An Ensemble Method to Automatically Grade Diabetic Retinopathy with Optical Coherence Tomography Angiography Images

Diabetic retinopathy (DR) is a complication of diabetes, and one of the major causes of vision impairment in the global population. As the early-stage manifestation of DR is usually very mild and hard to detect, an accurate diagnosis via eye-screening is clinically important to prevent vision loss at later stages. In this work, we propose an ensemble method to automatically grade DR using ultra-wide optical coherence tomography angiography (UW-OCTA) images available from Diabetic Retinopathy Analysis Challenge (DRAC) 2022. First, we adopt the state-of-the-art classification networks, i.e., ResNet, DenseNet, EfficientNet, and VGG, and train them to grade UW-OCTA images with different splits of the available dataset. Ultimately, we obtain 25 models, of which, the top 16 models are selected and ensembled to generate the final predictions. During the training process, we also investigate the multi-task learning strategy, and add an auxiliary classification task, the Image Quality Assessment, to improve the model performance. Our final ensemble model achieved a quadratic weighted kappa (QWK) of 0.9346 and an Area Under Curve (AUC) of 0.9766 on the internal testing dataset, and the QWK of 0.839 and the AUC of 0.8978 on the DRAC challenge testing dataset.Comment: 13 pages, 6 figures, 5 tables. To appear in Diabetic Retinopathy Analysis Challenge (DRAC), Bin Sheng et al., MICCAI 2022 Challenge, Lecture Notes in Computer Science, Springe

One-shot ultraspectral imaging with reconfigurable metasurfaces

One-shot spectral imaging that can obtain spectral information from thousands of different points in space at one time has always been difficult to achieve. Its realization makes it possible to get spatial real-time dynamic spectral information, which is extremely important for both fundamental scientific research and various practical applications. In this study, a one-shot ultraspectral imaging device fitting thousands of micro-spectrometers (6336 pixels) on a chip no larger than 0.5 cm$^2$, is proposed and demonstrated. Exotic light modulation is achieved by using a unique reconfigurable metasurface supercell with 158400 metasurface units, which enables 6336 micro-spectrometers with dynamic image-adaptive performances to simultaneously guarantee the density of spectral pixels and the quality of spectral reconstruction. Additionally, by constructing a new algorithm based on compressive sensing, the snapshot device can reconstruct ultraspectral imaging information ($\Delta\lambda$/$\lambda$~0.001) covering a broad (300-nm-wide) visible spectrum with an ultra-high center-wavelength accuracy of 0.04-nm standard deviation and spectral resolution of 0.8 nm. This scheme of reconfigurable metasurfaces makes the device can be directly extended to almost any commercial camera with different spectral bands to seamlessly switch the information between image and spectral image, and will open up a new space for the application of spectral analysis combining with image recognition and intellisense

BotMoE: Twitter Bot Detection with Community-Aware Mixtures of Modal-Specific Experts

Twitter bot detection has become a crucial task in efforts to combat online misinformation, mitigate election interference, and curb malicious propaganda. However, advanced Twitter bots often attempt to mimic the characteristics of genuine users through feature manipulation and disguise themselves to fit in diverse user communities, posing challenges for existing Twitter bot detection models. To this end, we propose BotMoE, a Twitter bot detection framework that jointly utilizes multiple user information modalities (metadata, textual content, network structure) to improve the detection of deceptive bots. Furthermore, BotMoE incorporates a community-aware Mixture-of-Experts (MoE) layer to improve domain generalization and adapt to different Twitter communities. Specifically, BotMoE constructs modal-specific encoders for metadata features, textual content, and graphical structure, which jointly model Twitter users from three modal-specific perspectives. We then employ a community-aware MoE layer to automatically assign users to different communities and leverage the corresponding expert networks. Finally, user representations from metadata, text, and graph perspectives are fused with an expert fusion layer, combining all three modalities while measuring the consistency of user information. Extensive experiments demonstrate that BotMoE significantly advances the state-of-the-art on three Twitter bot detection benchmarks. Studies also confirm that BotMoE captures advanced and evasive bots, alleviates the reliance on training data, and better generalizes to new and previously unseen user communities.Comment: Accepted at SIGIR 202

MindShift: Leveraging Large Language Models for Mental-States-Based Problematic Smartphone Use Intervention

