial symmetry breaking. In low-strain samples, over a filling range of about 2-3 electrons or holes per moiré unit cell, we observe atomic-scale reconstruction of the graphene lattice that accompanies a correlated gap in the tunneling spectrum. This short-scale restructuring appears as a Kekulé supercell -- implying spontaneous inter-valley coherence between electrons -- and persists in a wide range of magnetic fields and temperatures that coincide with the development of the gap. Large-scale maps covering several moiré unit cells further reveal a slow evolution of the Kekulé pattern, indicating that atomic-scale reconstruction coexists with translation symmetry breaking at the much longer moiré scale. We employ auto-correlation and Fourier analyses to extract the intrinsic periodicity of these phases and find that they are consistent with the theoretically proposed incommensurate Kekulé spiral order. Moreover, we find that the wavelength characterizing moiré-scale modulations monotonically decreases with hole doping away from half-filling of the bands and depends only weakly on the magnetic field. Our results provide essential insights into the nature of MATTG correlated phases in the presence of strain and imply that superconductivity emerges from an inter-valley coherent parent state.

Time-series forecasting (TSF) finds broad applications in real-world scenarios. Due to the dynamic nature of time-series data, it is crucial to equip TSF models with out-of-distribution (OOD) generalization abilities, as historical training data and future test data can have different distributions. In this paper, we aim to alleviate the inherent OOD problem in TSF via invariant learning. We identify fundamental challenges of invariant learning for TSF. First, the target variables in TSF may not be sufficiently determined by the input due to unobserved core variables in TSF, breaking the conventional assumption of invariant learning. Second, time-series datasets lack adequate environment labels, while existing environmental inference methods are not suitable for TSF. To address these challenges, we propose FOIL, a model-agnostic framework that enables timeseries Forecasting for Out-of-distribution generalization via Invariant Learning. FOIL employs a novel surrogate loss to mitigate the impact of unobserved variables. Further, FOIL implements a joint optimization by alternately inferring environments effectively with a multi-head network while preserving the temporal adjacency structure, and learning invariant representations across inferred environments for OOD generalized TSF. We demonstrate that the proposed FOIL significantly improves the performance of various TSF models, achieving gains of up to 85%.

Time series data are ubiquitous across a wide range of real-world domains. While real-world time series analysis (TSA) requires human experts to integrate numerical series data with multimodal domain-specific knowledge, most existing TSA models rely solely on numerical data, overlooking the significance of information beyond numerical series. This oversight is due to the untapped potential of textual series data and the absence of a comprehensive, high-quality multimodal dataset. To overcome this obstacle, we introduce Time-MMD, the first multi-domain, multimodal time series dataset covering 9 primary data domains. Time-MMD ensures fine-grained modality alignment, eliminates data contamination, and provides high usability. Additionally, we develop MM-TSFlib, the first-cut multimodal time-series forecasting (TSF) library, seamlessly pipelining multimodal TSF evaluations based on Time-MMD for in-depth analyses. Extensive experiments conducted on Time-MMD through MM-TSFlib demonstrate significant performance enhancements by extending unimodal TSF to multimodality, evidenced by over 15% mean squared error reduction in general, and up to 40% in domains with rich textual data. More importantly, our datasets and library revolutionize broader applications, impacts, research topics to advance TSA. The dataset is available at https://github.com/AdityaLab/Time-MMD.