Minutes-duration optical flares with supernova luminosities.

In recent years, certain luminous extragalactic optical transients have been observed to last only a few days1. Their short observed duration implies a different powering mechanism from the most common luminous extragalactic transients (supernovae), whose timescale is weeks2. Some short-duration transients, most notably AT2018cow (ref. 3), show blue optical colours and bright radio and X-ray emission4. Several AT2018cow-like transients have shown hints of a long-lived embedded energy source5, such as X-ray variability6,7, prolonged ultraviolet emission8, a tentative X-ray quasiperiodic oscillation9,10 and large energies coupled to fast (but subrelativistic) radio-emitting ejecta11,12. Here we report observations of minutes-duration optical flares in the aftermath of an AT2018cow-like transient, AT2022tsd (the 'Tasmanian Devil'). The flares occur over a period of months, are highly energetic and are probably nonthermal, implying that they arise from a near-relativistic outflow or jet. Our observations confirm that, in some AT2018cow-like transients, the embedded energy source is a compact object, either a magnetar or an accreting black hole.

Six-Transmembrane Epithelial Antigen of Prostate 3 Promotes Hepatic Insulin Resistance and Steatosis.

Nonalcoholic fatty liver disease (NAFLD) is a clinicopathological syndrome characterized by excessive deposition of fatty acids in the liver. Further deterioration leads to nonalcoholic steatohepatitis, cirrhosis, and hepatocellular carcinoma, creating a heavy burden on human health and the social economy. Currently, there are no effective and specific drugs for the treatment of NAFLD. Therefore, it is important to further investigate the pathogenesis of NAFLD and explore effective therapeutic targets for the prevention and treatment of the disease. Six-transmembrane epithelial antigen of prostate 3 (STEAP3), a STEAP family protein, is a metalloreductase. Studies have shown that it can participate in the regulation of liver ischemia-reperfusion injury, hepatocellular carcinoma, myocardial hypertrophy, and other diseases. In this study, we found that the expression of STEAP3 is upregulated in NAFLD. Deletion of STEAP3 inhibits the development of NAFLD in vivo and in vitro, whereas its overexpression promotes palmitic acid/oleic acid stimulation-induced lipid deposition in hepatocytes. Mechanistically, it interacts with transforming growth factor beta-activated kinase 1 (TAK1) to regulate the progression of NAFLD by promoting TAK1 phosphorylation and activating the TAK1-c-Jun N-terminal kinase/p38 signaling pathway. Taken together, our results provide further insight into the involvement of STEAP3 in liver pathology.

Calcium Scoring at Coronary CT Angiography Using Deep Learning.

Background Separate noncontrast CT to quantify the coronary artery calcium (CAC) score often precedes coronary CT angiography (CTA). Quantifying CAC scores directly at CTA would eliminate the additional radiation produced at CT but remains challenging. Purpose To quantify CAC scores automatically from a single CTA scan. Materials and Methods In this retrospective study, a deep learning method to quantify CAC scores automatically from a single CTA scan was developed on training and validation sets of 292 patients and 73 patients collected from March 2019 to July 2020. Virtual noncontrast scans obtained with a spectral CT scanner were used to develop the algorithm to alleviate tedious manual annotation of calcium regions. The proposed method was validated on an independent test set of 240 CTA scans collected from three different CT scanners from August 2020 to November 2020 using the Pearson correlation coefficient, the coefficient of determination, or r2, and the Bland-Altman plot against the semiautomatic Agatston score at noncontrast CT. The cardiovascular risk categorization performance was evaluated using weighted κ based on the Agatston score (CAC score risk categories: 0-10, 11-100, 101-400, and >400). Results Two hundred forty patients (mean age, 60 years ± 11 [standard deviation]; 146 men) were evaluated. The positive correlation between the automatic deep learning CTA and semiautomatic noncontrast CT CAC score was excellent (Pearson correlation = 0.96; r2 = 0.92). The risk categorization agreement based on deep learning CTA and noncontrast CT CAC scores was excellent (weighted κ = 0.94 [95% CI: 0.91, 0.97]), with 223 of 240 scans (93%) categorized correctly. All patients who were miscategorized were in the direct neighboring risk groups. The proposed method's differences from the noncontrast CT CAC score were not statistically significant with regard to scanner (P = .15), sex (P = .051), and section thickness (P = .67). Conclusion A deep learning automatic calcium scoring method accurately quantified coronary artery calcium from CT angiography images and categorized risk. © RSNA, 2021 See also the editorial by Goldfarb and Cao et al in this issue.

