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Idiopathic Pulmonary Fibrosis (IPF) is identifiable by the excessive increase of mesenchyme paired with the loss of epithelium. Total flavonoids of Astragalus (TFA), the main biologically active ingredient of the traditional Chinese medicine, Astragalus membranaceus (Huangqi), shows outstanding effects on treating pulmonary disorders, including COVID-19-associated pulmonary dysfunctions. This study was designed to evaluate the efficacy of TFA on treating pulmonary fibrosis and the possible mechanisms behind these effects. A549 cells were treated with TGF-[Formula: see text]1 and TFA to observe the potential effects of TFA on regulating alveolar epithelial cell proliferation, TGF-[Formula: see text]1-induced EMT, and the underlying mechanisms in vitro. Then, mouse pulmonary fibrosis was induced with a single intra-tracheal injection of bleomycin, and TFA was administrated by i.p. injection. Lung fibrosis was evaluated through histological and molecular analyses, and the possible mechanisms were explored using immunological methods. The results demonstrated that TFA could promote cell proliferation but inhibit TGF-[Formula: see text]1-induced EMT on A549 cells. TFA attenuated BLM-induced pulmonary fibrosis in mice by modulating inflammatory infiltration and M2 macrophage polarization; it furthermore modulated EMT through regulating the TGF-[Formula: see text]1/Smad pathway. In addition, TFA augmented the expression of the Wnt7b protein, which plays an important role in alveolar epithelium reparation. In conclusion, TFA alleviated bleomycin-induced mouse lung fibrosis by preventing the fibrotic response and increasing epithelium regeneration.

Preclinical and clinical studies have suggested that fibroblast growth factor (FGF) system contributed to the onset and development of schizophrenia (SCZ). However, there was no strong clinical evidence to link an individual FGF with SCZ. In this study, we aim to measure blood FGF9 levels in the patients with SCZ with and/or without medication, and test whether FGF9 has a potential to be a biomarker for SCZ. We recruited 130 patients with SCZ and 111 healthy individuals, and the ELISA and qRT-PCR assays were used to measure serum FGF9 levels in the participants. ELISA assay demonstrated that serum FGF9 protein levels were dramatically reduced in first-episode, drug-free patients, but not in chronically medicated patients when compared to healthy control subjects. Further analysis showed that treatment of the first-episode, drug-free SCZ patients with antipsychotics for 8 weeks significantly increased the serum FGF9 levels. In addition, we found that blood FGF9 mRNA levels were significantly lower in first-onset SCZ patients than controls. Under the receiver operating characteristic curve, the optimal cutoff values for FGF9 protein level as an indicator for diagnosis of drug-free SCZ patients was projected to be 166.4 pg/ml, which yielded a sensitivity of 0.955 and specificity of 0.86, and the area under the curve was 0.973 (95% CI, 0.954-0.993). Furthermore, FGF9 had good performance to discriminate between drug-free SCZ patients and chronically medicated patients, the optimal cutoff value for FGF9 concentration was projected to be 165.035 pg/ml with a sensitivity of 0.86 and specificity of 0.919, and the AUC was 0.968 (95% CI, 0.944, 0.991). Taken together, our results for the first time demonstrated the dysregulation of FGF9 in SCZ, and FGF9 has the potential to be served as a biomarker for SCZ.

Jeon et al . (Reports, 29 January 2021, p. 498) reported reversible fluctuations between disordered and crystalline states during nucleation. We argue that the adoption of “magic numbers” for separation of the size range into three parts is misleading when using the sigmoid functions and that their figure 3B was wrongly illustrated. The crystal shape effect was neglected during theoretical analysis.

In this paper, based on the nonparallel hyperplane classifier, ν -nonparallel support vector machine ( ν -NPSVM), we proposed its linear programming formulation, termed as ν -LPNPSVM. ν -NPSVM which has been proved superior to the twin support vector machines (TWSVMs), is parameterized by the quantity ν to let ones effectively control the number of support vectors. Compared with the quadratic programming problem of ν -NPSVM, the 1-norm regularization term is introduced to ν -LPNPSVM to make it to be linear programming problem which can be solved fastly and easily. We also introduce kernel functions directly into the formulation for the nonlinear case. The numerical experiments on lots of data sets verify that our ν -LPNPSVM is superior to TWSVMs and faster than standard NPSVMs. We also apply this new method to the vehicle recognition problem and justify its efficiency.

