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Evolutionary multitasking (EMT) is an emerging research direction in the field of evolutionary computation. EMT solves multiple optimization tasks simultaneously using evolutionary algorithms with the aim to improve the solution for each task via intertask knowledge transfer. The effectiveness of intertask knowledge transfer is the key to the success of EMT. The multifactorial evolutionary algorithm (MFEA) represents one of the most widely used implementation paradigms of EMT. However, it tends to suffer from noneffective or even negative knowledge transfer. To address this issue and improve the performance of MFEA, we incorporate a prior-knowledge-based multiobjectivization via decomposition (MVD) into MFEA to construct strongly related meme helper-tasks. In the proposed method, MVD creates a related multiobjective optimization problem for each component task based on the corresponding problem structure or decision variable grouping to enhance positive intertask knowledge transfer. MVD can reduce the number of local optima and increase population diversity. Comparative experiments on the widely used test problems demonstrate that the constructed meme helper-tasks can utilize the prior knowledge of the target problems to improve the performance of MFEA.

Attention mechanisms are now widely used in image captioning models. However, most attention models only focus on visual features. When generating syntax related words, little visual information is needed. In this case, these attention models could mislead the word generation. In this paper, we propose Task-Adaptive Attention module for image captioning, which can alleviate this misleading problem and learn implicit non-visual clues which can be helpful for the generation of non-visual words. We further introduce a diversity regularization to enhance the expression ability of the Task-Adaptive Attention module. Extensive experiments on the MSCOCO captioning dataset demonstrate that by plugging our Task-Adaptive Attention module into a vanilla Transformer-based image captioning model, performance improvement can be achieved.

Purpose: To study the effect of isoglycyrrhizin on LPS-mediated acute respiratory distress syndrome (ARDS) in a mouse model, as well as the associated mechanism of action.Methods: Ninety (90) wild-type C57BL/6 male mice were randomly assigned to 3 groups, viz, control, ARDS and isoglycyrrhizin groups. Pathological lesions in mice lungs were determined using H&E staining. The mRNA and protein expressions of inducible nitric oxide synthase (iNOS), heme oxygenase (HO-1), cyclooxygenase-2 (COX-2), AMP- dependent protein kinase (AMPK), serine/threonine proteinkinase (Akt), glycogen synthase kinase 3 (GSK3), nucleotide-binding domain-like receptor protein 3 (NLRP3), and Nrf2 were assayed using quantitative reverse transcription polymerase chain reaction (RT-PCR) and immunoblotting, respectively.Results: The levels of mRNA and protein expressions of INO) and COX-2 were significantly upregulated in ARDS, when compared to control, but were markedly down-regulated by isoglycyrrhizin (p < 0.05). Similarly, exposure of ARDS mice to isoglycyrrhizin led to upregulations of mRNA and proteinlevels of Nrf2, NQO1, HO-1, GCLM, GCLC, p-GSK3, GSK3, p-AMPK, AMPK, p-Akt and AKT (p < 0.05). Moreover, isoglycyrrhizin significantly downregulated p-IκB and Nucl-p65 with respect to protein and mRNA levels, but upregulated IκBα expression. Histopathological examination revealed that pretreatment of ARDS mice with isoglycyrrhizin significantly reduced the number of infiltrating inflammatory cells, edema and ARDS score (p < 0.05).Conclusion: Isoglycyrrhizin protects mouse lungs against ARDS via regulation of AMPK/Nrf2/ARE pathway. Thus, this compound has potential for use in the treatment of ARDS.

BACKGROUND Spinal cord injury (SCI) refers to the interruption of the tracts inside the spinal cord caused by various factors. The repair of damaged axons has always been a difficult point in clinical treatment and neuroscience research. The treatment of SCI with Buyang huanwu decoction (BYHWD), a well-known recipe for invigorating Qi (a vital force forming part of any living entity in traditional Chinese culture) and promoting blood circulation, shows a good effect. METHODS The rubrospinal tract (RST) transection model in rats was established in this study and rats were administrated with low (BL), medium (BM), or high (BH) doses of BYHWD. RESULTS Compared with the SCI group, BL, BM moderately, and BH significantly improved the motor function of forelimbs and increased the number of red nucleus neurons in SCI rats. As for the possible molecular mechanism, BL, BM moderately, and BH significantly increased mTOR whereas decreased Beclin-1 and LC3 in the red nucleus. CONCLUSION In conclusion, low, medium, and high doses of BYHWD could promote neural recovery in SCI rats through improving motor function and neuron survival in the red nucleus. The neuroprotective effects of BYHWD might be associated with affecting the mTOR signaling pathway and autophagy.

Ampullary adenomatous lesions of the gastrointestinal tract are rare and can be asymptomatic. Therefore, ampullary adenomas with malignant potential require prompt removal, regardless of whether they are adenomatous or carcinomatous lesions. Endoscopic papillectomy is a safe and effective alternative therapy to surgery to treat duodenal papillary lesions in selected patients. Accurate preoperative diagnosis and staging of ampullary adenomatous lesions are critical for predicting prognosis and determining the most appropriate therapeutic approach. Furthermore, the management and prevention of adverse events and endoscopic treatment for remnant or recurrent lesions and surveillance are essential for successful endoscopic management of ampullary adenomatous lesions. This literature review was based on PubMed and MEDLINE and focused on recent advancements in the endoscopic papillectomy technique to provide a comprehensive view of endoscopic papillectomy to treat ampullary adenomatous lesions.

Background The diagnostic methods of prostate cancer (PCa) present major drawbacks in that serum prostate specific antigen (PSA) testing lacks specificity for PCa and prostate needle biopsy is a painful and highly invasive procedure for patients. Thus, new alternative screening methods which are specific and non-invasive both in the early detection and in the clinical definitive diagnosis of PCa are in urgent need. Long non-coding RNA MYU has been shown to promote PCa cell proliferation and migration, and is significantly upregulated both at the cellular and tumor tissue level. Therefore, long non-coding RNA MYU may be a new potential diagnostic biomarker for PCa. Methods In the present study, we successfully developed a highly sensitive digital PCR assay to detect long non-coding RNA in clinical urine samples. dPCR was carried out using Qx200 ddPCR EvaGreen Supermix (Bio-Rad) according to the manufacturer's instructions. Results Our results indicated that the digital PCR assay showed better linearity, repeatability, and reproducibility when compared with real-time quantitative PCR. In addition, we identified the normalized MYU level and used the digital PCR assay to measure it in 100 clinical urine samples. Our study showed that the normalized MYU level is a promising diagnostic biomarker for predicting and evaluating the malignancy of PCa. Conclusions Our findings presented a non-invasive liquid biopsy method to detect an alternative diagnostic parameter which can assist the diagnosis of PCa in clinical practice.

