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This paper proposes a teaching model based on the concept of outcome-based education (OBE). OBE is meant to be a student-centered learning model. Based on OBE, the characteristics of project-based learning (PBL) and lecture-based teaching approach are analyzed. Then, a combined teaching model is constructed based on Acharya’s research findings and PBL. This proposed model integrates PBL and lecture-based teaching approach to help achieve ideal learning outcomes. It enhances learners’ learning initiative and creativity while ensuring holistic and systematic learning outcomes.

Poly(ethylene terephthalate) (PET) is the most abundant polyester plastic and a major contributor to plastic pollution. IsPETase, from the PET-assimilating bacterium Ideonella sakaiensis, is a unique PET-hydrolytic enzyme that shares high sequence identity to canonical cutinases, but shows substrate preference towards PET and exhibits higher PET-hydrolytic activity at ambient temperature. Structural analyses suggest that IsPETase harbours a substrate-binding residue, W185, with a wobbling conformation and a highly flexible W185-locating β6-β7 loop. Here, we show that these features result from the presence of S214 and I218 in IsPETase, whose equivalents are strictly His and Phe, respectively, in all other homologous enzymes. We found that mutating His/Phe residues to Ser/Ile could enhance the PET-hydrolytic activity of several IsPETase-like enzymes. In conclusion, the Ser/Ile mutations should provide an important strategy to improve the activity of potential PET-hydrolytic enzymes with properties that may be useful for various applications. In the face of global plastic pollution, enzymatic degradation of poly(ethylene terephthalate) (PET) has attracted much attention. Now, structural and biochemical studies reveal a minimal mutational strategy to increase the activity of PET-degrading enzymes, with potential evolutionary implications.

Activation of nucleotide-binding domain leucine-rich repeat containing family pyrin domain containing 3 (NLRP3) inflammasome in Kupffer cells (KCs) contributes significantly to hepatic ischemia/reperfusion (I/R) injury, while the mechanism of how NLRP3 inflammasome is regulated remains less well defined. Recent evidence has showed that mitophagy acts as a central player for maintaining mitochondrial homeostatis through elimination of damaged mitochondria, leading to the prevention of hyperinflammation triggered by NLRP3 activation. In this study, we aimed at investigating the potential role of PTEN-induced kinase 1 (PINK1)-mediated mitophagy in hepatic I/R injury. C57BL/6 mice subjected to partial warm hepatic I/R or primary KCs exposed to anoxia/reoxygenation (A/R) was used as in vivo or in vitro model, respectively. Mitophagy was measured by protein levels of PINK1, Parkin, LC3B-II, TOMM20 and p62. NLRP3, caspase-1 and IL-1β at mRNA and/or protein levels were used as indicators of inflammasome activation. Our results demonstrated remarkable hepatic inflammation and NLRP3 inflammasome activation during hepatic I/R, along with increased PINK1-mediated mitophagy. Notably, overexpression of PINK1 in vivo attenuated hepatic I/R injury, ROS production, NLRP3 activation and hepatic inflammation. In parallel, A/R challenge in vitro also triggered NLRP3 activation in KCs accompanied by increase in mitophagy. Enhanced mitophagy mediated by PINK1 overexpression further inhibited NLRP3 activation and reversed the KC-mediated inflammatory injury to hepatocytes. Kinase-dead mutation of PINK1 completely abolished the above protective effects by PINK1. Blocking of mitophagy/autophagy by silencing of PINK1/Parkin, ATG5, NDP52 or OPTN showed the totally opposite effects, respectively. Treatment with different autophagic inhibitors also consistently reversed the PINK1-mediated effects, suggesting that an intact PINK1-mediated mitophagy signaling was crucial for ablation of NLRP3 signaling in the presence of A/R. Together, these results support a critical role of PINK1-mediated mitophagy in mitochondrial quality control for KC activation and function in hepatic I/R.

