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The cost of operating Chinese football clubs has increased, prompting the need to examine their operating efficiency. Hence, this study proposes an integrated approach to analyse the efficiency of ...

Purpose Genetic factors have been studied to be associated with diabetic retinopathy (DR). This study aimed to investigate the association between the polymorphisms in the osteoproterin (OPG) gene and DR in a Han Chinese population. Methods There were 475 patients with diabetic retinopathy (DR), 478 type 2 diabetes mellitus without retinopathy (DNR) and 469 healthy controls collected in this study. OPG single-nucleotide polymorphisms (SNPs) rs2073618 and rs3134069 were genotyped by Mass ARRAY MALDI-TOF system. The genotype and allele frequencies were evaluated using the χ2 tests. Odds ratio (OR) and 95% confidence intervals (95% CI) were calculated for the risk of genotype and allele. Results There was a statistically significant difference for OPG SNP rs3134069 between DR cases and healthy controls in the allelic model (P = .036, OR = 1.33, 95% CI = 1.02-1.73). The C allele frequency of this polymorphism was 0.154 in the DR cases, whereas it was 0.120 in healthy controls, suggesting a risk effect for DR. SNP rs3134069 had a significant association with DR in the dominant model (P = .038, OR = 1.37, 95% CI = 1.02-1.84), indicating that the CC/AC genotype was more likely to suffer from DR. For rs2073618, no significant difference was identified in the allelic model (P = .632, OR = 0.95, 95% CI = 0.78-1.16) and the four genetic models. Conclusions This study showed that OPG SNP rs3134069 was associated with DR in the dominant model, suggesting that the OPG gene variant may be involved in the development of DR.

AimsTo identify single-nucleotide polymorphisms (SNPs) associated with central serous chorioretinopathy (CSCR) by a systematic review and meta-analysis, and to compare the association profiles between CSCR, neovascular age-related macular degeneration (nAMD) and polypoidal choroidal vasculopathy (PCV).MethodsWe searched the EMBASE, PubMed and Web of Science for genetic studies of CSCR from the starting dates of the databases to 12 September 2020. We then performed meta-analyses on all SNPs reported by more than two studies and calculated the pooled OR and 95% CIs. We also conducted sensitivity analysis and adopted the funnel plot to assess potential publication bias.ResultsTotally 415 publications were reviewed, among them 10 were eligible for meta-analysis. We found 10 SNPs that have been reported at least twice. Meta-analysis and sensitivity analysis confirmed significant associations between CSCR and six SNPs in three genes, namely age-related maculopathy susceptibility 2 (ARMS2) (rs10490924, OR=1.37; p=0.00064), complement factor H (CFH) (rs800292, OR=1.44; p=7.80×10−5; rs1061170, OR=1.34; p=0.0028; rs1329428, OR=1.40; p=0.012; and rs2284664, OR=1.36; p=0.0089) and tumour necrosis factor receptor superfamily, member 10a (TNFRSF10A) (rs13278062, OR=1.34; p=1.44×10−15). Among them, onlyTNFRSF10Ars13278062 showed the same trend of effect on CSCR, nAMD and PCV, while the SNPs inARMS2andCFHshowed opposite trends in the SNP associations.ConclusionsThis study confirmed the associations ofARMS2,CFHandTNFRSF10Awith CSCR, and revealed thatARMS2,CFHandTNFRSF10Amay affect different phenotypic expressions of CSCR, nAMD and PCV.

The disease spectrum of coronavirus disease 2019 (COVID‐19) varies from asymptomatic infection to critical illness and death. Identification of prognostic markers is vital for predicting progression and clinical practice. Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) RNA, known as RNAemia, has been detected in the blood. However, the potential clinical value of SARS‐CoV‐2 RNAemia remains unknown. We, therefore, conducted a meta‐analysis using a random‐effects model to estimate the pooled prevalence of SARS‐CoV‐2 RNAemia as well as summary strength of RNAemia in association with disease severity and unfavorable clinical outcomes. A total of 21 studies involving 2181 patients were included. SARS‐CoV‐2 RNAemia in COVID‐19 patients varied from 9.4% to 74.1%, with a pooled estimate of 34% (95% confidene interval [CI]: 26%–43%). Overall, SARS‐CoV‐2 RNAemia was associated with COVID‐19 severity with odds ratio (OR) of 5.43 (95% CI: 3.46–8.53). In addition, SARS‐CoV‐2 RNAemia was a significant risk factor for unfavorable clinical outcomes (OR = 6.54, 95% CI: 3.82–11.21). The summary OR was 4.28 (95% CI: 2.20–8.33) for intensive care unit (ICU) admission, 11.07 (95% CI: 5.60–21.88) for mortality. Furthermore, RNAemia was also a significant risk factor for invasive mechanical ventilation and multiple organ failure. SARS‐CoV‐2 RNAemia is associated with disease severity, ICU admission, death in COVID‐19, and may serve as a clinical predictor. More prospective trials in evaluating the potential of SARS‐CoV‐2 RNAemia as a prognostic indicator are necessary.

Background As a novel high magnification module (HMM) combining with OCT (OCT-HMM) is able to detect the microstructure of retina, we apply it to explore the ultrastructure of the macula after closure of the idiopathic macular hole (IMH) by surgery. Methods This is an observational case series study in which patients with full-thickness IMHs who had undergone successful macular closure by vitrectomy and internal limiting membrane peeling and healthy subjects were recruited. After comprehensive ophthalmic examinations, the images of macular area were obtained and collected by professional operators using OCT-HMM. Then images were independently analyzed by 4 masked vitreoretinal specialists. Results A total of 24 IMH eyes and 42 healthy eyes were examined. HMM images were obtained in 10 IMH eyes. Among them, 4 eyes whose macula closed completely with recovery of photoreceptor layer presented a dark arc nasal to the fovea, oriented to the optic, and the notch of arc faced temporally. Six eyes in which the macula closed incompletely with photoreceptor cells loss revealed a dark ring with uneven bright spots inside. The other 14 eyes failed to obtain clear images by OCT-HMM. The contra lateral eyes of the patients and the healthy subjects’ eyes succeeded to obtain the HMM images which displayed evenly grey background thickly covered with tiny bright dots that was in similar size and evenly and widely distributed and there no dark arc or ring. OCT B-scan and IR images could be acquired in all of the IMH and healthy eyes. Conclusion The preliminary application of HMM has supplied us a brand-new insight into the microstructure of closed IMH. A dark arc sign could be detected with OCT-HMM in the macula which was functionally closed after surgery that was probably the healing mark on a microstructure photoreceptors level. Its existence and shape indicated that the functional closure followed by a retinal displacement mainly horizontally from temporal side to nasal side but not symmetric centripetally.