Hepatectomy with tumor thrombectomy is the preferred treatment option for hepatocellular carcinoma (HCC) patients with bile duct tumor thrombus (BDTT); however, the impact of BDTT on their prognosis is unclear. We aimed to investigate the long-term surgical outcomes of HCC patients with BDTT. The data of HCC patients with and without BDTT who underwent hepatectomy were retrospectively reviewed and the long-term outcomes were compared. For propensity score matching (PSM) analysis, patients were matched in a 1:1 ratio. Subgroup analysis was conducted according to the American Joint Committee on Cancer (AJCC) staging system. Before PSM, HCC patients with BDTT had more advanced tumor stages and adverse clinicopathological features. Recurrence-free survival (RFS) and overall survival (OS) were significantly higher in the non-BDTT group before PSM (RFS, p

Background Previous research found that the cancer history of an individual’s sibling may be a better indicator than that of the parents. We aim to provide recommendations for opportunistic screening for individuals whose sibling had been diagnosed with cancer. Methods During the physical examination in Cancer Hospital, Chinese Academy of Medical Sciences, 43,300 people were asked if they have at least two siblings who developed cancer. Results A total of 1270 sibling-pairs from 766 families developed cancer, including 367 pairs of brothers (Bro-pairs), 368 pairs of sisters (Sis-pairs), and 535 pairs of brother-and-sister (BroSis-pairs). The mean ages at diagnosis of cancer for the three groups were from 58 to 62 years. More than half of Bro-pairs (55.3%) or Sis-pairs (51.1%) had cancer from the same systemic origin, and more than a quarter of Bro-pairs (28.1%) and Sis-pairs (37.2%) developed the same type of cancer. However, only 36.0% of BroSis-pairs developed cancers from the same systemic origin, and 18.9% developed the same type of cancer. In Bro-pairs and BroSis-pairs, lung cancer and digestive system cancer were the most common cancers, while in Sis-pairs, breast cancer, lung cancer, cervical cancer, liver cancer and thyroid cancer were the most common ones. Conclusions If an individual’s sibling is diagnosed with cancer, the individual should consider participating in opportunistic screening annually, especially for lung cancer and digestive system cancers for both sexes. For sisters, breast cancer, cervical cancer and thyroid cancer should be screened early. Additionally, genetic services are essential for individuals who have siblings with cancer.

Background Current methods for cervical cancer screening result in an increased number of referrals and unnecessary diagnostic procedures. This study aimed to develop and evaluate a more accurate model for cervical cancer screening. Methods Multiple predictors including age, cytology, high-risk human papillomavirus (hrHPV) DNA/mRNA, E6 oncoprotein, HPV genotyping, and p16/Ki-67 were used for model construction in a cross-sectional population including women with normal cervix (N = 1085), cervical intraepithelial neoplasia (CIN, N = 279), and cervical cancer (N = 551) to predict CIN2+ or CIN3+. A base model using age, cytology, and hrHPV was calculated, and extended versions with additional biomarkers were considered. External validations in two screening cohorts with 3-year follow-up were further conducted (NCohort-I = 3179, NCohort-II = 3082). Results The base model increased the area under the curve (AUC, 0.91, 95% confidence interval [CI] = 0.88–0.93) and reduced colposcopy referral rates (42.76%, 95% CI = 38.67–46.92) compared to hrHPV and cytology co-testing in the cross-sectional population (AUC 0.80, 95% CI = 0.79–0.82, referrals rates 61.62, 95% CI = 59.4–63.8) to predict CIN2+. The AUC further improved when HPV genotyping and/or E6 oncoprotein were included in the base model. External validation in two screening cohorts further demonstrated that our models had better clinical performances than routine screening methods, yielded AUCs of 0.92 (95% CI = 0.91–0.93) and 0.94 (95% CI = 0.91–0.97) to predict CIN2+ and referrals rates of 17.55% (95% CI = 16.24–18.92) and 7.40% (95% CI = 6.50–8.38) in screening cohort I and II, respectively. Similar results were observed for CIN3+ prediction. Conclusions Compared to routine screening methods, our model using current cervical screening indicators can improve the clinical performance and reduce referral rates.

Objective: To establish a new classification of biliary tumor thrombus (BTT). Methods: Overall survival of patients with BTT was first used to determine whether it correlated with current hepatocellular carcinoma staging systems. Univariate and multivariate analyses were used to determine factors affecting the overall survival (OS) to form the basis of our new classification for BTT. Results: All 6 international staging systems showed overlapping survival curves. Univariate followed by multivariate analyses showed that total bilirubin and intrahepatic/extrahepatic BTT were significant risk factors of OS. Based on these data, a new BTT classification was defined as: Type I: intrahepatic BTT; and Type II: extrahepatic BTT involving a common bile duct or common hepatic duct. Type I was further subdivided into type Ia: BTT involving a second-order intrahepatic duct or above, and type Ib: BTT involving a first-order intrahepatic duct. Type II was further subdivided into type IIa and type IIb using a cut-off total bilirubin (TB) > 300 μmol/L. The numbers (percentages) of patients with types I and II BTT were 69 (34.2%) and 133 (65.8%), respectively. The median OS of type I patients was significantly higher than that of type II patients (37.5 months vs. 23.2 months; P = 0.002). Using subgroup analyses, OS outcomes were significantly different between the subgroups of type IIb and type IIa, although there was no significant difference between the type Ia and type Ib subgroups (P = 0.07). Conclusions: A new BTT classification was established to predict prognoses of HCC patients with BTT who underwent liver resection.

The task of question generation (QG) aims to create valid questions and correlated answers from the given text. Despite the neural QG approaches have achieved promising results, they are typically developed for languages with rich annotated training data. Because of the high annotation cost, it is difficult to deploy to other low-resource languages. Besides, different samples have their own characteristics on the aspects of text contextual structure, question type and correlations. Without capturing these diversified characteristics, the traditional one-size-fits-all model is hard to generate the best results. To address this problem, we study the task of cross-lingual QG from an adaptive learning perspective. Concretely, we first build a basic QG model on a multilingual space using the labelled data. In this way, we can transfer the supervision from the high-resource language to the language lacking labelled data. We then design a task-specific meta-learner to optimize the basic QG model. Each sample and its similar instances are viewed as a pseudo-QG task. The asking patterns and logical forms contained in the similar samples can be used as a guide to fine-tune the model fitly and produce the optimal results accordingly. Considering that each sample contains the text, question and answer, with unknown semantic correlations among them, we propose a context-dependent retriever to measure the similarity of such structured inputs. Experimental results on three languages of three typical data sets show the effectiveness of our approach.

BACKGROUND AND AIM Previous studies suggest that serum ferritin may be associated with higher risk of liver cancer. However, additional studies of the association are needed. It is also not clear whether serum ferritin is associated with mortality from chronic liver disease (CLD). METHODS We performed a nested case-control study in the Linxian Nutrition Intervention Trials. Baseline serum ferritin was measured for 226 incident primary liver cancer cases, 281 CLD mortalities diagnosed, and 1061 age-matched, gender-matched, and trial-matched controls. We used multivariable logistic regression models to calculate odds ratios and 95% confidence intervals. Subgroup analysis and interaction tests were performed by age, gender, alcohol drinking, hepatitis B virus seropositivity (HBV+)/hepatitis C virus seropositivity (HCV+), and trial. RESULTS Participants with serum ferritin in the highest quartile, as compared with those in the lowest quartile, had an increased risk of CLD mortality (odds ratio = 1.72, 95% confidence interval = 1.12, 2.64, P-trend

Oxide double perovskites A2B′B′′O6 are a class of emerging materials in the fields of optoelectronics and catalysis. Due to the chemical flexibilities of perovskite structures, there are multiple elemental combinations of cations A, B′, and B′′, which leading to tremendous candidates. In this study, we comprehensively screened stable oxide double perovskite A2B′B′′O6 from a pool of 2,018 perovskite candidates using a high-throughput computational approach. By considering a tolerance factor (t)–octahedral factor (μ) phase diagram, 138 candidates with F m 3 ¯ m , P21/c, and R3c phases were selected and systematically studied via first-principles calculations based on density functional theory. The screening procedure finally predicted the existence of 21 stable perovskites, and 14 among them have never been reported. Verification with existing experimental results demonstrates that the prediction accuracy for perovskite formability is approximately 90%. The predicted oxide double perovskites exhibit quasi-direct bandgaps ranging from 0 to 4.4 eV with a significantly small direct-indirect bandgap difference, balanced electron and hole effective masses, and strong optical absorptions. The newly predicted oxide double perovskites may enlarge the pool of material candidates for applications in optoelectronics and photocatalysis. This study provides a route for computational screening of novel perovskites for functional applications.

