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Abstract Patients with multiple myeloma (MM) experience relapse and drug resistance; therefore, novel treatments are essential. Clotrimazole (CTZ) is a wide-spectrum antifungal drug with antitumor activity. However, CTZ’s effects on MM are unclear. We investigated CTZ’s effect on MM cell proliferation and apoptosis induction mechanisms. CTZ’s effects on MM.1S, NCI- H929, KMS-11, and U266 cell growth were investigated using Cell Counting Kit-8 (CCK-8) assay. The apoptotic cell percentage was quantified with annexin V-fluorescein isothiocyanate/7-amino actinomycin D staining. Mitochondrial membrane potential (MMP) and cell cycle progression were evaluated. Reactive oxygen species (ROS) levels were measured via fluorescence microscopy. Expression of apoptosis-related and nuclear factor (NF)-κB signaling proteins was analyzed using western blotting. The CCK-8 assay indicated that CTZ inhibited cell proliferation based on both dose and exposure time. Flow cytometry revealed that CTZ decreased apoptosis and MMP and induced G0/G1 arrest. Immunofluorescence demonstrated that CTZ dose-dependently elevated in both total and mitochondrial ROS production. Western blotting showed that CTZ enhanced Bax and cleaved poly ADP-ribose polymerase and caspase-3 while decreasing Bcl-2, p-p65, and p-IκBα. Therefore, CTZ inhibits MM cell proliferation by promoting ROS-mediated mitochondrial apoptosis, inducing G0/G1 arrest, inhibiting the NF-κB pathway, and has the potential for treating MM.

Abstract The application of ChatGPTin the medical field has sparked debate regarding its accuracy. To address this issue, we present a Multi-Role ChatGPT Framework (MRCF), designed to improve ChatGPT's performance in medical data analysis by optimizing prompt words, integrating real-world data, and implementing quality control protocols. Compared to the singular ChatGPT model, MRCF significantly outperforms traditional manual analysis in interpreting medical data, exhibiting fewer random errors, higher accuracy, and better identification of incorrect information. Notably, MRCF is over 600 times more time-efficient than conventional manual annotation methods and costs only one-tenth as much. Leveraging MRCF, we have established two user-friendly databases for efficient and straightforward drug repositioning analysis. This research not only enhances the accuracy and efficiency of ChatGPT in medical data science applications but also offers valuable insights for data analysis models across various professional domains.

Abstract Podocytes are specialized terminally differentiated cells in the glomerulus that are the primary target cells in many glomerular diseases. However, the current podocyte cell lines suffer from prolonged in vitro differentiation and limited survival time, which impede research progress. Therefore, it is necessary to establish a cell line that exhibits superior performance and characteristics. We propose a simple protocol to obtain an immortalized mouse podocyte cell (MPC) line from suckling mouse kidneys. Primary podocytes were cultured in vitro and infected with the SV40 tsA58 gene to obtain immortalized MPCs. The podocytes were characterized using Western blotting and quantitative real-time PCR. Podocyte injury was examined using the Cell Counting Kit-8 assay and flow cytometry. First, we successfully isolated an MPC line and identified 39 °C as the optimal differentiation temperature. Compared to undifferentiated MPCs, the expression of WT1 and synaptopodin was upregulated in differentiated MPCs. Second, the MPCs ceased proliferating at a nonpermissive temperature after day 4, and podocyte-specific proteins were expressed normally after at least 15 passages. Finally, podocyte injury models were induced to simulate podocyte injury in vitro. In summary, we provide a simple and popularized protocol to establish a conditionally immortalized MPC, which is a powerful tool for the study of podocytes.

ObjectiveTo investigate whether using Zishen Yutai Pills (ZYP) following embryo transfer would affect the live birth rate in frozen-thawed embryo transfer (FET) cycles.MethodsA retrospective analysis was performed on 15044 FET cycles in the Reproductive Medicine Center of The Affiliated Chenggong Hospital of Xiamen University from January 2013 to December 2020. Patients who used Zishen Yutai Pills were defined as Zishen Yutai Pills Group (ZYP, n=2735), while patients who did not use them were defined as Non- Zishen Yutai Pills Group (Non-ZYP, n=12309). The propensity score matching method was used to control for potential confounders between the two groups, and logistic regression analysis was also used to assess whether using ZYP would affect the live birth rate.ResultsAfter propensity score matching, basic characteristics were similar between the two groups. Using ZYP did not increase the pregnancy rate (51.5% vs. 52.7%, P=0.372), and live birth rate (43.0% vs. 44.7%, P=0.354). This was also confirmed by the logistic regression analysis results (OR=0.95, 95%CI=0.85-1.06). In the subgroup analysis of the endometrial preparation protocols, however, it was found that the use of ZYP in patients with natural cycles increased the live birth rate (47.4% vs. 41.5%, P=0.004). A significant interaction between endometrial preparation and ZYP was found (OR=1.38, 95%CI=1.07-1.79) in the multivariate model.ConclusionThe use of ZYP may not improve the live birth rate of unselected patients in FET cycles. However, a future study is needed on the effect of ZYP in natural cycles for endometrial preparation.

According to historical statistical data, management and organizational factors (MOFs) contribute more to process accidents than technique factors. Under the umbrella of socio-tech system theory, human reliability analysis (HRA) has become a critical part of systemic probability risk analysis. In many HRA techniques, MOFs are among the performance shaping factors (PSFs). However, the interactions and causality of MOFs to human errors are still difficult to quantify and lack validation. To fill these gaps, a framework is proposed, considering data source selection, CBN construction algorithm comparison, and results validation. The case study employed the open access eMARS database as a data source. The optimized hybrid structure learning algorithm and Bayesian criteria parameter learning algorithm are employed to build a Causal Bayesian Network (CBN) of (MOFs) that lead to human error. The proposed kernel CBN is validated through prediction accuracy and sensitivity analysis. For theoretical contribution, the validated kernel BN could generally serve as the heart part of more specific CBNs as a basis for future works. For practical applications, an application shows the model's ability to quantify the contribution of MOFs to system reliability. The results show that human-machine interacting system reliability is most sensitive to organizational factors such as adequate training and procedures.

Heart failure (HF) is an increasingly prevalent disease in humans; it induces multiple symptoms and damages health. The animal gut microbiota has critical roles in host health, which might be related to HF symptoms. Currently, several options are used to treat HF, including non-invasive ventilation (NIV). However, studies on gut microbiota responses to acute HF and associated treatments effects on gut communities in patients are scarce. Here, short-term (1 week after treatments) and long-term (3 months after treatment) variations in gut microbiota variations in rats with acute HF treated were examined NIV through high-throughput sequencing of the bacterial 16S rRNA gene. Through comparison of gut microbiota alpha diversity, it was observed lower gut microbiota richness and diversity in animals with acute HF than in normal animals. Additionally, beta-diversity analysis revealed significant alterations in the gut microbiota composition induced by acute HF, as reflected by increased Firmicutes/Bacteroidetes (F/B) ratios and Proteobacteria enrichment. When network analysis results were combined with the null model, decreased stability and elevated deterministic gut microbiota assemblies were observed in animals with acute HF. Importantly, in both short- and long-term periods, NIV was found to restore gut microbiota dysbiosis to normal states in acute HF rats. Finally, it was shown that considerable gut microbiota variations existed in rats with acute HF, that underlying microbiota mechanisms regulated these changes, and confirmed that NIV is suitable for HF treatment. In future studies, these findings should be validated with different model systems or clinical samples.

