GraphAdapter: Tuning Vision-Language Models With Dual Knowledge Graph

Adapter-style efficient transfer learning (ETL) has shown excellent performance in the tuning of vision-language models (VLMs) under the low-data regime, where only a few additional parameters are introduced to excavate the task-specific knowledge based on the general and powerful representation of VLMs. However, most adapter-style works face two limitations: (i) modeling task-specific knowledge with a single modality only; and (ii) overlooking the exploitation of the inter-class relationships in downstream tasks, thereby leading to sub-optimal solutions. To mitigate that, we propose an effective adapter-style tuning strategy, dubbed GraphAdapter, which performs the textual adapter by explicitly modeling the dual-modality structure knowledge (i.e., the correlation of different semantics/classes in textual and visual modalities) with a dual knowledge graph. In particular, the dual knowledge graph is established with two sub-graphs, i.e., a textual knowledge sub-graph, and a visual knowledge sub-graph, where the nodes and edges represent the semantics/classes and their correlations in two modalities, respectively. This enables the textual feature of each prompt to leverage the task-specific structure knowledge from both textual and visual modalities, yielding a more effective classifier for downstream tasks. Extensive experimental results on 11 benchmark datasets reveal that our GraphAdapter significantly outperforms previous adapter-based methods. The code will be released at https://github.com/lixinustc/GraphAdapterComment: Accepted by NeurIPS 2023. The manuscript will be further revised based on the review

Evaluation of a novel scoring system based on thrombosis and inflammation for predicting stroke-associated pneumonia: A retrospective cohort study

BackgroundInflammation and thrombosis are involved in the development of stroke-associated pneumonia (SAP). Our aim was to evaluate the predictive value of a novel, simplified, thrombo-inflammatory prognostic score (TIPS) that combines both inflammatory and thrombus biomarkers in the early phase of ischemic stroke (IS).MethodsThe study population consisted of 897 patients with a first diagnosis of IS admitted to the emergency department of five tertiary hospitals in China. Of these, the data from 70% of patients was randomly selected to derive the model and the other 30% for model validation. A TIPS of “2” was indicative of high inflammation and thrombosis biomarkers and “1” of one biomarker, with “0” indicative of absence of biomarkers. Multivariate logistic regression analyses were used to identify the association between TIPS and SAP.ResultsThe TIPS was an independent predictor of SAP and 90-day mortality, with the incidence of SAP being significantly higher for patients with a high TIPS. The TIPS provided superior predictive value for SAP than clinical scores (A2DS2) and biomarkers currently used in practice, for both the derivation and validation sets. Mediation analysis revealed that TIPS provided a predictive value than either thrombotic (NLR) and inflammatory (D-dimer) biomarkers alone.ConclusionThe TIPS score may be a useful tool for early identification of patients at high-risk for SAP after IS

Association between cognitive impairment and risk of atrial fibrillation: The Atherosclerosis Risk in Communities study

Background: Atrial fibrillation (AF) is reportedly a risk factor for cognitive impairment. Interestingly, recent studies have emphasized that impaired cognition is probably an initiating factor of cardiovascular disease. Thus, we aimed to explore the association between impaired cognition and the risk of AF, and clarify the potential mechanisms. Methods: Participants of visit 2 (1991–1993) in the Atherosclerosis Risk in Communities study were included. Global cognition z-scores and factor scores were calculated using the word fluency, delayed word recall, and digit symbol substitution tests. AF incidents were diagnosed by electrocardiography and inpatient records. The association of cognitive decline with AF risk and left atrial volume index (LAVI) was explored using Cox proportional hazards and linear regression models, respectively. Results: During the median follow-up of 18.2 ± 6.2 years, 2056/11,675 (17.6%) participants developed AF. Participants in the lowest quartile of global cognition z- and factor scores had a higher risk of AF (hazard ratio [HR]: 1.271, 95% confidence interval [CI]: 1.094–1.477, p = 0.002; HR: 1.305, 95% CI: 1.110–1.535, p = 0.001, respectively) than those in the highest quartile. Global cognition z- and factor scores were negatively correlated with the LAVI (B: –0.411, 95% CI: –0.749 to –0.074, p = 0.017; B: –0.425, 95% CI: –0.833 to –0.017, p = 0.041, respectively). Conclusions: Cognitive decline is significantly associated with a higher risk of AF, with atrial remodeling being a potential mechanism. Our results extend previous findings of the brain-heart axis and indicate the effects of cognitive injury on cardiac function and structure. Registration: URL: https://www.clinicaltrials.gov; unique identifier: NCT0000513

