Accurately predicting Drug-Drug Interaction (DDI) is a critical and challenging aspect of the drug discovery process, particularly in preventing adverse reactions in patients undergoing combination ...therapy. However, current DDI prediction methods often overlook the interaction information between chemical substructures of drugs, focusing solely on the interaction information between drugs and failing to capture sufficient chemical substructure details. To address this limitation, we introduce a novel DDI prediction method: Multi-layer Adaptive Soft Mask Graph Neural Network (MASMDDI). Specifically, we first design a multi-layer adaptive soft mask graph neural network to extract substructures from molecular graphs. Second, we employ an attention mechanism to mine substructure feature information and update latent features. In this process, to optimize the final feature representation, we decompose drug-drug interactions into pairwise interaction correlations between the core substructures of each drug. Third, we use these features to predict the interaction probabilities of DDI tuples and evaluate the model using real-world datasets. Experimental results demonstrate that the proposed model outperforms state-of-the-art methods in DDI prediction. Furthermore, MASMDDI exhibits excellent performance in predicting DDIs of unknown drugs in two tasks that are more aligned with real-world scenarios. In particular, in the transductive scenario using the DrugBank dataset, the ACC and AUROC and AUPRC scores of MASMDDI are 0.9596, 0.9903, and 0.9894, which are 2% higher than the best performing baseline.
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•Three novel compounds (1, 2, 3) were obtained from the flower buds of H. citrina.•Twelve known compounds were isolated from Hemerocallis genus for the first time.•Seven compounds ...exhibited NO inhibitory effect in the LPS induced BV2 cells.•Compound 1 play an anti-neuroinflammatory role through MAPK and NF-κB pathway.
Hemerocallis citrina Baroni (H. citrina) has been commonly utilized in diet and conventional medicine. In this study, 21 compounds were obtained from the flower buds of H. citrina. Compounds 1, 2 and 3 were three novel compounds isolated from Hemerocallis genus. Compounds 4, 6, 7, 9, 10, 13–19 were isolated from Hemerocallis genus for the first time. It indicated that compounds 1, 2, 3, 4, 5, 7 and 13 exhibited a significant NO inhibitory effect in the LPS induced BV2 cells. The analysis result of PPI and molecular docking showed that compound 1 may play an anti-neuroinflammatory role through MAPK signaling pathway. The result of pharmacological experiments proved that compound 1 effectively inhibited the generation of NO and inflammatory cytokines by inhibiting the activation of MAPK and NF-κB pathway. This research provided a basis for further study and utilization of H. citrina in anti-neuroinflammatory effect.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Due to their unique photoelectric properties, nontoxic tin‐based perovskites are emerging candidates for efficient near‐infrared LEDs. However, the facile oxidation of Sn2+ and the rapid ...crystallization rate of tin‐based perovskites result in suboptimal film quality, leading to inferior efficiencies of tin‐based perovskite light‐emitting diodes (Pero‐LEDs). In this study, we investigate the influence of commonly used solvents on the quality of the CsSnI3 films. Remarkably, DMSO exhibits a stronger interaction with SnI2, forming a stable intermediate phase of SnI2·3DMSO. This intermediate effectively inhibits the oxidation of Sn2+ and slows down the crystallization rate, bringing in lower defect state density and higher photoluminescence quantum yield of the prepared perovskite films. Consequently, the corresponding Pero‐LEDs achieve a maximum external quantum efficiency (EQE) of 5.6%, among the most efficient near‐infrared Pero‐LEDs. In addition, the device processes ultra‐low efficiency roll‐off and high reproducibility. Our research underscores the crucial role of solvent‐perovskite coordination in determining film quality. These findings offer valuable guidance for screening solvents to prepare highly efficient and stable tin‐based perovskites.
To mitigate Sn2+ oxidation and rapid crystallization in Sn‐based perovskite, we investigated the effects of four different solvents on the crystallization and quality of CsSnI3 film. Compared with DMF, NMP, and GBL solvents, the use of DMSO‐based CsSnI3 films demonstrated efficient inhibition of Sn2+ oxidation and a noticeably reduced crystallization rate. This benefit can be attributed to the strong interaction between the S=O group of DMSO and Sn2+, as well as the formation of SnI2·3DMSO intermediate phase.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
OBJECTIVETo examine the association between lymph node status and recurrence patterns in completely resected gastric adenocarcinoma. METHODSWe retrospectively assessed 1,694 patients who underwent ...curative gastrectomy from January 2010 to August 2014. Patients stratified according to lymph node status and recurrence patterns among different subgroups were compared. RESULTSOf all, 517 (30.5%) patients developed recurrent disease, and complete data of recurrence could be obtained in 493 (95.4%) patients. For pN0 patients, the patterns of recurrence were different according to pT stage: locoregional recurrence was most common in patients with pT1-2 disease (57.1%), distant recurrence was most common in patients with pT3 disease (57.1%), and peritoneal recurrence was most common in patients with pT4a disease (66.7%). For pN+ patients, distant metastasis was most common pattern irrespective of pT stage. The site-specific trend of recurrence showed that locoregional recurrence increased within 5 years in patients with pN0-2 disease but plateaued 3 years after surgery in patients with pN3 disease. Time to recurrence was significantly longer for the pN0 patients compared with the pN+ patients (median: 25 vs. 16 months, P=0.001). Moreover, post-recurrence survival was significantly better for the pN0 patients than for the pN+ patients (median: 12 vs. 6 months, P<0.001), especially in patients with non-peritoneal recurrence, late recurrence, single recurrence, and receipt of potential curative treatment. CONCLUSIONSAmong clinicopathologic factors, lymph node status is the most important factor associated with recurrence patterns after curative gastrectomy. Lymph node status may be used as an adjunct in clinical decision-making about postoperative therapeutic and follow-up strategies.