Polarimetric synthetic aperture radar (PolSAR) has attracted more attentions because of its excellent observation ability, and PolSAR image classification has become one of the significant tasks in remote sensing interpretation. Various types and sizes of land cover objects lead to misclassification, especially in the boundaries of different categories. To solve these issues, a multiscale superpixel-guided weighted graph convolutional network (MSGWGCN) is proposed for classifying PolSAR images. In the proposed MSGWGCN, multiscale superpixel features are imported into the weighted graph convolutional network to obtain higher level representation, which can make full use of land cover object information in PolSAR images. Moreover, to fuse pixel-level features at different scales, a multiscale feature cascade fusion module is built, which plays an important role in preserving classification details. Experiments on three PolSAR datasets indicate that the proposed MSGWGCN performs better than other advanced methods on PolSAR classification task.

Remote sensing image object detection with deep neural networks has been highly successful, but it heavily relies on a large number of labeled samples for optimal performance. Unfortunately, when faced with limited labeled samples, the performance of object detection deteriorates. In order to overcome these limitations, we propose a few-shot object detection (FSOD) method based on the reweighting of contrastive class-attention features for remote sensing images. A Siamese representation embedding model based on contrastive learning with a distinguishing operator is proposed to deal with interclass feature ambiguity between base classes and novel classes under complex backgrounds. At the same time, the attention class weights method on region of interest (ROI) features is utilized to boost the discrimination of the novel class features. We conducted comprehensive experiments on two widely used remote sensing object detection datasets, RSOD and DIOR. The proposed FSOD model demonstrated superior performance compared to MM-RCNN, achieving an improvement of approximately 4.7% in terms of mAP on the DIOR dataset. In addition, in comparison to the self-adaptive attention network (SAAN), the FSOD model exhibited an improvement of approximately 3.4% in mAP on the RSOD dataset.

Abstract Fabry disease (FD) is a rare X chromosome‐linked disorder and can be easily misdiagnosed. Here, we report the case of a 69‐year‐old male patient with FD who developed heart failure and showed extremely high pulmonary artery pressure. His initial symptom was recurrent atrial fibrillation. The left and right atrial inner diameters were large, and the ventricular wall was thick. Gene analysis which showed GLA c.215T>C p.Met72Thr mutation and single photon emission computed tomography indicated the diagnosis of FD with coronary microvascular dysfunction. The patient was prescribed anti‐heart failure drugs, including vericiguat. Following the treatment, his heart function and microvascular perfusion significantly improved, which might be due to the beneficial effects of vericiguat.

BackgroundLow-dose aspirin is one of the widely used adjuvants in assisted reproductive technologies with the hope of improving the live birth rate. However, the studies regarding its effects are conflicting. The study aimed to investigate the association between aspirin administration and live birth following frozen-thawed embryo transfer (FET) in patients with different body mass index (BMI).MethodsA retrospective cohort study was performed on 11,993 patients receiving FET treatments. 644 of which received a low-dose aspirin (100 mg/day) during endometrial preparation until 10 weeks after transfer. Propensity score matching was performed to avoid selection biases and potential confounders.ResultsThe clinical pregnancy rate and live birth rate were similar before matching (54.4% versus 55.4%, RR: 1.02, 95%CI: 0.95-1.09, and 46.3 versus 47.8, RR: 1.03, 95%CI: 0.95-1.12 respectively). A weak association in favor of aspirin administration was found in the matched cohort (49.5% versus 55.4%, RR: 1.12, 95%CI: 1.01-1.24, and 41.9% versus 47.8%, RR: 1.14, 95%CI: 1.01-1.29 respectively). However, when stratified the patients with WHO BMI criteria, a significant increase in live birth rate associated with aspirin treatment was found only in patients with low BMI (

The health monitoring of CRF (circulation water) pumps is essential for prognostics and management in nuclear power plants. However, the operational status of CRF pumps can vary due to environmental factors and human intervention, and the interrelationships between monitoring parameters are often complex. Consequently, the existing methods face challenges in effectively assessing the health status of CRF pumps. In this study, we propose a health monitoring model for CRF pumps utilizing a meta graph transformer (MGT) observer. Initially, the meta graph transformer, a temporal–spatial graph learning model, is employed to predict trends across the various monitoring parameters of the CRF pump. Subsequently, a fault observer is constructed to generate early warnings of potential faults. The proposed model was validated using real data from CRF pumps in a nuclear power plant. The results demonstrate that the average Mean Absolute Percentage Error (MAPE), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE) of normal predictions were reduced to 1.2385, 0.5614, and 2.6554, respectively. These findings indicate that our model achieves higher prediction accuracy compared to the existing methods and can provide fault warnings at least one week in advance.

Abstract Fault rupture is a common phenomenon in geotechnical engineering. To prevent rupture, laneway shoring is performed, prior to which, convergence deformation, failure criteria, and fracture development in soft rocks in the fault rupture zone are carefully analyzed. Then, a supporting structure corresponding to the actual situation of the soft rock in the rupture zone is created. Herein, the water-rich laneway shoring through the fault rupture zone of the Hongqingliang coal mine located in the Inner Mongolia Autonomous Region is taken as the research object. Then, the fracture development and characteristics of argillaceous siltstones and laneway shoring cross-fault rupture zone are studied. Site inspection, indoor and field tests, theoretical analysis, numerical simulation, and field monitoring were used for systematic fracture analysis. Results indicated that laneway shoring through the fault fracture zone in the Hongqingliang coal mine could help prevent disasters. This method was extended to laneway supports built through the fault rupture zones in mines in other areas of China.

Headspace solid-phase microextraction, combined with gas chromatography–mass spectrometry and partial least squares discriminant analysis, was adopted to study the rule of change in volatile organic compounds (VOCs) for domestic and imported fishmeal during storage with different freshness grades. The results showed that 318 kinds of VOCs were detected in domestic fishmeal, while 194 VOCs were detected in imported fishmeal. The total relative content of VOCs increased with storage time, among which acids and nitrogen-containing compounds increased significantly, esters and ketones increased slightly, and phenolic and ether compounds were detected only in domestic fishmeal. Regarding the volatile base nitrogen, acid value, pH value, and mold counts as freshness indexes, the freshness indexes were significantly correlated with nine kinds of VOCs (p < 0.05) through the correlation analysis. Among them, volatile base nitrogen had a significant correlation with VOCs containing nitrogen, acid value with VOCs containing carboxyl group and hydrocarbons, pH value with acids which could be used to adjust pH value, and mold counts with part of acids adjusting pH value and VOCs containing nitrogen. Due to the fact that the value of all freshness indexes increased with freshness degradation during storage, based on volatile base nitrogen and acid value, the fishmeal was divided into three freshness grades, superior freshness, corrupting, and completely corrupted. By using partial least squares discriminant analysis, this study revealed the differences in flavor of the domestic and imported fishmeal during storage with different freshness grades, and it identified four common characteristic VOCs, namely ethoxyquinoline, 6,7,8,9-tetrahydro-3H-benzo[e]indole-1,2-dione, hexadecanoic acid, and heptadecane, produced by the fishmeal samples during storage, as well as the characteristic VOCs of fishmeal at each freshness grade.

