Tumor necrosis factor receptor-associated factor 5 protects against intimal hyperplasia by regulation of macrophage polarization via directly targeting PPARγ.

OBJECTIVES: Intimal hyperplasia is a serious clinical problem associated with the failure of therapeutic methods in multiple atherosclerosis-related coronary heart diseases, which are initiated and aggravated by the polarization of infiltrating macrophages. The present study aimed to determine the effect and underlying mechanism by which tumor necrosis factor receptor-associated factor 5 (TRAF5) regulates macrophage polarization during intimal hyperplasia. METHODS: TRAF5 expression was detected in mouse carotid arteries subjected to wire injury. Bone marrow-derived macrophages, mouse peritoneal macrophages and human myeloid leukemia mononuclear cells were also used to test the expression of TRAF5 in vitro. Bone marrow-derived macrophages upon to LPS or IL-4 stimulation were performed to examine the effect of TRAF5 on macrophage polarization. TRAF5-knockout mice were used to evaluate the effect of TRAF5 on intimal hyperplasia. RESULTS: TRAF5 expression gradually decreased during neointima formation in carotid arteries in a time-dependent manner. In addition, the results showed that TRAF5 expression was reduced in classically polarized macrophages (M1) subjected to LPS stimulation but was increased in alternatively polarized macrophages (M2) in response to IL-4 administration, and these changes were demonstrated in three different types of macrophages. An in vitro loss-of-function study with TRAF5 knockdown plasmids or TRAF5-knockout mice revealed high expression of markers associated with M1 macrophages and reduced expression of genes related to M2 macrophages. Subsequently, we incubated vascular smooth muscle cells with conditioned medium of polarized macrophages in which TRAF5 expression had been downregulated or ablated, which promoted the proliferation, migration and dedifferentiation of VSMCs. Mechanistically, TRAF5 knockdown inhibited the activation of anti-inflammatory M2 macrophages by directly inhibiting PPARγ expression. More importantly, TRAF5-deficient mice showed significantly aggressive intimal hyperplasia. CONCLUSIONS: Collectively, this evidence reveals an important role of TRAF5 in the development of intimal hyperplasia through the regulation of macrophage polarization, which provides a promising target for arterial restenosis-related disease management.

Non-alcoholic fatty liver disease and gestational diabetes mellitus: a bidirectional two-sample mendelian randomization study.

PURPOSE: Previous observational studies have revealed a potential link between non-alcoholic fatty liver disease (NAFLD) and gestational diabetes mellitus (GDM), but their causal relationship remains unclear. Thus, this study aimed to examine whether a causal link exists between genetically determined NAFLD and GDM. METHODS: Utilizing publicly accessible genome-wide association studies (GWAS), a two-sample bidirectional Mendelian randomization (MR) analysis was conducted. The GWASs data pertaining to NAFLD and GDM were obtained from the UK Biobank Consortium and FinnGen database in primary analysis, respectively. The random-effects inverse variance weighted (IVW) method was utilized as primary analysis method. Several sensitivity analyses were utilized to verify the robustness of the results. Additionally, we also analyzed the causal effect of potential shared influencing factors on these two conditions. RESULTS: The result of the IVW method showed that there was no significant causal relationship between genetically determined NAFLD and GDM (OR = 0.98, 95% CI: 0.90-1.07, P = 0.691). Similarly, our reverse MR analysis failed to detect a significant causal effect of GDM on NAFLD (OR = 1.14, 95% CI: 0.97-1.36, P = 0.118). Sensitivity analyses further confirmed the robustness of the results. Moreover, we found that genetically determined body mass index, waist-to-hip ratio, triglycerides, and television viewing time may be positively correlated with NAFLD and GDM, while high-density lipoprotein cholesterol and apolipoprotein A-I may both be negatively correlated with NAFLD and GDM. CONCLUSIONS: The current bidirectional MR study failed to provide sufficient genetic evidence for the causal relationship between NAFLD and GDM.

A deep learning-based radiomics model for predicting lymph node status from lung adenocarcinoma.