Repetitive patterns in rapid optical variations in the nearby black-hole binary V404 Cygni.

How black holes accrete surrounding matter is a fundamental yet unsolved question in astrophysics. It is generally believed that matter is absorbed into black holes via accretion disks, the state of which depends primarily on the mass-accretion rate. When this rate approaches the critical rate (the Eddington limit), thermal instability is supposed to occur in the inner disk, causing repetitive patterns of large-amplitude X-ray variability (oscillations) on timescales of minutes to hours. In fact, such oscillations have been observed only in sources with a high mass-accretion rate, such as GRS 1915+105 (refs 2, 3). These large-amplitude, relatively slow timescale, phenomena are thought to have physical origins distinct from those of X-ray or optical variations with small amplitudes and fast timescales (less than about 10 seconds) often observed in other black-hole binaries-for example, XTE J1118+480 (ref. 4) and GX 339-4 (ref. 5). Here we report an extensive multi-colour optical photometric data set of V404 Cygni, an X-ray transient source containing a black hole of nine solar masses (and a companion star) at a distance of 2.4 kiloparsecs (ref. 8). Our data show that optical oscillations on timescales of 100 seconds to 2.5 hours can occur at mass-accretion rates more than ten times lower than previously thought. This suggests that the accretion rate is not the critical parameter for inducing inner-disk instabilities. Instead, we propose that a long orbital period is a key condition for these large-amplitude oscillations, because the outer part of the large disk in binaries with long orbital periods will have surface densities too low to maintain sustained mass accretion to the inner part of the disk. The lack of sustained accretion--not the actual rate--would then be the critical factor causing large-amplitude oscillations in long-period systems.

Integrative Predictive Models of Computed Tomography Texture Parameters and Hematological Parameters for Lymph Node Metastasis in Lung Adenocarcinomas.

OBJECTIVES: The aims of the study were to integrate characteristics of computed tomography (CT), texture, and hematological parameters and to establish predictive models for lymph node (LN) metastasis in lung adenocarcinoma. METHODS: A total of 207 lung adenocarcinoma cases with confirmed postoperative pathology and preoperative CT scans between February 2017 and April 2019 were included in this retrospective study. All patients were divided into training and 2 validation cohorts chronologically in the ratio of 3:1:1. The χ2 test or Fisher exact test were used for categorical variables. The Shapiro-Wilk test and Mann-Whitney U test were used for continuous variables. Logistic regression and machine learning algorithm models based on CT characteristics, texture, and hematological parameters were used to predict LN metastasis. The performance of the multivariate models was evaluated using a receiver operating characteristic curve; prediction performance was evaluated in the validation cohorts. Decision curve analysis confirmed its clinical utility. RESULTS: Logistic regression analysis demonstrated that pleural thickening (P = 0.013), percentile 25th (P = 0.033), entropy gray-level co-occurrence matrix 10 (P = 0.019), red blood cell distribution width (P = 0.012), and lymphocyte-to-monocyte ratio (P = 0.049) were independent risk factors associated with LN metastasis. The area under the curve of the predictive model established using the previously mentioned 5 independent risk factors was 0.929 in the receiver operating characteristic analysis. The highest area under the curve was obtained in the training cohort (0.777 using Naive Bayes algorithm). CONCLUSIONS: Integrative predictive models of CT characteristics, texture, and hematological parameters could predict LN metastasis in lung adenocarcinomas. These findings may provide a reference for clinical decision making.

MiR-337 suppresses pancreatic cancer development via STAT3/Wnt/ß-catenin axis.

