CFN-ESA: A Cross-Modal Fusion Network with Emotion-Shift Awareness for Dialogue Emotion Recognition

Multimodal Emotion Recognition in Conversation (ERC) has garnered growing attention from research communities in various fields. In this paper, we propose a cross-modal fusion network with emotion-shift awareness (CFN-ESA) for ERC. Extant approaches employ each modality equally without distinguishing the amount of emotional information, rendering it hard to adequately extract complementary and associative information from multimodal data. To cope with this problem, in CFN-ESA, textual modalities are treated as the primary source of emotional information, while visual and acoustic modalities are taken as the secondary sources. Besides, most multimodal ERC models ignore emotion-shift information and overfocus on contextual information, leading to the failure of emotion recognition under emotion-shift scenario. We elaborate an emotion-shift module to address this challenge. CFN-ESA mainly consists of the unimodal encoder (RUME), cross-modal encoder (ACME), and emotion-shift module (LESM). RUME is applied to extract conversation-level contextual emotional cues while pulling together the data distributions between modalities; ACME is utilized to perform multimodal interaction centered on textual modality; LESM is used to model emotion shift and capture related information, thereby guide the learning of the main task. Experimental results demonstrate that CFN-ESA can effectively promote performance for ERC and remarkably outperform the state-of-the-art models.Comment: 13 pages, 10 figure

Simple Model Also Works: A Novel Emotion Recognition Network in Textual Conversation Based on Curriculum Learning Strategy

Emotion Recognition in Conversation (ERC) has emerged as a research hotspot in domains such as conversational robots and question-answer systems. How to efficiently and adequately retrieve contextual emotional cues has been one of the key challenges in the ERC task. Existing efforts do not fully model the context and employ complex network structures, resulting in excessive computational resource overhead without substantial performance improvement. In this paper, we propose a novel Emotion Recognition Network based on Curriculum Learning strategy (ERNetCL). The proposed ERNetCL primarily consists of Temporal Encoder (TE), Spatial Encoder (SE), and Curriculum Learning (CL) loss. We utilize TE and SE to combine the strengths of previous methods in a simplistic manner to efficiently capture temporal and spatial contextual information in the conversation. To simulate the way humans learn curriculum from easy to hard, we apply the idea of CL to the ERC task to progressively optimize the network parameters of ERNetCL. At the beginning of training, we assign lower learning weights to difficult samples. As the epoch increases, the learning weights for these samples are gradually raised. Extensive experiments on four datasets exhibit that our proposed method is effective and dramatically beats other baseline models.Comment: 12 pages,9 figure

LBH589 Inhibits proliferation and metastasis of hepatocellular carcinoma via inhibition of gankyrin/stat3/akt pathway

Background: Gankyrin has shown to be overexpressed in human liver cancers and plays a complex role in hepatocarcinogenesis. Panobinostat (LBH589), a new hydroxamic acid-derived histone deacetylase inhibitor has shown promising anticancer effects recently. Here, we investigated the potential of LBH589 as a form of treatment for hepatocellular carcinoma (HCC). Methods: Gankyrin plasmid was transfected into HCC cells, and the cells were selected for more than 4 weeks by incubation with G418 for overexpression clones. The therapeutic effects of LBH589 were evaluated in vitro and in vivo. Cell proliferation, apoptosis, cell cycle, invasive potential, and epithelial-mesenchy-mal transition (EMT) were examined. Results: LBH589 significantly inhibited HCC growth and metastasis in vitro and in vivo. Western blotting analysis indicated that LBH589 could decrease the expression of gankyrin and subsequently reduced serine-phosphorylated Akt and tyrosine-phosphorylated STAT3 expression although the total Akt and STAT3 were unaffected. LBH589 inhibited metastasis in vitro via down-regulation of N-cadherin, vimentin, TWIST1, VEGF and up-regulation of E-cadherin. LBH589 also induced apoptosis and G1 phase arrest in HCC cell lines. Ectopic expression of gankyrin attenuated the effects of LBH589, which indicates that gankyrin might play an important role in LBH589 mediated anticancer effects. Lastly, in vivo study indicated that LBH589 inhibited tumor growth and metastasis, without discernable adverse effects comparing to control group, with abrogating gankyrin/STAT3/Akt pathway. Conclusions: Our results suggested that LBH589 could inhibit HCC growth and metastasis through down-regulating gankyrin/STAT3/Akt pathway. LBH589 may present itself as a novel therapeutic strategy for HCC