OBJECTIVES: At present, there are many limitations in the evaluation of lymph node metastasis of lung adenocarcinoma. Currently, there is a demand for a safe and accurate method to predict lymph node metastasis of lung cancer. In this study, radiomics was used to accurately predict the lymph node status of lung adenocarcinoma patients based on contrast-enhanced CT. METHODS: A total of 503 cases that fulfilled the analysis requirements were gathered from two distinct hospitals. Among these, 287 patients exhibited lymph node metastasis (LNM +) while 216 patients were confirmed to be without lymph node metastasis (LNM-). Using both traditional and deep learning methods, 22,318 features were extracted from the segmented images of each patient's enhanced CT. Then, the spearman test and the least absolute shrinkage and selection operator were used to effectively reduce the dimension of the feature data, enabling us to focus on the most pertinent features and enhance the overall analysis. Finally, the classification model of lung adenocarcinoma lymph node metastasis was constructed by machine learning algorithm. The Accuracy, AUC, Specificity, Precision, Recall and F1 were used to evaluate the efficiency of the model. RESULTS: By incorporating a comprehensively selected set of features, the extreme gradient boosting method (XGBoost) effectively distinguished the status of lymph nodes in patients with lung adenocarcinoma. The Accuracy, AUC, Specificity, Precision, Recall and F1 of the prediction model performance on the external test set were 0.765, 0.845, 0.705, 0.784, 0.811 and 0.797, respectively. Moreover, the decision curve analysis, calibration curve and confusion matrix of the model on the external test set all indicated the stability and accuracy of the model. CONCLUSIONS: Leveraging enhanced CT images, our study introduces a noninvasive classification prediction model based on the extreme gradient boosting method. This approach exhibits remarkable precision in identifying the lymph node status of lung adenocarcinoma patients, offering a safe and accurate alternative to invasive procedures. By providing clinicians with a reliable tool for diagnosing and assessing disease progression, our method holds the potential to significantly improve patient outcomes and enhance the overall quality of clinical practice.

Effect of alfalfa supplementary change dietary non-fibrous carbohydrate (NFC) to neutral detergent fiber (NDF) ratio on rumen fermentation and microbial function in Gansu alpine fine wool sheep (Ovis aries).

Bodyweight loss and rumen microbial dysfunction of grazing sheep was a challenge for the sheep production industry during cold season, which were considered to correlated with under-roughage-feeding. Alfalfa is a good roughage supplementary for ruminants, which can improve grazing sheep bodyweight-loss and rumen microbial dysfunction during grass-withering period. This study evaluated the effects of alfalfa hay supplementary change dietary non-fibrous carbohydrate/neutral detergent fiber (NFC/NDF) ratios on rumen fermentation and microbial function of Gansu alpine fine wool sheep during extreme cold season. 120 ewes (3-4 yrs) with an average body weight of 28.71 ± 1.22 kg were allocated randomly into three treatments, and fed NFC/NDF of 1.92 (H group), 1.11 (M group), and 0.68 (L group), respectively. This study was conducted for 107 d, including 7 d of adaption to the diets. The rumen fermentation parameters and microbial characteristics were measured after the end of feeding trials. The results showed that the concentrations of sheep body weight, nitrogen components (Total-N, Soluble protein-N and Ammonia-N), blood biochemical indices (LDH, BUN and CHO) and ruminal volatile fatty acids (TVFA and propionate) significantly increased with an increase in the proportion of NFC/NDF ratios (p < .05), and the acetate and acetate/propionat ratio presented a contrary decreasing trend (p < .05). A total of 1018 OTUs were obtained with 97% consistency. Ruminococcus, Ruminococcaceae and Prevotella were observed as the predominant phyla in ruminal fluid microbiota. Higher NFC/NDF ratios with Alfalfa supplementary increased the richness and diversity of ruminal fluid microbiota, and decreased ruminal fluid microbiota beta-diversity. Using clusters of orthologous groups (COG), the ruminal fluid microbiota of alfalfa supplementary feeding showed low immune pathway and high carbohydrate metabolism pathway. In summary, the study suggested that there was an increasing tendency in dietary NFC/NDF ratio of 1.92 in body weight, ruminal fermentation, microbial community composition and fermentation characteristics through developing alfalfa supplementary system.