Gastric cancer shows a strong male predominance, and sex steroid hormones have been hypothesized to explain this sex disparity. Previous studies examining the associations between sex hormones and sex hormone binding globulin (SHBG) and risk of gastric cancer come primarily from western populations and additional studies in diverse populations will help us better understand the association. We performed a nested case–control study in Linxian Nutrition Intervention Trials cohorts to evaluate the associations among Chinese men, where we had sufficient cases to perform a well-powered study. Using radioimmunoassays and immunoassays, we quantitated androgens, estrogens, and SHBG in baseline serum from 328 men that developed noncardia gastric cancer and matched controls. We used multivariable unconditional logistic regression to calculate ORs and 95% confidence intervals (CI) and explored interactions with body mass index (BMI), age, alcohol drinking, smoking, and follow-up time. Subjects with SHBG in the highest quartile, as compared with those in the lowest quartile, had a significantly increased risk of gastric cancer (OR = 1.87; 95% CI, 1.01–3.44). We found some evidence for associations of sex steroid hormones in men with lower BMI. Our study found a novel association suggesting that higher serum concentrations of SHBG may be associated with risk of gastric cancer in men. We found no overall associations with sex hormones themselves, but future studies should expand the scope of these studies to include women and further explore whether BMI modifies a potential association. Prevention Relevance: It was the first study to investigate the association of gastric cancer with prediagnostic sex steroid hormones and SHBG in an Asian male population. Although there were no overall associations for sex steroid hormone concentrations, higher concentrations of SHBG was associated with increased risk of noncardia gastric cancer.

Background Thymomas and thymic carcinomas are the most common tumor types among anterior mediastinal lesions. However, the relationship between molecular aberrations and thymoma patients are poorly understood, especially abnormal changes in the expression profiles of circRNAs. The purpose of the present study was to investigate the expression profiles of circRNAs in thymoma patients and their possible roles in the pathogenesis of thymoma. Methods Diseased tissues and surrounding normal thymic tissues in two thymoma patients were collected for circRNA sequencing. The top four upregulated circRNAs were selected as candidates and further validated with RT‐PCR in 20 thymoma patients. Gene ontology and signal transduction network analyses of circRNA‐related mRNAs were performed to analyze the functional properties. Survival analysis of their parental genes were also carried out to evaluate the clinical value of differentially expressed circRNA. Results A total of 73 circRNAs were differentially expressed in thymoma tissues using high‐throughput sequencing. Among these circRNAs, hsa_circ_0001173, hsa_circ_0007291, hsa_circ_0003550, and hsa_circ_0001947 were significantly upregulated in thymoma tissues compared with normal thymic tissues. We identified that these four circRNA‐related mRNAs were involved in cell–cell adhesion, MAPK pathways, and TNF pathway, which may contribute to the pathological immune disorder in thymoma. Finally, we also found that SCAP (hsa_circ_0007291 parental gene) and AFF2 (hsa_circ_0001947 parental gene) were all significantly related with progression‐free survival (PFS) of thymoma patients in a Kaplan‐Meier plot (p‐value, The expression levels of hsa_circ_0001173, hsa_circ_0007291, hsa_circ_0003550, and hsa_circ_0001947 were significantly upregulated and positively correlated with immune imbalance in thymoma patients. The discovery of new differentially expressed circRNAs can be used not only as a biomarker for diagnosis, but also as a potential target for the treatment of thymoma.

The optimal surgical method of patients with hepatocellular carcinoma (HCC) and bile duct tumor thrombus (BDTT) is still controversial. This study aims to investigate the impact of different surgical methods on BDTT patients. A multicenter retrospective study was carried out on HCC patients with BDTT who underwent surgery. The survival outcomes of different operation methods were studied. A total of 120 HCC patients with BDTT from 5 different clinical centers were included. The median disease-free survival (DFS) of the bile duct resection (BDR) group was significantly better than that of the non-BDR group (24.6 months vs. 18.9 months, p = 0.034), but the overall survival (OS) was similar between the two groups (33.6 months vs. 32.3 months, p = 0.193). When we divided the non-BDR group into two groups according to the operation sequence of the hepatic tumor and BDTT, we found that the OS of the thrombus-first group was significantly longer than that of the tumor-first group (42.7 months vs. 23.6 months, p = 0.016). When compared with the BDR group, the thrombus-first group showed similar OS (42.7 months vs. 33.6 months, p = 0.653) and DFS (24.7 months vs. 24.6 months, p = 0.150), which may be the reason the OS rate of the BDR group was similar to that of the non-BDR group. A thrombus-first technique could be considered for HCC patients with extrahepatic BDTT, especially for those patients in which the tumor thrombus did not invade the bile duct.

Background: Accumulating evidence has shown that serum calcium and vitamin D may be associated with or influence various cancer risks. However, no prospective studies have evaluated the independent and joint associations between prediagnostic levels of serum calcium and vitamin D and future risk of incident primary liver cancer. Methods: We used a nested case–control design to evaluate subjects over 22 years of follow-up. Serum calcium, 25-hydroxy vitamin D [25(OH)D], and three markers of hepatitis B virus and hepatitis C virus were measured in baseline serum from 226 incident primary liver cancer cases and 1,061 matched controls. We calculated ORs and 95% confidence intervals (CI) using logistic regression to estimate the associations between calcium, 25(OH)D, and primary liver cancer risk. Results: Multivariable adjusted models showed that subjects with both low (ORLow/Medium = 1.48, 95% CI = 1.01–2.17) or high (ORHigh/Medium = 1.92, 95% CI = 1.34–2.76) calcium had an increased primary liver cancer risk, while those with high 25(OH)D had a decreased risk of primary liver cancer (ORHigh/Medium = 0.54, 95% CI = 0.35–0.82). In joint analyses, when compared with subjects with medium calcium and 25(OH)D, subjects with high calcium and medium 25(OH)D had elevated odds of developing primary liver cancer (OR = 1.89, 95% CI = 1.17–3.05); those with medium calcium and high 25(OH)D had reduced odds of developing primary liver cancer (OR = 0.34, 95% CI = 0.17–0.67); and subjects in other classifications of calcium and serum 25(OH)D levels had no change in the odds of developing primary liver cancer (all P > 0.05). Conclusions: In a nutrient-deficient population, we found that serum calcium and serum 25(OH)D could potentially be modifiable risk or protective factors. Impact: Our findings provide potential targets for primary liver cancer prevention and control.

