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Abstract Aim To investigate the level of compassion fatigue among frontline nurses during the COVID-19 pandemic and to explore the relationship between occupational stressors and compassion fatigue among frontline nurses based on structural equation modelling. Background Three years into the COVID-19 pandemic, nurses on the frontlines of the battle were overwhelmed by affective and emotional inputs while caring for patients, and they generally experienced varying degrees of psychological problems. High levels of compassion fatigue can affect nursing quality and patient safety and therefore should be taken seriously by nursing managers. Methods A cross-sectional survey of 1432 frontline nurses in Sichuan Province, China, was conducted from January to March 2023 via convenience sampling methods. The General Information Questionnaire, the Nurses’ Occupational Stressors Scale, the Ego-Resilience Scale, the Chinese version of the Compassion Fatigue Brief Scale, and the Perceived Organizational Support Scale were used to collect the data. Hypotheses were tested using structural equation models and bootstrapping methods. Results Nurse occupational stressors had a significant direct effect on compassion fatigue (B = 2.429, p

Abstract Audio-visual event localization (AVEL) task aims to judge and classify an audible and visible event. Existing methods devote to this goal by transferring pre-trained knowledge as well as understanding temporal dependencies and cross-modal correlations of the audio-visual scene. However, most works comprehend the audio-visual scene from an entangled temporal-aware perspective, ignoring the learning of temporal dependency and cross-modal correlation in both forward and backward temporal-aware views. Recently, transferring the pre-trained knowledge from Contrastive Language-Image Pre-training model (CLIP) has shown remarkable results across various tasks. Nevertheless, since audio-visual knowledge of the AVEL task and image-text alignment knowledge of the CLIP exist heterogeneous gap, how to transfer the image-text alignment knowledge of CLIP into AVEL field has barely been investigated. To address these challenges, a novel Dual Temporal-aware scene understanding and image-text Knowledge Bridging (DTKB) model is proposed in this paper. DTKB consists of forward and backward temporal-aware scene understanding streams, in which temporal dependencies and cross-modal correlations are explicitly captured from dual temporal-aware perspectives. Consequently, DTKB can achieve fine-grained scene understanding for event localization. Additionally, a knowledge bridging (KB) module is proposed to simultaneously transfer the image-text representation and alignment knowledge of CLIP to AVEL task. This module regulates the ratio between audio-visual fusion features and CLIP’s visual features, thereby bridging the image-text alignment knowledge of CLIP and the audio-visual new knowledge for event category prediction. Besides, the KB module is compatible with previous models. Extensive experimental results demonstrate that DTKB significantly outperforms the state-of-the-arts models.

Abstract The use of anticoagulants has become more frequent due to the progressive aging population and increased thromboembolic events. Consequently, the proportion of anticoagulant-associated intracerebral hemorrhage (AAICH) in stroke patients is gradually increasing. Compared with intracerebral hemorrhage (ICH) patients without coagulopathy, patients with AAICH may have larger hematomas, worse prognoses, and higher mortality. Given the need for anticoagulant reversal and resumption, the management of AAICH differs from that of conventional medical or surgical treatments for ICH, and it is more specific. Understanding the pharmacology of anticoagulants and identifying agents that can reverse their effects in the early stages are crucial for treating life-threatening AAICH. When patients transition beyond the acute phase and their vital signs stabilize, it is important to consider resuming anticoagulants at the right time to prevent the occurrence of further thromboembolism. However, the timing and strategy for reversing and resuming anticoagulants are still in a dilemma. Herein, we summarize the important clinical studies, reviews, and related guidelines published in the past few years that focus on the reversal and resumption of anticoagulants in AAICH patients to help implement decisive diagnosis and treatment strategies in the clinical setting.

C32H44O6, monoclinic, P21 (no. 4), a = 12.2561 Å, b = 10.3674(4) Å, c = 23.3835(8) Å, β = 98.463°, V = 2938.85(19) Å3, Z = 2, Rgt(F) = 0.0602, wRref(F2) = 0.1537, T = 273(2) K.

