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Disseminated infection caused by Nocardia farcinica with primary nephrotic syndrome is exceedingly rare. A 66-year-old female visited the outpatient department due to fever and fatigue who had been diagnosed as membranous nephropathy and with a long-term prednisone and immunosuppressive therapy. After lung biopsy for many times, culture from space-occupying lesion of the right lung and species identification by mass spectrometry-based methods (MALDI-TOF) revealed Nocardia farcinica. By imaging examination, space-occupying lesions from the lungs, brain, abdominal cavity and kidney were found. After 2 weeks of meropenem intravenous and up to 6 months of trimethoprim-sulfamethoxazole (TMP-SMX) therapy, our patient has remained relapse-free at that time of writing. Disseminated infection caused by Nocardia farcinica is usually subacute with complex clinical manifestations. In addition, it can be easily confused with diseases such as tumor and mycobacterial infection, and lead to fatal consequences. Therefore, we hope that we can remind clinicians considering by discussing common features of disseminated Nocardia farcinica infection.

Objectives The different etiology of HF has different prognostic risk factors. Prognosis assessment of ICM and NICM has important clinical value. This study is aimed to explore the predicting factors for ICM and NICM. Methods 1082 HFrEF patients were retrospectively enrolled from Jan. 01, 2016 to Dec. 31, 2017. On Jan. 31, 2019, 873 patients were enrolled for analysis excluding incomplete, unfollowed, and unexplained data. The patients were divided into ischemic and non-ischemic group. The differences in clinical characteristics and long-term prognosis between the two groups were analyzed, and multivariate Cox analysis was used to predict the respective all-cause mortality, SCD and rehospitalization of CHF. Results 873 patients aged 64(53,73) were divided into two groups: ICM (403, 46.16%) and NICM. At the end, 203 died (111 in ICM, 54.68%), of whom 87 had SCD (53 in ICM, 60.92%) and 269 had rehospitalization for HF(134 in ICM, 49.81%). Independent risk factors affecting all-cause mortality in ICM: DM, previous hospitalization of HF, age, eGFR, LVEF; for SCD: PVB, eGFR, Hb, revascularization; for readmission of HF: low T3 syndrome, PVB, DM, previous hospitalization of HF, eGFR. Otherwise; factors affecting all-cause mortality in NICM: NYHA III-IV, paroxysmal AF/AFL, previous hospitalization of HF, β-blocker; for SCD: low T3 syndrome, PVB, nitrates, sodium, β-blocker; for rehospitalization of HF: paroxysmal AF/AFL, previous admission of HF, LVEF. Conclusions Both all-cause mortality and SCD in ICM is higher than that in NICM. Different etiologies of CHF have different risk factors affecting the prognosis.

Seleno-short-chain chitosan (SSCC) is a derivative of chitosan. In the present study, we sought to investigate the underlying antitumor mechanism of SSCC on human gastric cancer BGC-823 cells in vitro. MTT assay suggested that SSCC exhibited a dose-dependent inhibitory effect on the proliferation of BGC-823 cells. We found the SSCC-treated cells showed typical morphological characteristics of apoptosis in a dose dependent manner by observing on microscope. Annexin V-FITC/PI double staining and cell cycle assay identified that SSCC could induce BGC-823 cells apoptosis by triggering G2/M phase arrest. Our research provided the first evidence that SSCC could effectively induce the apoptosis of BGC-823 cells via an intrinsic mitochondrial pathway, as indicated by inducing the disruption of mitochondrial membrane potential (MMP), the excessive accumulation of reactive oxidative species (ROS), the increase of Bax/Bcl-2 ratio and the activation of caspase 3, caspase 9 and cytochrome C (Cyt-C) in BGC-823 cells. These combined results clearly indicated that SSCC could induce BGC-823 cells apoptosis by the involvement of mitochondrial signaling pathway, which provided precise experimental evidence for SSCC as a potential agent in the prevention and treatment of human gastric cancer.