Abstract Background In recent decades, the prevalence of metabolic diseases, particularly diabetes, hyperlipidemia, obesity, and non-alcoholic fatty liver disease (NAFLD), has increased dramatically, causing great public health and economic burdens worldwide. Traditional Chinese medicine (TCM) serves as an effective therapeutic choice. Xiao-Ke-Yin (XKY) is a medicine and food homology TCM formula consisting of nine “medicine and food homology” herbs and is used to ameliorate metabolic diseases, such as insulin resistance, diabetes, hyperlipidemia and NAFLD. However, despite its therapeutic potential in metabolic disorders, the underlying mechanisms of this TCM remain unclear. This study aimed to evaluate the therapeutic effectiveness of XKY on glucolipid metabolism dysfunction and explore the potential mechanisms in db/db mice. Methods To verify the effects of XKY, db/db mice were treated with different concentrations of XKY (5.2, 2.6 and 1.3 g/kg/d) and metformin (0.2 g/kg/d, a hypoglycemic positive control) for 6 weeks, respectively. During this study, we detected the body weight (BW) and fasting blood glucose (FBG), oral glucose tolerance test (OGTT), insulin tolerance test (ITT), daily food intake and water intake. At the end of the animal experiment, blood samples, feces, liver and intestinal tissue of mice in all groups were collected. The potential mechanisms were investigated by using hepatic RNA sequencing, 16 S rRNA sequencing of the gut microbiota and metabolomics analysis. Results XKY efficiently mitigated hyperglycemia, IR, hyperlipidemia, inflammation and hepatic pathological injury in a dose dependent manner. Mechanistically, hepatic transcriptomic analysis showed that XKY treatment significantly reversed the upregulated cholesterol biosynthesis which was further confirmed by RT-qPCR. Additionally, XKY administration maintained intestinal epithelial homeostasis, modulated gut microbiota dysbiosis, and regulated its metabolites. In particular, XKY decreased secondary bile acid producing bacteria (Clostridia and Lachnospircaeae) and lowered fecal secondary bile acid (lithocholic acid (LCA) and deoxycholic acid (DCA)) levels to promote hepatic bile acid synthesis by inhibiting the LCA/DCA-FXR-FGF15 signalling pathway. Furthermore, XKY regulated amino acid metabolism including arginine biosynthesis, alanine, aspartate and glutamate metabolism, phenylalanine, tyrosine and tryptophan biosynthesis, and tryptophan metabolism likely by increasing Bacilli, Lactobacillaceae and Lactobacillus, and decreasing Clostridia, Lachnospircaeae, Tannerellaceae and Parabacteroides abundances. Conclusion Taken together, our findings demonstrate that XKY is a promising “medicine food homology” formula for ameliorating glucolipid metabolism and reveal that the therapeutic effects of XKY may due to its downregulation of hepatic cholesterol biosynthesis and modulation of the dysbiosis of the gut microbiota and metabolites.

Three kinds of 6061 aluminum alloy cast-rolled plates with Mg/Si mass ratios of 1.23, 1.45, and 1.7 are prepared using NF6–300 vertical twin-roll casting and rolling mill. Metallurgical microscope (OM), x-ray diffraction (XRD), scanning electron microscope (SEM), energy dispersive spectrometer (EDS), room temperature tensile test, and other analysis methods studied the influence law and mechanism of Mg/Si ratio on the microstructure and texture of 6061 cast-rolled sheet. The best Mg/Si ratio cast-rolled sheet is then analyzed for formability. Research indicates that with increasing Mg/Si ratio, the grain size shows first decreasing and then increasing trend. Morphology of precipitated phases at the edge and the central of the sheet are different, however, the texture type has no obvious change, and a strong {112} 〈110〉 texture and weaker rotating cube {001} 〈110〉 texture is always observed. When the Mg/Si ratio is 1.45, the average grain size is the smallest, the edge size is 39.78 μ m, the central size is 31.31 μ m, and the precipitated phase is evenly distributed at the edge and central of the cast-rolled sheet. In addition, the elongation reaches 8.9%, the n-value is 0.072, and the r-value is 1.161 when the cast-rolled sheet reaches 90° along the cast-rolled direction under T6 state heat treatment.

Summary: Disruption of antigen presentation via loss of major histocompatibility complex (MHC) expression is a strategy whereby cancer cells escape immune surveillance and develop resistance to immunotherapy. Here, we develop the personalized genomics algorithm Hapster and accurately call somatic mutations within the MHC genes of 10,001 primary and 2,199 metastatic tumors, creating a catalog of 1,663 non-synonymous mutations that provide key insights into MHC mutagenesis. We find that MHC class I genes are among the most frequently mutated genes in both primary and metastatic tumors, while MHC class II mutations are more restricted. Recurrent deleterious mutations are found within haplotype- and cancer-type-specific hotspots associated with distinct mutational processes. Functional classification of MHC residues reveals significant positive selection for mutations disruptive to the B2M, peptide, and T cell binding interfaces, as well as to MHC chaperones.

Introduction: Polysaccharides, key components present in Grifola frondosa, can be divided into those derived from fruiting bodies, mycelium, and fermentation broth based on their source. The structure of G. frondosa fruiting body-derived polysaccharides has been fully characterized. However, the structure of G. frondosa mycelium-derived polysaccharides remains to be elucidated.Methods: In this study, we obtained mycelia from G. frondosa by liquid fermentation and extracted them with water and alkaline solution. Then, the mycelia were isolated and purified to obtain homogeneity and systematically characterized by methylation and FT infrared (FT-IR) and nuclear magnetic resonance (NMR) spectroscopy.Results and discussion: Structural analysis showed that two neutral fractions (WGFP-N-a and AGFP-N-a1) have a common backbone composed of α-1,6-D-Me-Galp and α-1,6-D-Galp that were substituted at O-2 by 1,2-Manp, α-1,3-L-Fucp, and α-T-D-Manp and thus are identified as fucomannogalactans. WGFP-A-a, AGFP-A-b, and AGFP-A-c are β-1,6-glucans with different molecular weights and are branched with β-1,3-D-Glcp and T-D-Glcp at the O-3 of Glc. Our results provide important structural information about G. frondosa mycelium-derived polysaccharides and provide the basis for their further development and application.

Objective: Using bioinformatics analyses, this study aimed to identify lncRNAs related to the immune status of acute myeloid leukemia (AML) patients and ascertain the potential impact in immunity-related competing endogenous RNA (ceRNA) networks on AML prognosis.Methods: AML-related RNA-seq FPKM data, AML-related miRNA expression microarray data, and gene sets associated with immunity-related pathways were, respectively, obtained from the TCGA, GEO, and ImmReg databases. An immunity-related ceRNA network was then constructed according to the predicted interactions between AML-related mRNAs, lncRNAs, and miRNAs. After performing LASSO and multivariate Cox regression analyses, lncRNAs in the ceRNA network were used to establish an AML prognostic model. According to mutual regulatory relationships and consistent trends of expression among candidate ceRNAs, two ceRNA subnetworks related to the AML prognostic model were determined. Finally, the correlation between the expression levels of mRNAs, lncRNAs, and miRNAs in each ceRNA subnetwork and immune cell infiltration (assessed by combining the ESTIMATE and CIBERSORT methods and ssGSEA) was analyzed.Results: A total of 424 immunity-related differentially expressed (IR-DE) mRNAs (IR-DEmRNAs), 191 IR-DElncRNAs, and 69 IR-DEmiRNAs were obtained, and a ceRNA network of 20 IR-DElncRNAs, 6 IR-DEmRNAs, and 3 IR-DEmiRNAs was established. Univariate Cox regression analysis was conducted on 20 IR-DElncRNAs, and 7 of these were identified to be significantly correlated with the overall survival (OS) time in AML patients. Then, two IR-DElncRNAs (MEG3 and HCP5) were screened as independent OS-related factors by LASSO and multivariable Cox regression analyses, and a prognostic model was constructed to evaluate the survival risk in AML patients. Survival analyses indicated that the OS of patients was often poor in the high-risk group. Additionally, from this model, two ceRNA regulatory pathways, namely, MEG3/miR-125a-5p/SEMA4C and HCP5/miR-125b-5p/IL6R, which were potentially involved in the immune regulation of AML prognosis were identified.Conclusion: lncRNAs HCP5 and MEG3 may act as key ceRNAs in the pathogenesis in AML by regulating immune cell representation as part of the regulatory lncRNA-miRNA-mRNA axes. The candidate mRNAs, lncRNAs, and miRNAs included in the ceRNA network identified here may serve as useful prognostic biomarkers and immunotherapeutic targets for AML.