Quality makers (Q-markers) are pivotal for the standardization of quality control for traditional Chinese medicine (TCM) drugs. However, it’s a great challenge to identify the Q-markers of TCM drugs especially for TCM formulas. This study was designed to provide a method to discover Q-markers of TCM formulas and applied to identify the Q-markers responsible for the anti-cholestatic effect of Danning tablet (DNT), a TCM formulae consisting with seven herbal ingredients. In this study, the anti-cholestatic effect of DNT was evaluated in mice with cholestasis induced by α-naphthyl isothiocyanate (ANIT). An untargeted metabolomic profiling were performed using serum and liver samples of mice. Xenobiotics derived from DNT and endogenous compounds responsible for the anti-cholestatic effect of DNT were screened by statistical analysis and the Q-markers of DNT were illustrated, followed by predicting the potential targets and mechanisms via network pharmacology study. DNT exhibited a protective effect against liver injury in mice with ANIT-induced cholestasis. Three endogenous compounds, namely taurochenodeoxycholic acid (TCDCA), taurocholic acid (TCA), and glycocholic acid (GCA), were identified as the endogenous markers responsible for the anti-cholestatic effect of DNT. By setting a cutoff value of the correlation co-efficient at 0.8, 6 promising Q-markers, including luteolin, kaempferol, apigenin, emodin, luteolin-7-glucoside, and 5,4′-dihydroxy-3,6,7,8,3′-pentamethoxyflavone, were screened out. These Q-markers were stably existed in DNT and predicted to be highly active in treating cholestasis. This study established a pipeline to screen out the potential Q-markers of TCM formulas and 6 key Q-markers responsible for the anti-cholestatic effect of DNT were identified.

Abstract Objective The exact mechanism and target molecules of liver fibrosis have remained largely elusive. Here, we investigated the role of long noncoding RNA Gm9866(lncRNA-Gm9866) on liver fibrosis. Methods The transcription of lncRNA-Gm9866 in activated cells and mouse fibrotic livers was determined by quantitative polymerase chain reaction (qRT-PCR). The effects of lentivirus-mediated knockdown or overexpression of lncRNA-Gm9866 in liver fibrosis were examined in vitro and in vivo. Furthermore, bioinformatics analysis, cell samples validation, fluorescence in situ hybridization (FISH) co-localization, RNA binding protein immunoprecipitation (RIP), actinomycin D test and Western blot (WB) were carried out to explore the potential mechanism of lncRNA-Gm9866. Results The expression of α-smooth muscle actin (α-SMA), Collagen I (COL-1) and lncRNA-Gm9866 were significantly increased in tissues and cells. Overexpressing lncRNA-Gm9866 promoted the activation of hepatic stellate cells (HSCs). Silencing lncRNA-Gm9866 inhibited the activation of HSCs and transforming growth factor-β1 (TGFβ1) induced fibrosis. Overexpressing lncRNA-Gm9866 promoted hepatocytes (HCs) apoptosis and the expression of pro-fibrogenic genes, inhibited the proliferation and migration of HCs. Knockdown of lncRNA-Gm9866 inhibited the apoptosis of HCs, the expression of pro-fibrogenic genes, TGFβ1 induced fibrosis and the occurrence of carbon tetrachloride (CCl4)-induced liver fibrosis, and promoted the proliferation and migration of HCs. Mechanistically, lncRNA-Gm9866 may directly bine with Fam98b. Silencing Fam98b in stably overexpressing lncRNA-Gm9866 cell lines reversed the increase of pro-fibrogenic genes and pro-apoptotic genes, fibrosis related pathway protein TGFβ1, Smad2/3, p-Smad2/3 and Notch3 induced by overexpressing lncRNA-Gm9866. Conclusions LncRNA-Gm9866 may regulate TGFβ/Smad and Notch pathways by targeting Fam98b to regulate liver fibrosis. LncRNA-Gm9866 may be a new target for diagnosis and treatment of liver fibrosis.

This review discusses the application scenarios of the machine learning-supported performance prediction and the optimization efficiency of tunnel boring machines (TBMs). The rock mass quality ratings, which are based on the Chinese code for geological survey, were used to provide “labels” suitable for supervised learning. As a result, the generation of machine prediction for rock mass grades reasonably agreed with the ground truth documented in geological maps. In contrast, the main operational parameters, i.e., thrust and torque, can be reasonably predicted based on historical data. Consequently, 18 collapse sections of the Yinsong project have been successfully predicted by several researchers. Preliminary studies on the selection of the optimal penetration rate and cost were conducted. This review also presents a summary of the main achievements in response to the initiatives of the Lotus Pool Contest in China. For the first time, large and well-documented TBM performance data has been shared for joint scientific research. Moreover, the review discusses the technical problems that require further study and the perspectives in the future development of intelligent TBM construction based on big data and machine learning.

