Search

Abstract Background Chronic ethanol exposure (CEE) is recognized as an important risk factor for depression, and the gut-brain axis has emerged as a key mechanism underlying chronic ethanol exposure-induced anxiety and depression-like behaviors. Short-chain fatty acids (SCFAs), which are the key metabolites generated by gut microbiota from insoluble dietary fiber, exert protective roles on the central nervous system, including the reduction of neuroinflammation. However, the link between gut microbial disturbances caused by chronic ethanol exposure, production of SCFAs, and anxiety and depression-like behaviors remains unclear. Methods Initially, a 90-day chronic ethanol exposure model was established, followed by fecal microbiota transplantation model, which was supplemented with SCFAs via gavage. Anxiety and depression-like behaviors were determined by open field test, forced swim test, and elevated plus-maze. Serum and intestinal SCFAs levels were quantified using GC-MS. Changes in related indicators, including the intestinal barrier, intestinal inflammation, neuroinflammation, neurotrophy, and nerve damage, were detected using Western blotting, immunofluorescence, and Nissl staining. Results Chronic ethanol exposure disrupted with gut microbial homeostasis, reduced the production of SCFAs, and led to anxiety and depression-like behaviors. Recipient mice transplanted with fecal microbiota that had been affected by chronic ethanol exposure exhibited impaired intestinal structure and function, low levels of SCFAs, intestinal inflammation, activation of neuroinflammation, a compromised blood-brain barrier, neurotrophic defects, alterations in the GABA system, anxiety and depression-like behaviors. Notably, the negative effects observed in these recipient mice were significantly alleviated through the supplementation of SCFAs. Conclusion SCFAs not only mitigate damage to intestinal structure and function but also alleviate various lesions in the central nervous system, such as neuroinflammation, and reduce anxiety and depression-like behaviors, which were triggered by transplantation with fecal microbiota that had been affected by chronic ethanol exposure, adding more support that SCFAs serve as a bridge between the gut and the brain.

Abstract Background Systemic lupus erythematosus (SLE) is linked to host gut dysbiosis. Here we performed faecal gut microbiome sequencing to investigate SLE-pathogenic gut microbes and their potential mechanisms. Methods There were 134 healthy controls (HCs) and 114 SLE cases for 16 S ribosomal RNA (rRNA) sequencing and 97 HCs and 124 SLE cases for shotgun metagenomics. Faecal microbial changes and associations with clinical phenotypes were evaluated, and SLE-associated microbial genera were identified in amplicon analysis. Next, metagenomic sequencing was applied for accurate identification of microbial species and discovery of their metabolic pathways and immunogenic peptides both relevant to SLE. Finally, contribution of specific taxa to disease development was confirmed by oral gavage into lupus-prone MRL/lpr mice. Results SLE patients had gut microbiota richness reduction and composition alteration, particularly lupus nephritis and active patients. Proteobacteria/Bacteroidetes (P/B) ratio was remarkably up-regulated, and Escherichia was identified as the dominantly expanded genus in SLE, followed by metagenomics accurately located Escherichia coli and Escherichia unclassified species. Significant associations primarily appeared among Escherichia coli, metabolic pathways of purine nucleotide salvage or peptidoglycan maturation and SLE disease activity index (SLEDAI), and between multiple epitopes from Escherichia coli and disease activity or renal involvement phenotype. Finally, gavage with faecal Escherichia revealed that it upregulated lupus-associated serum traits and aggravated glomerular lesions in MRL/lpr mice. Conclusion We characterize a novel SLE exacerbating Escherichia outgrowth and suggest its contribution to SLE procession may be partially associated with metabolite changes and cross-reactivity of gut microbiota-associated epitopes and host autoantigens. The findings could provide a deeper insight into gut Escherichia in the procession of SLE.

Abstract Background In the face of family stress and emerging family problems, the transactional model of stress and coping provides new perspectives for solving stress problems in the family. This study integrates it with the common fate model to reveal new paths for coping with educational anxiety problems from the level of parent-child dichotomous interaction in the family environment, aiming to provide some theoretical and practical support for alleviating parents’ education anxiety. Methods This study used a combination of interviews and questionnaires to stratify students and their parents from a public junior high school in Jinan City to participate in the study. Data were collected in two time periods (T1, T2; one year apart), and the demographic characteristics of parents and children, parent-child communication quality, education anxiety, and parent-child trust relationship of 495 families were finally analysed by SPSS 27.0. Results The results found that (1) based on the Common Fate Model, quality of parent-child communication negatively predicted parents’ education anxiety; (2) quality of parent-child communication positively predicted parent-child trust relationship; (3) parent-child trust relationship negatively predicted parents’education anxiety; (4) parent-child trust relationship mediated quality of parent-child communication and education anxiety. Conclusions This study sheds light on research related to stress coping and anxiety relief in the family environment, and provides theoretical and practical support for understanding the interaction between parents and children at the family level, and coping with stressful events together. It implies that future researchers should not only focus on one aspect when coping with and dealing with family problems, but should analyse the family as a whole, including the communication status and parent-child relationship between parents and children.

Left ventricular-arterial coupling (VAC) is essential for understanding both cardiovascular physiology and pathophysiology. Traditionally assessed through invasive techniques, recent advancements have introduced noninvasive methods that employ imaging modalities and physiological parameters to evaluate ventricular pressure, volume, and arterial load characteristics. This review examines commonly used noninvasive VAC assessment methods, including echocardiographic single-beat method, myocardial work, wave intensity, the ratio of pulse wave velocity to global longitudinal strain, and imaging-based pressure-volume loops. These methodologies have demonstrated potential in clinical applications, such as evaluating cardiac function, personalizing treatment plans, monitoring therapeutic effects, and assessing prognosis. The incorporation of advanced imaging and computational techniques is anticipated to further enhance the accuracy and clinical relevance of VAC assessment in the management of cardiovascular diseases.

Abstract Background Accurately identifying drug-target affinity (DTA) plays a pivotal role in drug screening, design, and repurposing in pharmaceutical industry. It not only reduces the time, labor, and economic costs associated with biological experiments but also expedites drug development process. However, achieving the desired level of computational accuracy for DTA identification methods remains a significant challenge. Results We proposed a novel multi-view-based graph deep model known as MvGraphDTA for DTA prediction. MvGraphDTA employed a graph convolutional network (GCN) to extract the structural features from original graphs of drugs and targets, respectively. It went a step further by constructing line graphs with edges as vertices based on original graphs of drugs and targets. GCN was also used to extract the relationship features within their line graphs. To enhance the complementarity between the extracted features from original graphs and line graphs, MvGraphDTA fused the extracted multi-view features of drugs and targets, respectively. Finally, these fused features were concatenated and passed through a fully connected (FC) network to predict DTA. Conclusions During the experiments, we performed data augmentation on all the training sets used. Experimental results showed that MvGraphDTA outperformed the competitive state-of-the-art methods on benchmark datasets for DTA prediction. Additionally, we evaluated the universality and generalization performance of MvGraphDTA on additional datasets. Experimental outcomes revealed that MvGraphDTA exhibited good universality and generalization capability, making it a reliable tool for drug-target interaction prediction.