Global research trends of the application of artificial intelligence in bladder cancer since the 21st century: a bibliometric analysis

IntroductionSince the significant breakthroughs in artificial intelligence (AI) algorithms, the application of AI in bladder cancer has rapidly expanded. AI can be used in all aspects of the bladder cancer field, including diagnosis, treatment and prognosis prediction. Nowadays, these technologies have an excellent medical auxiliary effect and are in explosive development, which has aroused the intense interest of researchers. This study will provide an in-depth analysis using bibliometric analysis to explore the trends in this field.MethodDocuments regarding the application of AI in bladder cancer from 2000 to 2022 were searched and extracted from the Web of Science Core Collection. These publications were analyzed by bibliometric analysis software (CiteSpace, Vosviewer) to visualize the relationship between countries/regions, institutions, journals, authors, references, keywords.ResultsWe analyzed a total of 2368 publications. Since 2016, the number of publications in the field of AI in bladder cancer has increased rapidly and reached a breathtaking annual growth rate of 43.98% in 2019. The U.S. has the largest research scale, the highest study level and the most significant financial support. The University of North Carolina is the institution with the highest level of research. EUROPEAN UROLOGY is the most influential journal with an impact factor of 24.267 and a total citation of 11,848. Wiklund P. has the highest number of publications, and Menon M. has the highest number of total citations. We also find hot research topics within the area through references and keywords analysis, which include two main parts: AI models for the diagnosis and prediction of bladder cancer and novel robotic-assisted surgery for bladder cancer radicalization and urinary diversion.ConclusionAI application in bladder cancer is widely studied worldwide and has shown an explosive growth trend since the 21st century. AI-based diagnostic and predictive models will be the next protagonists in this field. Meanwhile, the robot-assisted surgery is still a hot topic and it is worth exploring the application of AI in it. The advancement and application of algorithms will be a massive driving force in this field

Nutlin-3 overcomes arsenic trioxide resistance and tumor metastasis mediated by mutant p53 in Hepatocellular Carcinoma

Background: Arsenic trioxide has been demonstrated as an effective anti-cancer drug against leukemia and solid tumors both in vitro and in vivo. However, recent phase II trials demonstrated that single agent arsenic trioxide was poorly effective against hepatocellular carcinoma (HCC), which might be due to drug resistance. Methods: Mutation detection of p53 gene in arsenic trioxide resistant HCC cell lines was performed. The therapeutic effects of arsenic trioxide and Nutlin-3 on HCC were evaluated both in vitro and in vivo. A series of experiments including MTT, apoptosis assays, co-Immunoprecipitation, siRNA transfection, lentiviral infection, cell migration, invasion, and epithelial-mesenchy-mal transition (EMT) assays were performed to investigate the underlying mechanisms. Results: The acquisition of p53 mutation contributed to arsenic trioxide resistance and enhanced metastatic potential of HCC cells. Mutant p53 (Mutp53) silence could re-sensitize HCC resistant cells to arsenic trioxide and inhibit the metastatic activities, while mutp53 overexpression showed the opposite effects. Neither arsenic trioxide nor Nutlin-3 could exhibit obvious effects against arsenic trioxide resistant HCC cells, while combination of them showed significant effects. Nutlin-3 can not only increase the intracellular arsenicals through inhibition of p-gp but also promote the p73 activation and mutp53 degradation mediated by arsenic trioxide. In vivo experiments indicated that Nutlin-3 can potentiate the antitumor activities of arsenic trioxide in an orthotopic hepatic tumor model and inhibit the metastasis to lung. Conclusions: Acquisitions of p53 mutations contributed to the resistance of HCC to arsenic trioxide. Nutlin-3 could overcome arsenic trioxide resistance and inhibit tumor metastasis through p73 activation and promoting mutant p53 degradation mediated by arsenic trioxide

Diphenyl Difluoroketone: A Potent Chemotherapy Candidate for Human Hepatocellular Carcinoma