GraphScope Flex: LEGO-like Graph Computing Stack

Graph computing has become increasingly crucial in processing large-scale graph data, with numerous systems developed for this purpose. Two years ago, we introduced GraphScope as a system addressing a wide array of graph computing needs, including graph traversal, analytics, and learning in one system. Since its inception, GraphScope has achieved significant technological advancements and gained widespread adoption across various industries. However, one key lesson from this journey has been understanding the limitations of a "one-size-fits-all" approach, especially when dealing with the diversity of programming interfaces, applications, and data storage formats in graph computing. In response to these challenges, we present GraphScope Flex, the next iteration of GraphScope. GraphScope Flex is designed to be both resource-efficient and cost-effective, while also providing flexibility and user-friendliness through its LEGO-like modularity. This paper explores the architectural innovations and fundamental design principles of GraphScope Flex, all of which are direct outcomes of the lessons learned during our ongoing development process. We validate the adaptability and efficiency of GraphScope Flex with extensive evaluations on synthetic and real-world datasets. The results show that GraphScope Flex achieves 2.4X throughput and up to 55.7X speedup over other systems on the LDBC Social Network and Graphalytics benchmarks, respectively. Furthermore, GraphScope Flex accomplishes up to a 2,400X performance gain in real-world applications, demonstrating its proficiency across a wide range of graph computing scenarios with increased effectiveness

Large-scale patterned quantum dots as color conversion layer for organic light emitting diode by inkjet printing

In this work, we fabricated 6.6-inch QD display panel by inkjet printing technology, being cooperated with active matrix organic light emitting diodes (AMOLEDs). Here 3-stack blue OLEDs (BOLEDs) with top-emission structure acted as backlight and red QD layer acted as converted materials, which exhibited high quantum efficiency, high luminance, high color purity and improved wide viewing angle of output emission. We believe that inkjet-printed QD display with AMOLEDs would be promising candidate for the next generation display and lighting in the near future

Water-Borne Perovskite Quantum Dot-Loaded, Polystyrene Latex Ink

Highly lipophilic nanocrystals (NCs) of cesium lead halides were successfully embedded in polystyrene (PS) particles by deliberately controlling the swelling of the PS particles in the mixtures of good and bad organic solvents. The resulting composite particles were readily transferred into water via simple stepwise solvent exchange, which yielded water-borne perovskite NC-based inks with outstanding structural and chemical stability in aqueous media. Minimal change in the photoluminescence (PL) of the NCs loaded in the PS particles was visible after 1 month of incubation of the composite particles in water in a broad pH range from 1 to 14, which could otherwise be hardly realized. Loading into the PS particles also made the NCs highly stable against polar organic solvents, such as ethanol, intense light irradiation, and heat. The NC PL intensity slightly changed after the composite particles were heated at 75°C and under irradiation of strong blue light (@365 nm) for 1 h. Furthermore, the PS matrices could effectively inhibit the exchange of halide anions between two differently sized perovskite NCs loaded therein, thereby offering a considerable technical advantage in the application of multiple perovskite NCs for multicolor display in the future

Immune Infiltration in Atherosclerosis is Mediated by Cuproptosis-Associated Ferroptosis Genes

Aims: In this study, we aimed to identify cuproptosis-associated ferroptosis genes in the atherosclerosis microarray of the Gene Expression Omnibus (GEO) database and to explore hub gene-mediated immune infiltration in atherosclerosis.Background: Immune infiltration plays a crucial role in atherosclerosis development. Ferroptosis is a mode of cell death caused by the iron-dependent accumulation of lipid peroxides. Cuproptosis is a recently discovered type of programmed cell death. No previous studies have examined the mechanism of cuproptosis-associated ferroptosis gene regulation in immune infiltration in atherosclerosis.Methods: We searched the qualified atherosclerosis gene microarray in the GEO database, integrated it with ferroptosis and cuproptosis genes, and calculated the correlation coefficients. We then obtained the cuproptosis-associated ferroptosis gene matrix and screened differentially expressed genes. Subsequently, we performed Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses and protein–protein interaction network analysis of differentially expressed genes. We also screened hub genes according to the Matthews correlation coefficient (MCC) algorithm. We conducted enrichment analysis of hub genes to explore their functions and predict related microRNAs (P<0.05). We also used the single-sample gene set enrichment analysis (ssGSEA) algorithm to analyze the relationships between hub genes and immune infiltration, and used immune-associated hub genes to construct a risk model. Finally, we used the drug prediction results and molecular docking technology to explore potential therapeutic drugs targeting the hub genes.Results: Seventy-eight cuproptosis-associated ferroptosis genes were found to be involved in the cellular response to oxidative and chemical stress, and to be enriched in multiple pathways, including ferroptosis, glutathione metabolism, and atherosclerosis. Ten hub genes were identified with the MCC algorithm; according to the ssGSEA algorithm, these genes were closely associated with immune infiltration, thus indicating that cuproptosis-associated ferroptosis genes may participate in atherosclerosis by mediating immune infiltration. The receiver operating characteristic curve indicated that the model had a good ability to predict atherosclerosis risk. The results of drug prediction (adjusted P<0.001) and molecular docking showed that glutathione may be a potential therapeutic drug that targets the hub genes.Conclusion: Cuproptosis-associated ferroptosis genes are associated with immune infiltration in atherosclerosis