Background: Little is known about the genetic alterations characteristic of ovarian clear cell carcinoma (OCCC). Our aim was to identify targetable genomic alterations in this type of cancer. Methods: Forty-two OCCC formalin-fixed, paraffin-embedded (FFPE) tissue samples were analyzed by whole-exome sequencing (WES), and 74 FFPE tissue samples underwent targeted sequencing (TS) to confirm the relevant driver mutations. Cell proliferation was assessed by cell counting kit-8 (CCK8) assays. Findings: In the 42 samples, ARID1A (64.3%) and PIK3CA (28.5%) were frequently mutated, as were PPP2R1A (11.9%), PTEN (7.1%) and KRAS (4.8%), which have been reported in previous OCCC studies. We also detected mutations in MUC4 (28.6%), MAGEE1 (19%), and ARID3A (16.7%); associations with these genes have not been previously reported. The functional protein-activated pathways were associated with proliferation and survival (including the PI3K/AKT, TP53, and ERBB2 pathways) in 83% of OCCCs and with chromatin remodeling in 71% of OCCCs. Patients with alterations in MAGEE1 (64% in the targeted sequencing cohort) had worse clinical outcomes (log-rank p < 0.05). A functional study revealed that two MAGEE1 mutants, one lacking two MAGE domains and the other containing two MAGE domains, significantly decreased the proliferative capacity of OCCC cells. Funding: We successfully identified novel genetic alterations in OCCC using whole-exome sequencing and targeted sequencing of OCCC patient samples and potential therapeutic targets for the treatment of this malignancy. Declaration of Interest: The authors declare no conflict of interest. Ethical Approval: The use of samples and medical records was approved by the research ethics committees of Shanghai University of Medicine & Health Sciences Affiliated with Sixth People’s Hospital South Campus (approval number: 2017-KY-01), Fujian Provincial Maternity and Children's Hospital (approval number: 2017049), Nanjing Medical University Affiliated with Changzhou Maternal and Child Health Care Hospital (approval number: 2017005), Nanjing Medical University Affiliated with Changzhou No. 2 People’s Hospital (approval number: 2016-017-01), and Nanjing Medical University Affiliated with Suzhou Municipal Hospital (approval number: L2017003).

The use of the convolutional neural network for fault diagnosis has been a common method of research in recent years. Since this method can automatically extract fault features, it has played a good role in some research studies. However, this method has a clear drawback that the signals will be significantly affected by working conditions and sample size, and it is difficult to improve diagnostic accuracy by directly learning faults, regardless of working conditions. It is therefore a research orientation worthy of a diagnosis of high precision defect in various working conditions. In this article, using a fine-grained classification algorithm, the operating conditions of the object system are considered an approximate classification. A specific failure in different working conditions is considered a beautiful classification. Samples of different faults in different working conditions are learned uniformly and the common characteristics are extracted from the convolutional network so that different faults of different working conditions can simultaneously be identified on the basis of the entire sample. Experimental results show that the method effectively uses the set of samples of the working conditions of the variables to obtain the dual recognition of defects and specific working conditions and the accuracy of the recognition is significantly higher than the method of learning regardless of working conditions.

The PI3K/AKT/mTOR pathway is one of the most highly activated cellular signaling pathways in advanced ovarian cancer. Although several PI3K/AKT/mTOR inhibitors have been developed to treat various types of cancer, the antitumor efficacy of many of these compounds against ovarian cancer has remained unclear. Here, we tested and compared a panel of 16 PI3K/AKT/mTOR inhibitors (XL765, Miltefosine, Rapamycin, CCI-779, RAD001, FK506, XL147, GSK2110183, IPI-145, GSK2141795, BYL719, GSK458, CAL-101, XL765 analogue SAR245409, Triciribine, and GDC0941) that have entered clinical trials for antitumor activity against ovarian cancer, as well as the front line drug, paclitaxel. Antitumor efficacy was measured in both ovarian cancer cell lines and patient-derived ovarian primary tumor cell lines in vitro and in vivo. We identified the PI3K/mTOR dual inhibitor GSK458 as a potent inhibitor of proliferation in all cell lines tested at half maximal inhibitory concentrations (IC50) of approximately 0.01-1 µM, a range tens to hundreds fold lower than that of the other PI3K/AKT/mTOR inhibitors tested. Additionally, GSK458 showed the highest inhibitory efficacy against ovarian cancer cell migration. GSK458 also inhibited tumor growth and metastasis in nude mice intraperitoneally engrafted with SKOV3 cells or a patient-derived tumor cell xenograft (PDCX). Importantly, the inhibitory efficiency of GSK458 on cell proliferation and migration both in vitro and in vivo was comparable to that of paclitaxel. Mechanistically, the anti-tumor activity of GSK458 was found to be associated with inactivation of AKT and mTOR, and induction of cell cycle arrest at the G0/G1 phase. Based on our results, we conclude that GSK458 may serve as an attractive candidate to treat ovarian cancer.

In this work, we used a ternary blend strategy to improve the photovoltaic performance of organic solar cells (OSCs). PBDB-T:IDT-EDOT-based binary blend devices show a power conversion efficiency (PCE) of 9.93%, and the ternary devices with PC71BM as the third component exhibit a PCE of 12.07% with simultaneously enhanced Voc, Jsc and FF. The broadened absorption, optimized morphology and balanced charge carrier mobility of these devices are responsible for these improvements. The introduction of PC71BM can disperse the IDT-EDOT aggregates, enhance the phase purity, and increase the electroluminescence quantum efficiency (EQEEL). Furthermore, the performance of the ternary devices is not very sensitive to the weight ratio of the two acceptors. PCEs of over 11% are obtained even though the composition gradually varies from 1 : 1 : 0.2 to 1 : 0.4 : 0.8. Our results demonstrate that PC71BM is a highly promising second acceptor for the construction of high-efficiency ternary OSCs.