The aim of the present study was to investigate the incremental value of resting three-dimensional speckle-tracking echocardiography (3D-STE) in the detection of early-stage left ventricular dysfunction in patients with coronary artery disease (CAD). A total of 110 patients suspected of having CAD were recruited. All patients underwent 3D-STE and coronary artery angiography (CAG). They were divided to a CAD group and a normal group according to the results of CAG. Using 3D-STE software, the peak values of longitudinal strain (LS), circumferential strain (CS), radial strain (RS) and area strain (AS) and the time to peak value of these strains (T-LS, T-CS, T-RS and T-AS) were measured. A receiver operator characteristic curve (ROC) was used to analyze the sensitivity of these strains for the diagnosis of CAD. ROC analysis indicated that T-LS and composite indices combining the peak strain value and time to peak of LS, CS and AS have diagnostic value for the early detection of CAD; the area under the curve (AUC) values were 0.667, 0.692, 0.621 and 0.672 respectively (P

Unified judgment standards and methods are often adopted to identify traffic state in certain road network based on traffic flow parameters. However, drivers often have different perceptions about the traffic state on different road sections, since their expectations on traffic state vary more or less from each other on different road sections. In particular, under the vehicle networking, out of considerations for safety and other relevant factors, requirements for the correlation and coordination of running vehicles have also raised significantly. Therefore, it is necessary to take driver's perception about the driving conditions of certain road sections into consideration to adjust the release of traffic state. This paper has provided a comprehensive traffic state evaluation model linked with driver's perception under the vehicle networking. The authors first establish an ANFIS model based on the T---S model and then conduct statistical analysis on drivers' perceptions about certain traffic state. At last, the authors use the results of statistical analysis as regulatory factors to amend the parameters input through ANFIS. Through simulation, this paper has demonstrated that the model established has a high rate of convergence, a high identification precision and the generalization ability to conduct researches on the identification of traffic state.

TiO2 nanotube arrays were made on the titanium foil by the method of anodic oxidation. Large-area crystallized free-standing TiO2 nanotube arrays were fabricated by a two-step anodization, and then crystallized by different heat-treatment processes. The morphology and structure of the TiO2 nanotube arrays were characterized by scanning electron microscope (SEM) and X-ray diffraction (XRD). The results show that the diameter of the TiO2 nanotube at the voltage range of 50V~65V was about 100nm. Anatase phase is the unique phase observed in free-standing TiO2 arrays annealed at the temperature of 400°C~610°C. However, crystallographic orientation of anatase phase is influenced by the annealing temperature.

Fluoropyrimidine drugs are widely used in head and neck cancer (HNC). DPD deficiency is a pharmacogenetics syndrome associated with severe/lethal toxicities upon 5-FU or capecitabine intake. We have developed a simple, rapid, and inexpensive functional testing for DPD activity, as a means to identify deficient patients and to anticipate subsequent 5-FU-related toxicities. We present here the impact of fluoropyrimidine dose tailoring based on DPD functional screening in a prospective, open, non-controlled study, both in term of reduction in severe toxicities and of treatment efficacy. About 65 patients with HNC (59 ± 9 years, 52M/13F, Prospective Group) were entered into the study. Screening for DPD deficiency was performed prior to the beginning of the chemotherapy or radiochemotherapy. DPD status was evaluated by monitoring U/UH2 ratio levels in plasma as a surrogate marker for enzymatic functionality. 5-FU doses were reduced according to the extent of the detected DPD impairment, and adjusted on the basis of age, general condition, and other clinical/paraclinical covariates, if required. Treatment-related toxicities and subsequent impact on treatment delay were carefully monitored next for comparison with a retrospective, Reference subset of 74 other patients with HNC (mean age: 59 ± 10, 58M/16F, Reference Group), previously treated in the same institute with similar schedule but using standard 5-FU dosage. Thirty-one out of 65 patients (48%) were identified as mildly (28%) to markedly (20%) DPD deficient. Subsequently, dose reductions ranging from 10 to 100% with 5-FU were applied in those patients. In this group, six patients (9%) experienced severe toxicities, none of them being life threatening, and no toxic death was encountered. In comparison, 16 out of 74 patients (22%) of the Reference Group displayed severe side effects after standard 5-FU administration, 13% being life-threatening toxicities (e.g., G4 neutropenia + sepsis). Moreover, one toxic death was observed in this Reference Group. No postponement or cancelation of forthcoming chemoradiotherapy courses occurred in the Prospective Group, whereas treatment had to be disrupted in six patients (8%) from the Reference Group. No difference in first-line therapy efficacy was evidenced between the two subsets (78 vs. 79% response, P = 0.790). Although non-randomized, this study strongly suggests that prospective determination of DPD status has an immediate clinical benefit by reducing the drug-induced toxicities incidence in patients treated with 5-FU, allowing an optimal administration of several courses in a row, while maintaining efficacy. Our preliminary results thus advocate for systematic DPD screening in patients eligible for treatment with fluoropyrimidine drugs in HNC.