The efficacy and safety of mini-open (air/water medium) endoscopy-assisted anterior cervical discectomy and fusion for the treatment of cervical spondylotic myelopathy.

PURPOSE: To compare the clinical efficacy of mini-open (air/water medium) endoscopy-assisted anterior cervical discectomy and fusion (MOEA-ACDF) and anterior cervical decompression and fusion (ACDF) for cervical spondylotic myelopathy (CSM). METHODS: This study retrospectively analysed the clinical data of CSM patients who received surgical treatment from January 1, 2020, to December 31, 2022. Patients were divided into two groups according to the surgical method: the MOEA-ACDF group and the ACDF group. The preoperative and postoperative imaging results at one week and the last follow-up examination were compared between the two groups. The Japanese Orthopaedic Association (JOA) score, visual analogue scale (VAS) score and neck disability index (NDI) score were used to evaluate the clinical outcomes preoperatively, one week postoperatively and at the last follow-up examination. The minimum follow-up duration was 12 months. RESULTS: A total of 131 CSM patients who underwent surgery at our institution were included, including 61 patients in the MOEA-ACDF group and 70 patients in the ACDF group. In the MOEA-ACDF group, the postoperative C2-C7 Cobb angle and HAVB were significantly greater than the preoperative values (P < 0.05). In the ACDF group, the postoperative C2-C7 Cobb angle was also significantly greater than the preoperative value, and the C2-C7 ROM and HAVB significantly decreased (P < 0.05). The postoperative neurological function of the patients in both groups improved, and the postoperative VAS score and NDI score significantly decreased. Compared with ACDF, MOEA-ACDF is associated with a significantly larger postoperative C2-C7 Cobb angle and significantly better C2-C7 ROM and HAVB, as well as better clinical efficacy (P < 0.05). CONCLUSIONS: MOEA-ACDF combines endoscopic systems with ACDF technology to treat CSM, but its clinical efficacy is not inferior to that of ACDF in the short- to intermediate-term. It can effectively and safely restore the cervical intervertebral height, physiological curvature, and range of motion.

Mutation of OsMYB60 reduces rice resilience to drought stress by attenuating cuticular wax biosynthesis.

The cuticular wax layer on leaf surfaces limits non-stomatal water loss to the atmosphere and protects against pathogen invasion. Although many genes associated with wax biosynthesis and wax transport in plants have been identified, their regulatory mechanisms remain largely unknown. Here, we show that the MYB transcription factor OsMYB60 positively regulates cuticular wax biosynthesis and this helps rice (Oryza sativa) plants tolerate drought stress. Compared with the wild type (japonica cultivar 'Dongjin'), osmyb60 null mutants (osmyb60-1 and osmyb60-2) exhibited increased drought sensitivity, with more chlorophyll leaching and higher rates of water loss. Quantitative reverse-transcription PCR showed that the loss of function of OsMYB60 led to downregulation of wax biosynthesis genes, leading to reduced amounts of total wax components on leaf surfaces under normal conditions. Yeast one-hybrid, luciferase transient transcriptional activity, and chromatin immunoprecipitation assays revealed that OsMYB60 directly binds to the promoter of OsCER1 (a key gene involved in very-long-chain alkane biosynthesis) and upregulates its expression. Taken together, these results demonstrate that OsMYB60 enhances rice resilience to drought stress by promoting cuticular wax biosynthesis on leaf surfaces.

Nek6 knockdown polarized macrophages into a pro-inflammatory phenotype via inhibiting STAT3 expression.