Background Colon adenocarcinoma (COAD) patients who develop recurrence have poor prognosis. Our study aimed to establish effective prognosis prediction model based on competing endogenous RNAs (ceRNAs) for recurrence of COAD. Methods COAD expression profilings downloaded from The Cancer Genome Atlas (TCGA) were used as training dataset, and expression profilings of GSE29623 retrieved from Gene Expression Omnibus (GEO) were set as validation dataset. Differentially expressed RNAs (DERs) between non-recurrent and recurrent specimens in training dataset were screened, and optimum prognostic signature DERs were revealed to establish prognostic score (PS) model. Kaplan-Meier survival analysis was conducted for PS model, and GEO dataset was used for validation. Prognosis prediction efficiencies were evaluated by area under curve (AUC) and C-index. Meanwhile, ceRNA regulatory network was constructed by using signature mRNAs, lncRNAs and miRNAs. Results We identified 562 DERs including 42 lncRNAs, 36 miRNAs, and 484 mRNAs. PS prediction model, consisting of 17 optimum prognostic signature DERs, showed that high risk group had significantly poorer prognosis (5-year AUC = 0.951, C-index = 0.788), which also validated in GSE29623. Prognosis prediction model incorporating multi-RNAs with pathologic distant metastasis (M) and pathologic primary tumor (T) (5-year AUC = 0.969, C-index = 0.812) had better efficiency than clinical prognosis prediction model (5-year AUC = 0.712, C-index = 0.680). In the constructed ceRNA regulatory network, lncRNA NCBP2-AS1 could interact with hsa-miR-34c and hsa-miR-363, and lncRNA LINC00115 could interact with hsa-miR-363 and hsa-miR-4709. SIX4, GRAP, NKAIN4, MMAA, and ERVMER34–1 are regulated by hsa-miR-4709. Conclusion Prognosis prediction model incorporating multi-RNAs with pathologic M and pathologic T may have great value in COAD prognosis prediction.

Osteoarthritis (OA) is the most common joint disease type and is accompanied by varying degrees of functional limitation. Both hyaluronic acid (HA) joint injections and pain relievers are efficient treatments for early-stage osteoarthritis. However, for the decomposition by hyaluronidase and free radicals in the knee joint, HA injection treatment has limited effect time. The cerium oxide nanoparticles (CeO2) is a long time free radical scavenger. CeO2 combined with HA expected, may extend the HA decomposition time and have a positive effect on osteoarthritis therapy. In this study, CeO2 was successfully synthesized using the hydrothermal method with a particle size of about 120 nm, which possessed excellent dispersibility in the culture medium. The in vitro OA model was established by cell treated with H2O2 for 30 min. Our study found that the inhibition of chondrocyte proliferation dose-dependently increased with H2O2 concentration but was significantly decreased by supplementation of cerium oxide nanoparticles. COL2a1 and ACAN gene expression in chondrocytes was significantly decreased after H2O2 treatment, however, the tendency was changed after cerium oxide nanoparticles treatment, which suggested that damaged chondrocytes were protected against oxidative stress. These findings suggest that cerium oxide nanoparticles are potential therapeutic applications in the early stage of OA.

Background Pathogenesis and diagnostic biomarkers for diseases can be discovered by metabolomic profiling of human fluids. If the various types of coronary artery disease (CAD) can be accurately characterized by metabolomics, effective treatment may be targeted without using unnecessary therapies and resources. Objectives The authors studied disturbed metabolic pathways to assess the diagnostic value of metabolomics-based biomarkers in different types of CAD. Methods A cohort of 2,324 patients from 4 independent centers was studied. Patients underwent coronary angiography for suspected CAD. Groups were divided as follows: normal coronary artery (NCA), nonobstructive coronary atherosclerosis (NOCA), stable angina (SA), unstable angina (UA), and acute myocardial infarction (AMI). Plasma metabolomic profiles were determined by liquid chromatography–quadrupole time-of-flight mass spectrometry and were analyzed by multivariate statistics. Results We made 12 cross-comparisons to and within CAD to characterize metabolic disturbances. We focused on comparisons of NOCA versus NCA, SA versus NOCA, UA versus SA, and AMI versus UA. Other comparisons were made, including SA versus NCA, UA versus NCA, AMI versus NCA, UA versus NOCA, AMI versus NOCA, AMI versus SA, significant CAD (SA/UA/AMI) versus nonsignificant CAD (NCA/NOCA), and acute coronary syndrome (UA/AMI) versus SA. A total of 89 differential metabolites were identified. The altered metabolic pathways included reduced phospholipid catabolism, increased amino acid metabolism, increased short-chain acylcarnitines, decrease in tricarboxylic acid cycle, and less biosynthesis of primary bile acid. For differential diagnosis, 12 panels of specific metabolomics-based biomarkers provided areas under the curve of 0.938 to 0.996 in the discovery phase (n = 1,086), predictive values of 89.2% to 96.0% in the test phase (n = 933), and 85.3% to 96.4% in the 3-center external sets (n = 305). Conclusions Plasma metabolomics are powerful for characterizing metabolic disturbances. Differences in small-molecule metabolites may reflect underlying CAD and serve as biomarkers for CAD progression.