Background Pancreatic ductal adenocarcinoma (PDAC) is one of the most refractory and lethal cancer. The overall survival is dismal due to the high frequency of recurrence and metastasis after surgery and resistance to chemotherapy. Patients with the locally advanced or metastatic disease usually have the poorest prognosis. Herein, we report a rare highly responsive PDAC with liver metastasis. Case presentation A 49-year-old female presented with dull abdominal and back pain, discomfort after eating, fatigue, and recent weight loss of 5 kg. Clinical examination was normal and no relevant oncological history was observed. A routine blood test showed low red blood cell count and low hemoglobin level. Markedly increased carcinoembryonic antigen (CEA) and carbohydrate antigen (CA) 125 levels were detected. Computer tomography (CT) of the abdomen revealed a massive pancreatic tumor with the invasion of almost all important surrounding blood vessels and liver metastasis. After the genetic test and percutaneous biopsy for this tumor, a multidisciplinary team (MDT) discussion was initiated. Subsequently, oral chemotherapy (S-1) and 125I radiative seeds implantation were recommended. Surprisingly, the tumor shrank significantly after treatment. On August 14, 2019, pancreatoduodenectomy was performed. The tumor was successfully resected and liver metastasis was not detected. Based on the postoperative histopathological result, there was only fibrous tissue hyperplasia and inflammatory cell infiltration. Besides, no tumor tissue was found. Until now, through outpatient follow-up, no signs of recurrence and metastasis have been observed. Conclusion Although the therapeutic efficacy and prognosis of PDAC are dismal, we successfully cured a patient with a metastatic disease through multidisciplinary cooperation. However, the therapeutic experience should be summarized and further research should be performed to confirm whether it is appropriate for other PDAC patients.

PURPOSE: Obesity, measured by body mass index (BMI), is implicated in adverse pregnancy outcomes for women seeking in vitro fertilization (IVF) care. However, the shape of the dose-response relationship between BMI and IVF outcomes remains unclear. METHODS: We therefore conducted a dose-response meta-analysis using a random effects model to estimate summary relative risk (RR) for clinical pregnancy (CPR), live birth (LBR), and miscarriage risk (MR) after IVF. RESULTS: A total of 18 cohort-based studies involving 975,889 cycles were included. For each 5-unit increase in BMI, the summary RR was 0.95 (95% CI: 0.94–0.97) for CPR, 0.93 (95% CI: 0.92-0.95) for LBR, and 1.09 (95% CI: 1.05-1.12) for MR. There was evidence of a non-linear association between BMI and CPR (P(non-linearity) < 10(−5)) with CPR decreasing sharply among obese women (BMI > 30). Non-linear dose-response meta-analysis showed a relatively flat curve over a broad range of BMI from 16 to 30 for LBR (P(non-linearity) = 0.0009). In addition, we observed a J-shaped association between BMI and MR (P(non-linearity) = 0.006) with the lowest miscarriage risk observed with a BMI of 22–25. CONCLUSIONS: In conclusion, obesity contributed to increased risk of adverse IVF outcomes in a non-linear dose-response manner. More prospective trials in evaluating the effect of body weight control are necessary.

Fault induced delayed voltage recovery (FIDVR) is a credible concern in power systems with high penetration of single-phase air conditioner loads. Power system planning studies use dynamic load models, such as the Western Electricity Coordinating Council (WECC) composite load model CMPLDW to examine FIDVR in power systems. The behavior of modern variable frequency drive (VFD) air conditioners to voltage drops is not the same as traditional one- or two-speed air conditioning systems. This paper investigates the impact of increasing VFD air conditioner penetration within a power system on FIDVR events, by first modeling VFD air conditioners as a separate load and then as a power electronic component within the CMPLDW model. Simulation results show that increasing the penetration of VFD driven air conditioners decreases the post-fault voltage sag, recovery time, and number of customers interrupted by undervoltage load shedding.

Objectives This paper is aimed to explore the value of double source CT angiography (DS-CTA) for diagnosing in-stent restenosis in lower limb artery. Methods From January 2016 to October 2018, all patients with stent in lower limb artery in our hospital were investigated by both DS-CTA and digital subtraction angiography. We measured the minimum lumen diameter and the diameter of the proximal normal vessels under each stent placement. The in-stent restenosis is defined as restenosis when the lumen area decreased by more than 50%. Digital subtraction angiography was performed within 1 week after DS-CT scan. Relationship between DS-CTA and digital subtraction angiography for diagnosing in-stent restenosis in lower limb artery was analyzed. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of DS-CTA for diagnosis of in-stent restenosis were analyzed with digital subtraction angiography as the reference standard. A total of 68 stents were placed in 51 patients. Among these patients, 27 cases were diagnosed as in-stent restenosis, presenting as endovascular contrast agent bias or crescent filling defect with the lumen area reducing over 50%, 6 cases of which had no significant in-stent restenosis by digital subtraction angiography analysis. Furthermore, 12 cases were occlusion, in which there was no high density contrast agent in stents; the remaining 41 stents were unobstructed and the contrast agent was filled well, 8 cases of which had significant in-stent restenosis by digital subtraction angiography analysis. In addition, four stents were deformed or distorted. Statistical analysis demonstrated the concentrations of DS-CTA and digital subtraction angiography in diagnosing in-stent restenosis for lower limb artery were closely related, and the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of DS-CTA were 72.4%, 84.6%, 77.8%, 80.5%, and 79.4%, respectively. Conclusion DS-CTA has a potential reliability for diagnosis of in-stent restenosis in lower limb artery, which may be further improved to be used for clinical interventional treatment of vascular diseases.

Fatigue driving is one of the main factors which affect the safety of drivers and passengers in mountain freeway. To improve the driving safety, the application of fatigue driving detection system is a crucial measure. Accuracy, speed and robustness are key performances of fatigue detection system. However, most researches pay attention to one of them, instead of taking care of them all. It has limitation in practical application. This paper proposes a novel three-layered framework, named Real-time and Robust Detection System. Specifically, the framework includes three modules, called facial feature extraction, eyes regions extraction and fatigue detection. In the facial feature extraction module, the paper designs a deep cascaded convolutional neural network to detect the face and locate eye key points. Then, a face tracking sub-module is constructed to increase the speed of the algorithm, and a face validation submodule is applied to improve the stability of detection. Furthermore, to ensure the orderly operation of each sub-module, we designed a recognition loop based on the finite state machine. It can extract facial feature of the driver. In the second module, eyes regions of the driver were captured according to the geometric feature of face and eyes. In the fatigue detection module, the ellipse fitting method is applied to obtain the shape of driver's pupils. According to the relationship between the long and short axes of the ellipse, eyes state (opening or closed) can be decided. Lastly, the PERCLOS, which is defined by calculating the number of closed eyes in a period, is used to determine whether fatigue driving or not. The experimental results show that the comprehensive accuracy of fatigue detection is 95.87%. The average algorithm rate is 32.29 ms/f in an image of 640×480 pixels. The research results can serve the design of a new generation of driver fatigue detection system to mountain freeway.

Closed-loop deep brain stimulation (DBS) paradigm is gaining tremendous favor due to its potential capability of further and more efficient improvements in neurological diseases. Preclinical validation of closed-loop controller is quite necessary in order to minimize injury risks of clinical trials to patients, which can greatly benefit from real-time computational models and thus potentially reduce research and development costs and time. Here we developed an embedded multi-core real-time simulation platform (EMC-RTP) for a biological-faithful computational network model of basal ganglia (BG). The single neuron model is implemented in a highly real-time manner using a reasonable simplification. A modular mapping architecture with hierarchical routing organization was constructed to mimic the pathological neural activities of BG observed in parkinsonian conditions. A closed-loop simulation testbed for DBS validation was then set up using a host computer as the DBS controller. The availability of EMC-RTP and the testbed system was validated by comparing the performance of open-loop and proportional-integral (PI) controllers. Our experimental results showed that the proposed EMC-RTP reproduces abnormal beta bursts of BG in parkinsonian conditions while meets requirements of both real-time and computational accuracy as well. Closed-loop DBS experiments using the EMC-RTP suggested that the platform could perform reasonable output under different kinds of DBS strategies, indicating the usability of the platform.