Recently macrophage polarization has emerged as playing an essential role in the oathogenesis of atherosclerosis, which is the most important underlying process in many types of cardiovascular diseases. Although Nek6 has been reported to be involved in various cellular processes, the effect of Nek6 on macrophage polarization remains unknown. Macrophages exposed to lipopolysaccharide (LPS) or IL-4 were used to establish an in vitro model for the study of regulation of classically (M1) or alternatively (M2) activated macrophage. Bone marrow-derived macrophages (BMDMs) transfected with short hairpin RNA-targeting Nek6 were then in functional studies. We observed that Nek6 expression was decreased in both peritoneal macrophages (PMs) and BMDMs stimulated by LPS. This effect was seen at both mRNA and protein level. The opposite results were obtained after administration of IL-4. Macrophage-specific Nek6 knockdown significantly exacerbated pro-inflammatory M1 polarized macrophage gene expression in response to LPS challenge, but the anti-inflammatory response gene expression that is related to M2 macrophages was attenuated by Nek6 silencing followed by treatment with IL-4. Mechanistic studies exhibited that Nek6 knockdown inhibited the phosphorylated STAT3 expression that mediated the effect on macrophage polarization regulated by AdshNek6. Moreover, decreased Nek6 expression was also observed in atherosclerotic plaques. Collectively, these evidences suggested that Nek6 acts as a crucial site in macrophage polarization, and that this operates in a STAT3-dependent manner.

Promoted Generation of T Helper 1-Like Regulatory T Cells After Transient Middle Cerebral Artery Occlusion in Type-2 Diabetic Mice.

BACKGROUND: Regulatory T cells (Tregs) play a remarkable role in modulating post-ischemic neuroinflammation. However, the characteristics of Tregs in diabetic ischemic stroke remain unknown. METHODS: Transient middle cerebral artery occlusion (MCAO) was conducted on leptin receptor-mutated db/db mice and db/+ mice. The number, cytokine production, and signaling features of Tregs in peripheral blood and ipsilateral hemispheres were evaluated by flow cytometry. Treg plasticity was assessed by the adoptive transfer of splenic Tregs into mice. The effect of ipsilateral macrophages/microglia on Treg plasticity was determined by in vitro co-culture analysis. RESULTS: db/db mice had more infiltrating Tregs in their ipsilateral hemispheres than db/+ mice. Infiltrating Tregs in db/db mice expressed higher transforming growth factor-ß (TGF-ß), interleukin-10 (IL-10), forkhead box P3 (Foxp3), interferon-γ (IFN-γ), tumor necrosis factor-α (TNF-α), and T-box expressed in T cells (T-bet) in comparison to infiltrating Tregs in db/+ mice, suggesting promoted generation of T helper 1 (Th1)-like Tregs in the brains of db/db mice after stroke. The post-ischemic brain microenvironment of db/db mice significantly up-regulated IFN-γ, TNF-α, T-bet, IL-10, and TGF-ß in infiltrating Tregs. Moreover, ipsilateral macrophages/microglia remarkably enhanced the expression of IFN-γ, TNF-α, and T-bet but not IL-10 and TGF-ß in Tregs. db/db macrophages/microglia were more potent in up-regulating IFN-γ, TNF-α, and T-bet than db/+ macrophages/microglia. Interleukin-12 (IL-12) blockage partially abolished the modulatory effect of macrophages/microglia on Tregs. CONCLUSION: The generation of Th1-like Tregs was promoted in the brains of type 2 diabetic mice after stroke. Our study reveals significant Treg plasticity in diabetic stroke.Abbreviations: Foxp3: forkhead box P3; IFN-γ: interferon-γ; IL-10: interleukin-10; IL-12: interleukin-12; MCAO: middle cerebral artery occlusion; PBS: phosphate-buffered saline; STAT1: Signal transducer and activator of transcription 1; STAT5: Signal transducer and activator of transcription 1; T-bet: T-box expressed in T cells; TGF-ß: transforming growth factor-ß; Th1: T helper 1; TNF-α: tumor necrosis factor-α; Tregs: regulatory T cells. Foxp3: forkhead box P3; IFN-γ: interferon-γ; IL-10: interleukin-10; IL-12: interleukin-12; MCAO: middle cerebral artery occlusion; PBS: phosphate-buffered saline; STAT1: Signal transducer and activator of transcription 1; STAT5: Signal transducer and activator of transcription 1; T-bet: T-box expressed in T cells; TGF-ß: transforming growth factor-ß; Th1: T helper 1; TNF-α: tumor necrosis factor-α; Tregs: regulatory T cells.

