Environmental suitability of Yersinia pestis and the spatial dynamics of plague in the Qinghai Lake region, China.

Plague, a highly infectious disease caused by Yersinia pestis, has killed millions of people in history and is still active in the natural foci of the world nowadays. Understanding the spatiotemporal patterns of plague outbreaks in history is critically important, as it may help facilitate the prevention and control for potential future outbreaks. This study's objective was to estimate the effect of the topography, vegetation, climate, and other environmental factors on the Y. pestis ecological niche. A maximum entropy algorithm spatially modelled plague occurrence data from 2004-2018 and the environmental variables to evaluate the contribution of the variables to the distribution of Y. pestis. Our results found that the average minimum temperature in September (-8 °C to +5 °C) and the sheep population density (250 sheep per km2) were influential in characterising the niche. The rim of Qinghai Lake showed more favourable conditions for Y. pestis presence than other areas within the study area. Identifying various factors will assist any future modelling efforts. Our suitability map identifies hotspots and will help public health officials in resource allocation in their quest to abate future plague outbreaks.

Effects of a high-phosphorus diet on the gut microbiota in CKD rats.

OBJECTIVE: To investigate whether high-phosphorus diets alter gut microbiota in healthy rats and chronic kidney disease (CKD) rats. METHODS: In this 4-week randomized controlled trial, healthy rats and CKD rats were fed a regular-phosphorus (Pi: 0.8%) and high-phosphorus (Pi: 1.2%) diet. The subjects were divided into four groups: sham-group rats with regular-phosphorus diet intervention (CTL group), sham-group rats with high-phosphorus diet intervention (CTLP group), CKD model rats with regular-phosphorus diet intervention (CKD group), and CKD model rats with high-phosphorus diet intervention (CKDP group). The V3-V4 region of the 16S rRNA gene was sequenced to study the effect of a high-phosphorus diet on gut microbiota. RESULTS: A high-phosphorus intervention increased systolic blood pressure (SBP) and parathyroid hormone (PTH) in CTL and CKD rats but did not change serum creatinine and 25(OH)D levels. After the high-phosphorus diet, serum phosphate and fibroblast growth factor 23 (FGF23) increased in the CKDP group compared with the CKD group. The gut microbiota was significantly altered after intervention with a high-phosphorus diet in CTL and CKD group rats. A high-phosphorus diet reduced the Shannon index values of gut microbiota in all rats. The Chao1 and Ace indexes were decreased in the CTL group after high-phosphorus diet intervention. Some microbial genera were elevated significantly after high-phosphorus dietary intervention, such as Blautia and Allobaculum. The main bacteria linked to SBP and FGF23 also correlated directly with creatinine. After high-phosphorus diet intervention, the bacteria Prevotella were positively related to SBP in CTLP and CKDP groups. CONCLUSIONS: High-phosphorus diets were associated with adverse changes in gut microbiota and elevated SBP, which may have adverse consequences for long-term health outcomes.

Research on the Node Importance of a Weighted Network Based on the K-Order Propagation Number Algorithm.

To describe both the global and local characteristics of a network more comprehensively, we propose the weighted K-order propagation number (WKPN) algorithm to extract the disease propagation based on the network topology to evaluate the node importance. Each node is set as the source of infection, and the total number of infected nodes is defined as the K-order propagation number after experiencing the propagation time K. The simulation of the symmetric network with bridge nodes indicated that the WKPN algorithm was more effective for evaluation of the algorithm features. A deliberate attack strategy, which indicated an attack on the network according to the node importance from high to low, was employed to evaluate the WKPN algorithm in real networks. Compared with the other methods tested, the results demonstrate the applicability and advancement that a lower number of nodes, with a higher importance calculated by the K-order propagation number algorithm, has to achieve full damage to the network structure.

[Classification of emotional brain networks based on weighted K-order propagation number].