Immune checkpoint inhibitors (ICIs) have made a breakthrough in cancer therapy. Patients treated with ICIs may develop immune-related adverse events (irAEs) due to the upregulated activity of the immune system. With the increasing use of ICIs, irAEs are more frequently reported and have become important challenges in many patients. Neurological irAEs, which include encephalitis, myelitis, aseptic meningitis, peripheral neuropathy, myasthenia gravis, and myositis, consist of a distinct group of neuroinflammatory disorders. These disorders are rare but frequently severe with high mortality and morbidity. Patients with neurological irAEs are generally responsive to immune-modulating therapy. Therefore, early recognition and treatment are the most important ways to improve their prognosis. Here, we provide a comprehensive review of neurological irAEs associated with ICIs and focus on these affecting central nervous systems.

Quasi-two-dimensional (quasi-2D) perovskite is rising as a promising luminescent material for blue perovskite light-emitting diodes (PeLEDs). However, typical quasi-2D perovskites show a wide distr...

Summary The pump dynamometer card is a direct reflection of the operating conditions of the downhole pump, which is important for the diagnosis of sucker-rod pumping systems. In this paper, we propose a novel diagnostic method based on the estimation of the parameters from the polished-rod load vibration signal of sucker-rod pumping systems in a vertical well. In this study, we deduce a new analytic solution of the 1D wave equation of the sucker-rod string, which can be used for the predictive and diagnostic analyses. The relationship between the polished-rod load vibration and the pump equivalent impulse load based on the analytic solution is studied, and the diagnostic parameter estimating method is proposed. Therefore, the pump dynamometer card calculated method based on the surface dynamometer card is realized. This study shows that the method is efficient.

Several studies found that hip fracture patient outcome is greatly influenced by the time from admission to surgery. To avoid surgical delay, surgery for hip fracture may be performed at night or weekends. However, after-hours surgery may lead to a reduction in support staff and to surgeon fatigue, which ultimately increases mortality and complications. Therefore, we wanted to compare the outcomes of daytime and after-hours surgery in hip fracture patients. A literature search was performed in the Cochrane Library, and the Web of Science, PubMed, Embase, and Springer databases from inception to December 2019. Relevant studies comparing the results of operations performed at different time periods were included. The main clinical outcomes included total complications, mortality, blood loss, surgical time, and length of hospitalization. Data were pooled, and a meta-analysis was completed. Nine retrospective cohort studies and one randomized controlled trial met the inclusion criteria; the studies included a total of 583,290 patients. We found no significant differences in mortality, surgical time or blood loss between daytime and after-hours surgery in hip fracture patients (P > 0.05). Of note, the patients who underwent after-hours surgery had fewer surgical complications (P

Fedratinib is an oral, selective Janus kinase 2 inhibitor that is approved in the United States for the treatment of patients with intermediate-2 or high-risk myelofibrosis. Pharmacokinetics and tolerability of fedratinib in subjects with renal impairment (RI) and hepatic impairment (HI) were evaluated in two separate studies. In the renal study, male and female subjects with stable, chronic mild, moderate, and severe RI, as well as those with end-stage renal disease, were included. The hepatic study included subjects with stable, chronic mild HI. Both were phase 1, multicenter, open-label, single-dose studies, and included matched healthy subjects. Subjects received a single oral dose of fedratinib 300 mg on day 1, were discharged on day 4, returned for clinical visits on days 5–12, and had their end-of-study visit between days 14 and 16. Thirty-six and 17 subjects were included in the renal and hepatic studies, respectively. In the renal study, fedratinib area under the plasma concentration–time curve from time 0 to infinity (AUCinf) was 1.9- and 1.5-fold higher in subjects with severe and moderate RI, respectively, than in matched healthy subjects. In the hepatic study, fedratinib AUCinf did not appreciably differ between subjects with mild HI and matched healthy subjects. Overall, most treatment–emergent adverse events were gastrointestinal and mild. Mild RI and HI do not necessitate fedratinib dosage adjustments. Subjects with moderate RI should be monitored (with dosage adjustments made as necessary), whereas those with severe RI should receive a daily dose of 200 mg, reduced from the indicated dose of 400 mg.

Recently, imbalanced data classification has received much attention due to its wide applications. In the literature, existing researches have attempted to improve the classification performance by considering various factors such as the imbalanced distribution, cost-sensitive learning, data space improvement, and ensemble learning. Nevertheless, most of the existing methods focus on only part of these main aspects/factors. In this work, we propose a novel imbalanced data classification model that considers all these main aspects. To evaluate the performance of our proposed model, we have conducted experiments based on 14 public datasets. The results show that our model outperforms the state-of-the-art methods in terms of recall, G-mean, F-measure and AUC.

With the rapid growth of the big data, many approaches in the representation of text for sentiment classification have been successfully proposed in natural language processing. However, these approaches remedy this problem based on single-task supervised objectives learning and do not consider their relative of multiple tasks. Based on these defects, in this work, we consider these tasks are relative, and use weight-shared parameters for learning the representation of text in neural network model, we introduce and study a multi-task approach with variational auto-encoder generative model (MTVAE) by jointly learning them. Experimental results on six subsets of Amazon review data show that the proposed approach can effectively improve the sentiment classification accuracy by other relative tasks.

Multi-view Clustering has become a vital task with the rapidly growing amount of data in multiple representations. Under the context of unsupervised learning, the existing clustering methods show limited capability in leveraging the discriminative information from multiple views. View-independent noises and distribution differences among views are two main causes that may degrade the clustering performances. By introducing the inter-and-intra-view low rank decomposition, we propose Multi-view Clustering via Intra and Inter-view Low Rank Fusion (MCIIF). The proposed method facilitates clustering with the discriminative intra-view low rank structures that complement the shared inter-view transition. By recovering complementary low rank transitions from the differences between the shared inter-view transition and individual-view transitions, we pursue a more accurate transition probability matrix by combining the complementary intra-view transitions with the shared inter-view transition in an additive manner. To solve the corresponding optimization problem, we propose a procedure based on the Alternating Direction Method of Multipliers (ADMM) scheme with convergence guarantees. Experimental results on various real-world datasets verify the effectiveness of the proposed method over the state-of-art multi-view clustering methods.

The figure of merit is of crucial importance in materials design to search for candidates with optimal functionality. In the field of photovoltaics, the bandgap ( E g) is a well-recognized figure of merit for screening solar cell absorbers subject to the Shockley-Queisser limit. In this paper, the bandgap as the figure of merit is challenged since an ideal solar cell absorber requires multiple criteria such as stability, optical absorption, and carrier lifetime. Multiple criteria make the quantitative description of material candidates difficult and computationally time-consuming. Taking halide perovskites as an example, we combine thermodynamic stability (Δ H d) and E g into a unified figure of merit and use Bayesian optimization (BO) to accelerate materials screening. We have found that, in comparison to an exhaustive search via multiple parameters, BO based on the unified figure of merit can screen optimal candidates ( E g,PBE between 0.6– 1.2 eV, Δ H d>− 29 meV per atom) more efficiently. Therefore, the proposed method opens a viable route for the search of optimal solar cell absorbers from a large amount of material candidates with less computational cost.