Diphenyl difluoroketone (EF24), a molecule having structural similarity to curcumin, was recently reported to inhibit proliferation of various cancer cells significantly. Here we try to determine the effect and mechanism of EF24 on hepatocellular carcinoma. 2 µM EF24 was found to inhibit the proliferation of PLC/PRF/5, Hep3B, HepG2, SK-HEP-1 and Huh 7 cell lines. However, even 8 µM EF24 treatment did not affect the proliferation of normal liver LO2 cells. Accordingly, 20 mg/kg/d EF24 inhibited the growth of the tumor xenografts conspicuously while causing no apparent change in liver, spleen or body weight. In addition, significant apoptosis and G2/M phase cell cycle arrest were found using flow cytometry. Besides, caspases and PARP activation and features typical of apoptosis including fragmented nuclei with condensed chromatin were also observed. Furthermore, the mechanism was targeted at the reduction of nuclear factor kappa b (NF-κB) pathway and the NF-κB–regulated gene products Bcl-2, COX-2, Cyclin B1. Our study has offered a strategy that EF24 being a therapeutic agent for hepatocellular carcinoma

Effect of Scanning and Reconstruction Parameters on Three Dimensional Volume and CT Value Measurement of Pulmonary Nodules: A Phantom Study

Background and objective The computed tomography (CT) follow-up of indeterminate pulmonary nodules aiming to evaluate the change of the volume and CT value is the common strategy in clinic. The CT dose needs to considered on serious CT scans in addition to the measurement accuracy. The purpose of this study is to quantify the precision of pulmonary nodule volumetric measurement and CT value measurement with various tube currents and reconstruction algorithms in a phantom study with dual-energy CT. Methods A chest phantom containing 9 artificial spherical solid nodules with known diameter (D=2.5 mm, 5 mm, 10 mm) and density (-100 HU, 60 HU and 100 HU) was scanned using a 64-row detector CT canner at 120 Kilovolt & various currents (10 mA, 20 mA, 50 mA, 80 mA,100 mA, 150 mA and 350 mA). Raw data were reconstructed with filtered back projection and three levels of adaptive statistical iterative reconstruction algorithm (FBP, ASIR; 30%, 50% and 80%). Automatic volumetric measurements were performed using commercially available software. The relative volume error (RVE) and the absolute attenuation error (AAE) between the software measures and the reference-standard were calculated. Analyses of the variance were performed to evaluate the effect of reconstruction methods, different scan parameters, nodule size and attenuation on the RPE. Results The software substantially overestimated the very small (D=2.5 mm) nodule's volume [mean RVE: (100.8%±28%)] and underestimated it attenuation [mean AAE: (-756±80) HU]. The mean RVEs of nodule with diameter as 5 mm and 10 mm were small [(-0.9%±1.1%) vs (0.9%±1.4%)], however, the mean AAEs [(-243±26) HU vs (-129±7) HU)] were large. The ANOVA analysis for repeated measurements showed that different tube current and reconstruction algorithm had no significant effect on the volumetric measurements for nodules with diameter of 5 mm and 10 mm (F=5.60, P=0.10 vs F=11.13, P=0.08), but significant effects on the measurement of CT value (F=34.79, P<0.001 vs F=156.14, P<0.001). Conclusion An infinitesimally small errors of volumetric measurement of 5 mm or 10 mm nodule could achieved with very low current and ASIR reconstruction, suggesting a possibility of remarkable radiation dose reductions, while it is not applicable for 5 mm nodule. The attenuation acquired through three dimensional software has large measurement error and can not applied in clinical currently

A retrospective study of non-equidistant interstitial brain CT perfusion scanning and prediction of time to peak