Electroencephalography (EEG) signals are strongly correlated with human emotions. The importance of nodes in the emotional brain network provides an effective means to analyze the emotional brain mechanism. In this paper, a new ranking method of node importance, weighted K-order propagation number method, was used to design and implement a classification algorithm for emotional brain networks. Firstly, based on DEAP emotional EEG data, a cross-sample entropy brain network was constructed, and the importance of nodes in positive and negative emotional brain networks was sorted to obtain the feature matrix under multi-threshold scales. Secondly, feature extraction and support vector machine (SVM) were used to classify emotion. The classification accuracy was 83.6%. The results show that it is effective to use the weighted K-order propagation number method to extract the importance characteristics of brain network nodes for emotion classification, which provides a new means for feature extraction and analysis of complex networks.

The Effect of Mecp2 on Heart Failure.

BACKGROUND/AIMS: Heart failure is the end result of various kinds of cardiovascular diseases. It has a high rate of morbidity and mortality. This article aims to determine the effect of MeCP2, a key epigenetic regulator, on heart failure. METHODS: The genes associated with heart failure were selected and analyzed using Gene Ontology (GO) term analysis and protein-protein interaction (PPI) network analysis. Significantly up- or downregulated genes in a heart failure animal model were identified, and the genes that had the same or opposite alteration trends as MeCP2 were also recognized. Eighteen hub genes were picked based on topological parameters, and then aberrantly expressed genes with MeCP2 overexpression or knockout were analyzed by GO term, KEGG pathway and PPI analyses. RESULTS: MeCP2 was downregulated in the heart failure animal model. Through comparison and alignment, 10 dysregulated genes were selected from the 18 hub genes (JAK1, SETD1B, HRC, TTN, LYZ2, TPM3, MYH11, MYH6, ALOX5AP, DECR1). These genes were mainly enriched in cytoskeletal regulation mediated by Rho GTPase and inflammation mediated by chemokine and cytokine signaling pathways. CONCLUSIONS: These dysregulated genes provide a better understanding of the underlying mechanisms of the effect of MeCP2 on heart failure and might be used as targets and prognostic markers of heart failure.

Quantitative study of the influence of swimming therapy on osteoporosis rat models based on synchrotron radiation computed tomogaphy.

Osteoporosis is a bone disease with a variety of causes, leading to bone pain and fragility to fracture. Major treatment methods include nutrition therapy, exercise therapy, drug therapy and surgical treatment, among which exercise therapy, such as swimming, is the most effective. To investigate the optimal swimming therapy regime for postmenopausal women, the effects of eight weeks of different intensity swimming exercises were studied in rat models. After the swimming program, lumbar vertebrae were dissected from all the rats and scanned by synchrotron radiation computed tomography (SRCT). Histomorphometry analysis and finite-element analysis were carried out on the trabecular structure of the L4 lumbar based on the acquired SRCT slices. Histomorphometry analysis showed that swimming can alleviate the decrease in bone strength induced by estrogen deficiency, and moderate-intensity swimming was found to have the most significant effect.

Indirect Measurement of Rotor Dynamic Imbalance for Control Moment Gyroscopes via Gimbal Disturbance Observer.

The high-precision speed control of gimbal servo systems is the key to generating high-precision torque for control moment gyroscopes (CMGs) in spacecrafts. However, the control performance of gimbal servo systems may be degraded significantly by disturbances, especially a dynamic imbalance disturbance with the same frequency as the high-speed rotor. For assembled CMGs, it is very difficult to measure the rotor imbalance directly by using a dynamic balancing machine. In this paper, a gimbal disturbance observer is proposed to estimate the dynamic imbalance of the rotor assembled in the CMG. First, a third-order dynamical system is established to describe the disturbance dynamics of the gimbal servo system, in which the rotor dynamic imbalance torque along the gimbal axis and the other disturbances are modeled to be periodic and bounded, respectively. Then, the gimbal disturbance observer is designed for the third-order dynamical system by using the total disturbance as a virtual measurement. Since the virtual measurement is derived from the inverse dynamics of the gimbal servo system, the information of the rotor dynamic imbalance can be obtained indirectly only using the measurements of gimbal speed and three-phase currents. Semi-physical experimental results demonstrate the effectiveness of the observer by using a CMG simulator.

Fractalkine/CX3CR1 axis modulated the development of pancreatic ductal adenocarcinoma via JAK/STAT signaling pathway.