Abstract Heart failure (HF), with its high morbidity and mortality, remains a global public health issue. Right ventricular (RV) dysfunction is a sign of deterioration in the natural history of HF, and a thorough evaluation of the relationship between RV contractility and its afterload through RV–pulmonary arterial (RV–PA) coupling can aid in accurately assessing overall RV function. The ratio of RV end‐systolic elastance (Ees) to pulmonary arterial elastance (Ea) invasively measured by right heart catheterization served as the gold standard for evaluating RV–PA coupling. An echocardiographic index termed tricuspid annular plane systolic excursion/pulmonary artery systolic pressure (TAPSE/PASP) has been shown to correlate well with Ees/Ea. TAPSE/PASP is recognized as a non‐invasive surrogate of RV–PA coupling and has been extensively studied in patients with HF. This review briefly describes the methods of assessing RV–PA coupling, mainly discussing echocardiography, summarizes the clinical utility of TAPSE/PASP in patients with different HF types, and provides an overview of the available literature.

BackgroundThe prediction of ISLN pCR after neoadjuvant chemotherapy (NAC) based on inflammatory markers and its prognostic value have rarely been investigated.MethodsPatients diagnosed with ISLN-involved breast cancer who received NAC in West China Hospital between September 2009 and December 2020 were enrolled in the derivation cohort for model construction and survival analysis, and patients with the same criteria between January 2021 and July 2024 were involved in validation cohort for external validation. After randomly dividing patients into training and testing groups at 7:3 ratio, a nomogram predicting ISLN pCR was constructed based on logistic regression in training group. Internal validation was performed in the testing group and external validation was performed in the independent validation cohort. The ROC curves were applied to validate the accuracy of the model. Survival analysis was performed using Kaplan−Meier plots.ResultsA total of 120 eligible patients were involved in the derivation cohort to establish the nomogram (84 patients in training group and 36 patients in testing group), and 45 patients were involved in the independent validation cohort for external validation of the nomogram. Pretreatment NLR and hormone receptor (HR) status, as well as preoperative SII, CEA, CA15-3 and anti-HER2 therapy were included in the nomogram predicting ISLN pCR. The AUC were 0.906 (95% CI 0.837-0.975, P

ObjectiveTo develop a guideline for selecting biomarkers in the diagnosis and assessment in patients with axial spondyloarthritis (axSpA).MethodA joint effort was carried out by the core team, the literature review team and the multidisciplinary voting panel to formulate recommendations regarding biomarkers in axSpA, using an evidence-based and consensus-based strategy. Certainty of evidence and strength of recommendation were determined, and levels of agreement within the voting panel were calculated.ResultsA total of 20 recommendations were formulated in this guideline, with levels of agreement ranging from 6.48 to 9.71. The two strong recommendations, HLA-B27 testing in patients suspected of axSpA and regular-interval monitoring of CRP/ESR represent the status quo of axSpA evaluation, while the 13 conditional recommendations represent the promising biomarkers with clinical utility in diagnosis, disease activity assessment, prediction of radiographic progression and therapeutic responses. This guideline does not dictate clinical choices of tests on axSpA, and decisions should be made based on comprehensive consideration of costs, accessibility, patients’ values and willingness as well as the objective of testing in the local context.ConclusionThis guideline addresses the interpretation of the clinical significance of biomarkers in axSpA, and the biomarkers endorsed in this guideline composed a clinical toolkit for healthcare professionals to choose from.

Abstract Head‐direction (HD) cells are a fundamental component in the hippocampal‐entorhinal circuit for spatial navigation and help maintain an internal sense of direction to anchor the orientation in space. A classical HD cell robustly increases its firing rate when the head is oriented toward a specific direction, with each cell tuned to only one direction. Although unidirectional HD cells are reported broadly across multiple brain regions, computation modelling has predicted the existence of multiple equilibrium states of HD network, which has yet to be proven. In this study, a novel HD variant of bipolar HD cells in the medial entorhinal cortex (MEC) are identified that exhibit stable double‐peaked directional tuning properties. The bipolar patterns remain stable in the darkness and across environments of distinct geometric shapes. Moreover, bipolar HD cells co‐rotate coherently with unipolar HD cells to anchor the external visual cue. The discovery reveals a new spatial cell type of bipolar HD cells, whose unique activity patterns may comprise a potential building block for a sophisticated local neural circuit configuration for the internal representation of direction. These findings may contribute to the understanding of how the brain processes spatial information by shedding light on the role of bipolar HD cells in this process.

Abstract Neurologic Rosai–Dorfman disease (RDD) is a rare type of non-Langerhans cell histiocytosis that affects the central nervous system. Most neurologic RDDs grow like meningiomas, have clear boundaries, and can be completely resected. However, a few RDDs are invasive and aggressive, and no effective treatment options are available because the molecular mechanisms involved remain unknown. Here, we report a case of deadly and glucocorticoid-resistant neurologic RDD and explore its possible pathogenic mechanisms via single-cell RNA sequencing. First, we identified two distinct but evolutionarily related histiocyte subpopulations (the C1Q+ and SPP1+ histiocytes) that accumulated in the biopsy sample. The expression of genes in the KRAS signaling pathway was upregulated, indicating gain-of-function of KRAS mutations. The C1Q+ and SPP1+ histiocytes were highly differentiated and arrested in the G1 phase, excluding the idea that RDD is a lympho-histio-proliferative disorder. Second, although C1Q+ histiocytes were the primary RDD cell type, SPP1+ histiocytes highly expressed several severe inflammation-related and invasive factors, such as WNT5A, IL-6, and MMP12, suggesting that SPP1+ histiocytes plays a central role in driving the progression of this disease. Third, oligodendrocytes were found to be the prominent cell type that initiates RDD via MIF and may resist glucocorticoid treatment via the MDK and PTN signaling pathways. In summary, in this case, we report a rare presentation of neurologic RDD and provided new insight into the pathogenic mechanisms of progressive neurologic RDD. This study will also offer evidence for developing precision therapies targeting this complex disease.

Abstract Background Accurately identifying drug-target interaction (DTI), affinity (DTA), and binding sites (DTS) is crucial for drug screening, repositioning, and design, as well as for understanding the functions of target. Although there are a few online platforms based on deep learning for drug-target interaction, affinity, and binding sites identification, there is currently no integrated online platforms for all three aspects. Results Our solution, the novel integrated online platform Drug-Online, has been developed to facilitate drug screening, target identification, and understanding the functions of target in a progressive manner of “interaction-affinity-binding sites”. Drug-Online platform consists of three parts: the first part uses the drug-target interaction identification method MGraphDTA, based on graph neural networks (GNN) and convolutional neural networks (CNN), to identify whether there is a drug-target interaction. If an interaction is identified, the second part employs the drug-target affinity identification method MMDTA, also based on GNN and CNN, to calculate the strength of drug-target interaction, i.e., affinity. Finally, the third part identifies drug-target binding sites, i.e., pockets. The method pt-lm-gnn used in this part is also based on GNN. Conclusions Drug-Online is a reliable online platform that integrates drug-target interaction, affinity, and binding sites identification. It is freely available via the Internet at http://39.106.7.26:8000/Drug-Online/ .