Long noncoding RNAs (lncRNAs) have been wildly explored in various cellular processes and their aberrant expression could lead to tumorigenesis, development and progression. Differentiation antagonizing non-protein coding RNA (DANCR), a well-known lncRNA that is aberrant expression in various tumors, including hepatocellular carcinoma, gastric cancer, colorectal cancer, breast cancer, lung cancer and glioma and so on, in which it functions as oncogene mainly, contributing to cancer development and progression. High expressed DANCR is correlated with poor prognosis. In the present review, we summarize recent progression concerning the role, potential clinical utilities and underlying molecular mechanisms of DANCR related to occurrence and development of multiple cancers.

The vibration-based analysis is an effective technique for planetary gearbox fault diagnosis, but a difficult task is how to accurately identify fault features from noisy vibration signals. In this paper, a nonconvex wavelet thresholding total variation (WATV) denoising method is proposed for planetary gearbox fault diagnosis, which combines wavelet-domain sparsity and total variation (TV) regularization. The TV regularization algorithm is employed to modify the retained wavelet coefficients so that the occurrence of oscillations caused by wavelet thresholding is suppressed. To overcome the underestimation shortcoming of L1-norm regularization, nonconvex penalty function regularization is used to strongly promote the sparsity of estimation while guaranteeing that the global optimal solutions are obtained even though the objective function is nonconvex. Then, the split augmented Lagrangian shrinkage (SALSA) method is developed to solve the nonconvex WATV denoising problem. Two experimental studies are performed to verify the performance and effectiveness of the proposed method. Comparisons with the soft thresholding and basis pursuit denoising (BPD) methods show that the proposed method can accurately estimate the fault features from vibration signals, which means that the proposed method is an effective and promising tool for planetary gearbox fault diagnosis.

Screw-pile composite foundations have been widely implemented on multiple high-speed railways in China. Their distinctive design with variable sections makes the bearing behaviour of screw piles far more complex than that of common smooth piles. The bearing behaviour of a screw-pile composite foundation was analysed in silt soil on a national key construction project. A comparative analysis of the bearing characteristics of composite foundations of smooth piles and screw piles was performed through model tests. The results showed that, in a single-pile composite foundation and with the same pile diameter and length, the ultimate bearing capacity of the screw pile was 67% higher than that of the smooth pile. The smooth pile showed an area of negative frictional resistance at the top of the composite foundation. The screw pile had a negative friction area below the junction of the smooth section and the screw section in the screw-pile composite foundation.

— One of the most prevalent diseases, skin cancer, has been proven to be treatable at an early stage. Thus, techniques that allow individuals to identify skin cancer symptoms early are in great demand. This paper proposed an interactive skin lesion diagnosis system based on the ensemble of multiple sophisticated CNN models for image classification. The performance of ResNet50, ResNeXt50, ResNeXt101, EfficientNetB4, Mobile-NetV2, MobileNetV3, and MnasNet are investigated separately as ensemble components. Then, using various criteria, we constructed ensembles and compared the accuracy they achieved. Moreover, we designed a method to update the ensemble for new data and examined its performance. In addition, a few natural language processing (NLP) techniques were used to make our system more user-friendly. To integrate all the functionalities, we built a user interface with PyQt5. As a result, MobileNetV3 achieved 91.02% as the best accuracy among all single models; ensemble weighted by cubic precision achieved 92.84% accuracy as the highest one in this study; a notable improvement in accuracy demonstrated the effectiveness of the model updating approach, and a system with all of the desired features was successfully developed. These findings benefit in two aspects. For model performance, applying cubic precisions can increase ensemble learning classification accuracy. For the developed diagnosis system, it can aid in the

This article has been retracted: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/our-business/policies/article-withdrawal). This article has been retracted at the request of the Editor-in-Chief and authors. Following the publication of the above article, the Editor was notified by a concerned reader that the authors supplied duplicated images. Specifically, that in Fig. 5 A, both FACS panels are identical and in Fig 5E, two different proteins (HK2 and PDK1) have the same western blot. After checking the data in relation with Fig. 5A and E, the authors have confirmed that the two pictures indeed have the problems of duplication. The authors reported that this problem came from the authors' unintentional behavior, which may be due to a copy and paste error in the manner of image processing. The authors sincerely apologize for the inconvenience caused to our Editors and readers. Due to this duplication error, the authors and Editor have made the decision to retract this paper.