Abstract At present, the molecular mechanisms underlying inflammation remain unclear. In recent years, research on inflammation has focused on stimulating cell inflammation by using exogenous pro-inflammatory substances such as lipopolysaccharide (LPS) or inflammatory factors. To investigate the molecular mechanism of inflammation from a new perspective, we designed a nucleic acid nanoflowers (NFs) complex to directly activate inflammatory genes to study the inflammatory response without the need for external microbial factors to trigger an inflammatory response. An RNAa-type target gene-activated NFs was designed. Human umbilical vein endothelial cells (HUVECs) were transfected with NFs carrying small activating RNA (saRNAs) to directly co-activate microRNA (miR)-155 and SHIP1 genes. After RNA activation (RNAa)-type NFs were transferred into HUVECs, the expression of miR-155 and pro-inflammatory and cancer-related factors increased, anti-inflammatory factors were reduced, cell proliferation increased, and cell migration was promoted. IL-1β protein levels were decreased and SHIP1 expression was downregulated. When miR-155 and its target SHIP1 were both activated, the expression of both was unaltered, maintaining cell homeostasis. This points towards miR-155 overexpression can trigger inflammation, and that miR-155 and its target genes act as a molecular switch role in the development of inflammation.

Abstract Background Advanced models including time-lapse imaging and artificial intelligence technologies have been used to predict blastocyst formation. However, the conventional morphological evaluation of embryos is still widely used. The purpose of the present study was to evaluate the predictive power of conventional morphological evaluation regarding blastocyst formation. Methods Retrospective evaluation of data from 15,613 patients receiving blastocyst culture from January 2013 through December 2020 in our institution were reviewed. Generalized estimating equations (GEE) were used to establish the morphology-based model. To estimate whether including more features regarding patient characteristics and cycle parameters improve the predicting power, we also establish models including 27 more features with either LASSO regression or XGbosst. The predicted number of blastocyst were associated with the observed number of the blastocyst and were used to predict the blastocyst transfer cancellation either in fresh or frozen cycles. Results Based on early cleavage and routine observed morphological parameters (cell number, fragmentation, and symmetry), the GEE model predicted blastocyst formation with an AUC of 0.779(95%CI: 0.77–0.787) and an accuracy of 74.7%(95%CI: 73.9%-75.5%) in the validation set. LASSO regression model and XGboost model based on the combination of cycle characteristics and embryo morphology yielded similar predicting power with AUCs of 0.78(95%CI: 0.771–0.789) and 0.754(95%CI: 0.745–0.763), respectively. For per-cycle blastocyst yield, the predicted number of blastocysts using morphological parameters alone strongly correlated with observed blastocyst number (r = 0.897, P

Background: Male and female gametes factors might contribute to the total fertilization failure (TFF). In first in vitro fertilization (IVF) cycles, decision-making of insemination protocol was mainly based on semen quality for the contribution of female clinical characteristics to TFF remained obscure. The purpose of the study was to evaluate the role of semen quality in predicting unexpected TFF.Methods: A single-center retrospective cohort analysis was performed on 19539 cycles between 2013 and 2021. Two algorithms, a Least Absolute Shrinkage and Selection Operator (LASSO) and an Extreme Gradient Boosting (Xgboost) were used to create models with cycle characteristics parameters. By including semen parameters or not, the contribution of semen parameters to the performance of the models was evaluated. The area under the curve (AUC), the calibration, and the net reclassification index (NRI) were used to evaluate the performance of the models.Results: The prevalence of TFF were .07 (95%CI:0.07-0.08), and .08 (95%CI:0.07-0.09) respectively in the development and validation group. Including all characteristics, with the models of LASSO and Xgboost, TFF was predicted with the AUCs of .74 (95%CI:0.72-0.77) and .75 (95%CI:0.72-0.77) in the validation group. The AUCs with models of LASSO and Xgboost without semen parameters were .72 (95%CI:0.69-0.74) and .73 (95%CI:0.7-0.75). The models of LASSO and Xgboost with semen parameters only gave the AUCs of .58 (95%CI:0.55-0.61) and .57 (95%CI:0.55-0.6). For the overall validation cohort, the event NRI values were −5.20 for the LASSO model and −.71 for the Xgboost while the non-event NRI values were 10.40 for LASSO model and 0.64 for Xgboost. In the subgroup of poor responders, the prevalence was .21 (95%CI:0.18-0.24). With refitted models of LASSO and Xgboost, the AUCs were .72 (95%CI:0.67-0.77) and .69 (95%CI:0.65-0.74) respectively.Conclusion: In unselected patients, semen parameters contribute to limited value in predicting TFF. However, oocyte yield is an important predictor for TFF and the prevalence of TFF in poor responders was high. Because reasonable predicting power for TFF could be achieved in poor responders, it may warrant further study to prevent TFF in these patients.

BackgroundEctopic pancreas is a congenital anomaly in which pancreatic tissue is anatomically separated from the main gland and without vascular or ductal continuity. A case of retroperitoneal ectopic pancreas with adrenal adenoma has never yet been reported.Case PresentationA 54-year-old man presented three masses in the left retroperitoneum, and two of them were resected. The pathologic findings were a retroperitoneal ectopic pancreas with adrenal adenoma.ConclusionWe report an extremely rare case of a retroperitoneal ectopic pancreas and its characterization with dynamic gadolinium-enhanced magnetic resonance imaging (MRI).

Deep enclosing rocks exhibit non-homogeneous characteristics of dense joints and fissure development. Soft rocks subjected to multiple factors, such as high stress and hydrostatic pressure, are prone to damage and significant deformation, which can lead to instability of the surrounding rocks, failure of the supporting structure, and other accidents. In this study, we investigated the creep behaviour of deep soft rocks and siltstone-like materials subjected to different unloading confining pressures coupled with a high stress field and seepage. Subsequently, the laws and behaviours of parameters, such as the transient strain, creep deformation, and creep rate were derived and analysed under various conditions. The results indicate that the radial creep curve exhibits a variation pattern similar to that of the axial creep. However, the extent of radial creep exceeds that of axial creep in soft siltstone-like rocks under unloading confining pressure conditions. We derived expressions for the constitutive relation of siltstone-like specimens under various unloading confining pressure conditions in the presence of seepage using an improved viscoelasticmodel that considered the coupling effect of fissure and seepage flow. The correlation coefficients of the calculated model values with the experimental values, as obtained by the non-linear least-squares fitting, were all above 0.9178, indicating that the proposed model can accurately characterise the creep process in fissured siltstone.

Peach trees play an essential role as an economic crop in China. However, the increasing cost of labor has led to a decline in the benefits of peach cultivation. The use of dwarfing rootstock technology can increase planting density, reduce tree height, decrease labor requirements, and reduce production costs. The Cerasus humilis (Bge). Sok. is a promising dwarfing rootstock for peaches owing to its small tree size, abundant resources, strong resistance, and adaptability. In this study, we investigated the effect of Cerasus humilis rootstocks on peach growth and development, and related gene expression. We used Ruipan 4/Cerasus humilis and Ruipan 4/Amygdalus persica L. as experimental materials to measure the growth and fruiting characteristics of two-year-old Cerasus humilis rootstocks. In addition, we used bioinformatic methods to explore the effect of Cerasus humilis rootstock on peach growth gene expression. Our results showed that Cerasus humilis rootstocks can dwarf peach trees, reduce branches, increase pollen count and stigma receptivity, shorten spore development, and promote protein accumulation in the late stage of fruit maturity. The Cerasus humilis rootstock reduced the growth hormone content in peach trees while upregulating the expression of growth-related PpYucca5 and PpYucca2 genes. PpYucca6 expression was downregulated in the early stage of shoot growth and upregulated in the middle stage. By reducing the content of growth hormones, peach trees can be dwarfed, but their impact on fruit quality is minimal. These results indicate that Cerasus humilis is a suitable peach dwarfing rootstock and can provide a theoretical reference for the future breeding of peach dwarfing rootstocks.