Electrical Impedance Tomography (EIT), an imaging technique which operates non-invasively and without radiation exposure, provides information about ventilation- and cardiac-synchronous (pulsatile) changes in the lung. It is well known, that perfusion within the thorax is influenced by lung volume or intrathoracic pressure. In this observational study, it shall be investigated if this phenomenon can be monitored by EIT. Therefore, the impact of the amount of air within the lung on the pulsatile EIT signal was evaluated by carrying out EIT measurements with a spontaneously breathing lung healthy subject holding the breath at three different inspiratory and three various expiratory volume levels during normal tidal breathing. For EIT data analysis, a region of interest was defined by including lung tissue and excluding the heart region. The EIT data revealed, that the shape and the amplitude of the pulsatile EIT signal (evaluated per heartbeat) during the phases of breath holding were dependent on the enclosed lung volume. For lung volumes > 4 L, the amplitude of the pulsatile EIT signal increased with rising inspiratory level and the shape remained almost unchanged. For lung volumes < 4 L, a change in shape was visible but the amplitude remained more or less the same with decreasing expiratory level. Since the results of this observational study show that the pulsatile EIT signal is influenced by the lung volume, it might be used in future to draw conclusions of cardiacpulmonary interactions or intrathoracic pressure states, benefitting the treatment of intensive care patients.

Background: It has been shown that genetic factors play an important role in the pathogenesis of primary open-angle glaucoma (POAG). This study was conducted to investigate the association between the polymorphism rs11656696 located in the growth arrest-specific 7 gene (GAS7) and POAG. Methods: A cohort of 799 unrelated POAG patients and 799 unrelated control subjects was enrolled in this case-control association study. The polymorphism rs11656696 was genotyped using the SNaPshot method. The genotype and allele frequencies were evaluated using the χ2 tests. Results: The allele frequency distribution of rs11656696 in the GAS7 gene showed that there was significant difference between POAG cases and controls (P= .006448, OR = 0.82, 95%CI = (0.72-0.95). The minor "A" allele frequency of this polymorphism was 0.477 in the POAG cases, whereas it was 0.526 in controls, suggesting a protective effect for POAG. Significant associations were detected under the homozygous model (p = .006425, OR = 0.68, 95%CI = 0.51-0.90) and recessive model (p = .0003432, OR = 0.66, 95%CI = 0.52-0.84), indicating that subjects carrying rs11656696 AA genotype were less likely to suffer from POAG than those carrying AC/CC genotypes. Conclusion: This case-control association study showed that polymorphism rs11656696 in GAS7 is related to POAG and might be a protective factor against POAG.

In this study, the effects of three different types of doping elements on the thermoelectric properties, mechanical properties and thermal stability of Zr0.95A0.05NiSn (A = p-type dopant: Sc; isoelectronic dopants: Zr, Ti and Hf; n-type dopants: V, Nb and Ta) were systematically investigated. The sample was prepared by smelting multiple magnetic suspensions in combination with the spark plasma sintering method. X-ray diffraction analysis and scanning electron microscopy observations showed that nearly single-phase half-Heusler compounds were obtained for the levitation-melted ingots. The results demonstrate that p-type doping causes the semiconductor behavior of this material to change from n type to p type, resulting in poor thermoelectric properties. The mass fluctuations and stress fluctuations introduced by the isoelectronic doping cause the thermal conductivity to decrease, and n-type dopants increase the carrier concentration of the material, resulting in an increase in its power factor. On this basis, the ZTmax value of the Zr0.95M0.05NiSn (M = Ti0.25Hf0.25Nb0.25V0.25) sample reached 0.76, which is 58% higher than that of ZrNiSn within the measurement temperature range. In addition, all of the samples maintained excellent mechanical properties, and their microhardness (HV) was greater than 900; no significant endothermic or exothermic phenomenon of all these samples was observed from room temperature to 700 °C, confirming their good thermal stability.

The processing of unknown words is an important issue that impedes the performance of many natural language systems. In terms of the processing of financial public opinion, due to a wide variety of terminology in the financial sector and the suddenness of financial public opinion events as well as the proliferation of network vocabulary, a variety of unknown new words emerge while the traditional text classification method is basically incapable of processing these unrecognized characters. In this paper, an approach equipped with a new directional substitution model for processing the unknown words is proposed. Based on the semantic similarity of the context in word2ve algorithm, the model trains synonym substitution list and substitutes the unknown words in the original texts with synonyms. Also, the TFIDF (term frequency-inverse document frequency) -weighted Naive Bayes classifier is used to carry out the text classification experiments on the traditional datasets and the synthetic datasets including the unknown words. The experimental results show that the model has better classification effect than the traditional methods and can accurately identify the categories of the financial public opinion texts involving the unknown words by transforming the meaningless unknown words into the words containing meaning.

The 2019 coronavirus disease (COVID-19) outbreak caused by the SARS-CoV-2 virus is an ongoing global health emergency. However, the virus’ pathogenesis remains unclear, and there is no cure for the disease. We investigated the dynamic changes of blood immune response in patients with COVID-19 at different stages by using 5’ gene expression, T cell receptor (TCR), and B cell receptors (BCR) V(D)J transcriptome analysis at a single-cell resolution. We obtained single-cell mRNA sequencing (scRNA-seq) data of 341,420 peripheral blood mononuclear cells (PBMCs) and 185,430 clonotypic T cells and 28,802 clonotypic B cells from 25 samples of 16 patients with COVID-19 for dynamic studies. In addition, we used three control samples. We found expansion of dendritic cells (DCs), CD14+ monocytes, and megakaryocytes progenitor cells (MP)/platelets and a reduction of naïve CD4+ T lymphocytes in patients with COVID-19, along with a significant decrease of CD8+ T lymphocytes, and natural killer cells (NKs) in patients in critical condition. The type I interferon (IFN-I), mitogen-activated protein kinase (MAPK), and ferroptosis pathways were activated while the disease was active, and recovered gradually after patient conditions improved. Consistent with this finding, the mRNA level of IFN-I signal-induced gene IFI27 was significantly increased in patients with COVID-19 compared with that of the controls in a validation cohort that included 38 patients and 35 controls. The concentration of interferon-α (IFN-α) in the serum of patients with COVID-19 increased significantly compared with that of the controls in an additional cohort of 215 patients with COVID-19 and 106 controls, further suggesting the important role of the IFN-I pathway in the immune response of COVID-19. TCR and BCR sequences analyses indicated that patients with COVID-19 developed specific immune responses against SARS-CoV-2 antigens. Our study reveals a dynamic landscape of human blood immune responses to SARS-CoV-2 infection, providing clues for therapeutic potentials in treating COVID-19.

Highlights • Machine learning and artificial intelligence have gained popularity for medical applications. • We applied support vector machine (SV) and deep learning (DL) in termporal lobe epilepsy (TLE) • Structural and diffusion-based models showed similar classification accuracies. • Diffusion-based models to diagnose TLE performed better or similar compared to models to lateralize TLE. • Models for patients with hippocampal sclerosis were more accurate than models that stratified non-lesional patients., Artificial intelligence has recently gained popularity across different medical fields to aid in the detection of diseases based on pathology samples or medical imaging findings. Brain magnetic resonance imaging (MRI) is a key assessment tool for patients with temporal lobe epilepsy (TLE). The role of machine learning and artificial intelligence to increase detection of brain abnormalities in TLE remains inconclusive. We used support vector machine (SV) and deep learning (DL) models based on region of interest (ROI-based) structural (n = 336) and diffusion (n = 863) brain MRI data from patients with TLE with (“lesional”) and without (“non-lesional”) radiographic features suggestive of underlying hippocampal sclerosis from the multinational (multi-center) ENIGMA-Epilepsy consortium. Our data showed that models to identify TLE performed better or similar (68–75%) compared to models to lateralize the side of TLE (56–73%, except structural-based) based on diffusion data with the opposite pattern seen for structural data (67–75% to diagnose vs. 83% to lateralize). In other aspects, structural and diffusion-based models showed similar classification accuracies. Our classification models for patients with hippocampal sclerosis were more accurate (68–76%) than models that stratified non-lesional patients (53–62%). Overall, SV and DL models performed similarly with several instances in which SV mildly outperformed DL. We discuss the relative performance of these models with ROI-level data and the implications for future applications of machine learning and artificial intelligence in epilepsy care.