Background. The association between nonalcoholic fatty liver disease (NAFLD) and Helicobacter pylori (H. pylori) is controversial. We conducted a retrospective study to clarify the seroprevalence of H. pylori infection and the relationship between NAFLD and H. pylori infection in north urban Chinese. Methods. The retrospective study was performed at Aerospace Center Hospital in Beijing. All subjects in this study were a healthy population who underwent health examinations at the hospital between 2012 and 2015. A logistic regression model was used to calculate the association between NAFLD and H. pylori infection. Age, gender, underlying diseases, and metabolic syndrome (MS) were adjusted. Effects of NAFLD on H. pylori infection in a different age, gender, and number of MS characteristic subgroups were analyzed. Results. There were 7803 (43.4%) subjects with H. pylori infection, 3726 (20.7%) with mild NAFLD, 730 (4.1%) with moderate NAFLD, and 369 (2.1%) with severe NAFLD among 17971 subjects. H. pylori infection was related to the seroprevalence of any level of NAFLD, including mild, moderate, and severe NAFLD (OR=1.607, 95% CI: 1.487-1.736; OR=1.770, 95% CI: 1.519-2.063; and OR=2.120, 95% CI: 1.714-2.526, respectively). The results of subgroup analysis showed that the risk of incident NAFLD from H. pylori infection had significant interactions by subjects with or without MS characteristics. Moreover, as the number of MS characteristics in patients with a fatty liver increased, the risk of H. pylori infection also increased. Conclusions. NAFLD may be associated with H. pylori infection in a Chinese population. Younger, male NAFLD patients and those meeting more characteristics of MS were more likely to have H. pylori infection.

Objective To evaluate changes in chest X-rays, pulmonary function tests (PFTs) and quality of life in female breast cancer patients who had been treated with four cycles of neoadjuvant chemotherapy consisting of a regimen of cyclophosphamide, epirubicin and 5-fluorouracil (CEF regimen), and to determine the correlation between pulmonary function parameters and declined quality of life. Methods Twenty-nine eligible female patients diagnosed with breast cancer at the first visit who were 20−60 years old, were classified as the American Society of Anesthesiologists (ASA) I−II and patients whose body mass index (BMI) 0.05). Conclusions Neoadjuvant chemotherapy can reduce lung diffusion function and quality of life in females with breast cancer.

Background Sarcopenia is a decrease in skeletal muscle mass, physical performance, and muscle strength in older people. In this study, we aimed to explore the correlation between comorbidity and skeletal muscle mass and physical performance in older people. Methods This retrospective study included 168 subjects. Their medical history, physical function, computed tomography (CT) chest scans, and blood tests for nutrition were evaluated. The patients were divided into two groups: (1) a low muscle mass group and (2) a normal muscle mass group. Multivariate analysis of variance was used to compare multiple sets of mean vectors. Results Overall, 72.02% of the subjects had a low skeletal muscle index (SMI) and low gait speed. The patients with low skeletal muscle mass and physical performance were older, had more serious comorbidities, and had longer average hospitalization periods and lower albumin and hemoglobin levels. Subjects with a high Charlson comorbidity index (CCI) were more likely to be in the sarcopenic group than in the non-sarcopenic group. In addition, there was a linear correlation between the CCI and SMI (r = − 0.549, P P Conclusions We identified an independent association between comorbidity and skeletal muscle mass/physical performance by researching the correlation between the CCI and SMI/gait speed. Our results suggested that the CCI score may have important clinical diagnostic value for sarcopenia.

Objective: The number of immediate breast reconstruction (IBR) procedures has been increasing in China. This study aimed to investigate the oncological safety of IBR, and to compare the survival and surgical outcomes between implant-based and autologous reconstruction. Methods: Data from patients diagnosed with invasive breast cancer who underwent immediate total breast reconstruction between 2001 and 2016 were retrospectively reviewed. Long-term breast cancer-specific survival (BCSS), disease-free survival (DFS), and locoregional recurrence-free survival (LRFS) were evaluated. Patient satisfaction with the breast was compared between the implant-based and autologous groups. BCSS, DFS, and LRFS were compared between groups after propensity score matching (PSM). Results: A total of 784 IBR procedures were identified, of which 584 were performed on patients with invasive breast cancer (implant-based, n = 288; autologous, n = 296). With a median follow-up of 71.3 months, the 10-year estimates of BCSS, DFS, and LRFS were 88.9% [95% confidence interval (CI) (85.1%–93.0%)], 79.6% [95% CI (74.7%–84.8%)], and 94.0% [95% CI (90.3%–97.8%)], respectively. A total of 124 patients completed the Breast-Q questionnaire, and no statistically significant differences were noted between groups (P = 0.823). After PSM with 27 variables, no statistically significant differences in BCSS, DFS, and LRFS were found between the implant-based (n = 177) and autologous (n = 177) groups. Further stratification according to staging, histological grade, lymph node status, and lymph-venous invasion status revealed no significant survival differences between groups. Conclusions: Both immediate implant-based and autologous reconstruction were reasonable choices with similar long-term oncological outcomes and patient-reported satisfaction among patients with invasive breast cancer in China.

Background:. Prospective analyses have yet to identify a consistent relationship between sleep duration and the incidence of gastrointestinal (GI) cancers. The effect of changes in sleep duration on GI cancer incidence has scarcely been studied. Therefore, we aimed to examine the association between baseline sleep duration and annual changes in sleep duration and GI cancer risk in a large population-based cohort study. Methods:. A total of 123,495 participants with baseline information and 83,511 participants with annual changes in sleep duration information were prospectively observed from 2006 to 2015 for cancer incidence. Cox proportional-hazards models were used to calculate hazard ratios (HRs) and their confidence intervals (CIs) for GI cancers according to sleep duration and annual changes in sleep duration. Results:. In baseline sleep duration analyses, short sleep duration (≤5 h) was significantly associated with a lower risk of GI cancer in females (HR: 0.31, 95% CI: 0.10–0.90), and a linear relationship between baseline sleep duration and GI cancer was observed (P = 0.010), especially in males and in the >50-year-old group. In the annual changes in sleep duration analyses, with stable category (0 to −15 min/year) as the control group, decreased sleep duration (≤−15 min/year) was significantly associated with the development of GI cancer (HR: 1.29; 95% CI: 1.04–1.61), especially in the >50-year-old group (HR: 1.32; 95% CI: 1.01–1.71), and increased sleep duration (>0 min/year) was significantly associated with GI cancer in females (HR: 2.89; 95% CI: 1.14–7.30). Conclusions:. Both sleep duration and annual changes in sleep duration were associated with the incidence of GI cancer.

Aspect extraction is one of the key tasks in fine-grained sentiment analysis. This task aims to identify explicit opinion targets from user-generated documents. Currently, the mainstream methods for aspect extraction are built on recurrent neural networks (RNNs), which are difficult to parallelize. To accelerate the training/testing process, convolutional neural network (CNN)-based methods are introduced. However, such models usually utilize the same set of filters to convolve all input documents, and hence, the unique information inherent in each document may not be fully captured. To alleviate this issue, we propose a CNN-based model that employs a set of dynamic filters. Specifically, the proposed model extracts the aspects in a document using the filters generated from the aspect information intrinsic in the document. With the dynamically generated filters, our model is capable of learning more important features concerning aspects, thus promoting the effectiveness of aspect extraction. Furthermore, considering that aspects can be grouped into certain topics that conversely indicate the target words that need to be extracted, we naturally introduce a neural topic model (NTM) and integrate latent topics into the CNN-based module to help identify aspects. Experiments on two benchmark datasets demonstrate that the joint model is able to effectively identify aspects and produce interpretable topics.