Pancreatic ductal adenocarcinoma (PDAC) is a fatal malignancy with an estimated 5 year survival rate of approximately 5% of all stages combined. High potential of PDAC metastasis is a leading cause for high mortality and poor prognosis. The majority of patients present with distant metastasis at diagnosis. Fractalkine (FKN) is recognized as a chemokine and a specific ligand of CX3CR1. It has been reported that FKN/CX3CR1 system was upregulated in many types of solid tumors. However, role of FKN/CX3CR1 in PDAC development remains unclear. In the current investigation, we found that FKN and CX3CR1 expression was significantly increased in PDAC tissues, especially in the metastatic samples, and was highly-correlated with severity of PDAC. Ectopic expression of FKN promoted the proliferation and migration of PDAC, while knockdown of CX3CR1 reversed the function of FKN. In addition, PDAC cells with FKN-deficiency showed impaired proliferation and migration activity. The underlying mechanism is that FKN/CX3CR1 activated JAK/STAT signaling, which in turn regulated cell growth. Consistently, in vivo tumorigenesis assay validated the regulatory role of FKN/CX3CR1 in PDAC growth. Our investigation helped understanding the pathogenesis of PDAC occurrence, and demonstrated critical role of FKN/CX3CR1 in PDAC development.

Performance evaluation of three automated identification systems in detecting carbapenem-resistant Enterobacteriaceae.

BACKGROUND: Carbapenem-resistant Enterobacteriaceae (CRE) is prevalent around the world. Rapid and accurate detection of CRE is urgently needed to provide effective treatment. Automated identification systems have been widely used in clinical microbiology laboratories for rapid and high-efficient identification of pathogenic bacteria. However, critical evaluation and comparison are needed to determine the specificity and accuracy of different systems. The aim of this study was to evaluate the performance of three commonly used automated identification systems on the detection of CRE. METHODS: A total of 81 non-repetitive clinical CRE isolates were collected from August 2011 to August 2012 in a Chinese university hospital, and all the isolates were confirmed to be resistant to carbapenems by the agar dilution method. The potential presence of carbapenemase genotypes of the 81 isolates was detected by PCR and sequencing. Using 81 clinical CRE isolates, we evaluated and compared the performance of three automated identification systems, MicroScan WalkAway 96 Plus, Phoenix 100, and Vitek 2 Compact, which are commonly used in China. To identify CRE, the comparator methodology was agar dilution method, while the PCR and sequencing was the comparator one to identify CPE. RESULTS: PCR and sequencing analysis showed that 48 of the 81 CRE isolates carried carbapenemase genes, including 23 (28.4 %) IMP-4, 14 (17.3 %) IMP-8, 5 (6.2 %) NDM-1, and 8 (9.9 %) KPC-2. Notably, one Klebsiella pneumoniae isolate produced both IMP-4 and NDM-1. One Klebsiella oxytoca isolate produced both KPC-2 and IMP-8. Of the 81 clinical CRE isolates, 56 (69.1 %), 33 (40.7 %) and 77 (95.1 %) were identified as CRE by MicroScan WalkAway 96 Plus, Phoenix 100, and Vitek 2 Compact, respectively. The sensitivities/specificities of MicroScan WalkAway, Phoenix 100 and Vitek 2 were 93.8/42.4 %, 54.2/66.7 %, and 75.0/36.4 %, respectively. CONCLUSIONS: The MicroScan WalkAway and Viteck2 systems are more reliable in clinical identification of CRE, whereas additional tests are required for the Pheonix 100 system. Our study provides a useful guideline for using automated identification systems for CRE identification.

SIRT1 Protects Against Oxidative Stress-Induced Endothelial Progenitor Cells Apoptosis by Inhibiting FOXO3a via FOXO3a Ubiquitination and Degradation.