Multiresonance thermally activated delayed fluorescence (MR-TADF) emitters manifest great potential for organic light-emitting diodes (OLEDs) due to their high exciton-utilization efficiency and narrowband emission. Nonetheless, their tendency toward self-quenching caused by strong interchromophore interactions would induce doping sensitivity and deteriorate the device performances, and effective strategy to construct quenching-resistant emitters without sacrifycing color purity is still to be developed. By segregating the planar MR-TADF skeleton using two bulky carbazolyl units, herein a highly emissive molecule with enhanced quenching resistance is reported. The steric effect largely removes the formation of detrimental excimers/aggregates, and boosts the performance of the corresponding devices with a maximum external quantum efficiency (EQEmax ) up to 40.0% and full width at half maximum (FWHM) of 25 nm, representative of the only example of single OLED that can concurrently achieve narrow bandwidth and high EL efficiency surpassing 40% to date. Even at doping ratio of 30 wt%, the EQEmax is retained to be 33.3% with nearly unchanged emission spectrum. This work provides a viable approach to realize doping-insensitive MR-TADF devices with extreme EL efficiency and color purity for high-end OLED displays.

The long noncoding RNA (lncRNA) DLGAP1-AS2 has recently been characterized as an oncogenic lncRNA in several cancers. However, its biological roles and clinical significance in gastric cancer (GC) remains barely understood. In this study, we performed a systematic analysis of DLGAP1-AS2 expression with data from the TCGA and GEO database as well as our clinic GC samples. In agreement with previous studies, our findings demonstrated that DLGAP1-AS2 was significantly up-regulated in GC and its high expression was associated with poor prognosis, suggesting that DLGAP1-AS2 might be a putative oncogenic lncRNA of GC. Loss of DLGAP1-AS2 restricted cell proliferation, migration, and invasion in GC cell lines. Mechanically, Wnt1 was identified as the downstream target of DLGAP1-AS2 by using bioinformatics analysis coupled with qPCR and Western blot assays. Furthermore, DLGAP1-AS2 was found to directly interact with the transcriptional repressor Six3, and this interaction hampered Six3 binding to the promoter regions of the Wnt1 gene, thereby leading to transcriptional activation of Wnt1. Consequently, GC cells lacking DLGAP1-AS2 showed a decreased Wnt1 expression and weakened Wnt/β-catenin signaling. Further, Six3 silencing could reverse the above effects, highlighting a pivotal role of Six3 in the DLGAP1-AS2-mediated activation of Wnt/β-catenin signaling. Either genetic (Wnt1 knockdown) or pharmacological (LF3) inhibition of Wnt/β-catenin signaling could effectively abolish the activation of Wnt/β-catenin signaling by Six3 depletion, thereby preventing GC cell malignant transformation. Taken together, our results suggest that DLGAP1-AS2 functions as an oncogenic factor by directly interacting with Six3 to relieve its suppression on Wnt1 expression, thereby driving the malignancy of GC. DLGAP1-AS2/Six3/Wnt1/β-catenin signaling axis might serve as a promising diagnostic and therapeutic target for GC.

With the development of deep learning, the design of an appropriate network structure becomes fundamental. In recent years, the successful practice of Neural Architecture Search (NAS) has indicated that an automated design of the network structure can efficiently replace the design performed by human experts. Most NAS algorithms make the assumption that the overall structure of the network is linear and focus solely on accuracy to assess the performance of candidate networks. This paper introduces a novel NAS algorithm based on a multi-objective modeling of the network design problem to design accurate Convolutional Neural Networks (CNNs) with a small structure. The proposed algorithm makes use of a graph-based representation of the solutions which enables a high flexibility in the automatic design. Furthermore, the proposed algorithm includes novel ad-hoc crossover and mutation operators. We also propose a mechanism to accelerate the evaluation of the candidate solutions. Experimental results demonstrate that the proposed NAS approach can design accurate neural networks with limited size.

Emerging evidence has classified the aberrant expression of long non‐coding RNAs (lncRNAs) as a basic signature of various malignancies including gastric cancer (GC). LINC01225 has been shown to act as a hepatocellular carcinoma‐related gene, with its expression pattern and biological function not clarified in GC. Here, we verified that LINC01225 was up‐regulated in tumour tissues and plasma of GC. Analysis with clinicopathological information suggested that up‐regulation of LINC01225 was associated with advanced disease and poorer overall survival. Receiver operating characteristic (ROC) analysis showed that plasma LINC01225 had a moderate accuracy for diagnosis of GC. In addition, knockdown of LINC01225 led to retardation of cell proliferation, invasion and migration, and overexpression of LINC01225 showed the opposite effects. Mechanistic investigations showed that LINC01225 silencing inhibited epithelial‐mesenchymal transition (EMT) process and attenuated Wnt/β‐catenin signalling of GC. Furthermore, ectopic expression of Wnt1 or suppression of GSK‐3β abolished the si‐LINC01225‐mediated suppression against EMT, thereby promoting cell proliferation, invasion and migration of GC. In conclusion, LINC01225 promotes the progression of GC through Wnt/β‐catenin signalling pathway, and it may serve as a potential target or strategy for diagnosis or treatment of GC.