MiRNA is an important regulator of tumorigenesis and tumor progression. MiR-337 expression was increased in pancreatic cancer tissues and it was associated with patients' survival. This study aimed to explore the influence and the potential working mechanism of miR-337 on the malignant behaviors of pancreatic cancer cells. MiR-337 expression was detected by qRT-PCR. The expression levels of STAT3, epithelial-mesenchymal transition-related genes and Wnt/ß-Catenin pathway genes were evaluated by qRT-PCR and western blot. Cell counting kit -8 and colony formation assays were conducted to examine the proliferation of AsPC-1 and SW1990 cells. Wound healing and transwell assays were performed to determine the migration and invasion of AsPC-1 and SW1990 cells. The predicted target gene of miR-337 was verified by luciferase reporter assay. The expression of miR-337 was decreased and STAT3 expression was increased in pancreatic cancer tissues as well as tumor cells. Overexpression of miR-337 suppressed proliferation, invasion and migration of AsPC-1 and SW1990 cells. MiR-337 targeted 3'UTR of STAT3 and inhibited STAT3 expression. In addition, exogenous STAT3 partially restored the inhibitory role of miR-337 on proliferation, invasion and migration of AsPC-1 and SW1990 cells. Moreover, miR-337 impeded the expression of Wnt/ß-catenin pathway-related genes. Through the saving experiment, we found that the inhibitory effect of miR-337 on AsPC-1 and SW1990 cells was abolished by the addition of LiCl. These outcomes expounded that miR-337 inactivated the Wnt/ß-catenin pathway to suppress the malignant behaviors of pancreatic cancer cells through targeting STAT3. This study may provide a novel biomarker for diagnosis and a new therapeutic target for pancreatic cancer treatment.

Effect of Times to Blood Processing on the Stability of Blood Proteins Associated with Dementia.

BACKGROUND: The stability of proteins in the collecting tubes after blood draw is critical to the measured concentrations of the proteins. Although the guidelines issued by the Clinical and Laboratory Standards Institute (CLSI) suggest centrifugation should take place within 2 h of drawing blood, it is very difficult to follow these guidelines in hospitals or clinics. It is necessary to study the effect of times to blood processing on the stability of the proteins of interest. METHODS: In this work, the plasma proteins of interest were those relevant to dementia, such as amyloid ß 1-40 (Aß1-40), Aß1-42, Tau protein (Tau), and α-synuclein. The times to blood processing after blood draw ranged from 0.5 to 8 h. The storage temperatures of blood were room temperature (approx. 25°C) and 30°C. After storage, blood samples were centrifuged at room temperature to obtain plasma samples. Ultrasensitive immunomagnetic reduction was applied to assay these proteins in the plasma. RESULTS: The levels of plasma Aß1-40, Tau, and α-synuclein did not significantly change until 8 h after blood draw when stored at room temperature. Plasma Aß1-42 levels did not change significantly after 8 h of storage at room temperature before blood processing. Higher storage temperatures, such as 30°C, for blood samples accelerated the significant variations in the measured concentrations of Aß1-40, Tau, and α-synuclein in plasma. CONCLUSION: According to these results, for clinical practice, it is suggested that blood samples be stored at room temperature for no longer than 4.5 h after blood draw until centrifugation for the assay of dementia biomarkers in plasma.

Ultra-compact dual-polarization silicon mode-order converter.

The mode-order converter is a building block in a multimode optical transmission and switching system. It can be used for switching signals carried on different mode channels. However, such devices constructed by conventional structures can commonly accomplish one mode-order conversion process. It is because the phase-matching condition, which is utilized by a majority of designs, can usually be fulfilled between only one mode pair for specific device geometry. In this Letter, we propose a dual-polarization mode-order converter referring to the concept of a silicon planar metasurface. It can realize mode-order conversions on transverse electrical and transverse magnetic polarizations in parallel. In order to verify our concept, we design and experimentally demonstrate a prototype that can realize conversions from TE0 to TE1 and from TM0 to TM1 simultaneously. The footprint is 4 µm×1.6 µm. The measured insertion losses for both polarizations are smaller than 2.3 dB, and the crosstalk is lower than -11.5 dB within the wavelength range of 1525-1565 nm. We envision that the device can be a building block in polarization and mode multiplexed optical switching systems and endow the systems with simpler structure and a more compact footprint.