Cell loss due to apoptosis induced by oxidative stress is a major hurdle for endothelial progenitor cells (EPCs)-based therapy. Sirtuin 1 (SIRT1) plays important roles in many pathophysiological processes by deacetylating various substrates, including forkhead transcription factor (FOXO). However, after deacetylation, the fate of FOXO protein remains to be explored. In the present study, we investigated whether SIRT1 exerted a protective effect on hydrogen peroxide (H(2)O(2))-induced EPCs apoptosis and, if so, what the underlying mechanism might be. EPCs were isolated and obtained from human umbilical cord blood by density gradient centrifugation and identified by morphology, tube formation ability, cell surface markers, and the ability to take up acetylated low-density lipoprotein (Dil-Ac-LDL) and bind ulex europaeus agglutinin 1 (FITC-UEA-1). Immunofluorescence showed that SIRT1 is localized in the nucleus of EPCs in the presence or absence of H(2)O(2). SIRT1 protein level in EPCs was increased by the treatment with H(2)O(2) for 24 h. Incubation of EPCs with H(2)O(2) dose dependently induced EPCs apoptosis. SIRT1 overexpression reduced the rate of EPCs apoptosis induced by H(2)O(2), whereas SIRT1 downregulation and EX527, a specific SIRT1 inhibitor, exerted the opposite effect. SIRT1 overexpression decreased the total FOXO3a protein expression, whereas SIRT1 downregulation and EX527 increased the amount of FOXO3a protein. SIRT1 reduced FOXO3a transcriptional activity according to Bim expression. Co-immunoprecipitation assay showed that SIRT1 could bind to FOXO3a, reduce its acetylation level and increase its ubiquitination level. To sum up, our work demonstrated that SIRT1 had a pivotally protective role in the regulation of EPCs apoptosis induced by H(2)O(2) and that SIRT1 protected against apoptosis by inhibiting FOXO3a via FOXO3a ubiquitination and subsequent degradation.

Modulation of STAT3 and STAT5 activity rectifies the imbalance of Th17 and Treg cells in patients with acute coronary syndrome.

The signal transducer and activator of transcription (STAT) activity plays an important role in the differentiation and imbalance of Th17 and Treg cells in acute coronary syndrome (ACS) patients. We determined that the basal STAT3 phosphorylation level was significantly increased and exhibited a positive relationship with Th17 cells but was negatively correlated with Treg cells in ACS patients. Opposite effects were observed for STAT5 activity. Using the pharmaceutical inhibitor TG101348 or knockdown of STAT3 reduced the number of Th17 cells while promoting the number and function of Treg cells via the Janus kinase2 (JAK2)/STAT3 pathway in ACS patients. Significantly more STAT5 bound to the Foxp3 locus when STAT3 was knocked down, and overexpression of STAT5 led to an increased number of Treg cells but a decreased number of Th17 cells in ACS patients. Our findings demonstrate that modulation of STAT3/STAT5 activity rectifies the imbalance of Th17/Treg cells in ACS patients.

[Study on Steady State Visual Evoked Potential Target Detection Based on Two-dimensional Ensemble Empirical Mode Decomposition].

Brain computer interface is a control system between brain and outside devices by transforming electroencephalogram (EEG) signal. The brain computer interface system does not depend on the normal output pathways, such as peripheral nerve and muscle tissue, so it can provide a new way of the communication control for paralysis or nerve muscle damaged disabled persons. Steady state visual evoked potential (SSVEP) is one of non-invasive EEG signals, and it has been widely used in research in recent years. SSVEP is a kind of rhythmic brain activity simulated by continuous visual stimuli. SSVEP frequency is composed of a fixed visual stimulation frequency and its harmonic frequencies. The two-dimensional ensemble empirical mode decomposition (2D-EEMD) is an improved algorithm of the classical empirical mode decomposition (EMD) algorithm which extended the decomposition to two-dimensional direction. 2D-EEMD has been widely used in ocean hurricane, nuclear magnetic resonance imaging (MRI), Lena image and other related image processing fields. The present study shown in this paper initiatively applies 2D-EEMD to SSVEP. The decomposition, the 2-D picture of intrinsic mode function (IMF), can show the SSVEP frequency clearly. The SSVEP IMFs which had filtered noise and artifacts were mapped into the head picture to reflect the time changing trend of brain responding visual stimuli, and to reflect responding intension based on different brain regions. The results showed that the occipital region had the strongest response. Finally, this study used short-time Fourier transform (STFT) to detect SSVEP frequency of the 2D-EEMD reconstructed signal, and the accuracy rate increased by 16%.