Fault diagnosis of rotating machinery plays a significant role in the reliability and safety of modern industrial systems. The traditional fault diagnosis methods usually need manually extracting the features from raw sensor data before classifying them with pattern recognition models. This requires much professional knowledge and complex feature extraction, only to cause results in a poor flexibility of the model, which only applies to the diagnosis of a fault in particular equipment. In recent years, deep learning has developed rapidly, and great achievements have been made in image analysis, speech recognition and natural language processing. However, its application in fault diagnosis of rotating machinery is still at the initial stage. In order to solve the problem of end-to-end fault diagnosis, this paper focuses on developing a convolutional neural network to learn features directly from the original vibration signals and then diagnose faults. The effectiveness of the proposed method is validated through PHM (Prognostics and Health Management) 2009 gearbox challenge data and a planetary gearbox test rig. Compared with the other three traditional methods, the results show that the one-dimensional convolutional neural network (1-DCNN) model has higher accuracy for fixed-shaft gearbox and planetary gearbox fault diagnosis than that of the traditional diagnostic ones.

Two A−π–D−π–A-type non-fullerene acceptors (IDT-ToFIC and IDT-TiFIC) with 5-hexylthienyl chains substituted at the inner and outer β-positions of the thiophene π-bridge have been designed, respecti...

Side-chain engineering could tune the crystallinity, solubility and aggregation styles of fused-ring electron acceptors (FREAs), and thus could influence the morphology and charge carrier mobility of blend films as well as the final device performances. Herein, we developed a novel FREA called spiro-IDT-O-IC, which is composed of a spiro-bridged IDT core and two 1,1-dicyanomethylene-3-indanone (IC) terminal units. Similar acceptor molecule IDT-O-IC with four 4-octyloxyphenyl side chains is also prepared for the control experiment. The absorptions, energy levels, molecular configurations, and electronic wave functions of these two acceptor molecules have been comparatively studied. Polymer solar cells (PSCs) fabricated with PBDB-T:spiro-IDT-O-IC as the active layer demonstrated a PCE of 6.23% with a Jsc of 11.76 mA/cm2, a Voc of 0.84 V and an FF of 0.63. To the best of our knowledge, this is the first report that a spiro-bridged ladder type core was used for the fabrication of fused ring acceptors.

Two novel fused ring electron acceptors PDT and PDT-T have been designed, synthesized and used in organic solar cells. PDT comprises a central 4,10-bis(hexyloxy)-6,6,12,12-tetrakis(4-hexylphenyl)-6,12-dihydropyreno[1,2-b:6,7-b′]dithiophene (DDT) donor unit and two flanked 2-(5,6-difluoro-3-oxo-2,3-dihydro-1H-inden-1-ylidene)malononitrile acceptor units, while PDT-T has an extra thiophene bridge unit between the central donor unit and the acceptor unit. The introduction of a thiophene bridge unit can markedly broaden the absorption of acceptors and enhance the film absorption coefficient. The optical bandgaps of PDT and PDT-T are 1.59 and 1.44 eV, respectively. The photovoltaic performance of these two acceptors was investigated using PBDB-T as the electron donor. Wide photo-current responses extending to 800 nm for PDT based devices and to 900 nm for PDT-T based ones were observed. A power conversion efficiency (PCE) of 7.07% for PBDB-T:PDT based cells was obtained with a Voc of 0.96 V, Jsc of 13.48 mA cm−2 and FF of 54.0%, while the as-cast devices based on PBDB-T:PDT-T gave rise to a PCE of 11.02% with a Voc of 0.88 V, Jsc of 18.88 mA cm−2 and FF of 66.3%. These results highlight that DDT is a promising building block for constructing highly efficient fused ring acceptors and π-bridging can further boost the photovoltaic performance of the devices.

A fused-ring electron acceptor (FREA) NDIC is designed and synthesized. Inspired by IDIC, NDIC was constructed by replacing the benzene with a naphthalene ring in its core unit. IDIC exhibits an optical bandgap of 1.60 eV and a lower lowest unoccupied molecular orbital (LUMO) energy level of −3.92 eV. In comparison, NDIC displays an optical band gap of 1.72 eV and a higher lying LUMO energy level of −3.88 eV. Due to the higher energy level, inverted devices based on NDIC exhibit a higher open circuit voltage (Voc) of 0.90 V, which is much higher than that of IDIC (0.77 V). After a series of optimizations, a power conversion efficiency (PCE) of 9.43% was obtained with a PBDB-T:NDIC blend active layer, in comparison, a PCE of 9.19% was achieved based on IDIC. Our results demonstrate that a tiny variation in the molecular structure could dramatically affect the optical and electrochemical properties, and thus the photovoltaic performance.