In this article, efficiency performance of blue GaN/InGaN micro light emitting diodes (μ-LEDs) are investigated as functions of chip sizes, quantum barrier doping level and the number of quantum wells (QWs) by simulation. Internal quantum efficiency (IQE) and external quantum efficiency (EQE) drastically decrease with decreasing mesa sizes of μ-LEDs. The simulation indicates that μ-LEDs with n-doped quantum barriers can effectively suppress the Shockley-Read-Hall (SRH) nonradiative recombination and improve the efficiency compared to those with intrinsic quantum barriers in small μ-LEDs. The simulated results also show that decreasing the number of QWs can improve the IQE of μ-LEDs with higher radiative recombination rate in a single QW. An optimized design for 5×5 μm2 GaN/InGaN μ-LEDs with n-doped barriers and a single QW shows around 367% efficiency improvement at 1 A/cm2 comparing to the conventional intrinsic multiple QWs-based design in simulation.

Jia-Yi Wu,1,2,&ast; Zhen-Yu Yin,3,&ast; Yan-Nan Bai,1,2 Yu-Feng Chen,4 Song-Qiang Zhou,1,2 Shuang-Jia Wang,5 Jian-Yin Zhou,6 Yi-Nan Li,2 Fu-Nan Qiu,1,2 Bin Li,5 Mao-Lin Yan1,2 1Shengli Clinical Medical College of Fujian Medical University, Fuzhou, Fujian Province, 350001, People’s Republic of China; 2Department of Hepatobiliary Pancreatic Surgery, Fujian Provincial Hospital, Fuzhou, Fujian Province, 350001, People’s Republic of China; 3Department of Hepatobiliary Surgery, Xiamen Traditional Chinese Medical Hospital, Xiamen, Fujian Province, 361000, People’s Republic of China; 4Department of Hepatobiliary Surgery, The Zhangzhou Affiliated Hospital of Fujian Medical University, Zhangzhou, Fujian Province, 363000, People’s Republic of China; 5Department of Hepato-Biliary-Pancreatic and Vascular Surgery, The First Affiliated Hospital of Xiamen University, Xiamen, Fujian Province, 361000, People’s Republic of China; 6Department of Hepatobiliary Surgery, Zhongshan Hospital of Xiamen University, Xiamen, Fujian Province, 361000, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Mao-Lin Yan; Bin Li Tel +86 0591-88217130; +86 13606056652Fax +86 0591-87557768; +86 0592-2132222Email yanmaolin74@163.com; wasalee@126.comBackground: Lenvatinib (LEN) combined with anti-PD-1 antibodies (PD-1) exerted promising effects on unresectable hepatocellular carcinoma (uHCC). We assessed the safety and clinical efficacy of triple therapy [LEN+PD-1+transcatheter arterial chemoembolization (TACE)] in uHCC.Methods: uHCC patients with an ECOG PS score of 0– 1 and Child–Pugh class A who underwent triple therapy were included. The primary endpoint was objective response rate (ORR) based on mRECIST. Secondary endpoints were conversion rate to liver resection and treatment-related adverse events.Results: Between November 2018 and December 2020, 62 uHCC patients who underwent triple therapy at four major cancer centers in China were analyzed, including 35 in BCLC-C, 21 in BCLC-B, and 6 in BCLC-A. With a median follow-up of 12.2 months (range, 7.6– 33.3 months), the investigator and blinded independent central review-assessed ORR were 80.6% and 77.4%, respectively. A total of 33 patients (53.2%) reached the standard of conversion to resectable HCC and 29 patients underwent resection. The median interval between start of triple therapy and resection was 123 days (range, 55– 372 days). Pathological complete response and major pathological response were observed in 16 and 24 patients, respectively. Median overall survival and progression-free survival were not reached. Treatment-related adverse events occurred in 74.2% of the patients (grade ≥ 3, 14.5%; grade ≥ 4, 4.8%).Conclusion: Combination of LEN, PD-1 and TACE showed a high rate of tumor response and convert resection in uHCC patients, with manageable toxicity.Keywords: unresectable hepatocellular carcinoma, tumor response, adverse events, combination therapy, monotherapy

Lignin, one of the renewable constituents in natural plant biomasses, holds great potential as a sustainable source of functional carbon materials. Tremendous research efforts have been made on lignin-derived carbon electrodes for rechargeable batteries. However, lignin is considered as one of the most promising carbon precursors for the development of high-performance, low-cost porous carbon electrode materials for supercapacitor applications. Yet, these efforts have not been reviewed in detail in the current literature. This review, therefore, offers a basis for the utilization of lignin as a pivotal precursor for the synthesis of porous carbons for use in supercapacitor electrode applications. Lignin chemistry, the synthesis process of lignin-derived porous carbons, and future directions for developing better porous carbon electrode materials from lignin are systematically reviewed. Technological hurdles and approaches that should be prioritized in future research are presented.

PurposeBladder cancer (BLCA) is one of the most common cancers worldwide. In a large proportion of BLCA patients, disease recurs and/or progress after resection, which remains a major clinical issue in BLCA management. Therefore, it is vital to identify prognostic biomarkers for treatment stratification. We investigated the efficiency of CpG methylation for the potential to be a prognostic biomarker for patients with BLCA.Patients and MethodsOverall, 357 BLCA patients from The Cancer Genome Atlas (TCGA) were randomly separated into the training and internal validation cohorts. Least absolute shrinkage and selector operation (LASSO) and support vector machine-recursive feature elimination (SVM-RFE) were used to select candidate CpGs and build the methylation risk score model, which was validated for its prognostic value in the validation cohort by Kaplan–Meier analysis. Hazard curves were generated to reveal the risk nodes throughout the follow-up. Gene Set Enrichment Analysis (GSEA) was used to reveal the potential biological pathways associated with the methylation model. Quantitative real-time polymerase chain reaction (PCR) and western blotting were performed to verify the expression level of the methylated genes.ResultsAfter incorporating the CpGs obtained by the two algorithms, CpG methylation of eight genes corresponding to TNFAIP8L3, KRTDAP, APC, ZC3H3, COL9A2, SLCO4A1, POU3F3, and ADARB2 were prominent candidate predictors in establishing a methylation risk score for BLCA (MRSB), which was used to divide the patients into high- and low-risk progression groups (p < 0.001). The effectiveness of the MRSB was validated in the internal cohort (p < 0.001). In the MRSB high-risk group, the hazard curve exhibited an initial wide, high peak within 10 months after treatment, whereas some gentle peaks around 2 years were noted. Furthermore, a nomogram comprising MRSB, age, sex, and tumor clinical stage was developed to predict the individual progression risk, and it performed well. Survival analysis implicated the effectiveness of MRSB, which remains significant in all the subgroup analysis based on the clinical features. A functional analysis of MRSB and the corresponding genes revealed potential pathways affecting tumor progression. Validation of quantitative real-time PCR and western blotting revealed that TNFAIP8L3 was upregulated in the BLCA tissues.ConclusionWe developed the MRSB, an eight-gene-based methylation signature, which has great potential to be used to predict the post-surgery progression risk of BLCA.