In this paper, the reliability of contactor relay is studied. There are three main parts about reliability test and analysis. First, in order to analyze reliability level of contact relay, the failure ratio ranks are established as index base on the product level. Second, the reliability test method is put forward. The sample plan of reliability compliance test is gained from reliability sample theory. The failure criterion is ensured according to the failure modes of contactor relay. Third, after reliability test experiment, the analysis of failure physics is made and the failure reason is found.

The peak-hour cross-section passenger volume (PCPV) is a key index to characterize the travel demand of urban rail transit. To improve the forecasting accuracy of PCPV is of great importance in the urban rail transit passenger flow organization. Because of the expansive scale of urban rail transit network and the free transfer within it, the forecasting of PCPV is becoming more and more difficult. Thus a combined forecasting model based on correlation analysis is proposed in this paper to enhance the rationality and accuracy of PCPV forecasting. Firstly, key factors that affect PCPV are indentified. Secondly, regression models between PCPV and factors are established based on correlation analysis. An artificial neural network is utilized to analyze and forecast the PCPV time series, and then a combined forecasting model is constructed by regression approaches. A case study is conducted to show the effectiveness and practicability of the combined forecasting model through comparison.

We report here the case of a 19-year-old female patient who suffered from extremely severe toxicities (G4 mucitis, fever, diarrhea, alteration of general state) while undergoing low-dose capecitabine treatment for her metastatic corticosurrenaloma. The severe toxicities stopped as soon as treatment was suspended. Interestingly, this patient was not deficient in DPD, a pharmacogenetic syndrome usually associated with increased risk of developing severe/lethal toxicities in patients undergoing fluoropyrimidine therapy, and she had been treated previously with 5-FU with a good tolerance. We then hypothesized that cytidine deaminase (CDA) extensive phenotype could be responsible for the severe toxicities observed with capecitabine. CDA is affected by genetic polymorphism, with subsequent acquisition of either deficient or extensive metabolizer profile. Phenotypic investigations confirmed that CDA activity in this patient was +180% higher than the ones usually recorded in the general population. This strongly suggests that the extensive activation of triple-prodrug capecitabine could have occurred in this patient, resulting in overexposure to 5-FU and its cytotoxic metabolites eventually. This case report suggest for the first time that severe toxicities with a capecitabine-containing protocol could be, at least in part, linked with an extensive-CDA syndrome. The case reported here suggests therefore that besides DPD, screening for CDA activity could be of interest to ensure a better safety in the handling of oral capecitabine at the bedside.

According to analysis and practical situation of credit risk assessment in commercial banks, some indexes are selected to establish the index system. The credit risk classes are separated into two classes- normality and loss. To classify the credit risk data, support vector machines (SVM) model based on PCA (principal component analysis) is established. In order to verify the effectiveness of the method, a real case is given and SVM model without using PCA is also used to classify the same data. The experimental results show that SVM model based on PCA is effective in credit risk assessment and achieves better performance than SVM model without using PCA.

According to the practical situation of credit risk assessment in commercial banks, a set of index system is established. The index system includes financial indexes and non-financial indexes. Then support vector machines (SVM) algorithm is used for assessment in this research. In the method, training sets are selected by the increasing proportions. Proportions are determined by the number of samples. In order to verify the effectiveness of the method, a real case is given and the experimental results show that the model has high correct classification accuracy.

Researching the competition ability of the power plant in electric power marketing is a key problem of power plant management. In this paper, the comprehensive evaluation indexes system of the power plant characteristics is set up, and support vector machine (SVM) was used in the comprehensive evaluation of the power plant competition ability on the base of filtrating the formed indexes with the principal components analysis method. The test results show the performance of this method is good and practical.