Background and Purpose. Allergic asthma, a respiratory disease with high morbidity and mortality, is reported to be related to the airway allergic inflammation and autophagy-induced oxidative stress. Although the therapeutic effects of fermentate prebiotic (YFP) on allergic asthma have been widely claimed, the underlying mechanism is still unclear. This study is aimed at investigating the possible mechanism for the antiasthma property of YFP in a mouse model. Methods. Ovalbumin was used to induce allergic asthma following administration of YFP for one week in mice, to collect the lung tissues, bronchoalveolar lavage fluid (BLFA), and feces. The pathological state, tight-junction proteins, inflammatory and oxidative stress-associated biomarkers, and TLRs/NF-κB signaling pathway of the lung tissues were evaluated by HE staining, immunofluorescence, ELISA, and WB, separately. RT-PCR was used to test oxidative stress-associated genes. Leukocyte counts of BLFA and intestinal microbiota were also analyzed using a hemocytometer and 16S rDNA-sequencing, separately. Result. YFP ameliorated the lung injury of the mouse asthma model by inhibiting peribronchial and perivascular infiltrations of eosinophils and increasing tight-junction protein expression. YFP inhibited the decrease in the number of BALF leukocytes and expression of inflammatory-related genes and reversed OVA-induced TLRs/NF-κB signaling pathway activation. YFP ameliorated the level of oxidative stress in the lung of the mouse asthma model by inhibiting MDA and promoting the protein level of GSH-PX, SOD, CAT, and oxidative-related genes. ATG5, Beclin1, and LC3BII/I were significantly upregulated in asthma mice, which were greatly suppressed by the introduction of YFP, indicating that YFP ameliorated the autophagy in the lung of the mouse asthma model. Lastly, the distribution of bacterial species was slightly changed by YFP in asthma mice, with a significant difference in the relative abundance of 6 major bacterial species between the asthma and YFP groups. Conclusion. Our research showed that YFP might exert antiasthmatic effects by inhibiting airway allergic inflammation and oxidative stress level through suppressing autophagy.

Age-related macular degeneration (AMD) and diabetic retinopathy (DR), the leading causes of visual impairment in different ethnic groups, are known to be multifactorial and complex diseases with a strong genetic predisposition. In recent years, the advent of genome-wide association studies (GWAS) and whole-exome sequencing (WES) has greatly improved the screening and identification of genetic variants in these complex retinal diseases. In this chapter, we overviewed and summarized recent major advances in the association studies on AMD and DR in the Chinese population. Based on these studies, we found that the genetic variants in the HTRA1, CFH, SKIV2L, CETP genes were strongly associated with AMD. These genes including HTRA1, CFH, CETP, ARMS2, C3, FGD6, ABCG1, and ANGPT2, had significant associations with polypoidal choroidal vasculopathy (PCV), one type of AMD. There were also significant associations of several genes with DR in the Chinese population. These results further confirmed that genetic factors play a critical role in the development of these retina diseases.

Fractional-order Chua systems have drawn wide attention in view of rich dynamic characteristics, e.g., chaos and hyperchaos. How to generate chaotic series via encryption method in fractional-order Chua systems is a difficult point all the while. In this paper, we derive several encryption methods in fractional-order Chua systems to generate chaotic series. As one of the most direct application, image encryption is also discussed by the presented methods.

Wheat head detection can estimate various wheat traits, such as density, health, and the presence of wheat head. However, traditional detection methods have a huge array of problems, including low efficiency, strong subjectivity, and poor accuracy. In this paper, a method of wheat-head detection based on a deep neural network is proposed to enhance the speed and accuracy of detection. The YOLOv4 is taken as the basic network. The backbone part in the basic network is enhanced by adding dual spatial pyramid pooling (SPP) networks to improve the ability of feature learning and increase the receptive field of the convolutional network. Multilevel features are obtained by a multipath neck part using a top-down to bottom-up strategy. Finally, YOLOv3&prime, s head structures are used to predict the boxes of wheat heads. For training images, some data augmentation technologies are used. The experimental results demonstrate that the proposed method has a significant advantage in accuracy and speed. The mean average precision of our method is 94.5%, and the detection speed is 71 FPS that can achieve the effect of real-time detection.

Objective During the past three decades, applying IVF for infertility treatment PCOS women has increased significantly, and the landscape of treatment strategies has changed dramatically. However, early review of IVF on PCOS have insufficiently accounted for efficacy and safety of the technic. With abundant studies in recent years, there is a need to reconcile these new data. Material and methods To compare reproductive and obstetric outcomes of IVF between women with and without PCOS, a meta-analysis of 95 studies involving more than 21289 PCOS patients and 43036 controls was performed. Results Despite longer stimulation duration (WMD = 0.34 day, 95 % CI: 0.09, 0.59) and lower dose of Gn required (WMD = -361.3 IU, 95 % CI: -442.3, -280.4), more oocytes (WMD = 3.67, 95 % CI: 3.14−4.21) and matured oocytes (WMD = 2.16, 95 % CI: 1.52−2.80) per cycle were obtained from PCOS women. There were no statistically significant differences for cleavage, high-grade embryo and implantation rate. Although similar pregnancy and live birth rates per cycle were achieved in PCOS and non-PCOS women after IVF, women with PCOS still suffered from significantly increased risks of miscarriage (OR = 1.44, 95 % CI: 1.20−1.72), biochemical pregnancy loss (OR = 1.89, 95 % CI: 1.48−2.41), and OHSS (OR = 3.58, 95 % CI: 2.86−4.48), in addition to lower fertilization rate (OR = 0.79, 95 % CI: 0.71−0.88). Adverse obstetric outcomes including ectopics pregnancy and multiple pregnancies are comparable between two groups. The overall cycle cancellation rate was significantly higher among PCOS women with OR of 2.55 (95 % CI: 1.67−3.89), and concern over OHSS or hyper-response constitute the main cause. Similar results were also observed after stratified analysis. Conclusions Our results support the effectiveness of IVF for infertility treatment among PCOS patients. However, options to minimize adverse outcomes regarding to lower fertilization, miscarriage, biochemical pregnancy loss and OHSS are required. Further studies elucidating detailed mechanism underlying these adverse outcomes could be of great importance to improve the experience of IVF treatment.