Cancer cells are typically characterized by abnormal quality control of mitochondria, production of reactive oxygen species (ROS), dysregulation of the cell redox state, and the Warburg effect. Mutation or depletion of PTEN-induced kinase 1 (PINK1) or Parkin leads to mitophagy defects and accumulation of malfunctioning mitochondria, and is often detected in a variety of tumors. However, PINK1's role in the progression of gastric cancer (GC) remains unclear, with its main effect being on mitochondrial turnover, metabolic reprogramming, and tumor microenvironment (TME) alteration. To address these issues, we first assessed the expression levels of PINK1, mitophagy-associated molecules, ROS, HIF-1α, glycolysis-associated genes, and macrophage signatures in GC tissues and matched tumor-adjacent normal samples. In addition, GC cell lines (AGS and MKN-45) and xenograft mouse models were used to determine the mechanism by which PINK1 regulates mitophagy, metabolic reprogramming, tumor-associated macrophage (TAM) polarization, and GC progression. We found that PINK1 loss correlated with advanced stage GC and poorer overall survival. GC tissues with lower PINK1 levels showed compromised mitophagy signaling and enhanced glycolytic enzyme expression. In vitro experiments demonstrated that PINK1 deficiency promoted GC cell proliferation and migration through the inhibition of mitophagy, production of mitochondrial ROS, stabilization of HIF-1α, and facilitation of the Warburg effect under both normoxic and hypoxic conditions. Moreover, PINK1 deficiency in GC cells promoted TAM polarization toward the M2-like phenotype. Reintroduction of PINK1 or inhibition of HIF-1α effectively repressed PINK1 deficiency-mediated effects on GC cell growth, metabolic shift, and TAM polarization. Thus, mitophagy defects caused by PINK1 loss conferred a metabolic switch through accumulation of mtROS and stabilization of HIF-1α, thereby facilitating the M2 polarization of TAM to remodel an immunosuppressive microenvironment in GC. Our results clarify the mechanism between PINK1 and GC progression and may provide a novel strategy for the treatment of GC.

To solve the problem that the traditional feature selection methods, such as PCA and LDA, are unable to get the nonlinear relationship between characteristics. Deep belief networks cannot eliminate the noise and missing value, which affect the accuracy of the software defect prediction (SDP) model. Not only the methods of feature selection, but data preprocessing and learning algorithm can also affect the precision of the defect prediction model. This thesis uses deep belief networks and SVM to construct an SDP model (DBN-SVM) to increase prediction precision. Using denoising autoencoders and SVM to build an SDP model (DA - SVM), compared with the DBN - SVM, DA - SVM model not only improves the prediction precision, but also enhance the robustness of the model. The thesis also proposes an SDP model framework which includes data preprocessing, feature selection and learning algorithm.

Multi-resonance thermally activated delayed fluorescence (MR-TADF) offered exceptional solution for narrowband organic light emitting diode (OLED) devices in terms of color purity and luminescence efficiency, while the development of new MR skeleton remained an exigent task, especially for long wavelength region. We hereby demonstrate that a simple modification of the B (boron)-N (nitrogen) framework by sp3 -carbon insertion would significant bathochromic shift the short-range chargetransfer emission and improve the device performances. The bis(acridan)phenylenebased skeleton developed in this contribution presented a non-planar conformation and allowed facile introduction of isolating units to prevent triplet-involved quenching, deriving two luminophores with quantum yields approaching 90% and narrow FWMHs below 30 nm in film state. Corresponding green-emissive devices realized superior performances comparing to the planar carbazolyl-based MR-TADF analogues, with a maximum external quantum efficiency (EQEmax) up to 28.2% and small efficiency rolloff without the involvement of any sensitizing host

In this work, a ternary blend strategy based on PBDB-T and two small molecular acceptors (IDTT-OB and IDT-PDOT-C6) is demonstrated to simultaneously improve the photocurrent and reduce the voltage ...