The mining of underground iron ore in Yanchi mountain causes many geological disasters, such as mountain collapse, ground fissures, collapse and unstable slope, which threatens the safety of people’s lives and property, and causes ecological environment problems such as soil erosion, topographic landscape destruction and vegetation damage. According to the causes and current situation of geological hazards and ecological environment in Yanchi mountain, comprehensive treatments such as filling goaf and ground fissures, cutting slope to eliminate danger, building retaining wall and drainage ditch, hanging net spraying and slope greening have been taken to eliminate hidden dangers of geological hazards and restore ecological environment. These measures have achieved remarkable governance results, which can provide reference for comprehensive control and ecological restoration of mine geological hazards in similar areas.

HepG2 cell death with magnetic hyperthermia (MHT) using hydroxyapatite nanoparticles (mHAPs) and alternating magnetic fields (AMF) was investigated in vitro. The mHAPs were synthesized as thermo-seeds by co-precipitation with the addition of Fe(2+). The grain size of the HAPs and iron oxide magnetic were 39.1 and 19.5 nm and were calculated by the Scherrer formula. The HepG2 cells were cultured with mHAPs and exposed to an AMF for 30 min yielding maximum temperatures of 43 ± 0.5 °C. After heating, the cell viability was reduced by 50% relative to controls, lactate dehydrogenase (LDH) concentrations measured in media were three-fold greater than those measured in all control groups. Readouts of toxicity by live/dead staining were consistent with cell viability and LDH assay results. Measured reactive oxygen species (ROS) in cells exposed to MHT were two-fold greater than in control groups. Results of cDNA microarray and Western blotting revealed tantalizing evidence of ATM and GADD45 downregulation with possible MKK3/MKK6 and ATF-2 of p38 MAPK inhibition upon exposure to mHAPs and AMF combinations. These results suggest that the combination of mHAPs and AMF can increase intracellular concentrations of ROS to cause DNA damage, which leads to cell death that complement heat stress related biological effects.

IntroductionLeft ventricular ejection fraction (LVEF) ≤35%, as current significant implantable cardioverter-defibrillator (ICD) indication for primary prevention of sudden cardiac death (SCD) in heart failure (HF) patients, has been widely recognised to be inefficient. Improvement of patient selection for low LVEF (≤35%) is needed to optimise deployment of ICD. Most of the existing prediction models are not appropriate to identify ICD candidates at high risk of SCD in HF patients with low LVEF. Compared with traditional statistical analysis, machine learning (ML) can employ computer algorithms to identify patterns in large datasets, analyse rules automatically and build both linear and non-linear models in order to make data-driven predictions. This study is aimed to develop and validate new models using ML to improve the prediction of SCD in HF patients with low LVEF.Methods and analysisWe will conduct a retroprospective, multicentre, observational registry of Chinese HF patients with low LVEF. The HF patients with LVEF ≤35% after optimised medication at least 3 months will be enrolled in this study. The primary endpoints are all-cause death and SCD. The secondary endpoints are malignant arrhythmia, sudden cardiac arrest, cardiopulmonary resuscitation and rehospitalisation due to HF. The baseline demographic, clinical, biological, electrophysiological, social and psychological variables will be collected. Both ML and traditional multivariable Cox proportional hazards regression models will be developed and compared in the prediction of SCD. Moreover, the ML model will be validated in a prospective study.Ethics and disseminationThe study protocol has been approved by the Ethics Committee of the First Affiliated Hospital of Nanjing Medical University (2017-SR-06). All results of this study will be published in international peer-reviewed journals and presented at relevant conferences.Trial registration numberChiCTR-POC-17011842; Pre-results.