A-level scenic spots are a unique evaluation form of tourist attractions in China, which have an important impact on regional tourism development. Guizhou is a key tourist province in China. In recent years, the number of A-level scenic spots in Guizhou Province has been increasing, and the regional tourist economy has improved rapidly. The spatial distribution evolution characteristics and influencing factors of A-level scenic spots in Guizhou Province from 2005 to 2019 were measured using spatial data analysis methods, trend analysis methods, and geographical detector methods. The results elaborated that the number of A-level scenic spots in all counties of Guizhou Province increased, while in the south it developed slowly. From 2005 to 2019, the spatial distribution in A-level scenic spots were characterized by spatial agglomeration. The spatial distribution equilibrium degree of scenic spots in nine cities in Guizhou Province was gradually developed to reach the “relatively average” level. By 2019, the kernel density distribution of A-level scenic spots had formed the “two-axis, multi-core” layout. One axis was located in the north central part of Guizhou Province, and the other axis ran across the central part. The multi-core areas were mainly located in Nanming District, Yunyan District, Honghuagang District, and Xixiu District. From 2005 to 2007, the standard deviation ellipses of the scenic spots distribution changed greatly in direction and size. After 2007, the long-axis direction of the ellipses gradually formed a southwest to northeast direction. We chose elevation, population density, river density, road network density, tourism income, and GDP as factors, to discuss the spatiotemporal evolution of the scenic spots’ distribution with coupling and attribution analysis. It was found that the river, population distribution, road network density, and the A-level scenic spots’ distribution had a relatively high coupling phenomenon. Highway network density and tourist income have a higher influence on A-level tourist resorts distribution. Finally, on account of the spatiotemporal pattern characteristics of A-level scenic spots in Guizhou Province and the detection results of influencing factors, we put forward suggestions to strengthen the development of scenic spots in southern Guizhou Province and upgrade the development model of “point-axis network surface” to the current “two-axis multi-core” pattern of tourism development. This study can explain the current situation of the spatial development of tourist attractions in Guizhou Province, formulate a regulation mechanism of tourism development, and provide a reference for decision-making to boost the high-quality development of the tourist industry.

Strong convection nowcasting has been gaining importance in operational weather forecasting. Recently, deep learning methods have been used to meet the increasing requirement for precise and timely nowcasting. One of the promising deep learning models is the convolutional gated recurrent unit (ConvGRU), which has been proven to perform better than traditional methods in strong convection nowcasting. Despite its encouraging performance, ConvGRU tends to produce blurry radar echo images and fails to model radar echo intensities that have multi‐modal and skewed distributions. To overcome these disadvantages, we tested the structural similarity (SSIM) and multiscale structural similarity (MS‐SSIM) indexes as loss functions. The SSIM and MS‐SSIM loss functions are composed of luminance, contrast, and structure and provide more information about the intensity, grade, and shape of the radar echo, which can reduce blurring. Due to multi‐layer downscaling, MS‐SSIM extracted more radar echo characteristics, and its extrapolation was the most realistic and accurate among all of the loss function schemes. Only the MS‐SSIM scheme successfully predicted strong radar echoes after 2 h, especially those at the rainstorm level.

Face detection is an upstream task of facial image analysis. In many real-world scenarios, we need to detect small, occluded or dense faces that are hard to detect, but hard face detection is a challenging task in particular considering the balance between accuracy and inference speed for real-world applications. This paper proposes an Hourglass Face Detector (HFD) for hard face by developing a deep one-stage fully-convolutional hourglass network, which achieves an excellent balance between accuracy and inference speed. To this end, the HFD firstly shrinks a feature map by a series of stridden convolutional layers rather than pooling layers, so that useful subtle information is preserved better. Secondly, it exploits context information by merging fine-grained shallow feature maps with deep ones full of semantic information, making a better fusion of detailed information and semantic information to achieve a better detection of small faces. Moreover, the HFD exploits prior and multiscale information from the training data to enhance its scale-invariance and adaptability of anchor scales. Compared with the SSH and S3FD methods, the HFD can achieve a better performance in average precision on detecting hard faces as well as a quicker inference. Experiments on the WIDER FACE and FDDB datasets demonstrate the superior performance of our proposed method.

Free energy perturbation (FEP) has become widely used in drug discovery programs for binding affinity prediction between candidate compounds and their biological targets. However, limitations of FEP applications also exist, including, but not limited to, high cost, long waiting time, limited scalability, and breadth of application scenarios. To overcome these problems, we have developed XFEP, a scalable cloud computing platform for both relative and absolute free energy predictions using optimized simulation protocols. XFEP enables large-scale FEP calculations in a more efficient, scalable, and affordable way, for example, the evaluation of 5000 compounds can be performed in 1 week using 50-100 GPUs with a computing cost roughly equivalent to the cost for the synthesis of only one new compound. By combining these capabilities with artificial intelligence techniques for goal-directed molecule generation and evaluation, new opportunities can be explored for FEP applications in the drug discovery stages of hit identification, hit-to-lead, and lead optimization based not only on structure exploitation within the given chemical series but also including evaluation and comparison of completely unrelated molecules during structure exploration in a larger chemical space. XFEP provides the basis for scalable FEP applications to become more widely used in drug discovery projects and to speed up the drug discovery process from hit identification to preclinical candidate compound nomination.

Network embedding plays an important role in various real-world applications. Most traditional algorithms focus on the topological structure while ignore the information from node attributes. The attributed information is potentially valuable to network embedding. To solve this problem, we propose a deep learning model named Extractive Convolutional Adversarial Network (ECAN) for network embedding. This model aims to extract the latent representations from the topological structure, the attributed information, and labels via three components. In the first part, ECAN extracts features from the topological structure and the attributed information of nodes separately. The second part is a prediction model, which aims to exploit labels of vertices. The third part is a convolutional adversarial model. We train it to distinguish the extractive features which are generated by the hidden layers in the extractive network from either the attributed information or the topological structure. Experiments on six real-world datasets demonstrate the effectiveness of ECAN when compared with state-of-the-art embedding algorithms.

P–O–H polycondensation −O–Cu–O– ion-bonded bridges were formed in copper phosphate thermal insulation materials by mixing Al(OH)3 dissolved in H3PO4 with CuO filler and Al2O3, SiC, ZrC, and Cr2O3 as curing accelerators, alone or in combination. The effects of different additive combinations on the curing behavior and thermal stability of the copper phosphate thermal insulation material matrixes were compared using thermogravimetry/differential scanning calorimetry, X-ray diffractometry, and scanning electron microscopy. The copper phosphate materials exhibit good thermal stabilities and low thermal conductivities. The thermal weight losses before and after ceramic reinforcement were 4–19.8 and 3.8–9.4%, respectively, and the thermal conductivities of the P–O–H polycondensation −O–Cu–O– ion-bonded bridges formed in the copper phosphate thermal insulation materials were in the range of 0.656–1.824 W/(m·K).

ObjectivesDiverse evidence including clinical, genetic and microbiome studies support a major role of the gut microbiome in the common immune-mediated arthropathy, ankylosing spondylitis (AS). We set out to (1) further define the key microbial characteristics driving disease, and (2) examine the effects of tumour necrosis factor-inhibitor (TNFi) therapy upon the microbiome.MethodsThe stools from a case–control cohort of 250 Han-Chinese subjects underwent shotgun metagenomic sequencing. All subjects were genotyped using the Illumina CoreExome SNP microarray.ResultsPrevious reports of gut dysbiosis in AS were reconfirmed and several notable bacterial species and functional categories were differentially abundant. TNFi therapy was correlated with a restoration the perturbed microbiome observed in untreated AS cases to that of healthy controls, including several important bacterial species that have been previously associated with AS and other related diseases. Enrichment of bacterial peptides homologous to HLA-B27-presented epitopes was observed in the stools of patients with AS, suggesting that either HLA-B27 fails to clear these or that they are involved in driving HLA-B27-associated immune reactions. TNFi therapy largely restored the perturbed microbiome observed in untreated AS cases to that of healthy controls, including several important bacterial species that have been previously associated with AS and other related diseases. TNFi therapy of patients with AS was also associated with a reduction of potentially arthritogenic bacterial peptides, relative to untreated patients.ConclusionThese findings emphasise the key role that the gut microbiome plays in driving the pathogenesis of AS and highlight potential therapeutic and/or preventative targets.