Background Exosomes are extracellular vesicles that mediate cellular communication in health and diseases. Neutrophils could be polarized to a pro-tumor phenotype by tumor. The function of tumor-derived exosomes in neutrophil regulation remains unclear. Methods We investigated the effects of gastric cancer cell-derived exosomes (GC-Ex) on the pro-tumor activation of neutrophils and elucidated the underlying mechanisms. Results GC-Ex prolonged neutrophil survival and induced expression of inflammatory factors in neutrophils. GC-Ex-activated neutrophils, in turn, promoted gastric cancer cell migration. GC-Ex transported high mobility group box-1 (HMGB1) that activated NF-κB pathway through interaction with TLR4, resulting in an increased autophagic response in neutrophils. Blocking HMGB1/TLR4 interaction, NF-κB pathway, and autophagy reversed GC-Ex-induced neutrophil activation. Silencing HMGB1 in gastric cancer cells confirmed HMGB1 as a key factor for GC-Ex-mediated neutrophil activation. Furthermore, HMGB1 expression was upregulated in gastric cancer tissues. Increased HMGB1 expression was associated with poor prognosis in patients with gastric cancer. Finally, gastric cancer tissue-derived exosomes acted similarly as exosomes derived from gastric cancer cell lines in neutrophil activation. Conclusion We demonstrate that gastric cancer cell-derived exosomes induce autophagy and pro-tumor activation of neutrophils via HMGB1/TLR4/NF-κB signaling, which provides new insights into mechanisms for neutrophil regulation in cancer and sheds lights on the multifaceted role of exosomes in reshaping tumor microenvironment. Electronic supplementary material The online version of this article (10.1186/s12943-018-0898-6) contains supplementary material, which is available to authorized users.

The degradation of rolling bearings is complex, and traditional methods of degenerating feature degradation are highly dependent on previous research and expertise. However, the traditional methods’ ability for learning the complex relationship between degraded features and large amounts of measured data is limited. So, it is difficult to construct a single health indicator (HI) to predict the degradation state of the bearing. In order to solve this problem, a multi-scale convolutional neural network (MSCNN) is proposed, which uses the frequency signal as input to construct HI. In combination with the “bathtub curve,” the HI we proposed is constructed by the inverse hyperbolic tangent function (atanh) method which is different from the proportional HI construction method. Five kinds of processing methods, such as original vibration signal, frequency signal and three kinds of modal decomposition preprocessed signals, are tested with PHM 2012 bearing lifetime data. And the proposed method is compared with other three HI construction methods. The experimental results show that under the HI construction method of atanh, the MSCNN model with the input of frequency signal can better represent the degradation state of the bearing compared with other methods. Meanwhile, the remaining life prediction is more accurate compared.

The performance of polymer solar cells (PSCs) is commonly improved using additives or annealing treatment. However, these processes are accompanied by disadvantages, including poor reproducibility and stability. Herein, a molecular design strategy is proposed to obtain additive- and annealing-free PSCs. IDTOT2F containing two alkoxyl side chains at the central unit of the nonfullerene acceptor IDTT2F was developed. This molecular design results in excellent solubility in solutions, ordered molecular packing in films, slightly elevated energy levels, and a higher film absorption coefficient. Compared with its counterpart IDTT2F, its improved solubility provides an active layer with better morphology, its ordered molecular packing enhances the charge mobility in blend films, and its slightly elevated energy level furnishes a higher open-circuit voltage of devices. As a result, IDTOT2F-based devices display a maximum power conversion efficiency of 12.79%, which is one of the highest values reported for a PSC...

Background Long non-coding RNAs (lncRNAs) have emerged as important regulators of human cancers. However, the functional roles of lncRNAs and the mechanisms responsible for their aberrant expression in gastric cancer (GC) have not been well characterized. Methods In this study, we examined the expression of lncRNA UFC1 in GC by qRT-PCR and explored its correlation with clinicopathological parameters. In vitro cell functional assays and in vivo animal studies were performed to determine the roles of UFC1 in GC progression. Results UFC1 was elevated and predicted poorer prognosis in GC. UFC1 knockdown inhibited while UFC1 overexpression promoted GC cell proliferation, migration, and invasion. UFC1 bound to miR-498 to antagonize its tumor suppressive effect on Lin28b. Suppression of Lin28b by miR-498 could be rescued by UFC1 overexpression, whereas Lin28b overexpression partially rescued UFC1 knockdown-mediated inhibition of GC cell function. Lin28b expression was increased in GC and suggested a co-expression pattern with UFC1. Conclusions UFC1 has a promoting role in GC progression, at least in part, by acting as a miR-498 sponge and derepressing Lin28b expression, which would provide a novel biomarker for GC diagnosis and prognosis and offer a potential target for GC therapy. Electronic supplementary material The online version of this article (10.1186/s13046-018-0803-6) contains supplementary material, which is available to authorized users.