Proteome Scale-Protein Turnover Analysis Using High Resolution Mass Spectrometric Data from Stable-Isotope Labeled Plants.

Protein turnover is an important aspect of the regulation of cellular processes for organisms when responding to developmental or environmental cues. The measurement of protein turnover in plants, in contrast to that of rapidly growing unicellular organismal cultures, is made more complicated by the high degree of amino acid recycling, resulting in significant transient isotope incorporation distributions that must be dealt with computationally for high throughput analysis to be practical. An algorithm in R, ProteinTurnover, was developed to calculate protein turnover with transient stable isotope incorporation distributions in a high throughput automated manner using high resolution MS and MS/MS proteomic analysis of stable isotopically labeled plant material. ProteinTurnover extracts isotopic distribution information from raw MS data for peptides identified by MS/MS from data sets of either isotopic label dilution or incorporation experiments. Variable isotopic incorporation distributions were modeled using binomial and beta-binomial distributions to deconvolute the natural abundance, newly synthesized/partial-labeled, and fully labeled peptide distributions. Maximum likelihood estimation was performed to calculate the distribution abundance proportion of old and newly synthesized peptides. The half-life or turnover rate of each peptide was calculated from changes in the distribution abundance proportions using nonlinear regression. We applied ProteinTurnover to obtain half-lives of proteins from enriched soluble and membrane fractions from Arabidopsis roots.

Morphology, morphogenesis and molecular phylogeny of an oxytrichid ciliate, Rubrioxytricha haematoplasma (Blatterer & Foissner, 1990) Berger, 1999 (Ciliophora, Hypotricha).

The morphology and morphogenesis of an oxytrichid ciliate, Rubrioxytricha haematoplasma (Blatterer & Foissner, 1990) Berger, 1999, collected from brackish and marine waters in China, were investigated using live observation and the protargol staining method. The main features of the morphogenetic process are: (i) the parental adoral zone of membranelles is retained completely in the proter and the anlage of undulating membranes originates from dedifferentiation of the old structures; (ii) three frontal, four frontoventral, one buccal, five ventral and five transverse cirri are derived from the anlagen of the undulating membranes and the five streaks of frontal-ventral-transverse anlagen in the pattern of 1:3:3:3:4:4 from left to right; (iii) the morphogenesis of the dorsal kineties is simpler than the Oxytricha pattern, i.e. without fragmentation of the dorsal kinety 3 anlagen; (iv) the single caudal cirrus originates from the dorsal kinety 3 anlage on the right side; (v) the two macronuclear nodules fuse into a single mass during the mid-stage of morphogenesis. These features correspond well with Rubrioxytricha indica, indicating that the morphogenetic pattern of Rubrioxytricha is stable. Phylogenetic analysis based on small-subunit rRNA gene sequence data supports the monophyly of the genus Rubrioxytricha, which is nested within the non-Stylonychinae clade.

Stapled transperineal rectovaginal fistula repair for low- and mid-level rectovaginal fistulas: A comparison study with rectal mucosal advancement flap repair.

BACKGROUND: As an innovative treatment, stapled transperineal rectovaginal fistula repair (STR) for rectovaginal fistula (RVF) has demonstrated effectiveness in preliminary reports. This study aims to compare STR with rectal mucosal advancement flap repair (RAF), a widely utilized surgical procedure, for the surgical outcome of the low- and mid-level RVF. METHODS: In this retrospective cohort study, patients with low- and mid-level RVF who underwent STR or RAF were included from both the Sixth Affiliated Hospital of Sun Yat-sen University and Xi'an Daxing Hospital. Among the 99 total patients, 77 underwent STR and 22 underwent RAF. Patient demographics, operative data, and outcomes were collected and analyzed. Recurrence rate and associated risk factors were evaluated. RESULTS: There were no statistically significant differences among patients in terms of clinical characteristics like age, BMI, aetiology, and fistula features. During the follow-up period of 20 months (interquartile range 3.0-41.8 months), a total of 28 patients relapsed, with a significantly lower recurrence rate in the STR group (20.8 %) than in the RAF group (54.6 %) (P = 0.005). In the multivariate Cox analysis, STR was an independent protective factor against recurrence (HR: 0.37, 95%CI: 0.17-0.79, P = 0.01). Logistic regression indicated that there was no statistically significant difference between these two procedures in terms of surgical complications (OR: 0.53, 95%CI: 0.19-1.48, P = 0.23). CONCLUSION: For low- and mid-level RVF, STR may be an alternative option for treatment modality that offers a lower recurrence rate, without observed disadvantage in terms of surgical complication rates.