Background: Plant phenotyping by deep learning has increased attention. The detection of wheat head in the field is an important mission for estimating the characteristics of wheat heads such as the density, health, maturity, and presence or absence of awns. Traditional wheat head detection methods have problems such as low efficiency, strong subjectivity, and poor accuracy. However, with the development of deep learning theory and the iteration of computer hardware, the accuracy of object detection method using deep neural networks has been greatly improved. Therefore, using a deep neural network method to detect wheat heads in images has a certain value. Results: In this paper, a method of wheat head detection based on deep neural network is proposed. Firstly, for improving the backbone network part, two SPP networks are introduced to enhance the ability of feature learning and increase the receptive field of the convolutional network. Secondly, the top-down and bottom-up feature fusion strategies are applied to obtain multi-level features. Finally, we use Yolov3's head structures to predict the bounding box of object. The results show that our proposed detection method for wheat head has higher accuracy and speed. The mean average precision of our method is 94.5%, and the detection speed of our proposed method is 88fps. Conclusion: The proposed deep neural network can accurately and quickly detector the wheat head in the image which is based on Yolov4. In addition, the training dataset is a wheat head dataset with accurate annotations and rich varieties, which makes the proposed method more robust and has a wide range of application values. The proposed detector is also more suitable for wheat detection task, with the deeper backbone networks. The use of spatial pyramid pooling (SPP) and multi-level features fusion, which all play a crucial role in improving detector performance. Our method provides beneficial help for the breeding of wheat

We previously showed that microRNA-182 (miR-182) might promote cell proliferation and migration in triple-negative breast cancer (TNBC). This study aimed to investigate circular RNAs (circRNAs) that interact with miR-182 and play important roles in TNBC. Thirty patients with TNBC were enrolled. One pair of tumor and adjacent tissue samples (control) were submitted for circRNA sequencing to establish the expression profile of circRNAs. Concomitantly, circRNAs aberrantly expressed between TNBC and control groups were identified, and these differentially expressed circRNAs (DEcircRNAs) were subjected to Gene Ontology and KEGG pathway enrichment analyses, as well as prediction of interactions with miRNAs. The expression levels of 5 circRNAs interacting with miR-182 were validated using qRT-PCR. Associations between the expression of circUSP42 and clinicopathological features and prognosis were evaluated. A total of 825 upregulated and 1127 downregulated DEcircRNAs were identified between tumor and control groups. Upregulated DEcircRNAs were significantly involved in proteoglycans in cancer, and endocytosis. Downregulated DEcircRNAs were involved in the pathway of resistance to EGFR tyrosine kinase inhibitors. Prediction of circRNA-miRNA interactions showed that hsa_circ_0002032, chr6:131973682-132047340+, hsa_circ_0005982, hsa_circ_0007823 (circUSP42), and hsa_circ_0001777 might act as miRNA sponges for miR-182. qRT-PCR showed consistent results with circRNA sequencing data ( P < 0.05). Downregulation of circUSP42 was significantly associated with lymph node metastasis ( P = 0.005) and advanced clinical stage ( P = 0.032). Furthermore, Kaplan-Meier plots showed that low expression of circUSP42 was closely associated with poor outcome (log-rank test, P < 0.001). Our data suggested that dysregulation of circUSP42 might contribute to the development and progression of TNBC.

We propose a GAN(Generative Adversarial Networks)-based drawing board which takes the semantic (by segmentation) and color tone (by strokes) inputs from users and automatically generates paintings. Our approach is built on a novel and lightweight feature embedding which incorporates the colorization effects into the painting generation process. Unlike the existing GAN-based image generation models which take semantics input, our drawing board has the ability to edit the local colors after generation. Our method samples the color information from users’ strokes as extra input, then feeds it into a GAN model for conditional generation. We enable the creation of pictures or paintings with semantics and color control in real-time.

AIM: To systematically understand the genetic association between methylenetetrahydrofolate reductase (MTHFR) C677T polymorphism and primary open angle glaucoma (POAG). METHODS: A comprehensive literature search in Google Scholar, PubMed, Science Citation Index, Foreign Medical Literature Retrieval Service, Chinese National Knowledge Infrastructure and Wanfang Databases was performed to collect all eligible studies up to August 2019. Study selection, data abstraction and study quality evaluation were performed by two independent investigators. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated to assess the association. RESULTS: Eighteen case-control studies including 2156 cases and 2201 controls were identified. There was no significant difference in the terms of MTHFR C677T polymorphism and POAG in the Caucasian population (for T vs C OR=1.11, 95%CI: 0.88 to 1.39; for TT vs CC OR=1.01, 95%CI: 0.76 to 1.36; for TT+TC vs CC OR=1.15, 95%CI: 0.84 to 1.58 and for TT vs TC+CC OR=1.02, 95%CI: 0.78 to 1.33). However, a significant effect was revealed in the Asian population (for T vs C OR=1.34, 95%CI: 1.12 to 1.59; for TT+TC vs CC OR=1.41, 95%CI: 1.14 to 1.76). CONCLUSION: Based on 18 eligible studies, we provide a correlation between MTHFR C677T polymorphism and POAG among the Asians subgroup indicating that the T allele or TT +TC genotype may play a critical role in POAG development in Asians.

An ongoing outbreak of severe respiratory pneumonia associated with the 2019 novel coronavirus has recently emerged in China. Here we report the epidemiological, clinical, laboratory and radiological characteristics of 19 suspect cases. We compared the positive ratio of 2019-nCoV nucleic acid amplification test results from different samples including oropharyngeal swab, blood, urine and stool with 3 different fluorescent RT-PCR kits. Nine out of the 19 patients had 2019-nCoV infection detected using oropharyngeal swab samples, and the virus nucleic acid was also detected in eight of these nine patients using stool samples. None of positive results was identified in the blood and urine samples. These three different kits got the same result for each sample and the positive ratio of nucleic acid detection for 2019-nCoV was only 47.4% in the suspect patients. Therefore, it is possible that infected patients have been missed by using nucleic acid detection only. It might be better to make a diagnosis combining the computed tomography scans and nucleic acid detection. Keywords: 2019 Novel coronavirus pneumonia, Clinical diagnosis, Nucleic acid amplification test

Tunnel lining cavity is one of the diseases that threaten the safe operation of tunnel, so it has been the attention of test personnel. As a nondestructive testing method, Ground Penetrating Radar (GPR) has been widely used in tunnel lining disease inspection. In order to improve the detection accuracy and success rate of tunnel lining cavities, this paper applies the reverse-time migration (RTM) algorithm to image tunnel lining cavities with high accuracy. Firstly, the principle of GPR pre-stack RTM is described in detail, in which the finite difference time domain (FDTD) method is used to calculate the forward and backward electromagnetic fields, and the normalized cross-correlation imaging condition is used to obtain the RTM results. On this basis, the GPR RTM program is compiled and applied to the simulated dataset of a typical lining cavity GPR model. The comparison of RTM and Kirchhoff migration result showed that the diffracted wave in the steel bar and cavities has good convergence, and the profile’s resolution is improved effectively; In contrast to the Kirchhoff migration result, the RTM result can better focus the radar diffraction wave energy of the steel bars and cavities on the real space location generated by them, weaken the shielding effect of the steel mesh, and suppress multiple interference and clutter scattering waves. Finally, a physical model of lining cavities was detected by GPR, and the RTM algorithm was applied to data processing and interpretation. The RTM delimits the positions of steel mesh and cavities effectively, and the interpretation accuracy of GPR profile has been improved, which provide a scientific and effective way for accurately delimit the scope of tunnel lining cavities.