To discuss the effect and mechanism of adenovirus-mediated OX40Ig gene transfer in inducing long-term survival of liver allografts in rats.Orthotopic liver transplantation was performed from Lewis to Brown Norway (BN) rats through the modified two-cuffed technique, and all rats were randomly divided equally into four groups: control, AdEGFP, AdOX40Ig, and FK506. The survival times of the rats were recorded. The rats' liver function, serum cytokines, hepatocyte pathology, OX40Ig protein level, and mixed lymphocyte reaction (MLR) with or without recombinant interleukin-2 (rIL-2) were evaluated.Compared with the control and AdEGFP groups, the rats in the AdOX40Ig and FK506 groups survived longer (P 0.05), experienced less damage to hepatic function (P 0.05), and showed milder hepatic cellular rejection and less hepatic cellular apoptosis. Interferon (IFN)-γ and IL-2 content in the serum were lower after operation (P .05) in the AdOX40Ig and FK506 groups. On the contrary, IL-4 and IL-10 content in the serum was higher after operation (P 0.05) in the AdOX40Ig and FK506 groups. OX40Ig protein was significantly expressed in the AdOX40Ig group and reached the highest level on the 7th day after operation. With respect to the MLR between BN and Lewis rats, the AdOX40Ig group showed a lighter reaction for the same strain than the control and AdEGFP groups (P 0.05), which is different from the MLR between BN and F344 rats. After adding rIL-2 to the MLR system between BN rats in the AdOX40Ig group and Lewis rats, MLR was aggravated.Through OX40/OX4OL pathways, OX40Ig created an immunosuppressive effect after liver transplantation in rats. This immunosuppressive effect is associated with reduced IL-2 and can be reversed by adding IL-2 with antigen specificity.

Smart traffic prediction system provides significant benefits in solving the city traffic congestion. However, existing smart transportation system needs a lot of real-time traffic data and accurate location information to display the traffic condition. We hope that we can use the data which is easy to be obtained, and then predict a reliable congestion time. To address this problem, this paper studied a smart traffic forecasting system based on SWARIMA model. The system includes three steps: 1) use the sliding windows to calculate and process real-time data stream; 2) establish the SWARIMA model and make regression analysis; and 3) from a statistical point of view, calculate the elastic interval and predict the congestion trend. Our system is capable of accepting the real-time traffic data stream for the congestion prediction, in addition, we reduce the actual running parameters to three attributes: 1) speed; 2) time; and 3) location information. When faced with the challenges of real-time traffic congestion, the system can timely and effectively calculate the congestion trends and provide three reliable elastic intervals: 1) warning; 2) congestion; and 3) mitigation, which has significance to improve traffic condition and alleviate urban road congestion.

We have designed and synthesized two fused-ring small molecular acceptors IDT-PDOT and IDT-EDOT, comprising 3,4-propylenedioxythiophene (PDOT) and 3,4-ethylenedioxythiophene (EDOT) bridging units, respectively. The only structural difference between these two acceptors is one methylene group at the π-bridging unit. However, such a tiny structural difference exerts a great influence on the optical, electrical and photovoltaic properties of the acceptors. The molar absorption coefficient of IDT-EDOT is more than four times higher than that of IDT-PDOT. The electron mobility of the IDT-EDOT based blend film is one order of magnitude higher than that of the IDT-PDOT based one. Consequently, a high power conversion efficiency (PCE) of 11.32% for IDT-EDOT based devices was obtained, whereas a PCE of only 2.18% was achieved for IDT-PDOT based ones. Our results have demonstrated that changing the π-bridging unit in fused ring acceptors is an effective strategy to adjust their photovoltaic performance.

The smart city, as a new urbanization mode, provides a practicable initiative for achieving the win-win situation of economic development and environmental protection. This paper examines the influence of smart city construction on urban green total factor productivity (GTFP), explores the influence mechanism and further investigates the heterogeneous influence among the factors of urban scale, human capital and financial development, by conducting a quasi-natural experiment based on the first batch of pilot smart city in China and using panel data of 174 prefecture level cities over the period of 2005−2016. Our findings show that: (1) Smart city construction pilot significantly improves GTFP and green technological progress (GTP) in China, but its influence on GTE is not significant, which means smart city construction promotes GTFP mainly through promoting GTP. This conclusion is still valid after a series of robustness tests. (2) The estimation result of mediating effect models is that smart city construction promoted GTFP and GTP mainly through boosting urban technological innovation. The influence path of “smart city construction→technological innovation→GTFP” is verified. (3) Regarding city heterogeneity, cities with larger scale, richer human capital and higher level financial development have stronger positive effects on GTFP and GTP. These conclusions are of vital significance to improve the urban ecological environment and promote the high-quality development of urban economy.

Since the physical modeling method for the desiccant wheel system (DWS) is complex and costly for calculations, the modeling method based on neural network (NN) gains attention for its simplicity and effectiveness. The previous NN models of DWS are mostly based on backpropagation (BP) NN and adopt the gradient searching method to obtain the weights and thresholds. However, the gradient searching method results in “overfitting” easily. In this paper, a novel neural network training algorithm, trainmpga, is proposed. The algorithm searches the optimal weights and thresholds of NN by making use of the multiple population genetic algorithm, thereby conquering the “overfitting” of the gradient searching method and the “prematurity” of the genetic algorithm. Meanwhile, related configurations of NN, such as parameters and framework, are studied. Finally, the proposed modeling method trainmpga proves to have high training and prediction accuracy in comparison to the training algorithms in the MatLab toolb...