Automated detection and classification of coronary atherosclerotic plaques on coronary CT angiography using deep learning algorithm.

Background: Coronary artery disease (CAD) is the leading cause of mortality worldwide. Recent advances in deep learning technology promise better diagnosis of CAD and improve assessment of CAD plaque buildup. The purpose of this study is to assess the performance of a deep learning algorithm in detecting and classifying coronary atherosclerotic plaques in coronary computed tomographic angiography (CCTA) images. Methods: Between January 2019 and September 2020, CCTA images of 669 consecutive patients with suspected CAD from Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine were included in this study. There were 106 patients included in the retrospective plaque detection analysis, which was evaluated by a deep learning algorithm and four independent physicians with varying clinical experience. Additionally, 563 patients were included in the analysis for plaque classification using the deep learning algorithm, and their results were compared with those of expert radiologists. Plaques were categorized as absent, calcified, non-calcified, or mixed. Results: The deep learning algorithm exhibited higher sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy {92% [95% confidence interval (CI): 89.5-94.1%], 87% (95% CI: 84.2-88.5%), 79% (95% CI: 76.1-82.4%), 95% (95% CI: 93.4-96.3%), and 89% (95% CI: 86.9-90.0%)} compared to physicians with ≤5 years of clinical experience in CAD diagnosis for the detection of coronary plaques. The algorithm's overall sensitivity, specificity, PPV, NPV, accuracy, and Cohen's kappa for plaque classification were 94% (95% CI: 92.3-94.7%), 90% (95% CI: 88.8-90.3%), 70% (95% CI: 68.3-72.1%), 98% (95% CI: 97.8-98.5%), 90% (95% CI: 89.8-91.1%) and 0.74 (95% CI: 0.70-0.78), indicating strong performance. Conclusions: The deep learning algorithm has demonstrated reliable and accurate detection and classification of coronary atherosclerotic plaques in CCTA images. It holds the potential to enhance the diagnostic capabilities of junior radiologists and junior intervention cardiologists in the CAD diagnosis, as well as to streamline the triage of patients with acute coronary symptoms.

A multi-view contrastive learning for heterogeneous network embedding.

Graph contrastive learning has been developed to learn discriminative node representations on homogeneous graphs. However, it is not clear how to augment the heterogeneous graphs without substantially altering the underlying semantics or how to design appropriate pretext tasks to fully capture the rich semantics preserved in heterogeneous information networks (HINs). Moreover, early investigations demonstrate that contrastive learning suffer from sampling bias, whereas conventional debiasing techniques (e.g., hard negative mining) are empirically shown to be inadequate for graph contrastive learning. How to mitigate the sampling bias on heterogeneous graphs is another important yet neglected problem. To address the aforementioned challenges, we propose a novel multi-view heterogeneous graph contrastive learning framework in this paper. We use metapaths, each of which depicts a complementary element of HINs, as the augmentation to generate multiple subgraphs (i.e., multi-views), and propose a novel pretext task to maximize the coherence between each pair of metapath-induced views. Furthermore, we employ a positive sampling strategy to explicitly select hard positives by jointly considering semantics and structures preserved on each metapath view to alleviate the sampling bias. Extensive experiments demonstrate MCL consistently outperforms state-of-the-art baselines on five real-world benchmark datasets and even its supervised counterparts in some settings.

PPNet: Pyramid pooling based network for polyp segmentation.