Objective: This study aimed to analyze the function of metastasis suppressor 1 ( MTSS1) in triple negative breast cancer (TNBC). Methods: MTSS1 expression in 30 TNBC and paracancerous tissues was measured by quantitative reverse transcriptase polymerase chain reaction. The prognostic value of MTSS1 was assessed by Kaplan–Meier analysis followed by the log-rank test. MCF7 cells were transfected with si- MTSS1, while MDA-MB-231 cells were transfected with pcDNA3.1- MTSS1. Cell proliferation assay and transwell assay were performed to investigate the effects of MTSS1 on the biological behavior of breast cancer cells. Immunofluorescence and western blot were used to detect the influence of MTSS1 on epithelial–mesenchymal transition (EMT) markers. Results: MTSS1 expression was significantly lower in TNBC tissues compared with that in paracancerous tissues (0.012 vs. 0.370; P = 0.006). A lower MTSS1 expression level was also found in tumor tissues of patients with lymph node metastasis ( P = 0.002) or tumor node metastasis stage ( P = 0.010). Patients with low expression of MTSS1 (⩽ 0.009) had shorter disease-free survival (47.4 vs. 56.0 months; P = 0.012). The knockdown of MTSS1 in MCF7 cells inhibited cell proliferation, enhanced cell migration and invasion capacities, decreased the E-cadherin level, and increased the vimentin level, whereas overexpression of MTSS1 in MDA-MB-231 cells had the opposite effects ( P < 0.05). Conclusions: Our findings demonstrated that MTSS1 regulates proliferation, invasion, migration, and EMT in TNBC, and that decreased MTSS1 is associated with shorter disease-free survival.

With the development of the Internet, a large number of data sets are generated, which contain valuable resources. Meanwhile, there are various graphical representations in real life, such as social networks, citation networks, and user networks. For user networks, there also exists rich information about entities except the network structure. Therefore, predicting the type of nodes in the network can help us quickly identify user type, citations type etc. In this paper, a new method based on deep learning is proposed to predict the class of node. Two public data sets are used as training sets. First, the node features are embedded to pre-train the neighbor’s neighborhood structure features, then the pre-trained data is used to input to the classification model, and the structural feature parameters are loaded. The final result shows that the prediction accuracy is increased by nearly 25% higher than the baseline model. The F1 scores of the model tested on the two data sets are 83.5% and 80.2%, respectively.

Ultrasonic technology is a promising tool for washing oily sludge to remove oil, however, little information has been provided on the pilot scale application of ultrasonic washing. In this study, the ultrasonic conditions were optimized based on the pilot trial of the effects of ultrasonic properties on oil removal from oily sludge. An ultrasonic power of 0.24 w/cm2 was necessary to overcome the energy threshold for oil washing at the frequency of 25 kHz. The removal rate was changed from 46.0% to 60.7% with oily sludge content from 25.0% to 42.0%, respectively. The addition of surfactants could improve oil recovery, and the optimizing content for sodium petroleum sulfonate and Span 80 was 0.3% and 0.03%, respectively. A series of pilot scale test indicated that the oil removal rate could be 82–90% by ultrasound assistant with surfactants (Span 80). Thin-layer chromatographic flame ionization detection showed that the removal rate by ultrasonic wash was dropped with the increase of composition polarity. However, under the assistance of surfactants (Span 80), all compositions could be effectively removed. This pilot study will greatly improve the application of ultrasonic technology in oily sludge treatment.

Background and purpose Extensive research has been conducted to find neuroimaging biomarkers for psychiatric disorders. This study aimed at identifying trends of the 100 most highly cited articles on neuroimaging in primary psychiatric disorders. Methods The most highly cited original research articles were identified and analyzed, following searches of MEDLINE and Web of Science All Databases. Results The top 100 articles ranked by yearly citation (from 137.5 to 31.1) were published between 1989 and 2017. Depressive disorders (30 articles), schizophrenia spectrum and other psychotic disorders (27), autism spectrum disorder (17), substance-related and addictive disorders (7), and post-traumatic stress disorder (7) were among the most studied conditions. Functional magnetic resonance imaging (42), structural magnetic resonance imaging (30), and positron emission tomography (22) were the most utilized neuroimaging modalities. While 85 articles investigated the pathophysiology of psychiatric disorders (including 7 focusing on developmental changes and 1 on genetic susceptibility), 15 articles studied the impact of treatment, including antidepressants (6), deep brain stimulation (4), antipsychotics (3), behavior therapy (3), and exercise (1). The analysis also identified the most contributing authors, countries (the United States: 71 articles, the United Kingdom: 8, Canada: 5, and China: 5), and journals (JAMA Psychiatry: 20 articles and Biological Psychiatry: 17). Ninety-eight studies were prospective, and two were retrospective. The sample size ranged from 3 to 1,188 (median: 21). Conclusions Our study identified intellectual milestones in the utility of neuroimaging in investigating primary psychiatric disorders. The historic trends could help guide future research in this field.

To estimate the severity of airway abnormalities in cystic fibrosis (CF) Brody et al. developed a computed tomography (CT) scoring system. Each pulmonary lobe is analyzed separately considering various morphological defects. A study from Zhao et al. demonstrates that this CTbased score correlates with regional airway obstruction (RAO) measured by the real-time imaging method Electrical Impedance Tomography (EIT). Zhao et al. performed EIT measurements at the 5th intercostal space (ICS) and median RAO, including both lungs, was correlated with the associated score. In the present feasibility study, it was investigated if RAO determined by EIT within the left and right lung respectively at the 3rd and 5th ICS corresponds with the scores of the left and right lobes. EIT measurements and CT-based scoring were carried out on two CF patients. RAO was identified by ratios of impedance values associated to the maximal forced expiratory flow at 25% and 75% of the forced vital capacity. Mean RAO of each lung within both thorax sections was compared with the lobar scores. Airway abnormalities within upper lobes are assigned to RAO measured within the 3rd ICS, whereas abnormalities of the right middle lobe, both lower lobes and the lingula are mainly represented by EIT images of the 5th ICS. Results show that differences in the CT-based score between the left and right lung concur with differences in EIT derived RAO. The regional information provided by EIT might be used for a more targeted therapy of CF-related lung diseases.

The Raman background arising from optical fiber materials poses a critical problem for fiber optic surface-enhanced Raman spectroscopy (SERS). A novel filter is developed to fit the optical fiber background from the measured SERS spectrum of the target sample. The general model of the filter is built by incorporating a weighted term of matching the similarity between the estimated background spectrum and the measured background spectrum into the classic Savitzky–Golay (SG) smoothing filter model. Through respectively selecting Euclidean cosine coefficient (ECos) and Pearson correlation coefficient (PCor) as the similarity index, two different models of the weighted SG smoothing filter are derived and named as SG-ECos and SG-PCor accordingly. Furthermore, the algorithm is presented, implemented, successfully applied to experimentally measured SERS spectra of rhodamine 6G and crystal violet, and validated with mathematically simulated Raman spectra. Experimental and simulation results show that the SG-ECos filter is effective, fast, flexible, and of certain anti-noise capability in background fitting. It is suggested that the proposed filter may be also applicable for other Raman spectra measurements to remove spectral contaminants originated from sampling substrates such as glass slides.

To compare the outcomes of percutaneous ablation (PA) versus nephrectomy (NE) for small renal masses (SRMs) in patients with T1 renal cell carcinoma and evaluate the role of pre-procedural biopsy in the treatment of SRM. Retrospective cohort analysis of patients subjected to PA or NE for SRM (

Electrical Impedance Tomography (EIT) is a non-invasive, radiation-free imaging method which can be utilized to measure regional lung ventilation distribution in patients with cystic fibrosis (CF). Up to now, the progression of CF-related lung diseases as well as therapy effects are monitored by spirometry or imaging methods such as computed tomography (CT). Since spirometry does not deliver any regional information of the lung function and CT cannot be applied frequently due to radiation, EIT might be a promising method to trace disease progression and therapy effects in CF-related lung diseases. In this preliminary study, the effects of physiotherapeutic breathing therapy on ventilation distribution in CF-related lung disease were investigated. Regional ratios of relative impedance changes corresponding to the forced expiratory volume in one second and the forced vital capacity (ΔIFEV1/ΔIFVC) were determined in three CF patients before and after therapy. Ventilation homogeneity was evaluated by a slightly modified version of the global inhomogeneity index (GIFEV1/FVC). In all three CF patients, variations in regional ratios of ΔIFEV1 and ΔIFVC could be observed, whereby peripheral lung regions seemed to be more affected by the therapy than other lung regions. However, all three CF patients showed a more homogenous ventilation distribution after the physiotherapeutic breathing therapy than before. These first results indicate the suitability of EIT to trace physiotherapeutic breathing therapy effects in CF-related lung disease, which might benefit a more patient-specific therapy.