A method for the super-resolution imaging of two-dimensional (2D) high-contrast targets is presented. There are two main methods to reconstruct unknown targets with super resolution. One is to illuminate the targets with specific incident fields and transform the information about the evanescent waves into the propagation waves, and the other is to adopt non-linear inversion methods where the multiple scattering within the objects are considered. For the specific-incident-field method, it has been proved that the orbital-angular-momentum (OAM)-carrying electromagnetic (EM) waves can be employed to image unknown targets with super resolution. In fact, OAM-carrying EM waves can transform the information about the evanescent waves into the propagation waves. Thus the resolution of imaging results can break the Rayleigh limit, namely super resolution. At present, the application of OAM-based super-resolution algorithm is only valid for weak scatters based on Born approximation. For the non-linear inversion methods, the contrast source inversion (CSI) is widely used to reconstruct unknown targets, including large-contrast or complex ones. In the CSI method, the information about the evanescent waves is naturally involved since the EM coupling within the objects is taken into account. Thus super resolution can also be achieved by the CSI method. This paper demonstrates a novel algorithm for super resolution of large-contrast targets by combining the OAM-based super-resolution technique and the CSI method. And the better resolution is achieved than by the CSI method. Firstly, 2D OAM EM waves are generated using uniform circular array of line source, and the region of interest is illuminated by the OAM beams of different topological charges. So the information about the evanescent waves can be converted into the propagation waves. Secondly, Born approximation is used to obtain the starting value of the contrast. In the process of evaluating the contrast, the super-resolution information is fully utilized. Thirdly, the starting value of the contrast source is evaluated using the starting value of the contrast. Then the CSI method starts to be iterated. Since the information about the evanescent waves is always involved in the iterating process, super-resolution reconstruction can be obtained and is better than that obtained by the CSI method. Numerical experiments show the accuracy of the algorithm by testing different scenarios. The resolution and outline of the target are reconstructed accurately even when the measurement data are corrupted by noise. To sum up, to reconstruct unknown targets with super resolution, one should firstly transform the information about the evanescent waves into the propagation waves, and secondly make full use of the super-resolution information in the inversion methods. The conclusion of this paper may provide an insight into the super resolution in EM inverse scattering.

On the basis of analyzing the difficult of evaluating the basic driving factors, the evaluation index system of basic driving factors is established, while the weightiness values of the indexes are calculated out by AHP. The difficult of armored vehicles basic driving factors is quantitative evaluated by the application of similar systems theory, the quantitative evaluation results of degree of difficulty of different basis driving factors is given. And the foundation of the subsequent research on armored vehicles driving is laid.

In order to lucubrate in armored equipment training support, the IDEF0 function modeling method is used to construct the function model of armored equipment training support system based on the analysis of the main operation contents of armored equipment training support. The IDEF3 process modeling method is applied in constructing the model of armored equipment training support process flow PFN and the model of object state transition OSTN through the analysis of armored equipment training support process. The operating mechanism of the armored equipment training support system is defined, which does well in optimizing training support resource deployment and improving training support benefit.

In recent years, the two-way parabolic equation method (2WPE) has been widely utilized for studying the tropospheric ground-wave propagation under the irregular terrain. This algorithm can deal with the influences of the irregular terrain characteristic and the different electromagnetic parameters of the surface structure on wave propagation. However, there are still some defects in 2WPE method. Firstly, the method considers the irregular terrain and obstacles as a whole, so it cannot deal with the situation where the medium parameters of obstacles and the ground are different. Secondly, its calculation precision is limited with the inclination of the undulating terrain: if there are obstacles the upper bound of the inclination is easily broken through. Therefore, in this paper, a novel two-way parabolic equation method is proposed for analyzing the radio wave propagation in obstacle environment. According to the principle of domain decomposition, the obstacle zones are divided into two domains in the new algorithm, and the two subdomains are calculated, respectively. Meanwhile, in order to avoid the calculation error caused by the abrupt truncation of the obstacle zone, the field at the upper boundary of obstacles is modified to ensure the continuity of tangential field. To further improve the accuracy of the new algorithm, according to the historical transmission paths, we exactly retrieve the phases of each forward and backward wave, especially when stepping in and out of the obstacles. Furthermore, the method of moment (MoM) is used to verify the calculation accuracy of the new algorithm in obstacle environment. Although the accuracy of the MoM is very high, it also requires a great deal of calculation resources: it can only be employed to compute the fields in short distance. To overcome the difficulty, we use the image principle in the obstacle environment and do not subdivide the ground into segments; therefore the verification accuracy can be improved. On this basis, to unify the source setting of the new algorithm and the MoM, the equivalent source model is used to set the initial field. Finally, through numerical experiments, the simulation results of both methods agree very well, so the effectiveness of the boundary correction and the phase correction which are presented in this paper are both verified. The accuracy and superiority of the new algorithm in obstacle environment are also demonstrated. To sum up, the novel two-way parabolic equation method can be used to accurately calculate the field of the space in the obstacle environment, and lays the foundation for the field calculation of radio wave propagation in real environment.