Abstract Background Network meta-analysis (NMA) has been widely used in the field of medicine and health, but the research topics and development trends are still unclear. This study aimed to identify the cooperation of countries and institutes and explore the hot topics and future prospects in the field of NMA. Methods Data of publications were downloaded from the Web of Science Core Collection. We used CiteSpace V, HistCite 2.1, and Excel 2016 to analyze literature information, including years, journals, countries, institutes, authors, keywords, and co-cited references. Results NMA research developed gradually before 2010 and rapidly in the following years. 2846 NMA studies were published in 771 journals in six languages. The PLoS One (110, 3.9%) was the most productive journal, and N Engl J Med (5904 co-citations) was the most co-cited journal. The most productive country was the United States (889, 31%) and the most productive institute was the University of Bristol (113, 4.0%). The active collaborations were observed between developed countries and between productive institutes. Of the top 10 authors, four were from the UK, and among the top 10 co-cited authors, six were from the UK. Randomized evidence, oral anti-diabetic drugs, coronary artery bypass, certolizumab pegol, non-valvular atrial fibrillation, and second-line antihyperglycemic therapy were the hot topics in this field. Conclusions NMA studies have significantly increased over the past decade, especially from 2015 to 2017. Compared with developing countries, developed countries have contributed more to these publications and have closer cooperation, indicating that cooperation between developed and developing countries should be further strengthened. The treatment of diabetes, cardiovascular diseases, and immune rheumatism are the main hot topics.

Human and Organizational Factors (HOFs) are usually the root causes of complex system failures. Human reliability analysis (HRA) methods to build the structure of HOFs have been proposed. However, they typically lack validated data. To address this limitation, learning from the past has been considered regarding the EU Major Accident Reporting System’s (eMARS) records. Category data analysis has been applied to support the quantitative analysis. With the HOFs related near-miss and major accidents recorded by eMARS reports, the obtained results show deep insights about the co-influence and contributions of HOFs to the accidents and the possibility to predict the hazards to the process safety, environment, and cost consequences. Our framework contributes to enhancements in HOFs accidents control and mitigation by enabling risk awareness.

Lacking data has always been a challenging problem for risk analysts on human and organizational factors (HOFs) since the theme comes to birth. Accident reports are an essential source of HOFs information, but they are often in the form of unstructured text, making it challenging to apply the number statistic method directly. The traditional manual coding of accident records could introduce uncertainties and inefficiencies, especially when a large number of records is available. Thanks to the development of the natural language processing (NLP) technique, some analysts have attempted to mine the text of accident reports (Single et al., 2020). A similar approach was adopted to highlight HOFs contributing to the accidents. The NLP and HOFs categories have then been introduced to obtain the critical structure of HOFs related accidents. Furthermore, the approach of text similarities calculation is applied to support the relationship analysis of performance influencing factors (PIF) based on the mining of data of the EU Major Accident Reporting System’s (eMARS). In general terms, a framework is proposed to efficiently exploit the information contained in accident records to assess the HOFs elements better to be included in process risk assessment.

To explore the effect of storage conditions on the freshness of fishmeal, the acid value (AV), volatile basic nitrogen (VBN), and pH value were used as freshness evaluation indexes to explore the changes in freshness during storage and the influence of mold count on these indexes. The effects of storage temperature and relative humidity (RH) on AV, VBN, pH value, and mold count were studied using a single-factor test, and grey relation analysis (GRA) was used to assess the association between mold count and freshness indexes. The appropriate storage conditions were determined using the technique for order preference by similarity to ideal solution (TOPSIS) method, which provides theoretical support for fishmeal storage. The results showed that the AV increased during the storage of fishmeal, while the VBN and pH value decreased; the pH value tended to be stable in the later storage stage. The VBN and pH values could not be used as evaluation indexes in the early stage of deterioration. Higher storage temperature was conducive to the storage of fishmeal, but higher RH was not. The results of the GRA showed that the mold count was correlated with each freshness index. The correlation between mold count and VBN was the largest, followed by AV, and the correlation with pH value was the smallest. The TOPSIS method finally determined the suitable storage conditions for fishmeal to be around 25 °C for storage temperature and 60% for RH. The results serve as a future reference for the storage of fishmeal.

In modern electronic warfare, the intelligence of the jammer greatly worsens the anti-jamming performance of traditional passive suppression methods. How to actively design anti-jamming strategies to deal with intelligent jammers is crucial to the radar system. In the existing research on radar anti-jamming strategies’ design, the assumption of jammers is too ideal. To establish a model that is closer to real electronic warfare, this paper explores the intelligent game between a subpulse-level frequency-agile (FA) radar and a transmit/receive time-sharing jammer under jamming power dynamic allocation. Firstly, the discrete allocation model of jamming power is established, and the multiple-round sequential interaction between the radar and the jammer is described based on an extensive-form game. A detection probability calculation method based on the signal-to-interference-pulse-noise ratio (SINR) accumulation gain criterion (SAGC) is proposed to evaluate the game results. Secondly, considering that the competition between the radar and the jammer has the feature of imperfect information, we utilized neural fictitious self-play (NFSP), an end-to-end deep reinforcement learning (DRL) algorithm, to find the Nash equilibrium (NE) of the game. Finally, the simulation results showed that the game between the radar and the jammer can converge to an approximate NE under the established model. The approximate NE strategies are better than the elementary strategies from the perspective of detection probability. In addition, comparing NFSP and the deep Q-network (DQN) illustrates the effectiveness of NFSP in solving the NE of imperfect information games.

To investigate the role of N6-methyladenosine (m6A)- related long non-coding RNAs (lncRNAs) in bladder cancer (BC). 50 m6A-related lncRNAs were screened out and were correlated with prognosis from BC samples in The Cancer Genome Atlas (TCGA). The lncRNAs were subdivided into cluster 1 and cluster 2 with consensus cluster analysis, and it was found that lncRNAs in cluster 2 were associated with poor prognosis and increased PD-L1 expression. Gene set enrichment analysis (GSEA) revealed tumor-related pathways in cluster 2. Through least absolute shrinkage and selection operator (LASSO) Cox regression analysis, univariate and multivariate Cox regression, and ROC analyses, 14 prognostic lncRNAs were selected and used to construct the m6A-related lncRNA prognostic signature (m6A-LPS), furthermore, that m6A-LPS was as a valuable independent prognostic factor. Interestingly, the m6A-LPS risk score was positively correlated with the immune score, PD-L1 expression, and the infiltration of immune cell subtypes in BC. SNHG16, a member of the high-risk group based on m6A-LPS, was highly expressed in BC tissues and cell lines and interfered with siRNA resulted in suppressed proliferation, migration, and invasion in vitro. Our study illustrates the role of m6A-related lncRNAs in BC. The m6A-LPS may be an important regulatory target of the tumor microenvironment (TME) in BC.