Purpose: The aim of this study was to identify the top 50 cited articles on the use of cone-beam computed tomography (CBCT) for oral and maxillofacial applications and to summarise the characteristics of the most impactful research articles in this domain. Material and methods: A database was generated by combining the search results from Thomson Reuters Web of Science and Elsevier's Scopus to ensure that all top-cited publications were captured. We used three search fields to generate the database: 1) CBCT, 2) oral and maxillofacial pathologies, and 3) oral and maxillofacial anatomical structures. Publications were then ranked by citation counts and reviewed by two independent reviewers. Results: A total of 50 top publications were included in the study. Their citation count ranged from 43 to 170 with a median of 55.5. Five publications were cited more than 100 times. All except for one paper were published after 2000. The most well published journal was the American Journal of Orthodontics and Dentofacial Orthopedics (n = 12), and the United States of America (n = 15) was the most productive country in the field. The majority of the studies (n = 27) discussed the imaging of primary tooth pathologies, but there are also a significant number of articles that discuss imaging of bone grafts or dental implants (n = 7), upper airways (n = 5), the skull (n = 4), and other maxillofacial structures (n = 7). Conclusions: Our study identifies 50 research articles with the highest number of citations in oral and maxillofacial CBCT, discusses the characteristics and commonalities between these articles, and predicts future trends in the field.

The RANS (Reynolds-averaged Navier–Stokes equations) with CFD (Computational Fluid Dynamics) simulation method is used to analyze the head hump formation mechanism in the double-suction centrifugal pump under a part load condition. The purpose is to establish a clear connection between the head hump and the microcosmic flow field structure, and reveal the influence mechanism between them. It is found that the diffuser stall causes a change in the impeller capacity for work, and this is the most critical reason for hump formation. The change in the hydraulic loss of volute is also a reason for hump, and it is analyzed using the energy balance equation. The hump formation mechanism has not been fully revealed so far. This paper found the most critical flow structure inducing hump and revealed its inducing mechanism, and greatly promoted the understanding of hump formation. The impeller capacity for work is analyzed using torque and rotational speed directly, avoiding large error caused by the Euler head formula, greatly enhancing the accuracy of establishing the connection between the impeller capacity for work and the coherent structure in the flow field under a part load condition. When a pump is running in the hump area, a strong vibration and noise are prone to occur, endangering the pump safety and reliability, and even the pump start and the transition of different working conditions may be interrupted. Revealing the hump formation mechanism provides a key theoretical basis for suppressing hump. Hump problems are widespread in many kinds of pumps, causing a series of troubles and hazards. The analysis method in this paper also provides a reference for other pumps.

Electrical impedance tomography (EIT) has mostly been used in the Intensive Care Unit (ICU) to monitor ventilation distribution but is also promising for the diagnosis in spontaneously breathing patients with obstructive lung diseases. Beside tomographic images, several numerical measures have been proposed to quantitatively assess the lung state. In this study two common measures, the 'Global Inhomogeneity Index' and the 'Coefficient of Variation' were compared regarding their capability to reflect the severity of lung obstruction. A three-dimensional simulation model was used to simulate obstructed lungs, whereby images were reconstructed on a two-dimensional domain. Simulations revealed that minor obstructions are not adequately recognized in the reconstructed images and that obstruction above and below the electrode plane may result in misleading values of inhomogeneity measures. EIT measurements on several electrode planes are necessary to apply these measures in patients with obstructive lung diseases in a promising manner.

The doubly selective (DS) channel estimation in the large-scale multiple-input multiple-output (MIMO) systems is a challenging problem due to the large number of the channel coefficients to be estimated, which requires unaffordable and prohibitive pilot overhead. In this paper, first we conduct the analysis about the common sparsity of the basis expansion model (BEM) coefficients among all the BEM orders and all the transmit–receive antenna pairs. Then, a novel pilot pattern is proposed, which inserts the guard pilots to deal with the intercarrier interference under the superimposed pilot pattern. Moreover, by exploiting the common sparsity of the BEM coefficients among different BEM orders and different antennas, we propose a block distributed compressive sensing-based DS channel estimator for the large-scale MIMO systems. Its structured sparsity leads to the reduction of the pilot overhead under the premise of guaranteeing the accuracy of the estimation. Furthermore, taking consideration of the block structure, a pilot design algorithm referred to as block discrete stochastic optimization is proposed. It optimizes the pilot positions by reducing the coherence among different blocks of the measurement matrix. Besides, a linear smoothing method is extended to large-scale MIMO systems to improve the accuracy of the estimation. Simulation results verify the performance gains of our proposed estimator and the pilot design algorithm compared with the existing schemes.

Orthogonal frequency-division multiplexing (OFDM) and multicell architecture are widely adopted in current high-speed train (HST) systems for providing high-data-rate wireless communications. In this paper, a typical multiantenna OFDM HST communication system with multicell architecture is considered, where the intercarrier interference (ICI) caused by high mobility and the multicell interference (MCI) are both taken into consideration. By exploiting the train position information, a new position-based interference elimination method is proposed to eliminate both the MCI and the ICI for a general basis expansion model. We show that the MCI and the ICI can be completely eliminated by the proposed method to get the ICI-free pilots at each receive antenna. In addition, for the considered multicell HST system, we develop a low-complexity compressed channel estimation method and consider the optimal pilot pattern design. Both the proposed interference elimination method and the optimal pilot pattern are robust to the train speed and position, as well as the multicell multiantenna system. Simulation results demonstrate the benefits and robustness of the proposed method in the multicell HST system.

Purpose: Many genes have been associated with primary open-angle glaucoma (POAG). This study was conducted to investigate whether catalase (CAT) polymorphisms play a significant role in POAG in a Chinese population. Methods: A cohort of 416 unrelated POAG patients and 997 unrelated control subjects was included in this case–control association study. CAT functional single-nucleotide polymorphisms (SNPs), including rs1001179, rs7943316, and rs769217, were genotyped by SNaPshot method. The genotype and allele frequencies were evaluated using the χ2 tests. The linkage disequilibrium (LD) and haplotype block structure association were examined using the program Haploview (Broad Institute, Cambridge, MA). Results: There was a statistically significant difference for CAT functional SNP rs769217 between POAG cases and controls in the allelic model (p = 0.004, OR = 1.27, 95% CI 1.08–1.49). At this SNP, the allele frequency of the C allele in POAG cases was 0.587, which was higher than that in controls (0.528). However, no association was found for rs1001179 and rs7943316 with POAG. Pairwise LD analysis showed high LD between rs769217 and rs7943316 (D’ = 0.857, r2 = 0.252, confidence bounds 0.71–0.93). After the association analysis for haplotype block structure generated from rs769217 with rs7943316, the data showed no significant association between the cases and controls. Conclusions: This study showed that CAT functional SNP rs769217 was significantly associated with POAG, implying that the CAT gene variants may play a role in the pathogenesis of POAG in the Chinese population.