Background and aimsTranscatheter tricuspid valve replacement (TTVR) has recently emerged as a novel therapeutic approach for managing severe tricuspid regurgitation (TR). However, surgical tricuspid valve replacement (STVR) continues to be the predominant treatment modality. There are limited comparative data on both procedures. This study aimed to compare clinical and echocardiographic outcomes between patients who underwent mini-thoracotomy transatrial LuX-Valve TTVR and those who underwent STVR.MethodsThis study prospectively collected patients with severe TR who underwent TTVR (n = 29) or isolated STVR (n = 59) at Wuhan Union Hospital from 2019 to 2022. All TTVR patients received the LuX-Valve via a mini-thoracotomy and transatrial approach. The clinical and echocardiographic outcomes were compared at 30-day and one-year follow-ups.ResultsAt baseline, patients with LuX-Valve TTVR had higher surgical risk scores and a greater proportion of right ventricular dysfunction compared with STVR. In the early postoperative period, the STVR group had a greater decrease in right ventricular function. Hospital length of stay (LOS), intensive care unit LOS, total procedure time, and tracheal intubation time were shorter in the TTVR than in the STVR group. The incidence of postoperative paravalvular leaks was higher among patients who underwent TTVR. Compared to the STVR group, the pacemaker implantation rate was lower in the TTVR group. During follow-up, the peak tricuspid valve velocity and mean gradient in the TTVR group were consistently lower than those in the STVR group. There was similar mortality between TTVR and STVR at 30-day and one-year follow-ups.ConclusionsThe mini-thoracotomy transatria LuX-Valve TTVR has a higher incidence of paravalvular leaks and a lower rate of pacemaker implantation than STVR, with similar 30-day and one-year mortality rates. In some respects, mini-thoracotomy transatrial LuX-Valve TTVR may be a feasible and safe treatment option for specific populations, or it could potentially serve as an alternative therapy to supplement conventional STVR. Further follow-up is required to assess differences in long-term clinical outcomes and valve durability.

Sleep deprivation (SD) is commonplace in today’s fast-paced society. SD is a severe public health problem globally since it may cause cognitive decline and even neurodegenerative disorders like Alzheimer’s disease. Melatonin (MT) is a natural chemical secreted by the pineal gland with neuroprotective effects. The purpose of this study was to investigate the protective effect and mechanism of MT on chronic sleep deprivation-induced cognitive impairment. A 3-week modified multi-platform method was used to create the SD rat model. The Morris water maze test (MWM), Tissue staining (including Hematoxylin and Eosin (H & E) staining, Nissl staining, and immunofluorescence), Western blot, Enzyme-linked immunosorbent assay (ELISA), and Quantitative real-time polymerase chain reaction (qPCR) were used to investigate the protective effect and mechanism of MT in ameliorating cognitive impairment in SD rats. The results showed that MT (50 and 100 mg/kg) significantly improved cognitive function in rats, as evidenced by a shortening of escape latency and increased time of crossing the platform and time spent in the quadrant. Additionally, MT therapy alleviated hippocampus neurodegeneration and neuronal loss while lowering levels of pathogenic factors (LPS) and inflammatory indicators (IL-1β, IL-6, TNF-α, iNOS, and COX2). Furthermore, MT treatment reversed the high expression of Aβ42 and Iba1 as well as the low expression of ZO-1 and occludin, and inhibited the SD-induced TLR4/MyD88/NF-κB signaling pathway. In summary, MT ameliorated spatial recognition and learning memory dysfunction in SD rats by reducing neuroinflammation and increasing neuroprotection while inhibiting the TLR4/MyD88/NF-κB signaling pathway. Our study supports the use of MT as an alternate treatment for SD with cognitive impairment.

Abstract Background Ultrasound-targeted microbubble destruction (UTMD) has emerged as a promising strategy for the targeted delivery of bone marrow mesenchymal stem cells (MSCs) to the ischemic myocardium. However, the limited migration capacity and poor survival of MSCs remains a major therapeutic barrier. The present study was performed to investigate the synergistic effect of UTMD with platelet-derived growth factor BB (PDGF-BB) on the homing of MSCs for acute myocardial infarction (AMI). Methods MSCs from male donor rats were treated with PDGF-BB, and a novel microbubble formulation was prepared using a thin-film hydration method. In vivo, MSCs with or without PDGF-BB pretreatment were transplanted by UTMD after inducing AMI in experimental rats. The therapeutic efficacy of PDGF-BB-primed MSCs on myocardial apoptosis, angiogenesis, cardiac function and scar repair was estimated. The effects and molecular mechanisms of PDGF-BB on MSC migration and survival were explored in vitro. Results The results showed that the biological effects of UTMD increased the local levels of stromal-derived factor-1 (SDF-1), which promoted the migration of transplanted MSCs to the ischemic region. Compared with UTMD alone, UTMD combined with PDGF-BB pretreatment significantly increased the cardiac homing of MSCs, which subsequently reduced myocardial apoptosis, promoted neovascularization and tissue repair, and increased cardiac function 30 days after MI. The vitro results demonstrated that PDGF-BB enhanced MSC migration and protected these cells from H2O2-induced apoptosis. Mechanistically, PDGF-BB pretreatment promoted MSC migration and inhibited H2O2-induced MSC apoptosis via activation of the phosphatidylinositol 3-kinase/serine-threonine kinase (PI3K/Akt) pathway. Furthermore, crosstalk between PDGF-BB and stromal-derived factor-1/chemokine receptor 4 (SDF-1/CXCR4) is involved in the PI3K/AKT signaling pathway. Conclusion The present study demonstrated that UTMD combined with PDGF-BB treatment could enhance the homing ability of MSCs, thus alleviating AMI in rats. Therefore, UTMD combined with PDGF-BB pretreatment may offer exciting therapeutic opportunities for strengthening MSC therapy in ischemic diseases.

Accurate calculation of drug-target affinity (DTA) is crucial for various applications in the pharmaceutical industry, including drug screening, design, and repurposing. However, traditional machine learning methods for calculating DTA often lack accuracy, posing a significant challenge in accurately predicting DTA. Fortunately, deep learning has emerged as a promising approach in computational biology, leading to the development of various deep learning-based methods for DTA prediction. To support researchers in developing novel and highly precision methods, we have provided a comprehensive review of recent advances in predicting DTA using deep learning. We firstly conducted a statistical analysis of commonly used public datasets, providing essential information and introducing the used fields of these datasets. We further explored the common representations of sequences and structures of drugs and targets. These analyses served as the foundation for constructing DTA prediction methods based on deep learning. Next, we focused on explaining how deep learning models, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Transformer, and Graph Neural Networks (GNNs), were effectively employed in specific DTA prediction methods. We highlighted the unique advantages and applications of these models in the context of DTA prediction. Finally, we conducted a performance analysis of multiple state-of-the-art methods for predicting DTA based on deep learning. The comprehensive review aimed to help researchers understand the shortcomings and advantages of existing methods, and further develop high-precision DTA prediction tool to promote the development of drug discovery.

Introduction: Leeches are flesh-eating and bloodsucking parasitic worms. They are being used as a traditional Chinese medicine for centuries in activating blood and dissolving statis, dreging the meridims and tick. Hirudin, an active peptide product present in leech, has blood anticoagulant property and can assist in the treatment of thrombosis and diseases related to blood circulation. The efficacy and potential mechanism of action of leeches in such diseases should be further explored. Materials and methods: First, network pharmacology was used to screen the predicted potential targets of the active constituents of leech and AS. The common targets of the active constituents of leech and AS were obtained using Venn diagram. Further, the drug-active-constituent–target network diagram, protein–protein interaction, and GO and KEGG pathway enrichment analyses were used to construct the active-constituent–AS target–pathway network diagram. Subsequently, the protein–drug molecule docking model was drawn. Finally, the results of network pharmacology were validated using a mouse model of AS. Results: In total, 34 active constituents of leech and 1172 AS-related gene targets were selected, took the drug action targets and potential disease targets to get the common targets, and took the top 10 of degree value as the main active constituents for the treatment of atherosclerosis. There were 89 common targets and 12 core targets. The main targets included MAPK, EGFR, PIK3CB, etc. Potential regulatory pathways included cancer pathways, EGFR tyrosine kinase inhibitor resistance, Rap1 signaling pathway, PPAR signaling pathway, PI3K-Akt signaling pathway, C-type lectin receptor signaling pathway, and AGE-RAGE signaling pathway in diabetic complications. Animal experiments using mouse model of AS confirmed that AS plaques were smaller after treatment with leeches. SRC level was measured using western blotting. Expression of SRC in myocardial tissue was remarkably lower in the mice treated with leech than in the mice from model group fed on high-fat chow. Conclusions: To the best of our knowledge, this is the first study to explore the mechanism of action of the active components of leech in AS prevention. The active components of leeches play a coordinated role in preventing AS through multicomponent, multitarget, and multichannel mechanism of action related to inflammatory response, oxidative stress, and lipid metabolism. This study provided a reference for subsequent cellular and animal experiments.