Colonoscopy is the gold standard method for investigating the gastrointestinal tract. Localizing the polyps in colonoscopy images plays a vital role when doing a colonoscopy screening, and it is also quite important for the following treatment, e.g., polyp resection. Many deep learning-based methods have been applied for solving the polyp segmentation issue. However, precisely polyp segmentation is still an open issue. Considering the effectiveness of the Pyramid Pooling Transformer (P2T) in modeling long-range dependencies and capturing robust contextual features, as well as the power of pyramid pooling in extracting features, we propose a pyramid pooling based network for polyp segmentation, namely PPNet. We first adopt the P2T as the encoder for extracting more powerful features. Next, a pyramid feature fusion module (PFFM) combining the channel attention scheme is utilized for learning a global contextual feature, in order to guide the information transition in the decoder branch. Aiming to enhance the effectiveness of PPNet on feature extraction during the decoder stage layer by layer, we introduce the memory-keeping pyramid pooling module (MPPM) into each side branch of the encoder, and transmit the corresponding feature to each lower-level side branch. Experimental results conducted on five public colorectal polyp segmentation datasets are given and discussed. Our method performs better compared with several state-of-the-art polyp extraction networks, which demonstrate the effectiveness of the mechanism of pyramid pooling for colorectal polyp segmentation.

Codelivery of dihydroartemisinin and chlorin e6 by copolymer nanoparticles enables boosting photodynamic therapy of breast cancer with low-power irradiation.

Given that chemotherapy as a stand-alone therapeutic strategy may not be sufficient to effectively treat cancer, there is increasing interest in combination of chemotherapy and alternative therapies. Photodynamic therapy has the advantages of high selectivity and low side effects, so the combination of photodynamic therapy and chemotherapy has become one of the most appealing strategies for tumor treatment. In this work, we constructed a nano drug codelivery system (PPDC) to realize the combined treatment of chemotherapy and photodynamic therapy through encapsulating chemotherapeutic drug dihydroartemisinin and photosensitizer chlorin e6 in PEG-PCL. The potentials, particle size and morphology of nanoparticles were characterized by dynamic light scattering and transmission electron microscopy. We also investigated the reactive oxygen species (ROS) generation and drug release ability. The antitumor effect in vitro was investigated by methylthiazolyldiphenyl-tetrazolium bromide assays and cell apoptosis experiments, and the potential cell death mechanisms were explored by ROS detection and Western blot analysis. The in vivo antitumor effect of PPDC was evaluated under the guidance of fluorescence imaging. Our work provides a potential antitumor treatment approach and expands the application of dihydroartemisinin for breast cancer therapy.

Development and validation of radiomics nomograms for preoperative prediction of characteristics in non-small cell lung cancer and circulating tumor cells.

To develop and validate 3 radiomics nomograms for preoperative prediction of pathological and progression diagnosis in non-small cell lung cancer (NSCLC) as well as circulating tumor cells (CTCs). A total of 224 and 134 patients diagnosed with NSCLC were respectively gathered in 2018 and 2019 in this study. There were totally 1197 radiomics features that were extracted and quantified from the images produced by computed tomography. Then we selected the radiomics features with predictive value by least absolute shrinkage and selection operator and combined them into radiomics signature. Logistic regression models were built using radiomics signature as the only predictor, which were then converted to nomograms for individualized predictions. Finally, the performance of the nomograms was assessed on both cohorts. Additionally, immunohistochemical correlation analysis was also performed. As for discrimination, the area under the curve of pathological diagnosis nomogram and progression diagnosis nomogram in NSCLC were both higher than 90% in the training cohort and higher than 80% in the validation cohort. The performance of the CTC-diagnosis nomogram was somehow unexpected where the area under the curve were range from 60% to 70% in both cohorts. As for calibration, nonsignificant statistics (P > .05) yielded by Hosmer-Lemeshow tests suggested no departure between model prediction and perfect fit. Additionally, decision curve analyses demonstrated the clinically usefulness of the nomograms. We developed radiomics-based nomograms for pathological, progression and CTC diagnosis prediction in NSCLC respectively. Nomograms for pathological and progression diagnosis were demonstrated well-performed to facilitate the individualized preoperative prediction, while the nomogram for CTC-diagnosis prediction needed improvement.