This review summarizes the research outcomes and findings documented in 45 journal papers using a shared tunnel boring machine (TBM) dataset for performance prediction and boring efficiency optimization using machine learning methods. The big dataset was collected during the Yinsong water diversion project construction in China, covering the tunnel excavation of a 20 km-section with 199 items of monitoring metrics taken with an interval of one second. The research papers were the result of a call for contributions during a TBM machine learning contest in 2019 and covered a variety of topics related to the intelligent construction of TBM. This review comprises two parts. Part I is concerned with the data processing, feature extraction, and machine learning methods applied by the contributors. The review finds that the data-driven and knowledge-driven approaches in extracting important features applied by various authors are diversified, requiring further studies to achieve commonly accepted criteria. The techniques for cleaning and amending the raw data adopted by the contributors were summarized, indicating some highlights such as the importance of sufficiently high frequency of data acquisition (higher than 1 second), classification and standardization for the data preprocessing process, and the appropriate selections of features in a boring cycle. The review finds that both supervised and unsupervised machine learning methods have been utilized by various researchers. The ensemble and deep learning methods have found wide applications. Part I highlights the important features of the individual methods applied by the contributors, including the structures of the algorithm, selection of hyperparameters, and model validation approaches.

Abstract In hadron spectrum physics, the partial wave analysis is a primary method used to extract properties of hadronic resonances. The covariant orbital-spin coupling scheme holds unique advantages over other partial wave methods due to its Lorentz covariant form and determined orbital-spin quantum numbers. This paper presents a general form of the covariant orbital-spin coupling scheme based on the irreducible tensor of the homogeneous proper Lorentz group and its little groups. A systematic procedure for constructing partial wave amplitude in a Lorentz covariant way is provided, which can be applied to both massive and massless particles. Specific examples are also included.

With the development of underground rail transit, the concept of intelligent tunnel construction has been proposed and promoted. High-quality networking during tunnel construction is a prerequisite for this, making it highly urgent to establish networking during tunnel construction. When studying intra-tunnel networking, it is necessary to consider the propagation characteristics of radio waves in the tunnel. In this paper, according to the actual needs of engineering in tunnel construction and the characteristics of tunnel scenes, an improved ray tracing method is proposed, which considers the type and installation position of antennas, transceiver frequency band and power in channel modeling, and proposes a field strength calculation method under different coordinate systems according to the characteristics of straight and curved segments during tunnel construction. In addition, the propagation characteristics of radio waves in dynamic tunnel construction scenarios are quantitatively analyzed. In this paper, by establishing antenna diagram, two-dimensional and three-dimensional models of tunnels, the computer simulation method is applied to compare with the improved algorithm, and the results have good consistency, in addition, the improved algorithm does not require a lot of modeling work in the early stage, and has high applicability and portability. Not only that, this paper also makes actual measurements of the subway under construction in Zhengzhou, China in different scenarios, and verifies the effectiveness of the method.

We aimed to determine the molecular characteristics of carbapenem-resistant Pseudomonas aeruginosa strains 18081308 and 18083286, which were isolated from the urine and the sputum of two Chinese patients, respectively. Additionally, we conducted a comparative analysis between Tn6411 carrying blaIMP-1 in strain 18083286 and transposons from the same family available in GenBank. Bacterial genome sequencing was carried out on strains 18081308 and 18083286 to obtain their whole genome sequence. Average nucleotide identity (ANI) was used for their precise species identification. Serotyping and multilocus sequence typing were performed. Furthermore, the acquired drug resistance genes of these strains were identified. The carbapenem-resistant P. aeruginosa strains isolated in the present study were of sequence type ST865 and serotype O6. They all carried the same resistance genes (aacC2, tmrB, and blaIMP-1). Tn6411, a Tn7-like transposon carrying blaIMP-1, was found in strain 18083286 by single molecule real time (SMRT) sequencing. We also identified the presence of this transposon sequence in other chromosomes of P. aeruginosa and plasmids carried by Acinetobacter spp. in GenBank, indicating the necessity for heightening attention to the potential transferability of this transposon.

Byline: Jiaying. Qiu, Jiajia. Gu, Shiyi. Chang, Zhenyu. Zhang, Haibo. Zhang, Tianqing. Liu, Jing. Jie, Jinhuan. Wei Background: Multiple sclerosis (MS) is an autoimmune disease characterized by inflammatory demyelinating lesions [...]

Abstract Aim The aim was to examine the effect of role overload, work addiction and leader‐member exchange on missed nursing care. Design A cross‐sectional study. Methods Chinese registered nurses from five Sichuan province public hospitals were studied from March 2022–May 2022. The measurements were derived from a questionnaire on role overload, work addiction, missed nursing care, leader‐member exchange and a sociodemographic datasheet. Descriptive statistics and inferential statistics were conducted (N = 403). Results Role overload was associated with missed nursing care, and work addiction played a mediation role. Leader‐member exchange negatively predicted work addiction and played a moderating role between role overload and work addiction. The effect of role overload on work addiction was attenuated when the level of leader‐member exchange was higher. Promoting leader‐member exchange could mitigate how role overload undermines missed nursing care.