Neuron-glial communication mediated by TNF-α and glial activation in dorsal root ganglia in visceral inflammatory hypersensitivity.

Communication between neurons and glia in the dorsal root ganglia (DRG) and the central nervous system is critical for nociception. Both glial activation and proinflammatory cytokine induction underlie this communication. We investigated whether satellite glial cell (SGC) and tumor necrosis factor-α (TNF-α) activation in DRG participates in a 2,4,6-trinitrobenzene sulfonic acid (TNBS)-induced rat model of visceral hyperalgesia. In TNBS-treated rats, TNF-α expression increased in DRG and was colocalized to SGCs enveloping a given neuron. These SGCs were activated as visualized under electron microscopy: they had more elongated processes projecting into the connective tissue space and more gap junctions. When nerves attached to DRG (L6-S1) were stimulated with a series of electrical stimulations, TNF-α were released from DRG in TNBS-treated animals compared with controls. Using a current clamp, we noted that exogenous TNF-α (2.5 ng/ml) increased DRG neuron activity, and visceral pain behavioral responses were reversed by intrathecal administration of anti-TNF-α (10 µg·kg(-1)·day(-1)). Based on our findings, TNF-α and SGC activation in neuron-glial communication are critical in inflammatory visceral hyperalgesia.

Joint extraction model of entity relations based on decomposition strategy.

Named entity recognition and relation extraction are two important fundamental tasks in natural language processing. The joint entity-relationship extraction model based on parameter sharing can effectively reduce the impact of cascading errors on model performance by performing joint learning of entities and relationships in a single model, but it still cannot essentially get rid of the influence of pipeline models and suffers from entity information redundancy and inability to recognize overlapping entities. To this end, we propose a joint extraction model based on the decomposition strategy of pointer mechanism is proposed. The joint extraction task is divided into two parts. First, identify the head entity, utilizing the positive gain effect of the head entity on tail entity identification.Then, utilize a hierarchical model to improve the accuracy of the tail entity and relationship identification. Meanwhile, we introduce a pointer model to obtain the joint features of entity boundaries and relationship types to achieve boundary-aware classification. The experimental results show that the model achieves better results on both NYT and WebNLG datasets.

Progestin effects on cell proliferation pathways in the postmenopausal mammary gland.

INTRODUCTION: Menopausal hormone therapies vary widely in their effects on breast cancer risk, and the mechanisms underlying these differences are unclear. The primary goals of this study were to characterize the mammary gland transcriptional profile of estrogen + progestin therapy in comparison with estrogen-alone or tibolone and investigate pathways of cell proliferation in a postmenopausal primate model. METHODS: Ovariectomized female cynomolgus macaque monkeys were randomized into the following groups: placebo (Con), oral conjugated equine estrogens (CEE), CEE with medroxyprogesterone acetate (MPA) (CEE + MPA), and tibolone given at a low or high dose (Lo or Hi Tib). All study treatment doses represented human clinical dose equivalents and were administered in the diet over a period of 2 years. RESULTS: Treatment with CEE + MPA had the greatest effect on global mRNA profiles and markers of mammary gland proliferation compared to CEE or tibolone treatment. Changes in the transcriptional patterns resulting from the addition of MPA to CEE were related to increased growth factors and decreased estrogen receptor (ER) signaling. Specific genes induced by CEE + MPA treatment included key members of prolactin receptor (PRLR)/signal transducer and activator of transcription 5 (STAT5), epidermal growth factor receptor (EGFR), and receptor activator of nuclear factor kappa B (RANK)/receptor activator of nuclear factor kappa B ligand (RANKL) pathways that were highly associated with breast tissue proliferation. In contrast, tibolone did not affect breast tissue proliferation but did elicit a mixed pattern of ER agonist activity. CONCLUSION: Our findings indicate that estrogen + progestin therapy results in a distinct molecular profile compared to estrogen-alone or tibolone therapy, including upregulation of key growth factor targets associated with mammary carcinogenesis in mouse models. These changes may contribute to the promotional effects of estrogen + progestin therapy on breast cancer risk.

Hydrogen peroxide induced impairment of endothelial progenitor cell viability is mediated through a FoxO3a dependant mechanism.