Potentially functional polymorphisms in DNA repair genes and non-small-cell lung cancer survival: a pathway-based analysis.

To assess systematically whether potentially functional polymorphisms in DNA repair genes influence the clinical behavior of non-small-cell lung cancer (NSCLC), we examined the impact of a comprehensive panel of 218 signal nucleotide polymorphisms (SNP) in 50 candidate DNA repair genes on overall survival of NSCLC in a case-cohort of 568 lung cancer patients. SNPs associated with lung cancer prognosis primarily mapped to 14 genes in different repair pathways, and 6 SNPs were remained in the final model after multivariate stepwise Cox regression analysis: ATM rs189037; MRE11A rs11020802; ERCC2 rs1799793; MBD4 rs140693; XRCC1 rs25487, and PMS1 rs5742933. In the combined analysis of these 6 SNPs, an increasing number of unfavorable loci was associated with a poorer prognosis (P for trend: <0.0001) and patients having 2-4 unfavorable loci had a 1.99-fold elevated risk of death 95% confidence interval (CI) = 1.58-2.50, compared with those carrying 0-1 unfavorable loci, and this elevated risk was more evident among stages I-II patients (hazard ratio = 3.04, 95% CI = 1.86-4.98, P for heterogeneity: 0.07). Furthermore, a significant effect of SNPs in nucleotide excision repair pathway on lung cancer survival was observed among 185 stages III-IV patients treated with platinum-based chemotherapy without surgical operation: XPC rs2228000 (Ala499Val; P = 0.002) and ERCC1 rs11615 (Asn118Asn; P = 0.012). Our data indicate that potentially functional polymorphisms in DNA repair genes may serve as candidate prognostic markers of clinical outcome of NSCLC.

Effect of Loading Rate and Initial Strain on Seismic Performance of an Innovative Self-Centering SMA Brace.

In order to improve the energy dissipation capacity and to reduce the residual deformation of civil structures simultaneously, this paper puts forwards an innovative self-centering shape memory alloy (SMA) brace that is based on the design concepts of SMA's superelasticity and low friction slip. Seven self-centering SMA brace specimens were tested under cyclic loading, and the hysteresis curves, bond curves, secant stiffness, energy dissipation coefficient, equivalent damping coefficient, and the self-centering capacity ratio of these specimens were investigated, allowing us to provide an evaluation of the effects of the loading rate and initial strain on the seismic performance. The test results show that the self-centering SMA braces have an excellent energy dissipation capacity, bearing capacity, and self-centering capacity, while the steel plates remain elastic, and the SMA in the specimens that are always under tension are able to return to the initial state. The hysteresis curves of all of the specimens are idealized as a flag shape with low residual deformation, and the self-centering capacity ratio reached 89.38%. In addition, both the loading rate and the initial strain were shown to have a great influence on the seismic performance of the self-centering SMA brace. The improved numerical models combined with the Graesser model and Bouc-Wen model in MATLAB were used to simulate the seismic performance of the proposed braces with different loading rates and initial strains, and the numerical results are consistent with the test results under the same conditions, meaning that they can accurately predict the seismic performance of the self-centering SMA brace proposed here.

Clinical feasibility of using effective atomic number maps derived from non-contrast spectral computed tomography to identify non-calcified atherosclerotic plaques: a preliminary study.