Abstract Background Central post-stroke pain (CPSP) is an intractable and disabling central neuropathic pain that severely affects patients’ lives, well-being, and socialization abilities. However, CPSP has been poorly studied mechanistically and its treatment remains challenging. Here, we used a rat model of CPSP induced by thalamic hemorrhage to investigate its underlying mechanisms and the effect of stellate ganglion block (SGB) on CPSP and emotional comorbidities. Methods Thalamic hemorrhage was produced by injecting collagenase IV into the ventral-posterolateral nucleus (VPL) of the right thalamus. The up-and-down method with von Frey hairs was used to measure the mechanical allodynia. Behavioral tests were carried out to examine depressive and anxiety-like behaviors including the open field test (OFT), elevated plus maze test (EPMT), novelty-suppressed feeding test (NSFT), and forced swim test (FST). The peri-thalamic lesion tissues were collected for immunofluorescence, western blotting, and enzyme-linked immunosorbent assay (ELISA). Genetic knockdown of thalamic hypoxia-inducible factor-1α (HIF-1α) and NOD-like receptor thermal protein domain associated protein 3 (NLRP3) with microinjection of HIF-1α siRNA and NLRP3 siRNA into the VPL of thalamus were performed 3 days before collagenase injection into the same regions. Microinjection of lificiguat (YC-1) and MCC950 into the VPL of thalamus were administrated 30 min before the collagenase injection in order to inhibited HIF-1α and NLRP3 pharmacologically. Repetitive right SGB was performed daily for 5 days and laser speckle contrast imaging (LSCI) was conducted to examine cerebral blood flow. Results Thalamic hemorrhage caused persistent mechanical allodynia and anxiety- and depression-like behaviors. Accompanying the persistent mechanical allodynia, the expression of HIF-1α and NLRP3, as well as the activities of microglia and astrocytes in the peri-thalamic lesion sites, were significantly increased. Genetic knockdown of thalamic HIF-1α and NLRP3 significantly attenuated mechanical allodynia and anxiety- and depression-like behaviors following thalamic hemorrhage. Further studies revealed that intra-thalamic injection of YC-1, or MCC950 significantly suppressed the activation of microglia and astrocytes, the release of pro-inflammatory cytokines, the upregulation of malondialdehyde (MDA), and the downregulation of superoxide dismutase (SOD), as well as mechanical allodynia and anxiety- and depression-like behaviors following thalamic hemorrhage. In addition, repetitive ipsilateral SGB significantly restored the upregulated HIF-1α/NLRP3 signaling and the hyperactivated microglia and astrocytes following thalamic hemorrhage. The enhanced expression of pro-inflammatory cytokines and the oxidative stress in the peri-thalamic lesion sites were also reversed by SGB. Moreover, LSCI showed that repetitive SGB significantly increased cerebral blood flow following thalamic hemorrhage. Most strikingly, SGB not only prevented, but also reversed the development of mechanical allodynia and anxiety- and depression-like behaviors induced by thalamic hemorrhage. However, pharmacological activation of thalamic HIF-1α and NLRP3 with specific agonists significantly eliminated the therapeutic effects of SGB on mechanical allodynia and anxiety- and depression-like behaviors following thalamic hemorrhage. Conclusion This study demonstrated for the first time that SGB could improve CPSP with comorbid anxiety and depression by increasing cerebral blood flow and inhibiting HIF-1α/NLRP3 inflammatory signaling.

ObjectiveCognitive dysfunction is common in insulinoma patients, but the underlying neural mechanisms are less well understood. This study aimed to explore the alterations of intra- and inter-network connectivity patterns associated with patients with insulinoma.MethodsResting-state fMRI were acquired from 13 insulinoma patients and 13 matched healthy controls (HCs). Group Independent component analysis (ICA) was employed to capture the resting-state networks (RSNs), then the intra- and inter-network connectivity patterns, were calculated and compared. Montreal Cognitive Assessment (MoCA) was used to assess the cognitive function. The relationship between connectivity patterns and MoCA scores was also examined.ResultsInsulinoma patients performed significantly worse on MoCA compared to HCs. The intra-network connectivity analysis revealed that patients with insulinoma showed decreased connectivity in the left medial superior frontal gyrus within anterior default mode network (aDMN), and decreased connectivity in right lingual gyrus within the visual network (VN). The intra-network connectivity analysis showed that patients with insulinoma had an increased connectivity between the inferior-posterior default mode network (ipDMN) and right frontoparietal network (rFPN) and decreased connectivity between the ipDMN and auditory network (AUN). There was a significant negative correlation between the ipDMN-rFPN connectivity and MoCA score.ConclusionThis study demonstrated significant abnormalities in the intra- and inter-network connectivity in patients with insulinoma, which may represent the neural mechanisms underlying the cognitive impairment in insulinoma patients.