OBJECTIVES: Increased oxidative stress has been suggested to contribute to the functional impairment of endothelial progenitor cells (EPCs). The Forkhead box O transcription factors (FoxOs) are critical regulators involved in various cellular processes including cell apoptosis. Here, we investigated whether FoxOs are required in oxidative stress induced EPC apoptosis. METHODS AND RESULTS: EPCs were cultured from cord blood derived mononuclear cells and treated with hydrogen peroxide (H2O2) for induction of oxidative stress. Incubation with H2O2 dose dependently reduced viability and increased apoptosis in EPCs. Western blotting showed that EPCs predominantly expressed FoxO3a and the expression was markedly increased upon H2O2 treatment. Transduction with adenoviral vectors expressing either a wide-type or a non-phosphorylatable, constitutively active mutant of FoxO3a led to further increased apoptosis of EPCs after H2O2 treatment. Conversely, FoxO3a silencing rescued EPCs from these H2O2 induced deleterious effects. Overexpression of FoxO3a also increased the level of the pro-apoptotic protein Bim, whereas FoxO3a silencing downregulated H2O2 induced Bim expression. Furthermore, Matrigel assay demonstrated that FoxO3a overexpression significantly impaired the tube forming ability of EPCs, whereas its silencing completely protected EPCs from H2O2 induced decrease of capillary formation. CONCLUSIONS: These data suggest that oxidative stress induced impairment of EPC survival is mediated through a FoxO3a dependant mechanism, possibly by transcriptional regulation of Bim. Our data indicate FoxO3a as a potential therapeutic target for improvement of EPC number and function in patients with ischemic heart disease.

A multi-head residual connection GCN for EEG emotion recognition.

Electroencephalography (EEG) emotion recognition is a crucial aspect of human-computer interaction. However, conventional neural networks have limitations in extracting profound EEG emotional features. This paper introduces a novel multi-head residual graph convolutional neural network (MRGCN) model that incorporates complex brain networks and graph convolution networks. The decomposition of multi-band differential entropy (DE) features exposes the temporal intricacy of emotion-linked brain activity, and the combination of short and long-distance brain networks can explore complex topological characteristics. Moreover, the residual-based architecture not only enhances performance but also augments classification stability across subjects. The visualization of brain network connectivity offers a practical technique for investigating emotional regulation mechanisms. The MRGCN model exhibits average classification accuracies of 95.8% and 98.9% for the DEAP and SEED datasets, respectively, highlighting its excellent performance and robustness.

Exosome and lipid metabolism-related genes in pancreatic adenocarcinoma: a prognosis analysis.

OBJECTIVE: The purpose of the study was to investigate the role of exosome and lipid metabolism-related genes (EALMRGs) mRNA levels in the diagnosis and prognosis of Pancreatic Adenocarcinoma (PAAD). METHODS: The mRNA expression pattern of PAAD and pan-cancers with prognostic data were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. EALMRGs were acquired from GeneCards and MSigDB database after merging and deduplication. Prognostic EALMRGs were screened through univariate COX regression analysis, and a prognostic model was constructed based on these genes by least absolute shrinkage and selection operator (LASSO) regression. The prognostic value of EALMRGs was then validated in pan-cancer data. The time characteristics ROC curve analysis was performed to evaluate the effectiveness of the prognostic genes. RESULTS: We identified 5 hub genes (ABCB1, CAP1, EGFR, PPARG, SNCA) according to high and low-risk groups of prognoses. The risk formula was verified in three other cohort of pancreatic cancer patients and was explored in pan-cancer data. Additionally, T cell and dendritic cell infiltration was significantly increased in low-risk group. The expression of the 5 hub genes was also identified in single-cell sequencing data of pancreatic cancer with pivotal pathways. Additionally, functional enrichment analysis based on pancreatic cancer data in pancreatic cancer showed that protein serine/threonine kinase activity, focal adhesion, actin binding, cell-substrate junction, organic acid transport, and regulation of transporter activity were significant related to the expression of genes in EALMRGs. CONCLUSIONS: Our risk formula shows potential prognostic value in multiple cancers and manifest pivotal alterations in immune infiltration and biological pathway in pancreatic cancer.