The strength of the roadbed composed of soft rock decreases following water immersion. Cement slurry is mixed with a soft rock to strengthen the soft rock roadbed to address this problem. The uniaxial compressive strength was determined, and the triaxial compression tests were conducted to analyze muddy sandstones mixed with different amounts of the cement slurry of the same composition. Some of the cured samples were soaked in water, and the samples were analyzed. The results were compared with the results obtained by analyzing unsoaked samples. The MIDAS/GTS NX software was used to develop a three-dimensional finite model to simulate the settlement patterns of roadbeds developed in the presence of natural water, saturated water, and muddy sandstone reinforcements. The experimental results have been presented and discussed. (1) When the filling rate corresponding to the cement slurry is 32%, the uniaxial compressive strength of muddy sandstone containing natural water reaches 3.32 MPa, which is approximately 5 times higher than the strength of muddy sandstone devoid of cement slurry. (2) The water absorption energy of the reinforced muddy sandstone was analyzed from the perspective of saturated water content. The water plugging effect observed after the addition of the cement slurry was studied, and the equations defining uniaxial compressive strength, elastic modulus, and free saturated water content were established. (3) An increase in the content of the cement slurry admixture resulted in a change in the nature of the partial stress–strain curves generated for muddy sandstone. The curve change from strain-hardening to strain-softening type and the deformation modulus and extent of cohesion realized increased exponentially with an increase in the cement slurry filling rate. A positive linear correlation was observed between the internal friction angle and the cement slurry filling rate. (4) An increase in the cement slurry filling rate corresponding to the saturated muddy sandstone resulted in an exponential decrease in the settlement deformation value. The vertical displacement decreased to 0.3497 mm when the grouting rate reached 32% under conditions of saturation. The deformation tended to converge and stabilize, indicating that the introduction of the admixture consisting of the cement slurry could help in effectively controlling the property of settlement deformation observed in the fully weathered muddy sandstone roadbed. The results helped in the scientific evaluation of the reinforcement effect. The reported results also helped develop a theoretical basis for the development of soft foundation reinforcement.

Abstract Background Sepsis-associated encephalopathy (SAE) is related to increased short-term mortality in patients with sepsis. We aim to establish a user-friendly nomogram for individual prediction of 30-day risk of mortality in patients with SAE. Methods Data were retrospectively retrieved from the Medical Information Mart for Intensive Care (MIMIC III) open source clinical database. SAE was defined by Glasgow Coma Score (GCS) < 15 or delirium at the presence of sepsis. Prediction model with a nomogram was constructed in the training set by logistic regression analysis and then undergone internal validation and sensitivity analysis. Results SAE accounted for about 50% in patients with sepsis and was independently associated with the 30-day mortality of sepsis. Variables eligible for the nomogram included patient’s age and clinical parameters on the first day of ICU admission including the GCS score, lactate, bilirubin, red blood cell distribution width (RDW), mean value of respiratory rate and temperature, and the use of vasopressor. Compared with Sequential Organ Failure Assessment (SOFA) and Logistic Organ Dysfunction System (LODS), the nomogram exhibited better discrimination with an area under the receiver operating characteristic curve (AUROC) of 0.763 (95%CI 0.736–0.791, p < 0.001) and 0.753 (95%CI 0.713–0.794, p < 0.001) in the training and validation sets, respectively. The calibration plot revealed an adequate fit of the nomogram for predicting the risk of 30-day mortality in both sets. Regarding to clinical usefulness, the DCA of the nomogram exhibited greater net benefit than SOFA and LODS in both of the training and validation sets. Besides, the nomogram exhibited acceptable discrimination, calibration, and clinical usefulness in sensitivity analysis. Conclusions SAE is related to increased 30-day mortality of patients with sepsis. The nomogram presents excellent performance in predicting 30-day risk of mortality in SAE patients, which can be used to evaluate the prognosis of patients with SAE and may be more beneficial once specific treatments towards SAE are developed.

Fault diagnosis is an important technology to ensure the safe and reliable operation of equipment. Deep learning driven by big data brings new opportunities for fault diagnosis. Due to the diversity and complexity of the actual fault data distribution, a fault diagnosis algorithm based on non-negative sparse constrained deep neural networks (NSCDNN) and Dempster-Shafer theory (DST) is proposed in this paper. The deep neural network is trained by non-negative constraint and sparse constraint, which can learn part-based representation of fault data. The improved DST is combined with the classification confidence and accuracy of NSCDNN model, which can deal with the uncertainty of information from different sensors. Experimental results of the data provided by Case Western Reserve University Bearing Data Center show that the proposed NSCDNN-DST algorithm can improve the accuracy of fault diagnosis effectively.

Abstract Introduction Postoperative delirium is one of the most common and dangerous psychiatric complications after hip surgery. The aim of this study was to investigate the incidence of postoperative delirium in elderly patients after hip fracture surgery and to identify risk factors for such, as part of developing a risk stratification index (RSI) system to predict a patient's risk of postoperative delirium. Methods Elderly patients (aged 65 years or older) with hip fractures who had received surgical treatment in our hospital between March 2018 and December 2019 were retrospectively included. Clinical data were collected, and multivariate logistic regression analysis was performed to investigate the relevant risk factors of postoperative delirium. An RSI system was developed based on factors identified in the regression analysis. Results Of 272 patients included, 52 (19.12%) experienced postoperative delirium. Drinking history (> 3/ week), the perioperative lactic acid level (Lac > 2 mmol/L), postoperative visual analog score (VAS) > 3, American Society of Anesthesiologists (ASA) physical status > II, application of the bispectral index, and preoperative diabetes were independent risk factors of postoperative delirium. When RSI ≥ 5, the rate of postoperative delirium significantly increased (p

Reachability, as a vital parameter in product maintainability design, exerts a tremendous influence in practical maintenance, especially in the usage stage. To decrease subjectivity in maintenance reachability analysis, this study proposes an automatic and quantitative approach based on the spatial data of the human arm to implement maintenance reachability analysis. The approach focused on two aspects, namely, accuracy and efficiency. In terms of accuracy, the presented methodology starts from the maintenance spot where the human hand is attached. An original global data sequence set was generated, including the wrist, elbow, and shoulder joints, under the constraints of kinematics, in which a data sequence represents an arm motion. Moreover, the surrounding objects are represented by their geometric data, in which each data sequence is analyzed to judge whether collision occurs between arm segments and surrounding objects. In this filtering process, the data sequence is retained if the aforementioned collision does not occur. In terms of efficiency, owing to the large number of global data sequences, the efficiency of the interval selection in collision calculation is also taken into consideration in this methodology. Unlike the traditional methods in the virtual environment, the starting point is the maintenance spot, rather than the human body. Hence, nearly all possibilities of arm postures are considered in a global perspective with little subjective involvement, which enhances the automation and objectivity in maintenance reachability analysis to a certain extent. The case study shows the usability and feasibility by a practical maintenance scene.

Remote sensing image scene classification has drawn extensive attention for its wide application in various scenarios. Scene classification in many practical cases faces the challenge of few-shot conditions. The major difficulty of few-shot remote sensing image scene classification is how to extract effective features from insufficient labeled data. To solve these issues, a multi-scale graph-based feature fusion (MGFF) model is proposed for few-shot remote sensing image scene classification. In the MGFF model, a graph-based feature construction model is developed to transform traditional image features into graph-based features, which aims to effectively represent the spatial relations among images. Then, a graph-based feature fusion model is proposed to integrate graph-based features of multiple scales, which aims to enhance sample discrimination based on different scale information. Experimental results on two public remote sensing datasets prove that the MGFF model can achieve superior accuracy than other few-shot scene classification approaches.