Clinical predictors of surgical intervention for gastrointestinal magnetic foreign bodies in children.

BACKGROUND/AIMS: To investigate the clinical situation, treatment methods, and clinical predictors of surgical intervention in children with magnetic foreign bodies in the digestive tract. MATERIALS AND METHODS: From January 2019 to June 2022, we retrospectively analyzed the clinical data of 72 children who ingested magnetic foreign bodies inadvertently in our hospital, including their general information, admissions, clinical manifestations, and treatment methods, as well as pertinent literature and statistical data. Following software processing, univariate and multivariate logistic regression analyses were conducted to determine the independent risk factors of this study. RESULTS: In this study, 16 patients (22.2%) were discharged smoothly following conservative treatment and 19 patients (26.4%) were cured by gastroscopy. The remaining 37 patients (51.4%) were underwent surgery, in which 26 cases developed gastrointestinal perforation. There were statistical differences between surgery group and non- surgery group in the days of eating by mistake, clinical manifestations (nausea and vomiting, intermittent abdominal pain, abdominal muscle tension) and movement trajectory by every 24-h radiograph (P < 0.01). Logistic regression analysis showed that intermittent abdominal pain and abdominal muscle tension were independent risk factors for surgical treatment. CONCLUSION: Magnetic foreign bodies seriously endanger children's health. This study offers a single-center basis for the choice of surgical opportunity for intestinal obstruction or perforation caused by magnetic foreign bodies. Clinicians need immediate surgical intervention if the child shows symptoms of abdominal pain or abdominal tension.

Parameter-Free State Estimation Based on Kalman Filter with Attention Learning for GPS Tracking in Autonomous Driving System.

GPS-based maneuvering target localization and tracking is a crucial aspect of autonomous driving and is widely used in navigation, transportation, autonomous vehicles, and other fields.The classical tracking approach employs a Kalman filter with precise system parameters to estimate the state. However, it is difficult to model their uncertainty because of the complex motion of maneuvering targets and the unknown sensor characteristics. Furthermore, GPS data often involve unknown color noise, making it challenging to obtain accurate system parameters, which can degrade the performance of the classical methods. To address these issues, we present a state estimation method based on the Kalman filter that does not require predefined parameters but instead uses attention learning. We use a transformer encoder with a long short-term memory (LSTM) network to extract dynamic characteristics, and estimate the system model parameters online using the expectation maximization (EM) algorithm, based on the output of the attention learning module. Finally, the Kalman filter computes the dynamic state estimates using the parameters of the learned system, dynamics, and measurement characteristics. Based on GPS simulation data and the Geolife Beijing vehicle GPS trajectory dataset, the experimental results demonstrated that our method outperformed classical and pure model-free network estimation approaches in estimation accuracy, providing an effective solution for practical maneuvering-target tracking applications.

Deep Spatio-Temporal Graph Network with Self-Optimization for Air Quality Prediction.

The environment and development are major issues of general concern. After much suffering from the harm of environmental pollution, human beings began to pay attention to environmental protection and started to carry out pollutant prediction research. A large number of air pollutant predictions have tried to predict pollutants by revealing their evolution patterns, emphasizing the fitting analysis of time series but ignoring the spatial transmission effect of adjacent areas, leading to low prediction accuracy. To solve this problem, we propose a time series prediction network with the self-optimization ability of a spatio-temporal graph neural network (BGGRU) to mine the changing pattern of the time series and the spatial propagation effect. The proposed network includes spatial and temporal modules. The spatial module uses a graph sampling and aggregation network (GraphSAGE) in order to extract the spatial information of the data. The temporal module uses a Bayesian graph gated recurrent unit (BGraphGRU), which applies a graph network to the gated recurrent unit (GRU) so as to fit the data's temporal information. In addition, this study used Bayesian optimization to solve the problem of the model's inaccuracy caused by inappropriate hyperparameters of the model. The high accuracy of the proposed method was verified by the actual PM2.5 data of Beijing, China, which provided an effective method for predicting the PM2.5 concentration.