Problematic smartphone use negatively affects physical and mental health. Despite the wide range of prior research, existing persuasive techniques are not flexible enough to provide dynamic persuasion content based on users' physical contexts and mental states. We first conduct a Wizard-of-Oz study (N=12) and an interview study (N=10) to summarize the mental states behind problematic smartphone use: boredom, stress, and inertia. This informs our design of four persuasion strategies: understanding, comforting, evoking, and scaffolding habits. We leverage large language models (LLMs) to enable the automatic and dynamic generation of effective persuasion content. We develop MindShift, a novel LLM-powered problematic smartphone use intervention technique. MindShift takes users' in-the-moment physical contexts, mental states, app usage behaviors, users' goals & habits as input, and generates high-quality and flexible persuasive content with appropriate persuasion strategies. We conduct a 5-week field experiment (N=25) to compare MindShift with baseline techniques. The results show that MindShift significantly improves intervention acceptance rates by 17.8-22.5% and reduces smartphone use frequency by 12.1-14.4%. Moreover, users have a significant drop in smartphone addiction scale scores and a rise in self-efficacy. Our study sheds light on the potential of leveraging LLMs for context-aware persuasion in other behavior change domains

Structural effects of inosine substitution in telomeric DNA quadruplex

The telomeric DNA, a distal region of eukaryotic chromosome containing guanine-rich repetitive sequence of (TTAGGG)n, has been shown to adopt higher-order structures, specifically G-quadruplexes (G4s). Previous studies have demonstrated the implication of G4 in tumor inhibition through chromosome maintenance and manipulation of oncogene expression featuring their G-rich promoter regions. Besides higher order structures, several regulatory roles are attributed to DNA epigenetic markers. In this work, we investigated how the structural dynamics of a G-quadruplex, formed by the telomeric sequence, is affected by inosine, a prevalent modified nucleotide. We used the standard (TTAGGG)n telomere repeats with guanosine mutated to inosine at each G position. Sequences (GGG)4, (IGG)4, (GIG)4, (GGI)4, (IGI)4, (IIG)4, (GII)4, and (III)4, bridged by TTA linker, are studied using biophysical experiments and molecular modeling. The effects of metal cations in quadruplex folding were explored in both Na+ and K+ containing buffers using CD and UV-melting studies. Our results show that antiparallel quadruplex topology forms with the native sequence (GGG)4 and the terminal modified DNAs (IGG)4 and (GGI)4 in both Na+ and K+ containing buffers. Specifically, quadruplex hybrid was observed for (GGG)4 in K+ buffer. Among the other modified sequences, (GIG)4, (IGI)4 and (GII)4 show parallel features, while (IIG)4 and (III)4 show no detectable conformation in the presence of either Na+ or K+. Our studies indicate that terminal lesions (IGG)4 and (GGI)4 may induce certain unknown conformations. The folding dynamics become undetectable in the presence of more than one inosine substitution except (IGI)4 in both buffer ions. In addition, both UV melting and CD melting studies implied that in most cases the K+ cation confers more thermodynamic stability compared to Na+. Collectively, our conformational studies revealed the diverse structural polymorphisms of G4 with position dependent G-to-I mutations in different ion conditions

Alkali and alkaline earth metals in liquid salts for supercapattery

The full oxidation of lithium metal (4Li + O2 ⇌ 2Li2O) offers a mass normalised Gibbs energy change greater than that for the combustion of carbon (C + O2 ⇌ CO2) or any hydrocarbon fuel (CnH2n+2 + ((3n+1)/2)O2 ⇌ nCO2 + (n+1)H2O). This thermodynamic comparison promises a lithium-oxygen (air) battery with a petrol comparable energy density. Similar analyses apply to other abundant alkali and alkaline earth metals (AAEMs) which are all featured by their very high specific charge capacity and most negative electrode potentials. The success of lithium ion batteries (LIBs) in both research and commercial development confirms such thermodynamic predictions. However, the experimentally demonstrated energy capacities of all AAEM based batteries are only small fractions of the thermodynamic values. A main cause is that a satisfactory oxygen positive electrode (positrode) is still to be developed, whilst the very few options of AAEM storage positrodes still do not match with AAEM negative electrodes (negatrodes) in charge capacity. Another challenge results from the complicated interactions between AAEMs and the currently used organic carbonate electrolytes that not only reduce the negatrode capacity but also exert restriction on both electron and ion transfers. The flammability of currently used organic electrolytes is another major concern on the safety of AAEMs batteries. Herein, we introduce the concept and potential, and review the relevant practices of a promising ionic liquid supercapattery that couples an AAEM negatrode with a supercapacitor positrode to bypass the thermodynamic and kinetic difficulties of an oxygen or AAEM storage positrode. Further discussion aims at the selection of ionic liquid-based electrolytes that can enable the reversible anodic dissolution of AAEMs and a wide potential window for the supercapacitor positrode. The use of molten salt-based electrolytes is also postulated and analysed, not only because of their high ionic conductivity, low cost and unique applications, but also their high temperatures that eliminate dendritic growth on the negatrode and heat buildup in the cell