AimsThe present study aimed to investigate alterations in neuroinflammation after heart failure (HF) and explore the potential mechanisms.MethodsMale wild-type (WT) and Toll-like receptor 4 (TLR4)-knockout (KO) mice were subjected to sham operation or ligation of the left anterior descending coronary artery to induce HF. 8 weeks later, cardiac functions were analyzed by echocardiography, and intestinal barrier functions were examined by measuring tight junction protein expression, intestinal permeability and plasma metabolite levels. Alterations in neuroinflammation in the brain were examined by measuring microglial activation, inflammatory cytokine levels and the proinflammatory signaling pathway. The intestinal barrier protector intestinal alkaline phosphatase (IAP) and intestinal homeostasis inhibitor L-phenylalanine (L-Phe) were used to examine the relationship between intestinal barrier dysfunction and neuroinflammation in mice with HF.ResultsEight weeks later, WT mice with HF displayed obvious increases in intestinal permeability and plasma lipopolysaccharide (LPS) levels, which were accompanied by elevated expression of TLR4 in the brain and enhanced neuroinflammation. Treatment with the intestinal barrier protector IAP significantly attenuated neuroinflammation after HF while effectively increasing plasma LPS levels. TLR4-KO mice showed significant improvements in HF-induced neuroinflammation, which was not markedly affected by intestinal barrier inhibitors or protectors.ConclusionHF could induce intestinal barrier dysfunction and increase gut-to-blood translocation of LPS, which could further promote neuroinflammation through the TLR4 pathway.

Remote sensing image classification is a prominent topic in earth observation research, but there is a performance bottleneck when classifying single-source objects. As the types of remote sensing data are gradually diversified, the joint classification of multi-source remote sensing data becomes possible. However, the existing classification methods have limitations in heterogeneous feature representation of multimodal remote sensing data, which restrict the collaborative classification performance. To resolve this issue, a position-channel collaborative attention network is proposed for the joint classification of hyperspectral and LiDAR data. Firstly, in order to extract the spatial, spectral, and elevation features of land cover objects, a multiscale network and a single-branch backbone network are designed. Then, the proposed position-channel collaborative attention module adaptively enhances the features extracted from the multi-scale network in different degrees through the self-attention module, and exploits the features extracted from the multiscale network and single-branch network through the cross-attention module, so as to capture the comprehensive features of HSI and LiDAR data, narrow the semantic differences of heterogeneous features, and realize complementary advantages. The depth intersection mode further improves the performance of collaborative classification. Finally, a series of comparative experiments were carried out in the 2012 Houston dataset and Trento dataset, and the effectiveness of the model was proved by qualitative and quantitative comparison.

Aims: The development of neuroinflammation deteriorates the prognosis of myocardial infarction (MI). We aimed to investigate the effect of renal denervation (RDN) on post-MI neuroinflammation in rats and the related mechanisms.Methods and Results: Male adult Sprague-Dawley rats were subjected to sham or ligation of the left anterior descending coronary artery to induce MI. One week later, the MI rats received a sham or RDN procedure. Their cardiac functions were analyzed by echocardiography, and their intestinal structures, permeability, and inflammatory cytokines were tested. The intestinal microbiota were characterized by 16S rDNA sequencing. The degrees of neuroinflammation in the brains of rats were analyzed for microglia activation, inflammatory cytokines, and inflammation-related signal pathways. In comparison with the Control rats, the MI rats exhibited impaired cardiac functions, intestinal injury, increased intestinal barrier permeability, and microbial dysbiosis, accompanied by increased microglia activation and pro-inflammatory cytokine levels in the brain. A RDN procedure dramatically decreased the levels of renal and intestinal sympathetic nerve activity, improved cardiac functions, and mitigated the MI-related intestinal injury and neuroinflammation in the brain of MI rats. Interestingly, the RDN procedure mitigated the MI-increased intestinal barrier permeability and pro-inflammatory cytokines and plasma LPS as well as ameliorated the gut microbial dysbiosis in MI rats. The protective effect of RDN was not significantly affected by treatment with intestinal alkaline phosphatase but significantly reduced by L-phenylalanine treatment in MI rats.Conclusions: RDN attenuated the neuroinflammation in the brain of MI rats, associated with mitigating the MI-related intestinal injury.

Heritability of Spondyloarthritis (SpA) is highlighted by several familial studies and a high association with the presence of human leukocyte antigen (HLA)-B*27. Though it has been over four decades since the association of HLA-B*27 with SpA was first determined, the pathophysiological roles played by specific HLA-B*27 allotypes are not fully understood. Popular hypotheses include the presentation of arthritogenic peptides, triggering of endoplasmic reticulum (ER) stress by misfolded HLA-B*27, and the interaction between free heavy chains or heavy chain homodimers of HLA-B*27 and immune receptors to drive IL-17 responses. Several non-HLA susceptibility loci have also been identified for SpA, including endoplasmic reticulum aminopeptidases (ERAP) and those related to the IL-23/IL-17 axes. In this review, we summarize clinical aspects of SpA including known characteristics of gut inflammation, enthesitis and new bone formation and the existing models for understanding the association of HLA-B*27 with disease pathogenesis. We also examine newer insights into the biology of HLA class I (HLA-I) proteins and their implications for expanding our understanding of HLA-B*27 contributions to SpA pathogenesis.

Pulmonary arterial hypertension (PAH) is a progressive pulmonary vascular disease associated with dysfunction of pulmonary artery endothelial cells and pulmonary artery smooth muscle cells (PASMCs). To explore the potential mechanism of miR-193-3p in pulmonary arterial hypertension, human PASMCs and rats were respectively stimulated by hypoxia and monocrotaline to establish PAH model in vivo and in vitro. The expressions of miR-193-3p and p21-activated protein kinase 4 (PAK4) in the lung samples of PAH patients and paired healthy samples from the healthy subjects in PHA cells and rats were detected by quantitative reverse transcriptase-PCR. Morphological changes in lung tissues were determined using hematoxylin and eosin staining. Right ventricular systolic pressure (RVSP) and ratio of right ventricle to left ventricle plus septum (RV/LV p S) were measured. The binding relationship between miR-193-3p and PAK4 was analyzed by TargetScan and verified by luciferase reporter assay. Cell viability, apoptosis, and migration were detected by 3-(4, 5-Dimethylthiazol-2- yl)-2,5-diphenyltetrazolium bromide (MTT) flow cytometry, and wound-healing assays, respectively. The protein expressions of PAK4, proliferating cell nuclear antigen (PCNA), P21, p-AKT, and AKT in vivo or in vitro were determined by Western blot. In this study, we found that in pulmonary arterial hypertension, miR-193-3p expression was downregulated and PAK4 expression was up-regulated. MiR-193-3p directly targeted PAK4 and negatively regulated its expression. Hypoxia condition promoted cell proliferation, migration, and inhibited apoptosis accompanied with increased expressions of PCNA and p-AKT/AKT and decreased expression of P21 in PASMCs. MiR-193-3p overexpression attenuated the effects of hypoxia on PASMCs via downregulating PAK4. Monocrotaline treatment increased p-AKT/AKT and decreased P21 expression and caused pulmonary vascular remodeling in the model rats. MiR-193-3p overexpression attenuated pulmonary vascular remodeling, decreased p-AKT/AKT, and increased P21 levels via downregulating PAK4 in monocrotaline-induced rats. The results in this study demonstrated that upregulation of miR-193-3p reduced cell proliferation, migration, and apoptosis of PAH in vitro and pulmonary vascular remodeling in PAH in vivo through downregulating PAK4.

B lymphocyte-induced maturation protein-1 (Blimp1) is a key regulator that promotes the terminal differentiation of mature B lymphocytes into plasma cells, and is essential for the survival of Multiple myeloma (MM)cells. However, the expression of Blimp1 in MM and its effect on the signaling pathway remain unknown. Studies have found that during long-term endoplasmic reticulum (ER) stress, activated ATF4 may also stimulate the CCAAT-enhancer-binding protein homologous protein (CHOP) gene, triggering the unfolded protein response (UPR) terminal apoptotic pathway in plasma cells. Moreover Aspirin can induce MM cell apoptosis through mitochondria and death receptor pathway. Therefore, we aim to explore whether Aspirin could induce AFT4/CHOP apoptosis pathway in MM by inhibiting Blimp1 expression, thereby promoting MM cell apoptosis and exerting anti-tumor effects.