LncRNA ZFPM2-AS1 drives the progression of nasopharyngeal carcinoma via modulating the downstream miR-3612/DTL signaling.

LncRNA ZFPM2-AS1 has been illuminated to function as a carcinogenic driver in various human cancers. Whereas, the role of ZFPM2-AS1 in nasopharyngeal carcinoma (NPC) remains puzzled. To further understand NPC pathogenesis, we investigated the regulatory effects of ZFPM2-AS1 in NPC. Expression analysis for ZFPM2-AS1, miR-3612 and denticleless E3 ubiquitin protein ligase homolog (DTL) mRNA was carried out using real-time quantitative PCR. For the expression analysis of DTL protein, a western blot assay was applied. Cell proliferation was ascertained using the cell counting kit-8 assay and colony formation assay. Cell apoptosis was estimated based on the expression levels of BCL2-Associated X and B-cell lymphoma-2 using western blot assay. To verify the role of ZFPM2-AS1, a Xenograft model was prepared in vivo. The underlying binding between miR-3612 and ZFPM2-AS1 or DTL was validated through dual-luciferase-reporter assay or protein immunoprecipitation assay. ZFPM2-AS1 showed upregulated expression in NPC samples and cells. Meanwhile, ZFPM2-AS1 was mainly located in the cytoplasm. Knockdown of ZFPM2-AS1 restrained NPC cell proliferation and induced apoptosis, as well as suppressed tumorigenesis in animal models. ZFPM2-AS1 targeted miR-3612 whose expression was decreased in NPC samples and cells. Repression of miR-3612 aggravated NPC cell development and largely reversed the functional role of ZFPM2-AS1 silencing on NPC cell growth. MiR-3612 directly interacted with DTL, and DTL expression was upregulated in NPC. Downregulation of DTL blocked NPC cell growth, while miR-3612 inhibition partly abrogated the effects of DTL knockdown. ZFPM2-AS1 knockdown considerably restrained NPC development via targeting the miR-3612/DTL signaling. The study provided new insights to understand NPC pathogenesis.

Response to the Temperature and Solvent Stimulation of MOF Material in a Single-Crystal to Single-Crystal Manner.

Under solvothermal conditions, a three-dimensional mononuclear crystal AQNU-1, {[Co(H2L)(DPD)(H2O)2]·2DMA}n (H2L = 5-(bis(4-carboxybenzyl)amino)isophthalic acid, DPD = 4,4'-(2,5-diethoxy-1,4-phenylene)dipyridine) has been synthesized. The transformations of AQNU-1 to binuclear {[Co2(L)(DPD)1.5(H2O)3]·DMA·H2O}n (AQNU-2) and pentanuclear {[Co5(L)2(DPD)2(OH)2]·2H2O}n (AQNU-3) were realized by double stimulation of temperature and solvent, which were accomplished by single-crystal to single-crystal (SC-SC) reaction.

Buserelin Inhibits the Immunosuppressive Activity of Regulatory T Cells through the Protein Kinase A Signaling in a Central Precocious Puberty Model.