Background: To assess the clinical feasibility of using effective atomic number (Zeff) maps derived from non-contrast-enhanced computed tomography (NCECT) scans obtained by dual-layer spectral computed tomography (DLCT) to identify non-calcified atherosclerotic plaques. Methods: A total of 37 patients with 86 non-calcified atherosclerotic plaques confirmed by contrast-enhanced CT (CECT) were enrolled in this retrospective study. Both spectral-based-images (SBI) and conventional images (CI) were reconstructed from NCECT and CECT scans. The presence of plaques on NCECT Zeff maps and CIs were independently assessed by 2 radiologists. In CECT scans, plaques and regions of interest (ROIs) in vessel lumens were assessed with CT attenuation and Zeff values, and the proportion of plaques was determined as Area (plaque)/Area (vessel). The CT and Zeff values for plaques and blood were recorded from both CECT and NCECT scans. Contrast-to-noise ratios (CNRs) of the plaques were calculated and compared using CT attenuation and Zeff values. Finally, interobserver agreement was evaluated. Results: A total of 47 of the 86 (54.7%) plaques were identified on Zeff map images derived from the NCECT scans while only 7 (8.1%) plaques were identified on the CI. There was no significant difference between the mean vessel ROI area measured on CIs and that measured on Zeff map images (502.19 vs. 498.14 mm2; P=0.28), while the mean plaque ROI area was larger (81.45 vs. 75.46 mm2). The observer consensus of vessel and plaque ROI area measurements using both methods was excellent, with interclass correlation coefficients (ICCs) of 0.99 and 0.94, respectively. For the 7 plaques detected both by NCECT CI and Zeff mapping, the CT attenuation and Zeff blood values were both larger than the plaque values [42.00 vs. 25.67 Hounsfield unit (HU); 7.33 vs. 7.19 HU; both P<0.05]; the plaque ROI area measurement on the NCE Zeff map was smaller than that on the CE CI (48.73 vs. 77.76 mm2), but was much larger than that on the NCE CI (18.39 mm2). For all 47 plaques detected by NCE Zeff mapping, the CT attenuation and Zeff values of blood and plaques on the NCECT images showed no significant differences (42.53 vs. 35.14 HU; P=0.18; 7.32 vs. 7.31, P=0.71); however, the CNR of Zeff was significantly higher than the CT attenuation value (1.69 vs. 1.12; P<0.05) derived from the NCECT scans. Inter-reviewer agreement was good (ICC =0.78). Conclusions: Zeff map images derived from NCECT SBI with DLCT provide a potentially feasible approach for identifying non-calcified atherosclerotic plaques, which might be clinically useful for the screening of asymptomatic at-risk patients.

Iodine-based extracellular volume for evaluating myocardial status in patients undergoing percutaneous coronary intervention for acute myocardial infarction by using dual-layer spectral detector computed tomography: a comparison study with magnetic resonance.

Background: The myocardial status of patients who undergo percutaneous coronary intervention (PCI) must be evaluated accurately to enable treatment plans to be made for potential complications such as abrupt vessel closure, stent deformation, and myocardial chronic ischemia. This study examined the modality and clinical feasibility of iodine-based extracellular volume (ECV) assessment of the myocardium versus cardiovascular magnetic resonance (CMR) imaging in patients undergoing PCI. Methods: In all, 21 patients who underwent PCI were prospectively enrolled in the study. All patients underwent follow-up cardiac dual-layer spectral detector computed tomography (SDCT) and CMR imaging after PCI. Myocardial ECV was quantified by either computed tomography (ECVCT) or magnetic resonance (ECVMR) using iodine or T1-weighted mapping, respectively. The quality of SDCT and CMR images was independently assessed by two radiologists using a 4-point scale (1= poor and 4= excellent). Any patient with an image quality (IQ) score <2 was excluded. Consistency between radiologists was evaluated using intraclass correlation coefficients (ICC). Correlations between ECVCT and ECVMR values were analyzed using Pearson's test, and consistency was analyzed with Bland-Altman plots. Results: Nineteen of 21 patients completed both cardiac CT and CMR examinations, while three patients were excluded after IQ assessment (two with poor CMR IQ; one with a discontinuous coronary artery on CT images). The mean (±SD) IQ scores for CT and CMR images were 3.81±0.40 and 3.25±0.58, respectively, and interobserver agreement was good (ICC =0.93 and 0.92 for CT and CMR, respectively). The mean (±SD) ECVCT and ECVMR values were 35.93%±9.73% and 33.89%±7.51%, respectively, with good correlation (r=0.79, P<0.001). Bland-Altman analysis showed a difference of 2.04% (95% CI: -9.56%, 13.64%) between the ECVCT and ECVMR values. Conclusions: There is high correlation between iodine-based ECVCT and ECVMR values, which indicates that ECVCT is clinically feasible for evaluating the status of myocardial recovery in patients undergoing PCI.