•We extend the successful RPN+BF framework to combine handcrafted features and CNN features for pedestrian detection.•RoI-pooling is used to extract features from handcrafted and CNN channels, and ...with larger output resolution for the former.•We explore several handcrafted channels such as HOG+LUV, Checkerboards, and RotatedFilters in our framework.•Experimental results on Caltech pedestrian dataset demonstrate the effectiveness of the proposed framework.•When using a more advanced RPN, our approach can be further improved and get competitive results on the benchmarks.
Pedestrian detection has achieved great improvements with the help of Convolutional Neural Networks (CNNs). CNN can learn high-level features from input images, but the insufficient spatial resolution of CNN feature channels (feature maps) may cause a loss of information, which is harmful especially to small instances. In this paper, we propose a new pedestrian detection framework, which extends the successful RPN+BF framework to combine handcrafted features and CNN features. RoI-pooling is used to extract features from both handcrafted channels (e.g. HOG+LUV, CheckerBoards or RotatedFilters) and CNN channels. Since handcrafted channels always have higher spatial resolution than CNN channels, we apply RoI-pooling with larger output resolution to handcrafted channels to keep more detailed information. Our ablation experiments show that the developed handcrafted features can reach better detection accuracy than the CNN features extracted from the VGG-16 net, and a performance gain can be achieved by combining them. Experimental results on Caltech pedestrian dataset with the original annotations and the improved annotations demonstrate the effectiveness of the proposed approach. When using a more advanced RPN in our framework, our approach can be further improved and get competitive results on both benchmarks.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
This study aimed to evaluate the incidence and prognosis of primary cardiac lymphoma (PCL) by using the Surveillance, Epidemiology, and End Results Program (SEER) database. Patients diagnosed with ...PCL and the disease incidence in the SEER database from 1975 to 2016 were included. Overall survival (OS) and cause‐specific survival (CSS) curves were calculated using the Kaplan‐Meier method and compared by the log‐rank test. Univariate and multivariable Cox proportional hazard regression analyses were used to identify associations with outcome measures. The incidence of PCL was 0.011/100 000, and a predominance of elderly and male patients was observed. A total of 144 patients were enrolled. The median age of onset was 68 (9‐96) years, including 80 (55.6%) males and 64 (44.4%) females. Multivariate analysis revealed that age and chemotherapy were independent prognostic factors for OS (both P < .05). Ann Arbor stage and chemotherapy were independent prognostic factors for CSS (both P < .05). In terms of treatment modality, chemotherapy combined with surgery was an independent protective factor for OS and CSS (both P < .05). For patients with primary cardiac diffuse large B‐cell lymphoma (cardiac DLBCL), multivariate analysis also showed that age, Ann Arbor stage, and chemotherapy were all independent prognostic factors for OS and CSS (all P < .05). Chemotherapy combined with surgery was associated with a significant benefit in terms of OS and CSS (both P < .05). Our study confirmed that older age and advanced Ann Arbor stage were independent risk factors for PCL, and treatment with chemotherapy or cooperation with surgery resulted in better long‐term survival.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
A high-resolution mass spectrometer combined with multiple data processing methods and various databases were employed to determine the components of flowers of Hemerocallis citrina Baroni (HF), and ...2,2-diphenyl-1-picrylhydrazyl (DPPH) pre-column derivatization combined with UHPLC–Q-TOF-MS method was used to screen antioxidant active compounds. A total of 132 components, including flavonoids, phenylpropanoids, lipids, alkaloids, and other types of compounds were identified. Among them, 41 chemical constituents were identified for the first time in HF. Eighteen compounds were screened with significant DPPH free radical scavenging activity. A sensitive UHPLC–QQQ-MS/MS method was first developed and fully validated for the simultaneous quantification of six phenylpropanoids and ten flavonoids in HF. The highest concentration of phenylpropanoids in HF was found to be 3-O-(E)-p-coumaroylquinic acid. In terms of flavonoids, rutin accounted for the highest concentration in HF. Correlation analysis was used to analyze the correlation between the contents of different compounds in different batches, Hierarchical cluster analysis (HCA) and principal component analysis (PCA) was used to distinguish HF of different origins. Considering the compounds content in HF, correlation analysis, principal component analysis and DPPH free radical scavenging activity, five components were recommended for the quality control of HF.