To accurately predict the detonation and safety performances of high-energy explosives, it is necessary to investigate their reaction mechanisms on different scales, which, however, presents a challenge due to the complex reaction kinetics of the explosives and a lack of experimental methods presently. This work introduces the time-resolved pump-probe experiments capabilities aiming at high-energy explosives based on large-scale laser facilities and presents the recent progress in research on the dynamic process of the explosives, obtaining the following understandings: (1) First, the micron-sized single-crystal 1,3,5-triamino-2,4,6-trinitrobenzene (TATB) can be compressed to an overdriven detonation state at a laser facility, followed by the shock Hugoniot measurements of TATB; (2) Second, high resolution transient X-ray radiography makes it possible to achieve the dynamic imaging of the internal deformation, damage, and reaction dynamics of high-energy explosive under dynamic loading; (3) Third, the phase transformation and chemical reaction products of the shock-compressed explosives can be investigated using dynamic X-ray diffraction or scattering spectra; (4) Finally, the structural changes, molecular reactions, molecular bond cleavage, and intermediate product components of explosives under ultrafast pumping can be explored using ultrafast laser spectroscopy. Large-scale laser facilities can provide various flexible pump-probe methods, including laser shock loading, transient X-ray imaging, dynamic X-ray diffraction, and ultrafast spectroscopy, allowing a series of experiments to be carried out to evaluate different levels of ignitions from low-pressure to overdriven detonations. Furthermore, the facilities also enable in situ, real-time investigations of the internal deformation, phase transition, and ultrafast dynamics of explosives under dynamic loading at high spatial and temporal resolutions. The study of the reaction kinetics and mechanisms of high-energy explosives on microscopic-mesoscopic scales provides an efficient means to unravel the mystery of explosive reactions.

The quality of molten iron not only has a significant impact on the strength, toughness, smelting cost and service life of cast iron but also directly affects the satisfaction of users. The establishment of timely and accurate blast furnace molten iron quality prediction models is of great significance for the improvement of the production efficiency of blast furnace. In this paper, Si, S and P content in molten iron is taken as the important index to measure the quality of molten iron, and the 989 sets of production data from a No.1 blast furnace from August to October 2020 are selected as the experimental data source, predicting the quality of molten iron by the I-GWO-CNN-BiLSTM model. First of all, on the basis of the traditional data processing method, the missing data values are classified into correlation data, temporal data, periodic data and manual input data, and random forest, the Lagrangian interpolation method, the KNN algorithm and the SVD algorithm are used to complete them, so as to obtain a more practical data set. Secondly, CNN and BiLSTM models are integrated and I-GWO optimized hyperparameters are used to form the I-GWO-CNN-BiLSTM model, which is used to predict Si, S and P content in molten iron. Then, it is concluded that using the I-GWO-CNN-BiLSTM model to predict the molten iron quality can obtain high prediction accuracy, which can provide data support for the regulation of blast furnace parameters. Finally, the MCMC algorithm is used to analyze the influence of the input variables on the Si, S and P content in molten iron, which helps the steel staff control the quality of molten iron in a timely manner, which is conducive to the smooth running of blast furnace production.

Blast furnace ironmaking plays an important role in modern industry and the development of the economy. A reasonable ingredient scheme is crucial for energy efficiency and emission reduction in blast furnace production. Determining the right blast furnace ingredients is a complicated process; therefore, this study examines the optimization of the ingredient ratio. In this paper a model of the blast furnace ingredients is established by considering cost of per ton iron, CO2 emissions, and the theoretical coke ratio as the objective functions; ingredient parameters, process parameters, main and by-product parameters as variables; and the blast furnace smelting theory and equilibrium equation as constraints. Then, the model is solved by using an improved grey wolf optimization algorithm and an improved multi-objective grey wolf optimization algorithm. Using the data collected from the steel mill, the conclusion is that multi-objective optimization can consider the indexes of each target, so that the values of all the targets are excellent; we also compared the multi-objective solution results with the original production scheme of the steel mill, and we found that using the blast furnace ingredient scheme optimized in this study can reduce the cost of iron per ton, CO2 emissions per ton, and the theoretical coke ratio in blast furnace production by 350 CNY/t, 1000 kg/t, and 20 kg/t, respectively, compared with the original production plan. Thus, steel mill decision makers can choose the blast furnace ingredients according to different business strategies and the actual needs of steel mills can be better met.

Abstract Microsporidia are a class of obligate intracellular parasitic unicellular eukaryotes that infect a variety of hosts, even including humans. Although different species of microsporidia differ in host range and specificity, they all share a similar infection organelle, the polar tube, which is also defined as the polar filament in mature spores. In response to the appropriate environmental stimulation, the spore germinates with the polar filament everted, forming a hollow polar tube, and then the infectious cargo is transported into host cells via the polar tube. Hence, the polar tube plays a key role in microsporidian infection. Here, we review the origin, structure, composition, function, and application of the microsporidian polar tube, focusing on the origin of the polar filament, the structural differences between the polar filament and polar tube, and the characteristics of polar tube proteins. Comparing the three-dimensional structure of PTP6 homologous proteins provides new insight for the screening of additional novel polar tube proteins with low sequence similarity in microsporidia. In addition, the interaction of the polar tube with the spore wall and the host are summarized to better understand the infection mechanism of microsporidia. Due to the specificity of polar tube proteins, they are also used as the target in the diagnosis and prevention of microsporidiosis. With the present findings, we propose a future study on the polar tube of microsporidia. Graphical Abstract

Abstract Background The ratio of hemoglobin to red blood cell distribution width (HRR) can reflect the degree of oxidative stress and systemic inflammatory response in the body, and is a potential indicator to predict the prognosis of patients with cardiac arrest (CA). Methods We retrospectively analyzed 126 patients successfully resuscitated after out-of-hospital cardiac arrest. Patients were grouped according to their survival status at discharge: 35 survived and 91 died. Binary logistic regression was used to analyze the independent factors affecting the prognosis of patients after cardiopulmonary resuscitation (CPR). A receiver operating characteristic (ROC) curve was used to analyze the predictive value of each independent factor for the prognosis of patients after CPR. Results The HRR in death group was lower than that in the survival group (P