BACKGROUND: Gonadotropin-releasing hormone analogs (GnRHas) are used for treating central precocious puberty (CPP). However, their roles in the regulation of immune cells especially regulatory T cells (Tregs) remains elusive. Therefore, we characterized buserelin-induced phenotypical and functional changes of Tregs. METHODS: A rat CPP model was established followed by administration of buserelin acetate. Flow cytometry was used to evaluate the expression of functional molecules in splenic Tregs. The suppressive activity of Tregs was determined by the suppression assay. GnRHR expression in Tregs was assessed by flow cytometry analysis and Immunoblotting. Normal Tregs were then stimulated and treated with buserelin acetate in vitro. After that, Foxp3 expression, Treg proliferation, and cytokine production were analyzed by flow cytometry. Intracellular signaling was evaluated by Immunoblotting, and Treg function was determined by the suppression assay. RESULTS: After in vivo buserelin treatment, the frequency of splenic Tregs was decreased, with the reduction in the expression of Foxp3, IL-10, and TGF-ß. The suppressive activity of Tregs was weakened. Buserelin down-regulated Foxp3 expression while promoting the expression of RORγt and IL-17 in Tregs through activating the protein kinase A (PKA) pathway in vitro. The PKA inhibitor H-89 abolished the effect of buserelin and enhanced Treg function. CONCLUSION: Buserelin impaired the immunosuppressive activity of Tregs through the PKA signal pathway. Buserelin-induced activation of PKA signaling down-regulated Foxp3 expression while promoting RORγt expression in Tregs, and subsequently weakened Treg function. Our study indicates the necessity of monitoring Treg activity in CPP patients to avoid potential autoimmunity or inflammation.

A Variational Bayesian Deep Network with Data Self-Screening Layer for Massive Time-Series Data Forecasting.

Compared with mechanism-based modeling methods, data-driven modeling based on big data has become a popular research field in recent years because of its applicability. However, it is not always better to have more data when building a forecasting model in practical areas. Due to the noise and conflict, redundancy, and inconsistency of big time-series data, the forecasting accuracy may reduce on the contrary. This paper proposes a deep network by selecting and understanding data to improve performance. Firstly, a data self-screening layer (DSSL) with a maximal information distance coefficient (MIDC) is designed to filter input data with high correlation and low redundancy; then, a variational Bayesian gated recurrent unit (VBGRU) is used to improve the anti-noise ability and robustness of the model. Beijing's air quality and meteorological data are conducted in a verification experiment of 24 h PM2.5 concentration forecasting, proving that the proposed model is superior to other models in accuracy.

NB-LRR genes: characteristics in three Solanum species and transcriptional response to Ralstonia solanacearum in tomato.

MAIN CONCLUSION: NB-LRR genes in the three Solanum species showed specific constitution characteristics and evolved multiple clusters and duplicates. Some genes could respond to biotic stresses such as tomato bacterial wilt. Nucleotide-binding and leucine-rich repeat (NB-LRR, NLR) is a largest resistance gene family in plants, which plays a key role in response to biotic stresses. In this study, NB-LRR genes in cultivated tomato Solanum lycopersicum (Sl) and its wild relatives S. pennellii (Spe) and S. pimpinellifolium (Spi) were analyzed using bioinformatics approaches. In total, 238, 202 and 217 NB-LRR genes of 8 different types were found in Sl, Spe and Spi, respectively. The three species showed similar genomic characteristics. The NB-LRR genes were mainly distributed on chromosomes 4, 5 and 11 and located at the distal zones, forming multiple clusters and tandem duplicates. A large number of homologs appeared through gene expansion, with most Ka/Ks values being less than 1, indicating that purifying selection had occurred in evolution. These genes were mainly expressed in root and could respond to different biotic stresses. RT-qPCR analysis revealed that SlNLR genes could respond to tomato bacterial wilt, with SlNLR1 probably involved in the resistance response, whereas others being the opposite. The transcription factors (TFs) and interaction proteins that regulate target genes were mainly Dof, NAC and MYB families and kinases. The results provide a basis for the isolation and application of related genes in plant disease resistance breeding.

Multi-Channel Fusion Classification Method Based on Time-Series Data.