ObjectiveTo investigate the role of diagnostic imaging in the clinical diagnosis, treatment, and follow-up management of patients in response to disasters.MethodsA MEDLINE (OVID) search of original research articles identified 177 articles on this topic published since 2000. A bibliometric analysis was conducted on the top 100 articles ranked by average yearly citation.ResultsThe most frequently studied disaster categories were disease outbreak (55 articles), armed conflict (23 articles), terrorist incident (10 articles), and earthquake (7 articles). The most studied disasters were the H1N1 influenza outbreak in 2009 (28 articles), Severe Acute Respiratory Syndrome outbreak in 2003 (24 articles), War in Afghanistan, 2001-2014 (8 articles), Iraq War, 2003-2011 (6 articles), and the Sichuan earthquake (China) in 2008 (6 articles). Among the first authors, 59 were primarily affiliated with Radiology. The United States of America produced the most articles (25 articles), followed by the People’s Republic of China (24 articles). Eighty-one studies were retrospective, with 19 studies being prospective. Computed tomography was the most investigated modality (52.8%), followed by conventional radiography (33.3%) and ultrasound (9.7%).ConclusionsOur study identifies intellectual milestones in the utility of diagnostic imaging in response to various disasters, and could help guide future research in developing disaster management plans. (Disaster Med Public Health Preparedness. 2018;12:265–277)

Electrical impedance tomography (EIT) has the potential to measure ventilation and perfusion related impedance changes in the lung. Ventilation heterogeneity has already been confirmed by EIT in patients with obstructive lung diseases, such as chronic obstructive pulmonary disease (COPD) or cystic fibrosis (CF). In the present study, ventilation and cardiac/perfusion associated impedance changes (∆IV and ∆IC) were investigated in 12 CF patients. Differences in ∆IV and ∆IC ratios over the course of inspiration and expiration during normal tidal breathing were analyzed. Significant differences in ∆IV/∆IC within the expiration were determined (p

Electrical Impedance Tomography (EIT) is a medical imaging modality which is mainly used in mechanically ventilated patients to monitor the regional distribution of ventilation. Recently, the potential of EIT has also been demonstrated as additional tool for diagnosis in spontaneously breathing patients with obstructive lung diseases, such as cystic fibrosis or chronic obstructive lung disease. Besides the generation of images depicting lung ventilation in real-time, EIT also provides quantitative measures to numerically describe the inhomogeneity of ventilation. In this work the impact of ventilation inhomogeneity and lung obstruction on the reconstructed EIT images is evaluated using three dimensional simulation models with different severities of obstruction. Simulation results reveal that the ventilation inhomogeneity determined with EIT raises for increasing and more severe obstructions. For obstructions affecting less than 25% of lung tissue the ventilation inhomogeneity in EIT images underestimates the disease state.

In this paper, a novel approach was developed for the enhanced growth of ZnO nanowires on optical fiber surface. The method combined a hydrothermal process with the efficient UV irradiation from the fiber core, and the effects of UV irradiation on the growth behavior of ZnO nanowires were investigated. The results show that UV irradiation had great effects on the preferred growth orientation and the quality of the ZnO nanowires. The crystallization velocity along the c-axis would increase rapidly with the increase of the irradiation power, while the growth process in the lateral direction was marginally affected by the irradiation. The structure of ZnO nanowires also shows less oxygen vacancy with UV irradiation of higher power. The developed approach is applicable for the efficient growth of nanowires on the fiber surface, and the ZnO nanowires/optical fiber hybrid structures have great potentials for a wide variety of applications such as optical fiber sensors and probes.

In this work, the gas sensor based on a novel ZnO nanowires/optical fiber hybrid structure was proposed in order to enhance the sensing properties of ethanol detection with UV irradiation. The results showed that UV irradiation was able to enhance the sensitivity and shorten the response time, and the sensor performed a good long-term stability as well. The UV-assisted sensor could response to the low concentration at ppb-level of ethanol at relatively lower temperatures, and a sensing mechanism was proposed to understand the effect of UV irradiation in the ethanol detection process. The gas sensor based on the ZnO nanowires/optical fiber hybrid structure is practical for detecting gas with ultra-low concentration and the combination of UV irradiation is an effective approach to develop high-performance gas sensors.

We propose a bi-objective optimization model for extracting optical fiber background from the measured surface-enhanced Raman spectroscopy (SERS) spectrum of the target sample in the application of fiber optic SERS. The model is built using curve fitting to resolve the SERS spectrum into several individual bands, and simultaneously matching some resolved bands with the measured background spectrum. The Pearson correlation coefficient is selected as the similarity index and its maximum value is pursued during the spectral matching process. An algorithm is proposed, programmed, and demonstrated successfully in extracting optical fiber background or fluorescence background from the measured SERS spectra of rhodamine 6G (R6G) and crystal violet (CV). The proposed model not only can be applied to remove optical fiber background or fluorescence background for SERS spectra, but also can be transferred to conventional Raman spectra recorded using fiber optic instrumentation.

// Dingding Zhang 1, * , Xiaoxin Guo 1, * , Jinliang Hu 2, 3, * , Guangqun Zeng 4 , Maomin Huang 1, 5 , Dandan Qi 1 , Bo Gong 1 1 Sichuan Provincial Key Laboratory for Disease Gene Study, Hospital of University of Electronic Science and Technology of China and Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan, 610072, China 2 Institute of Health Policy and Hospital Management, Sichuan Academy of Medical Science and Sichuan Provincial People’s Hospital, Chengdu, Sichuan, 610072, China 3 School of Public Health, Sichuan University, Chengdu, Sichuan, 610041, China 4 Department of Clinical Laboratory, People’s Hospital of Pengzhou, Pengzhou, Sichuan, 611930, China 5 Department of Immunology, Zunyi Medical College, Zunyi, Guizhou, 563000, China * These authors contributed equally to this study Correspondence to: Bo Gong, email: gongbo2007@hotmail.com Keywords: gastric cancer, meta-analysis, hOGG1 rs1052133, association Received: January 10, 2017 Accepted: March 04, 2017 Published: March 11, 2017 ABSTRACT Purpose: To conduct a comprehensive evaluation of the association of the human8-oxoguanine glycosylase 1 ( hOGG1 ) gene polymorphism rs1052133 with gastric cancer (GC) through a systematic review and meta-analysis of genetic association study. Results: A total of 15 articles from published papers were included in our analysis. The meta-analyses for hOGG1 rs1052133, composed of 4024GC patients and 6022controls, showed low heterogeneity for the included populations in all the genetic models, except for the Caucasian population under allelic genetic model, the Asian population under addictive model and Caucasian population under dominant model. The analyses of all the genetic models in overall pooled populations did not identify any significant association between GC and hOGG1 rs1052133 (Allelic model: C vs. G , p = 0.746; Addictive model: CC vs. GG, p = 0.888; Recessive model: CC +GC vs. GG, p = 0.628; Dominant model: CC vs. GG+GC, p = 0.147), even though stratified analyses were conducted in different ethnicities under each genetic model. Materials and Methods: All case-control association studies on hOGG1 and GC reported up to December 15, 2016 in PubMed, Embase, Web of Science, and the Chinese Biomedical Database were retrieved. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated for single-nucleotide polymorphism (SNP) using fixed- and random- effects models according to between-study heterogeneity. Publication bias analyses were conducted using Begg test. Conclusions: This meta-analysis showed there was no association between hOGG1 rs1052133 and GC. Given the limited sample size, further investigations including more ethnic groups are required to validate the association.