ABSTRACT Microsporidia are obligate intracellular parasites that infect a wide variety of hosts including humans. Microsporidian spores possess a unique, highly specialized invasion apparatus involving the polar filament, polaroplast, and posterior vacuole. During spore germination, the polar filament is discharged out of the spore forming a hollow polar tube that transports the sporoplasm components including the nucleus into the host cell. Due to the complicated topological changes occurring in this process, the details of sporoplasm formation are not clear. Our data suggest that the limiting membrane of the nascent sporoplasm is formed by the polaroplast after microsporidian germination. Using electron microscopy and 1,1′-dioctadecyl-3,3,3′,3′ tetramethyl indocarbocyanine perchlorate staining, we describe that a large number of vesicles, nucleus, and other cytoplasm contents were transported out via the polar tube during spore germination, while the posterior vacuole and plasma membrane finally remained in the empty spore coat. Two Nosema bombycis sporoplasm surface proteins (NbTMP1 and NoboABCG1.1) were also found to localize in the region of the polaroplast and posterior vacuole in mature spores and in the discharged polar tube, which suggested that the polaroplast during transport through the polar tube became the limiting membrane of the sporoplasm. The analysis results of Golgi-tracker green and Golgi marker protein syntaxin 6 were also consistent with the model of the transported polaroplast derived from Golgi transformed into the nascent sporoplasm membrane.IMPORTANCEMicrosporidia, which are obligate intracellular pathogenic organisms, cause huge economic losses in agriculture and even threaten human health. The key to successful infection by the microsporidia is their unique invasion apparatus which includes the polar filament, polaroplast, and posterior vacuole. When the mature spore is activated to geminate, the polar filament uncoils and undergoes a rapid transition into the hollow polar tube that transports the sporoplasm components including the microsporidian nucleus into host cells. Details of the structural difference between the polar filament and polar tube, the process of cargo transport in extruded polar tube, and the formation of the sporoplasm membrane are still poorly understood. Herein, we verify that the polar filament evaginates to form the polar tube, which serves as a conduit for transporting the nucleus and other sporoplasm components. Furthermore, our results indicate that the transported polaroplast transforms into the sporoplasm membrane during spore germination. Our study provides new insights into the cargo transportation process of the polar tube and origin of the sporoplasm membrane, which provide important clarification of the microsporidian infection mechanism.

Aiming at the problems of small sample size and large feature dimension in the identification of ipsilateral supraclavicular lymph node metastasis status in breast cancer using ultrasound radiomics, an optimized feature combination search algorithm is proposed to construct linear classification models with high interpretability. The genetic algorithm (GA) is used to search for feature combinations within the feature subspace using least absolute shrinkage and selection operator (LASSO) regression. The search is optimized by applying a high penalty to the L1 norm of LASSO to retain excellent features in the crossover operation of the GA. The experimental results show that the linear model constructed using this method outperforms those using the conventional LASSO regression and standard GA. Therefore, this method can be used to build linear models with higher classification performance and more robustness.

Abstract Background The cholinergic anti-inflammatory pathway (CAP) has been widely studied to modulate the immune response. Current stimulating strategies are invasive or imprecise. Noninvasive low-intensity pulsed ultrasound (LIPUS) has become increasingly appreciated for targeted neuronal modulation. However, its mechanisms and physiological role on myocarditis remain poorly defined. Methods The mouse model of experimental autoimmune myocarditis was established. Low-intensity pulsed ultrasound was targeted at the spleen to stimulate the spleen nerve. Under different ultrasound parameters, histological tests and molecular biology were performed to observe inflammatory lesions and changes in immune cell subsets in the spleen and heart. In addition, we evaluated the dependence of the spleen nerve and cholinergic anti-inflammatory pathway of low-intensity pulsed ultrasound in treating autoimmune myocarditis in mice through different control groups. Results The echocardiography and flow cytometry of splenic or heart infiltrating immune cells revealed that splenic ultrasound could alleviate the immune response, regulate the proportion and function of CD4+ Treg and macrophages by activating cholinergic anti-inflammatory pathway, and finally reduce heart inflammatory injury and improve cardiac remodeling, which is as effective as an acetylcholine receptor agonists GTS-21. Transcriptome sequencing showed significant differential expressed genes due to ultrasound modulation. Conclusions It is worth noting that the ultrasound therapeutic efficacy depends greatly on acoustic pressure and exposure duration, and the effective targeting organ was the spleen but not the heart. This study provides novel insight into the therapeutic potentials of LIPUS, which are essential for its future application. Graphical Abstract

This study aimed to investigate the incidence of patent processus vaginalis (PPV) in pediatric patients with a unilateral nonpalpable testis and explore the associated factors. From May 2014 to April 2017, 152 boys who were diagnosed with a unilateral nonpalpable testis and underwent laparoscopy in Shanghai Children's Hospital (Shanghai, China) were included in this study. The data were collected and reviewed, and the results were analyzed regarding the age at operation, side, development, and position of the nonpalpable testis. The mean age of the patients was 2.6 (standard deviation: 2.3) years. The testis was absent in 14 cases, nonviable in 81 cases, and viable in 57 cases. The incidence of PPV was 37.5% (57 of 152) on the ipsilateral side and 16.4% (25 of 152) on the contralateral side. The ipsilateral PPV was more prevalent when the nonpalpable testis occurred on the right side (P < 0.01). Besides, patients with a viable testis had a greater incidence of ipsilateral PPV than those with a nonviable or absent testis (P < 0.01). Moreover, this rate was the highest when the testis was in the abdominal cavity and the lowest when the testis was in the scrotum (both P < 0.01). However, the incidence of contralateral PPV was independent of all the factors. In conclusion, in children with a nonpalpable testis, the incidence of an ipsilateral PPV was significantly related to the side, development, and position of the testis, while it was independent of these factors on the contralateral side.

Abstract Background Metabolic reprogramming is a hallmark of cancer, alteration of nucleotide metabolism of hepatocellular carcinoma (HCC) is not well-understood. MYBL2 regulates cell cycle progression and hepatocarcinogenesis, its role in metabolic regulation remains elusive. Patients and methods Copy number, mRNA and protein level of MYBL2 and IMPDH1 were analyzed in HCC, and correlated with patient survival. Chromatin Immunoprecipitation sequencing (Chip-seq) and Chromatin Immunoprecipitation quantitative polymerase chain reaction (ChIP-qPCR) were used to explore the relationship between MYBL2 and IMPDH1. Metabolomics were used to analyze how MYBL2 affected purine metabolism. The regulating effect of MYBL2 in HCC was further validated in vivo using xenograft models. Results The Results showed that copy-number alterations of MYBL2 occur in about 10% of human HCC. Expression of MYBL2, IMPDH1, or combination of both were significantly upregulated and associated with poor prognosis in HCC. Correlation, ChIP-seq and ChIP-qPCR analysis revealed that MYBL2 activates transcription of IMPDH1, while knock-out of MYBL2 retarded IMPDH1 expression and inhibited proliferation of HCC cells. Metabolomic analysis post knocking-out of MYBL2 demonstrated that it was essential in de novo purine synthesis, especially guanine nucleotides. In vivo analysis using xenograft tumors also revealed MYBL2 regulated purine synthesis by regulating IMPDH1, and thus, influencing tumor progression. Conclusion MYBL2 is a key regulator of purine synthesis and promotes HCC progression by transcriptionally activating IMPDH1, it could be a potential candidate for targeted therapy for HCC.