Time-series data generally exists in many application fields, and the classification of time-series data is one of the important research directions in time-series data mining. In this paper, univariate time-series data are taken as the research object, deep learning and broad learning systems (BLSs) are the basic methods used to explore the classification of multi-modal time-series data features. Long short-term memory (LSTM), gated recurrent unit, and bidirectional LSTM networks are used to learn and test the original time-series data, and a Gramian angular field and recurrence plot are used to encode time-series data to images, and a BLS is employed for image learning and testing. Finally, to obtain the final classification results, Dempster-Shafer evidence theory (D-S evidence theory) is considered to fuse the probability outputs of the two categories. Through the testing of public datasets, the method proposed in this paper obtains competitive results, compensating for the deficiencies of using only time-series data or images for different types of datasets.

The New Trend of State Estimation: From Model-Driven to Hybrid-Driven Methods.

State estimation is widely used in various automated systems, including IoT systems, unmanned systems, robots, etc. In traditional state estimation, measurement data are instantaneous and processed in real time. With modern systems' development, sensors can obtain more and more signals and store them. Therefore, how to use these measurement big data to improve the performance of state estimation has become a hot research issue in this field. This paper reviews the development of state estimation and future development trends. First, we review the model-based state estimation methods, including the Kalman filter, such as the extended Kalman filter (EKF), unscented Kalman filter (UKF), cubature Kalman filter (CKF), etc. Particle filters and Gaussian mixture filters that can handle mixed Gaussian noise are discussed, too. These methods have high requirements for models, while it is not easy to obtain accurate system models in practice. The emergence of robust filters, the interacting multiple model (IMM), and adaptive filters are also mentioned here. Secondly, the current research status of data-driven state estimation methods is introduced based on network learning. Finally, the main research results for hybrid filters obtained in recent years are summarized and discussed, which combine model-based methods and data-driven methods. This paper is based on state estimation research results and provides a more detailed overview of model-driven, data-driven, and hybrid-driven approaches. The main algorithm of each method is provided so that beginners can have a clearer understanding. Additionally, it discusses the future development trends for researchers in state estimation.

Magnitude and associated factors of perceived stress and its consequence among undergraduate students of Salale University, Ethiopia: cross-sectional study.

Excessive stress may have a negative impact on students' performance and learning ability. The aim of this study is to assess the magnitude and associated factors of perceived stress and its consequences among undergraduate students at Salale University, Ethiopia. A self-administered cross-sectional study has been conducted among 421 students of Salale University from April 1st to May 30th, 2018. Multiple linear regressions and Spearman's rank correlation were applied. The overall response rate is 95.49 %. The mean perceived stress score (PSS-14) was 29.97 (standard deviation =7.48). Spearman correlation test has shown that perceived stress is significantly but negatively correlated with grade point average [rs = -0.25 (-0.334 - -0.153)] and year of studies [rs = -0.13 (-0.232 - -0.032)]. Increased perceived stress indices are significantly associated with female gender (P < 0.001), grade point average (P < 0.01), academic stressors (P < 0.01), and psychosocial stressors (P < 0.01). Mean of PSS-14 was high among health science students (31.42 ± 9.37) than agricultural (30.78 ± 7.69) and business students (28.04 ± 5.43), however, there were no statistically significant differences. These findings are sufficient to allow a large-scale study to further help better understanding the stress-vulnerability factors of undergraduate students.

Distributed Deep Fusion Predictor for a Multi-Sensor System Based on Causality Entropy.

Trend prediction based on sensor data in a multi-sensor system is an important topic. As the number of sensors increases, we can measure and store more and more data. However, the increase in data has not effectively improved prediction performance. This paper focuses on this problem and presents a distributed predictor that can overcome unrelated data and sensor noise: First, we define the causality entropy to calculate the measurement's causality. Then, the series causality coefficient (SCC) is proposed to select the high causal measurement as the input data. To overcome the traditional deep learning network's over-fitting to the sensor noise, the Bayesian method is used to obtain the weight distribution characteristics of the sub-predictor network. A multi-layer perceptron (MLP) is constructed as the fusion layer to fuse the results from different sub-predictors. The experiments were implemented to verify the effectiveness of the proposed method by meteorological data from Beijing. The results show that the proposed predictor can effectively model the multi-sensor system's big measurement data to improve prediction performance.