•132 chemical components were identified in flowers of Hemerocallis citrina Baroni (HF).•41 compounds were identified in HF for the first time.•A method for determination of 16 compounds in HF was established.•DPPH pre-column derivatization with UHPLC-Q-TOF-MS identified antioxidant components.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Background
Choosing the appropriate treatment for elderly patients with esophageal cancer remains a contentious issue. While surgery is still a valid option, we aimed to identify predictors and ...outcomes in elderly esophagectomy patients with esophageal cancer.
Patients and Methods
We analyzed characteristics, surgical outcomes, survival rates, cause-specific mortality, and recurrence in 120 patients with stage I–IV esophageal cancer. Univariate and multivariate analyses were used to identify risk factors for event-free survival (EFS) and overall survival (OS).
Results
The median follow-up period was 31 months, with 5-year overall survival (OS) and event-free survival (EFS) rates standing at 45.2% and 41.5%, respectively. Notably, lower body mass index (BMI ≤ 22 kg/m
2
) and reduced preoperative albumin levels (pre-ALB < 40 g/L) led to a significant decrease in OS rates. Postoperative pulmonary complications resulted in higher in-hospital and 90-day mortality rates. After about 31 months post-surgery, the rate of cancer-specific deaths stabilized. The most common sites for distant metastasis were the lungs, supraclavicular lymph nodes, liver, and bone. The study identified lower BMI, lower pre-ALB levels, and postoperative pulmonary complications as independent risk factors for poorer EFS and OS outcomes.
Conclusions
Esophagectomy remains a safe and feasible treatment for elderly patients, though the prevention of postoperative pulmonary infection is crucial. Factors such as lower BMI, lower pre-ALB levels, advanced tumor stage, postoperative pulmonary complications, and certain treatment modalities significantly influence the outcomes in elderly esophagectomy patients. These findings provide critical insights into the characteristics and outcomes of this patient population.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Abstract Recently, lead‐free Sn‐based perovskite light‐emitting diodes (PeLEDs) have attracted wide attention due to their near‐infrared emission and environmental friendliness. However, desired Sn ...2+ is easily oxidized to Sn 4+ in the crystallization process, resulting in defects and intrinsically p‐doped properties in the perovskite films. The uncontrollable oxidation affects the charge injection balance and radiative recombination, leading to poor device performance. Herein, a bi‐functional conductive molecular, 2,7‐bis(diphenylphosphoryl)‐9,9′‐spirobifluorene (SPPO13) with two P═O functional groups, is used to interact with perovskite to passivate defects and suppress the oxidation of Sn 2+ . Moreover, the SPPO13 modification layer inserted between the perovskite emitter and the electron transport layer can regulate the carrier injection and transport, thus promoting the charge balance. As a result, the high‐performance near‐infrared CsSnI 3 PeLEDs with a record external quantum efficiency (EQE) of 6.60% and ultra‐low efficiency roll‐off are achieved. The work provides a novel approach to regulate defect passivation and charge transport for efficient Sn‐based PeLEDs.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
With the increasing demand for high-quality telecommunication services, cellular KPI prediction becomes crucial for telecommunication network monitoring and management. In this work, we propose a ...novel framework for cellular KPI prediction, which considers its distribution discrepancy under different network operation scenarios. In particular, three specific predictors for normal, target alarm, and neighbor alarm scenarios are proposed based on spatiotemporal graph neural networks and unified through transfer learning. Temporal convolution and attention mechanism are embedded to model the impact of anomalies on KPIs and its propagation across neighboring cells according to the cellular network topology. An experiment on a real cellular KPI dataset shows the effectiveness of the proposed method compared to the state-of-the-arts. Note to Practitioners -Cellular network KPI prediction under scenarios of network alarms is crucial to evaluate the impact of alarms on network services and guides cellular network maintenance policies. This problem is similar to a general multivariate time series prediction problem with data multimodality. However, the first challenge in our case is that, under different scenarios, i.e., normal, target alarm, and neighbor alarm, the effective information and spatiotemporal dependencies among KPIs are different. The second challenge is the imbalanced or sparse sample size for specific scenarios, deteriorating the model performance. This paper proposes a cellular KPI prediction framework consisting of three scenario-specific predictors with similar but different modules to process different scenario-specific data. To address the dataset imbalance across scenarios, we adopt a transfer learning strategy to unify the training and prediction of three predictors. The experiment results on a real cellular KPI dataset demonstrate that the proposed framework is more feasible and effective than the state-of-the-art models for multivariate time series prediction. Future research can consider developing maintenance policies such that the cost caused by abnormal KPIs can be minimized.
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