Abstract Background To investigate the effect of different depth of anesthesia on inflammatory factors and hospital outcomes in elderly patients undergoing laparoscopic radical gastrectomy for gastric cancer, in order to select an appropriate depth of anesthesia to improve the prognosis of patients undergoing surgery and improve the quality of life of patients. Methods A total of 80 elderly patients aged 65 and above who underwent laparoscopic radical gastrectomy in our hospital were by convenience sampling and randomly divided into two groups : 55 groups ( group H ) and 45 groups ( group L ), 40 cases in each group. The depth of anesthesia was maintained using a closed-loop target-controlled infusion system: the EEG bispectral index was set to 55 in the H group and 45 in the L group. Venous blood samples were collected 2 h (T2), 24 h (T3) and 72 h (T4) after the start of surgery. The intraoperative dosage of propofol and remifentanil, operation duration, postoperative PACU stay time, intraoperative consciousness occurrence, postoperative hospital stay and postoperative pulmonary inflammatory events were recorded. Results The patient characteristic of the two groups had no statistical difference and were comparable (P > 0.05). The intraoperative dosage of propofol in group H was lower than that in group L (P

Targeted and controlled nitric oxide (NO) release is critical due to an extremely short half life and low bioavailability for treating cardiovascular diseases. To address this challenge, various sustained‐release precursors and NO donors activated by light, enzyme, or pH are developed. However, their efficacy is limited by the deep location and rapid blood flow of the heart. Herein, a platelet membrane‐coated nanoparticle (B‐P@PLT) is designed with a polymeric core loaded with BNN6, an ultrasound‐responsive NO donor, for the targeted treatment of myocardial ischemia reperfusion injury (MIRI). B‐P@PLT can specifically target the ischemic myocardium and release NO during ultrasound (US) irradiation, thereby increasing the local concentration of NO. B‐P@PLT + US shows promising results in promoting angiogenesis, reducing reactive oxygen species production, protecting cardiomyocytes both in vitro and in vivo, and ultimately decreasing cardiac injury and improving heart function in MIRI mice. These findings demonstrate a simple and noninvasive strategy for targeted delivery and controlled release of NO, highlighting its potential therapeutic application in MIRI.

Though with bioaccumulation and toxicity, chlorinated paraffins (CPs) are still high produced and widely utilized in various daily necessities for extender plasticization and flame retardation. CPs can be released during the reprocessing processes of finishing materials and distributed in multi-environmental media. Herein, concentrations and compositions of CPs in four representative media including interior finishing materials, PM10, total suspended particulate (TSP), and dust samples collected from eight interior finishing stages were studied. Unexpectedly, CP concentrations in ceramic tiles was found to be high with a mean value of 7.02 × 103 μg g−1, which could be attributed to the presence of CPs in the protective wax coated on ceramic tiles surfaces. Furthermore, the pollution characteristics of short-chain and medium-chain CPs (SCCPs and MCCPs) in those samples were inconsistent. According to the investigation regarding Kdust−TSP and KPM10-TSP, the occurrence and distribution of CPs in indoor atmospheric particles (PM10 and TSP) and dust were highly affected by reprocessing processes (cutting, hot melting, etc.) compared to that in the finishing materials. Moreover, dermal contact was the primary pathway of CP exposure for the occupational population (interior construction workers) for most interior finishing stages, and the interior finishing process is the prime CP exposure period for the occupational groups. As suggested by our assessment, though hardly posing an immediate health risk, CPs exposure still presents unneglected adverse health effects, which calls for adequate personal protections during interior finishing, especially in developing countries.

The non-conventional structure layered double hydroxides (LDHs) as pollutant adsorbents with significant adsorption efficiency are promising valuable research topics. In this work, the defect ordering MgAl-LDHs nanosheets for the highly efficient removal of Congo red (CR) are designed and fabricated by a facile environmental-friendly hydrothermal method based on solid insoluble substances magnesium oxide (MgO) and aluminum hydroxide (Al(OH)3) as precursors. The decrease of Mg/Al ordering changes the interlayer spacing of LDHs and improves the defect sites with low oxygen coordination on the LDHs laminate, which enhances the removal efficiency of CR from 45.6 to 97.7%. This study reveals that a defect enhancing combined mechanism of surface adsorption and the anion-exchange in MgAl-LDHs can obtain an outstanding adsorption efficiency for removing CR. The reactivity of the Mg/Al disorder with O defect on the LDHs laminate increases with the reduction of frontier orbitals energy gap (ΔEgap), resulting in a high adsorption capacity for CR. The uncover of the defect enhancing adsorption mechanism provides a new strategy to fabricate MgAl-LDHs with high capability for wastewater remediation.

ObjectiveColorectal cancer is one of the most common primary malignancies and the third most common cause of cancer death in both men and women in the United States. Among people diagnosed with initial colorectal cancer, 22% had metastatic colorectal cancer, while the 5-year survival rate was less than 20%. The purpose of this study is to develop a nomogram for predicting distant metastasis in newly diagnosed colorectal cancer patients and to identify high-risk groups.MethodsWe retrospectively reviewed the data of patients who were diagnosed with colorectal cancer at Zhong nan Hospital of Wuhan University and People’s Hospital of Gansu Province between January 2016 and December 2021. Risk predictors for distant metastasis from colorectal patients were determined by the univariate and multivariate logistic regression analyses. Nomograms were developed to predict the probabilities of distant metastatic sites of colorectal cancer patients and evaluated by calibration curves, receiver operating characteristic curves, and decision curve analysis (DCA).ResultsA total of 327 cases were included in this study: 224 colorectal cancer patients from Zhong nan Hospital of Wuhan University were incorporated into the training set, and 103 colorectal cancer patients from Gansu Provincial People’s Hospital were incorporated into the testing set. By univariate logistic regression analysis, platelet (PLT) level (p = 0.009), carcinoembryonic antigen (CEA) level (p = 0.032), histological grade (p < 0.001), colorectal cancer tumor markers (p < 0.001), N stage (p < 0.001), and tumor site (p = 0.005) were associated with distant metastasis in colorectal cancer patients. Multivariate logistic regression analysis showed that N stage (p < 0.001), histological grade (p = 0.026), and colorectal cancer markers (p < 0.001) were independent predictors of distant metastasis in patients initially diagnosed with colorectal cancer. The above six risk factors were used to predict distant metastasis of newly diagnosed colorectal cancer. The C-indexes for the prediction of the nomogram were 0.902 (95% confidence interval (CI), 0.857–0.948).ConclusionThe nomogram showed excellent accuracy in predicting distant metastatic sites, and clinical utility may facilitate clinical decision-making.

Kimberlite in the Mengyin area serves as an excellent medium for studying the characteristics and evolutionary processes of the Paleozoic mantle. In order to determine the age of the primary calcite within the kimberlite, in situ carbonate U–Pb dating was conducted in the Mengyin area. The results indicate that the primary calcite in the kimberlite originated approximately 383 ± 18 Ma (MSWD = 6.6). This age constraint suggests that the eruption of the kimberlite took place during this period, leading to the thermal alteration of limestone xenoliths, ultimately forming marble. Consequently, it can be inferred that lithospheric thinning occurred no later than the Late Devonian period. Fluid inclusions found within the marble provide further insights into its formation. The recorded formation temperature of the marble ranges from 243°C to 370°C, with a salinity range of 2.57%–14.77% (NaCl). The pressure estimates fall within the range of 3.22–20.70 MPa, indicating a depth mainly between 900 and 1,000 m. Based on these findings, it can be inferred that the overall denudation depth in the west Shandong area, since the Late Devonian, is estimated to be approximately 900–1,000 m. Furthermore, the overall crustal rise rate is estimated to be approximately 3 m/Ma.