Spinal cord ischemia and reperfusion (SCIR) injury can induce autophagy, which is involved in the survival of neurons. However, whether autophagy plays a neuroprotective or a detrimental role in SCIR injury remains controversial. Angiopoietin-1 (Ang-1), an endothelial growth factor, has been shown to have neuroprotective effects. The present study aimed to explore the neuroprotective mechanisms of Ang-1 in neuronal cells in a rat model of SCIR injury in vivo. Ang-1 protein and rapamycin were injected intrathecally. Basso Beattie Bresnahan (BBB) scoring and hematoxylin and eosin staining were used to assess the degree of SCIR injury. Proteins that reflected the level of autophagy expression, such as Beclin-1 and LC3, were evaluated by western blotting. The results indicated that SCIR injury resulted in loss in lower limb motor function. Ang-1 protein inhibited the expression of Beclin-1 and LC3, which improved the BBB score and alleviated spinal cord injury. In contrast, rapamycin, an autophagy activator, caused the opposite effect. This study provides evidence that Ang-1 plays a neuroprotective role by inhibiting of autophagy expression in SCIR injury. Overall, findings could be useful for the treatment of SCIR injury.

Although Sn-Pb perovskites sensing near-ultraviolet-visible-near-infrared light could be an attractive alternative to silicon in photodiodes and imaging, there have been no clear studies on such devices constructed on metal/silicon substrates, hindering their direct integration with complementary metal-oxide semiconductor (CMOS) and silicon electronics. Typically, high surface roughness and severe pinholes of Sn-rich binary perovskites make it difficult for them to fulfill the requirements of efficient photodiodes and imaging. These issues cause inherently high dark current and poor (dark and photo-) current uniformity. Herein, we propose and demonstrate the room-temperature crystallization in the Sn-rich binary perovskite system to effectively control film crystallization kinetics. With experimental and theoretical studies of the crystallization mechanism, we successfully tune the density and location of nanocrystals in precursor films to achieve compact nanocrystals, which coalesce into high-quality (smooth, dense, and pinhole-free) perovskites with intensified preferred orientation and decreased trap density. The high-quality perovskites reduce dark current and improve (dark and photo-) current uniformity of perovskite photodiodes on CMOS-compatible metal/silicon substrates. Meanwhile, self-powered devices achieve a high responsivity of 0.2 A/W at 940 nm, a large dynamic range of 100 dB, and a fast fall time of 2.27 μs, exceeding those of most silicon-based imaging sensors. Finally, a 6 × 6 pixel integrated photodiode array is successfully demonstrated to realize the imaging application. The work contributes to understanding the fundamentals of the crystallization of Sn-rich binary perovskites and advancing perovskite integration with Si-based electronics.

This study adopted an improved fuzzy clustering and optical flow method for the multiscale identification and forecasting of a cloud system based on the cloud images from a 10.8-micron infrared channel of the Advanced Geosynchronous Radiation Imager. First, we used the locally constrained fuzzy c-means (FCM) clustering method to identify typhoon-dominant cloud systems. Second, we coupled the background field-constrained optical flow method with the semi-Lagrangian scheme to forecast typhoon-dominant cloud systems. The experimental results for Typhoon Maria showed that the improved FCM method was able to effectively identify changes in the cloud system while retaining its edge information through the effective removal of the offset field. The identified dominant cloud system was consistent with the precipitation field of the Global Precipitation Measurement mission. We optimized the semi-Lagrangian nonlinear extrapolation of the optical flow field by introducing background field information, thus improving the forecast accuracy of the optical flow field. Based on the assessment indicators of structural similarity, normalized mutual information, peak signal-to-noise ratio, relative standard deviation, and root mean square error, the forecast results demonstrated that the forecast effect of the background field-constrained optical flow method was better than that of the standard optical flow method.

Two dimensional (2D) materials-based plasmon-free surface-enhanced Raman scattering (SERS) is an emerging field in nondestructive analysis. However, impeded by the low density of state (DOS), an inferior detection sensitivity is frequently encountered due to the low enhancement factor of most 2D materials. Metallic transition-metal dichalcogenides (TMDs) could be ideal plasmon-free SERS substrates because of their abundant DOS near the Fermi level. However, the absence of controllable synthesis of metallic 2D TMDs has hindered their study as SERS substrates. Here, we realize controllable synthesis of ultrathin metallic 2D niobium disulfide (NbS2) ( 160 μm). We have explored the SERS performance of as-obtained NbS2, which shows a detection limit down to 10-14 mol·L-1. The enhancement mechanism was studied in depth by density functional theory, which suggested a strong correlation between the SERS performance and DOS near the Fermi level. NbS2 features the most abundant DOS and strongest binding energy with probe molecules as compared with other 2D materials such as graphene, 1T-phase MoS2, and 2H-phase MoS2. The large DOS increases the intermolecular charge transfer probability and thus induces prominent Raman enhancement. To extend the results to practical applications, the resulting NbS2-based plasmon-free SERS substrates were applied for distinguishing different types of red wines.

Traditional methods of annotating the sentiment of an unlabeled document are based on sentiment lexicons or machine learning algorithms, which have shown low computational cost or competitive performance. However, these methods ignore the semantic composition problem displaying in several ways such as negative reversing and intensification. In this paper, we propose a new method for sentiment classification using negative and intensive sentiment supplementary information, so as to exploit the linguistic feature of negative and intensive words in conjunction with the context information. Particularly, our method can solve the domain-specific problem without relying on the external sentiment lexicons. Experimental results on two real-world datasets demonstrate the effectiveness of our proposed method.

Background and objectives Immediate postmastectomy breast reconstruction (IPBR) has gained wide popularity in China. We sought to clarify the prevalence and predictors of implant‐based vs autologous IPBR among Chinese patients. Methods A retrospective cohort study was performed using a prospectively maintained database. Women who underwent IPBR during 2001‐2017 were included. The modality‐specific trends were deciphered by curve fitting analysis. The association of sociodemographic and oncological features with the decision for implant‐based vs autologous IPBR was investigated using multivariate logistic regression and structural equation modeling. Results Among 905 patients included in the study, 479 underwent implant‐based IPBR and 426 underwent autologous procedures. The implant/autologous ratio has increased exponentially over time. Multivariate analysis demonstrated that unmarried patients with BMI ≤ 24 kg/m2, earlier clinical tumor stage, and preoperative pathological diagnosis of noninvasive lesion are more likely to choose implant‐based IPBR compared to autologous procedures. The indirect effects of age, mastectomy type, and neoadjuvant chemotherapy were further demonstrated by the structural equations. Conclusions The sociodemographic and oncological features are directly or indirectly associated with the decision on type of IPBR. The findings may facilitate both patients and physicians to make a high‐quality decision by holistic evaluation of the sociodemographic and oncological features.