Background: Eexploring the limits of CT cranial perfusion scan acquisition intervals and predicting time to peak. Methods: A retrospective analysis was conducted on 45 patients with suspected stroke who underwent brain CTP scans. Different sampling intervals were set based on the TDC. The patients were divided into four groups: Group 1 underwent continuous scanning with a uniform interval of 1.5 s; Group 2 had a uniform interval of 3 s; Group 3 had a 1.5-s interval between arterial and venous peak vertices with 1 point retained before and after the peak for 1.5 s and with a remaining acquisition interval of 4.5 s; and Group 4 had a uniform interval of 4.5 s. Statistical analysis was performed on the perfusion parameters of each group. Additionally, in 286 patients who underwent head and neck CTA examinations, the peak time of contrast medium was recorded, and the peak time was predicted based on factors such as age, height, weight, heart rate, systolic blood pressure, diastolic blood pressure, triglycerides, and total cholesterol. The results compared with Group 1 and Group 2, as well as Group 1 and Group 3, the P values of CBF, CBV, MTT, and Tmax in the left and right cerebral hemispheres of healthy subjects and in the infarct and noninfarct areas of patients were all >0.05. A comparison between Group 1 and Group 4 showed that right cerebral hemisphere CBF and CBV, left cerebral hemisphere CBF, CBV, and Tmax, infarct area CBV and Tmax, and noninfarct area CBF, CBV, and MTT had P values > 0.05, while other groups all had P values < 0.05. Bland‒Altman analysis showed that the perfusion parameters in Group 1 were consistent with those in Group 2, and those in Group 1 were consistent with those in Group 3. The radiation doses in the second and third groups were lower, and the dose in the third group was lower than that in the second group. Conclusion: Continuous acquisition between the peak points of the arterial and venous phases, with 1 point reserved before and after the peak and a 4.5-s interval for the rest, represents the maximum time interval for CTP scanning and can effectively reduce the radiation dose. The formula Tmax (s) = 0.290 × height (cm) − 0.226 × heart rate (times/min) + 0.216 × age (years) − 1.901 × triglycerides (mmol/L) − 0.061 × systolic blood pressure (mmHg) − 7.216 (R2 = 0.449, F = 17.905, P < 0.01) was established for predicting time to peak enhancement

Joint Power and Bandwidth Allocation with RCS Fluctuation Characteristic for Space Target Tracking

Reasonable allocation of space-based radar resources is a crucial aspect of improving the accuracy of space multi-target tracking and enhancing spatial awareness. The conventional resource allocation algorithm fails to exploit the high dynamic radar cross-section (RCS) characteristics, resulting in poor tracking robustness, tracking divergence, or even loss of tracking. However, the RCS of space targets fluctuates considerably in actual tracking scenarios, which cannot be disregarded for space target tracking tasks. To address this issue, we propose an adaptive allocation method that considers the dynamic RCS fluctuation characteristic for space-based radar tracking assignments. The proposed method exploits the predictable orbital information of space target to calculate the real-time observation angle of radar, and then obtains the multi-target dynamic RCS through the target RCS dataset. By combining the obtained RCS sequence, radar power, and bandwidth, an optimal model for radar tracking accuracy is established based on the multi-target posterior Cramér–Rao lower bound (PCRLB) to evaluate the tracking performance. By resolving the aforementioned multivariance optimization problem, we eventually acquire the results of power and bandwidth pre-allocation for tracking multiple space targets. Simulation results validate that, compared with the traditional methods, the proposed joint dynamic RCS power and bandwidth allocation (JRPBA) method can achieve superior tracking accuracy and minimize instances of missed tracking

Effects of Bacterial Translocation and Autophagy on Acute Lung Injury Induced by Severe Acute Pancreatitis

Aim. To reveal the role of bacterial translocation (BT) and autophagy in severe acute pancreatitis-induced acute lung injury (SAP-ALI). Methods. Rats were separated into a control (sham-operation) group (n=10) and a SAP group (n=30). Sodium taurocholate (5%) was retrogradely injected into the cholangiopancreatic duct to induce SAP-ALI in rats. Then, 16S rDNA sequencing was used to detect bacterial translocation (BT). Hematoxylin eosin staining (HE) was used to detect morphological changes to the pancreas, intestine, and lung. And lung tissue wet/dry weight ratio (W/D ratio) was used to assess the extent of pulmonary edema. The expressions of LC3II and Beclin1 proteins were analyzed by western blot and immunofluorescence. Glutathione peroxidase (GPx), malondialdehyde (MDA), and superoxide dismutase (SOD) were used to assess oxidative stress in lung tissue. Results. Levels of TNF-α, IL-6, lipase, and amylase in the SAP group were significantly higher than those in the control group (P<0.01). Histopathological score and W/D ratio of the lung in the SAP-BT(+) group were significantly higher than that in the SAP-BT(-) group (P<0.01). LC3II expression was higher in the SAP-BT(-) group than that in the SAP-BT(+) group (P<0.01). The results were consistent with those of LC3II immunofluorescence assay. The expression of Beclin1 was similar to that of LC3II (P<0.01). MDA content in the SAP-BT(+) group was significantly higher than that in the SAP-BT(-) group (P<0.01), whereas SOD and GPX activities were opposite (P<0.01). Conclusions. BT can aggravate SAP-ALI with the increasing oxidative stress level, which may be related to the decrease of autophagy level