Fenofibrate suppresses corneal neovascularization by regulating lipid metabolism through PPARα signaling pathway

Purpose: The purpose of this study was to explore the potential underlying mechanism of anti-vascular effects of peroxisome proliferator–activated receptor α (PPARα) agonist fenofibrate against corneal neovascularization (CNV) through the changes of lipid metabolism during CNV.Methods: A suture-induced CNV model was established and the clinical indications were evaluated from day 1 to day 7. Treatments of vehicle and fenofibrate were performed for 5 days after suture and the CNV areas were compared among the groups. The eyeballs were collected for histological analysis, malondialdehyde (MDA) measurement, terminal deoxynucleotidyl transferase 2′-deoxyuridine 5′-triphosphate nick end labeling (TUNEL) staining, western blot, quantitative real-time PCR (qRT-PCR) assays and immunohistochemical (IHC) staining to elucidate pathological changes and the underlying mechanism.Results: Lipi-Green staining and MDA measurement showed that lipid deposition and peroxidation were increased in the CNV cornea while the expression of long-chain acyl-coenzyme A synthetase 1 (ACSL1), carnitine palmitoyltransterase 1A(CPT1A) and medium-chain acyl-coenzyme A dehydrogenase (ACADM), which are key enzymes of fatty acid β-oxidation (FAO) and targeted genes of peroxisome proliferator-activated receptor alpha (PPARα) pathway, were decreased in CNV cornea. Fenofibrate suppressed lipid accumulation and peroxidation damage in the CNV cornea. Fenofibrate upregulated the expression levels of PPARα, ACSL1, CPT1A, and ACADM compared with vehicle group. IHC staining indicated that fenofibrate also decreased the expression of VEGFa, VEGFc, TNFα, IL1β and CD68.Conclusion: Disorder of lipid metabolism may be involved in the formation of suture-induced CNV and fenofibrate played anti-neovascularization and anti-inflammatory roles on cornea by regulating the key enzymes of lipid metabolism and ameliorating lipid peroxidation damage of cornea through PPARα signaling pathway

Using Integrative Analysis of DNA Methylation and Gene Expression Data in Multiple Tissue Types to Prioritize Candidate Genes for Drug Development in Obesity

Obesity has become a major public health issue which is caused by a combination of genetic and environmental factors. Genome-wide DNA methylation studies have identified that DNA methylation at Cytosine-phosphate-Guanine (CpG) sites are associated with obesity. However, subsequent functional validation of the results from these studies has been challenging given the high number of reported associations. In this study, we applied an integrative analysis approach, aiming to prioritize the drug development candidate genes from many associated CpGs. Association data was collected from previous genome-wide DNA methylation studies and combined using a sample-size-weighted strategy. Gene expression data in adipose tissues and enriched pathways of the affiliated genes were overlapped, to shortlist the associated CpGs. The CpGs with the most overlapping evidence were indicated as the most appropriate CpGs for future studies. Our results revealed that 119 CpGs were associated with obesity (p ≤ 1.03 × 10−7). Of the affiliated genes, SOCS3 was the only gene involved in all enriched pathways and was differentially expressed in both visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT). In conclusion, our integrative analysis is an effective approach in highlighting the DNA methylation with the highest drug development relevance. SOCS3 may serve as a target for drug development of obesity and its complications

The Simons Observatory: Magnetic Shielding Measurements for the Universal Multiplexing Module

The Simons Observatory (SO) includes four telescopes that will measure the temperature and polarization of the cosmic microwave background using over 60,000 highly sensitive transition-edge bolometers (TES). These multichroic TES bolometers are read out by a microwave RF SQUID multiplexing system with a multiplexing factor of 910. Given that both TESes and SQUIDs are susceptible to magnetic field pickup and that it is hard to predict how they will respond to such fields, it is important to characterize the magnetic response of these systems empirically. This information can then be used to limit spurious signals by informing magnetic shielding designs for the detectors and readout. This paper focuses on measurements of magnetic pickup with different magnetic shielding configurations for the SO universal multiplexing module (UMM), which contains the SQUIDs, associated resonators, and TES bias circuit. The magnetic pickup of a prototype UMM was tested under three shielding configurations: no shielding (copper packaging), aluminum packaging for the UMM, and a tin/lead-plated shield surrounding the entire dilution refrigerator 100 mK cold stage. The measurements show that the aluminum packaging outperforms the copper packaging by a shielding factor of 8-10, and adding the tin/lead-plated 1K shield further increases the relative shielding factor in the aluminum configuration by 1-2 orders of magnitude.Comment: 7 pages, 4 figure, conference proceedings submitted to the Journal of Low Temperature Physic