Background: Myocardial remodeling is the key step in the development of ischemic cardiomyopathy. We aimed to compare effects of renal denervation (RDN) with those of angiotensin receptor neprilysin inhibitors (ARNi) on cardiac remodeling after myocardial infarction (MI), and explore underlying mechanism. Methods: Sprague-Dawley rats (n = 40; male) were subjected to ligation of left anterior descending coronary artery to induce MI; six rats served as controls. ARNi was administered at a dose of 60 mg/kg/day for 4 weeks starting 1 week after MI. An RDN/Sham-RDN procedure was performed 1 week after MI. Rats in all groups were studied 5 weeks after MI. Echocardiography was used to evaluate cardiac function. Masson staining and TUNEL staining were used to determine the extent of cardiac remodeling. Indicators of oxidative stress in heart and brain were used to analyze the potential mechanisms involved. Results: Five weeks after MI, both RDN and ARNi significantly improved cardiac function and cardiac remodeling; however, RDN was superior to ARNi at attenuating myocardial apoptosis. Compared to ARNi, RDN was also more effective at decreasing the abnormal oxidative stress caused by MI; this was especially true in case of the brain and was confirmed by evaluating the changes in reactive oxygen species (ROS) levels and other oxidative stress parameters following MI. Conclusions: RDN is not inferior to ARNi with respect to the improvement of cardiac remodeling in rats with ischemic cardiomyopathy. The effect of RDN might be associated with effective inhibition of oxidative stress in both the heart and brain.

Background/Aims: To investigate the impact of renal denervation (RDN) on myocardial fibrosis and ventricular arrhythmias (VAs) in rats with ischemic cardiomyopathy. Methods: An ischemic cardiomyopathy model was reproduced with myocardial infarction (MI) in adult Sprague–Dawley male rats. The RDN/Sham-RDN procedure was performed at 2 weeks after MI. Sham-MI and sham-RDN rats served as the control group. At 4 weeks after RDN, programmed electrical stimulation (PES) was used to induce VAs, including ventricular tachycardia and ventricular fibrillation, in all 3 groups (MI+RDN, MI, and control groups). At the end of PES, heart and kidney samples were harvested. Immunofluorescence labeling was used to investigate the distribution of connexin 43 (Cx43) in the infarcted border zone. Masson’s trichrome stain was adopted to determine the degree of cardiac fibrosis. Western blotting was performed to identify the expression of transforming growth factor beta 1 (TGF-β1), α-smooth muscle actin (α-SMA), and Cx43. An enzyme-linked immunosorbent assay (ELISA) was used to detect the serum levels of B-type natriuretic peptide (BNP) and the amino-terminal pro-peptides of type I and III collagen (PINP and PIIINP, respectively) and the expression level of renal norepinephrine. Results: Compared with the MI group, RDN significantly decreased the inducibility of VAs (MI+RDN 3/8 rats vs. MI 8/9 rats, P < 0.05; control 1/8 rats) with PES, reduced myocardial fibrosis estimated by collagen volume fraction (MI+RDN 31.10 ± 3.97% vs. MI 54.80 ± 16.39%, P < 0.001; control 4.41 ± 0.92% ), suppressed TGF-β1 (P < 0.01) and α-SMA (P < 0.001) levels, and attenuated both PINP (MI+RDN 41.44 ± 10.10 ng/mL vs. MI 95.49 ± 24.83 ng/mL, P < 0.001; control 11.90 ± 4.96 ng/mL) and PIIINP (MI+RDN 82.12 ± 30.79 ng/mL vs. MI 124.60 ± 26.64 ng/mL, P < 0.05; control 64.69 ± 23.84 ng/mL) levels. Moreover, RDN reversed the abnormal myocardial distribution of Cx43 and its reduction by MI damage (P < 0.01). Conclusions: RDN reduced myocardial fibrosis and suppressed VAs in a rat model of ischemic cardiomyopathy.

Abstract Background Multipotent mesenchymal stromal cell (MSC) therapy has been widely recognized as a feasible strategy for regenerating injured myocardial tissue. However, little is known about the efficacy of intravenous injection of allogeneic umbilical cord (UC) MSCs in preclinical models of porcine myocardial infarction. Methods Different dosages of allogeneic UC-MSCs or the vehicle [phosphate-buffered saline (PBS)] were delivered intravenously into an acute myocardial infarction (AMI) porcine model twice after coronary ligation. Echocardiography was performed to examine the cardiac function and single photon emission computed tomography (SPECT) and positron emission tomography (PET)/computed tomography (CT) was performed to detect cardiac perfusion and nonviable myocardium. At the end of the experiment, 2,3,5-triphenyl-tetrazolium chloride (TTC) staining and Masson T staining were performed to determine the infarct area. The protein and gene expression levels associated with cardiac function, inflammation, and angiogenesis were examined by Western blot and real time polymerase chain reaction (PCR). In vivo trafficking of intravenous injection of allogeneic UC-MSCs enhanced green fluorescent protein (eGFP) was detected by real time PCR and immunofluorescence. Results After systemic delivery, allogeneic UC-MSCs were largely distributed in the lungs and some in the infracted myocardium. At week 8 following AMI, echocardiography demonstrated significantly improved fractional shortening in the high-dose (1.5 × 106 cells/kg) group. SPECT-PET/CT showed that UC-MSC treatment in both high and low doses markedly ameliorated the left ventricle (LV) infarct area but did not significantly improve the myocardial perfusion defect. LV remodeling was inhibited by UC-MSC therapy, as reflected by a marked reduction in rthe fibrosis area at basal, middle, and apical levels and reduced extracellular matrix deposition in the total myocardial area. Inflammatory biomarkers (tumor necrosis factor alpha and interleukin-6) were reduced and pro-angiogenesis factors (vascular endothelial growth factor and platelet/endothelial cell adhesion molecule 1) were augmented in the myocardial infarct and border area. High-dose UC-MSCs increased the connexin 43 (Cx43) (myocardium preservation) expression in remote area of the LV myocardium after AMI. Conclusions Intravenous injection of UC-MSCs is a feasible and effective way to preserve LV function and ameliorate myocardial remodeling in porcine AMI. The cardioprotective effects of UC-MSCs were attributed to paracrine factors that appear to augment angiogenesis, limit inflammation, and preserve Cx43 gap junction.

Abstract Background Contactin1 (CNTN1) has been shown to play an important role in the invasion and metastasis of several tumors; however, the role of CNTN1 in breast cancer has not been fully studied. The purpose of this study is to investigate the role of CNTN1 in regulating tumor growth, migration and invasion in breast cancer. Results To investigate its function, CNTN1 was expressed in Hs578T cells. CNTN1 expression was confirmed by western blot, immunohistochemistry and real-time RT-PCR. The effect of CNTN1 overexpression on proliferation, migration and invasion of Hs578T breast cancer cells was assessed in vitro and in vivo. Our results showed that CNTN1 overexpression promoted Hs578T cell proliferation, cell cycle progression, colony formation, invasion and migration. Notably, overexpression of CNTN1 in Hs578T cells enhanced the growth of mouse xenograft tumors. Conclusions CNTN1 promotes growth, metastasis and invasion of Hs578T breast cancer cell line. Thus, therapies targeting CNTN1 may prove efficacious for breast cancer. However, further investigation is required to understand the mechanism by which CNTN1 influences proliferation, metastasis and invasion in breast cancer.