BackgroundThe relationship between acute myeloid leukemia (AML) or acute lymphoblastic leukemia (ALL) and cardiac function is not well established. This study aimed to evaluate whether AML patients exist early myocardial damages prior to chemotherapy and to investigate its association with cardiovascular biomarkers.MethodsConventional echocardiography and three-dimensional speckle-tracking strain analysis were performed prospectively in 72 acute leukemia (AL) patients before any chemotherapy therapy (of whom 44 were AML patients, 28 ALL patients). The results were compared with those from 58 control group matched for age and gender.ResultsThere were no significant differences in conventional biventricular systolic function parameters between AL patients and controls. The left ventricular global longitudinal strain (LVGLS) and right ventricular free wall longitudinal strain (RVFWLS) were significantly lower in AL patients (−23.0 ± 1.4% vs. −24.1 ± 1.3% and −27.9 ± 7.1% vs. −33.0 ± 4.6%, respectively, P

Abstract Accurately predicting the remaining mileage of electric vehicles (EVs) can effectively alleviate user's mileage anxiety and develop refinement of energy management strategy. However, traditional prediction methods not only consume time and resources, but also accumulate errors and lack interpretability. In this paper, we proposed a model based on dimension expansion and model fusion strategy, which uses the extreme gradient boosting (XGBoost) algorithm to directly predict the remaining mileage of EVs. After pre‐processing the real running data of EVs, we constructed the field of remaining driving range and analyzed the relationship between features and remaining driving range, and then directly predicted the remaining driving mileage. Compared with other machine learning methods, XGBoost model has the highest accuracy. Then dimensional extended data set was obtained based on prior knowledge and symbol conversion, which improved the model performance. Finally, the model fusion strategy was adopted to further improve the generalization ability and stability of the model. The experimental results show that the Bootstrap aggregating (Bagging) fusion model has the highest predictive performance on the test set and outperformed other methods. The maximum RAE is not more than 3.5%, RMSE is less than 3km and MAE is about 2 km.

Abstract Metastatic triple-negative breast cancer (mTNBC) is a heterogeneous disease with a poor prognosis. Individualized survival prediction tool is useful for this population. We constructed the predicted nomograms for breast cancer-specific survival (BCSS) and overall survival (OS) using the data identified from the Surveillance, Epidemiology, and End Results database. The Concordance index (C-index), the area under the time-dependent receiver operating characteristic curve (AUC) and the calibration curves were used for the discrimination and calibration of the nomograms in the training and validation cohorts, respectively. 1962 mTNBC patients with a median follow-up was 13 months (interquartile range, 6–22 months), 1639 (83.54%) cases died of any cause, and 1469 (74.87%) died of breast cancer. Nine and ten independent prognostic factors for BCSS and OS were identified and integrated to construct the nomograms, respectively. The C-indexes of the nomogram for BCSS and OS were 0.694 (95% CI 0.676–0.712) and 0.699 (95% CI 0.679–0.715) in the training cohort, and 0.699 (95% CI 0.686–0.712) and 0.697 (95% CI 0.679–0.715) in the validation cohort, respectively. The AUC values of the nomograms to predict 1-, 2-, and 3-year BCSS and OS indicated good specificity and sensitivity in internal and external validation. The calibration curves showed a favorable consistency between the actual and the predicted survival in the training and validation cohorts. These nomograms based on clinicopathological factors and treatment could reliably predict the survival of mTNBC patient. This may be a useful tool for individualized healthcare decision-making.

Abstract Sensor ontology is a standard conceptual model that describes information of sensor device, which includes the concepts of various sensor modules and the relationships between them. The problem of heterogeneity between sensor ontologies is introduced because different sensor ontology engineers have different ways of describing sensor devices and different structures for the construction of sensor ontologies. Addressing the heterogeneity of sensor ontologies contributes to facilitate the semantic fusion of two sensor ontologies, enabling the sharing and reuse of sensor information. To solve the above problem, an ontology meta-matching method is proposed by this paper to find out the correspondence between entities in distinct sensor ontologies. How to measure the degree of similarity between entities with a set of suitable similarity measures and how to better integrate multiple measures to determine the equivalent entities are the challenges of the ontology meta-matching problem. In this paper, two approximate measurement methods of the quality for ontology matching results are designed, and a multi-objective optimization model for the ontology meta-matching problem is constructed based on these methods. Eventually, a multi-objective particle swarm optimization (MOPSO) algorithm is propounded to dispose of the problem and optimize the quality of ontology meta-matching results, which is named density and distribution-based competitive mechanism multi-objective particle swarm algorithm (D $$^{2}$$ 2 CMOPSO). The sophistication of the D $$^{2}$$ 2 CMOPSO based sensor ontology meta-matching method is verified through experiments. Comparing with other matching systems and advanced systems of Ontology Alignment Evaluation Initiative (OAEI), the proposed method can improve the quality of matching results more effectively.

ObjectivesOccult breast cancer (OBC) is a rare malignant breast tumor. Because of the rare cases and limited clinical experience, a huge therapeutic difference has existed all over the world and standardized treatments have yet been established.MethodsA meta-analysis was conducted using MEDLINE and Embase databases to identify the choice of OBC surgical procedures in all studies: (1) patients undergoing axillary lymph node dissection (ALND) or sentinel lymph node biopsy (SLNB) only; (2) patients undergoing ALND with radiotherapy (RT); (3) patients undergoing ALND with breast surgery (BS); (4) patients undergoing ALND with RT and BS; and (5) patients undergoing observation or RT only. The primary endpoints were mortality rates, the second endpoints were distant metastasis and locoregional recurrence.ResultsAmong the 3,476 patients, 493 (14.2%) undergo ALND or SLNB only; 632 (18.2%) undergo ALND with RT; 1483 (42.7%) undergo ALND with BS; 467 (13.4%) undergo ALND RT and BS, and 401 (11.5%) undergo observation or RT only. After comparing the multiple groups, both groups 1 and 3 have higher mortality rates than group 4 (30.7% vs. 18.6%, p < 0.0001; 25.1% vs. 18.6%, p = 0.007), and group 1 has higher mortality rates than groups 2 and 3 (30.7% vs.14.7%, p < 0.00001; 30.7 vs. 19.4%, p < 0.0001). Group (1 + 3) had a prognosis advantage over group 5 (21.4% vs. 31.0%, p < 0.00001). There was no significant difference both in the distant recurrence rates and locoregional rates between group (1 + 3) and group (2 + 4) (21.0% vs. 9.7%, p = 0.06; 12.3% vs. 6.5%, p = 0.26).ConclusionOn the basis of this meta-analysis, our study indicates that BS including modified radical mastectomy (MRM) and breast-conserving surgery (BCS) combined RT may appear as the optimal surgical approach in patients with OBC. RT cannot prolong both the time of distant metastasis and the local recurrences.

Background: Several studies performed thus far indicate that neuroinflammation may be one of the mechanisms underlying the pathogenesis of neuropathic pain (NP). Autophagy, as an adaptive response, has been regarded as an active process of removing the inflammatory stimulus and restoring homeostatic balance. Resolution of inflammation is a biochemical process mediated by the so-called aspirin-triggered specialized proresolving lipid mediators (AT-SPMs), which are thought to exert protective effects in NP. Recent studies have proposed mechanisms in models of inflammatory disorders and showed a relationship between resolution of inflammation and autophagy. This study aimed to validate the functional effects of Aspirin-triggered Resolvin D1 (AT-RvD1) on in vitro and in vivo models of inflammation and to determine their roles in the regulation of autophagy and activation of the Nod-like receptor protein 3 (NLRP3) inflammasome signaling pathway.Methods: An NP model was established using L5-6 spinal nerve ligation (SNL) and a model of tumor necrosis factor alpha (TNF-α)-stimulated primary microglia was established to evaluate the effect of SPMs. Western blotting was used to detect the level of NLRP3 inflammasomes complexes proteins (NLRP3, ASC, and Caspase-1) and autophagy-related proteins (LC3B, and Beclin1). Immunofluorescence staining was used to understand the autophagy and NLRP3 inflammasome activation process. The behavioral changes in rats were analyzed using paw withdrawal thresholds (PWT) and paw withdrawal latency (PWL) test.Results: Our results showed that AT-SPMs significantly upregulated the activation of autophagy, which was characterized by an increase in the ratio of LC3B-II/I and accumulation of ATG5 and Beclin1. AT-RvD1 showed a dose-dependent decrease in the upregulated PWT and PWL induced by SNL and suppressed the expression of the NLRP3 inflammasome protein and the production of its corresponding downstream proinflammatory factors. Additionally, AT-RvD1 induced the activation of autophagy of the microglia and decreased the expression of the NLRP3 inflammasome protein and the accumulation of proinflammatory factors in TNF-ɑ-challenged microglia.Conclusion: Thus, these results showed that AT-RvD1 may be a potential alternative therapeutic strategy for the prevention or treatment of NP by inhibition of the NLRP3 inflammasome signaling pathway by targeting the induction of autophagy.

With styrene and acrylonitrile in ABS plastic toys as examples, this paper introduces to the development of a systematic strategy for studying the chemical migration risk in toys. The approach, included the detection method, establishment of migration model, model verification, and the practical application of the model in risk assessment. First, simple and sensitive methods for detecting analyte residues and migration were developed by headspace GC-MS. Then, the migration models were established based on the migration data from 5 min to 168 h and verified using 11 ABS samples. The results showed that the predicted values of the models and the experimental values had a good fit (RMSE=0.10–8.72 %). Subsequently, the migration of analytes in 94 ABS toys was predicted with these models at specific migration times. The daily average exposure level to styrene and acrylonitrile were estimated for children (3 months to 3 years). At last, the migration models reasonably predicted that the cancer risk of styrene and acrylonitrile in ABS toys were 1.6 × 10−8–1.4 × 10−6 and 3.1 × 10−8–1.6 × 10−6, respectively. This research contributes to promote toy safety and child health by enriching migration models and risk assessments.

In order to study the influence law of northern acid rain on mechanical properties of concrete-filled steel tubular members , it is necessary to study the change law of mechanical properties of steel tube with different corrosion degree under acid rain corrosion condition. Hence, referring to the chemical composition of acid rain statistics over the years in Dalian City, the method of indoor accelerated corrosion with artificially prepared simulation acid rain solution was used to carry out monotonic tensile test on Q235 steel. Results showed that rust pits were easy to form on the steel surface after acid rain corrosion. The fracture of tensile coupons with low corrosion rate (β ≤ 10%) was mainly normal fracture failure, while the fracture of tensile coupons with high corrosion rate (25% ≥ β ≥ 15%) was mainly oblique fracture failure. Meanwhile, the yield strength, elastic modulus, ultimate strength, and elongation percentage of steel afterempirical acid rain corrosion decreased with the increase of corrosion rate, while Poisson’s ratio increased with the increase of corrosion rate. Based on the test data, the simplified empirical calculation formula of the mechanical properties index of Q235 steel under the condition of simulated acid rain corrosion condition was regressed, which could provide theoretical basis and scientific basis for the design and structural safety assessment of concrete-filled steel tubular composite structure in acid rain area.

Drought stress under a changing climate can significantly affect agricultural production. Simulation of soil water dynamics in field conditions becomes necessary to understand changes of soil water conditions to develop irrigation guidelines. In this study, three models including Auto-Regressive Integrated Moving Average (ARIMA), Back-Propagation Artificial Neural Network (BP-ANN), and Least Squares Support Vector Machine (LS-SVM) were used to simulate the soil water content in the 0–14 cm and 14–33 cm soil layers across the Taihu Lake region of China. Rainfall, evaporation, temperature, humidity and wind speed that affect soil water content changes were considered in the BP-ANN and LS-SVM, but not in ARIMA. The results showed that the variability of soil water content in the 0–14 cm soil layer was greater than that in 14–33 cm. Correlation coefficients (r) of soil water content between simulations and observations were highest (0.9827) using LS-SVM in the 14–33 cm soil layer, while they were the lowest (0.7019) using ARIMA in the 0–14 cm soil layer; but no significant difference in r values was observed between the two soil layers with the BP-ANN model. Compared with the other two models, the LS-SVM model seems to be more accurate for forecasting the dynamics of soil moisture. The results suggested that agro-climatic data can be used to predict the severity of soil drought stress and provide guidance for irrigation to increase crop production in the Taihu Lake region of China. HIGHLIGHTS To understand the dynamics of soil water in the Taihu Lake region of China.; The simulation accuracy of LS-SVM was the highest.; To predict the trend of soil water content in the study area.;

Since natural fractures are often non-equidimensional, the circular disc model still has great limitations. By contrast, the elliptical disc model is more applicable to representing natural fractures, especially for slender ones. This paper developed a universal elliptical disc (UED) model by incorporating the center point, size, and azimuth of fractures as variables. Specifically, with respect to the azimuth of elliptical fractures in three-dimensional (3D) space, we proposed a paradigm to construct its probability density function (PDF) by coupling the orientation and rotation angle of long axis based on three coordinate transformations. To illustrate the construction process of the PDF of the fracture azimuth, we took the orientation following the Fisher distribution and the rotation angle following Von Mises distribution as an example. A rock slope is used to show the use of the developed UED model, and the 3D DFNs for the slope rock mass are generated by Monte Carlo simulation. In addition, the DFNs for the rock mass are also generated based on the existing circular disc model and non-universal elliptical disc model. The comparison results from the three models clearly illustrate the superiority of the UED model over the existing circular and non-universal elliptical disc models.

Abstract Background Growing evidence suggests an association between Parkinson’s disease (PD) and diabetes mellitus (DM). At the cellular level, long-term elevated levels of glucose have been shown to lead to nigrostriatal degeneration in PD models. However, the underlying mechanism is still unclear. Previously, we have elucidated the potential of type 2 diabetes mellitus (T2DM) in facilitating PD progression, involving aggregation of both alpha-synuclein (α-syn) and islet amyloid polypeptide in the pancreatic and brain tissues. However, due to the complicated effect of insulin resistance on PD onset, the actual mechanism of hyperglycemia-induced dopaminergic degeneration remains unknown. Methods We employed the type 1 diabetes mellitus (T1DM) model induced by streptozotocin (STZ) injection in a transgenic mouse line (BAC-α-syn-GFP) overexpressing human α-syn, to investigate the direct effect of elevated blood glucose on nigrostriatal degeneration. Results STZ treatment induced more severe pathological alterations in the pancreatic islets and T1DM symptoms in α-syn-overexpressing mice than in wild-type mice, at one month and three months after STZ injections. Behavioral tests evaluating motor performance confirmed the nigrostriatal degeneration. Furthermore, there was a marked decrease in dopaminergic profiles and an increase of α-syn accumulation and Serine 129 (S129) phosphorylation in STZ-treated α-syn mice compared with the vehicle-treated mice. In addition, more severe neuroinflammation was observed in the brains of the STZ-treated α-syn mice. Conclusion Our results solidify the potential link between DM and PD, providing insights into how hyperglycemia induces nigrostriatal degeneration and contributes to pathogenic mechanisms in PD.

In this paper, an observer-based adaptive control method is investigated for the horizontal trajectory tracking of autonomous underwater vehicles (AUV) with input saturation and system disturbances. Firstly, the desired surge speed and trajectory angle are established, which could decouple the tracking error subsystem and avoid the complex form. Secondly, the input saturation is approximated by a smooth function, and a nonlinear extended states observer (NESO) is designed for estimating system disturbances. Based on the command filtered backstepping technique, which can avoid the explosion caused by the derivative of the virtual control, an observer-based adaptive output feedback control method is developed, and an auxiliary system is applied to compensate for filtered tracking errors, input saturation bias, and observer errors. Finally, simulation results show the proposed method has good robustness in the face of system uncertainties, and the error is nearly 33.3% smaller than that of other control methods when meeting sudden trajectory changes. A good control performance is guaranteed.