Unlocking Low-Light-Rainy Image Restoration by Pairwise Degradation Feature Vector Guidance

Rain in the dark is a common natural phenomenon. Photos captured in such a condition significantly impact the performance of various nighttime activities, such as autonomous driving, surveillance systems, and night photography. While existing methods designed for low-light enhancement or deraining show promising performance, they have limitations in simultaneously addressing the task of brightening low light and removing rain. Furthermore, using a cascade approach, such as ``deraining followed by low-light enhancement'' or vice versa, may lead to difficult-to-handle rain patterns or excessively blurred and overexposed images. To overcome these limitations, we propose an end-to-end network called $L^{2}RIRNet$ which can jointly handle low-light enhancement and deraining. Our network mainly includes a Pairwise Degradation Feature Vector Extraction Network (P-Net) and a Restoration Network (R-Net). P-Net can learn degradation feature vectors on the dark and light areas separately, using contrastive learning to guide the image restoration process. The R-Net is responsible for restoring the image. We also introduce an effective Fast Fourier - ResNet Detail Guidance Module (FFR-DG) that initially guides image restoration using detail image that do not contain degradation information but focus on texture detail information. Additionally, we contribute a dataset containing synthetic and real-world low-light-rainy images. Extensive experiments demonstrate that our $L^{2}RIRNet$ outperforms existing methods in both synthetic and complex real-world scenarios

Scenario-Aware Hierarchical Dynamic Network for Multi-Scenario Recommendation

Click-Through Rate (CTR) prediction is a fundamental technique in recommendation and advertising systems. Recent studies have shown that implementing multi-scenario recommendations contributes to strengthening information sharing and improving overall performance. However, existing multi-scenario models only consider coarse-grained explicit scenario modeling that depends on pre-defined scenario identification from manual prior rules, which is biased and sub-optimal. To address these limitations, we propose a Scenario-Aware Hierarchical Dynamic Network for Multi-Scenario Recommendations (HierRec), which perceives implicit patterns adaptively and conducts explicit and implicit scenario modeling jointly. In particular, HierRec designs a basic scenario-oriented module based on the dynamic weight to capture scenario-specific information. Then the hierarchical explicit and implicit scenario-aware modules are proposed to model hybrid-grained scenario information. The multi-head implicit modeling design contributes to perceiving distinctive patterns from different perspectives. Our experiments on two public datasets and real-world industrial applications on a mainstream online advertising platform demonstrate that our HierRec outperforms existing models significantly

Synergistic treatment of osteosarcoma with biomimetic nanoparticles transporting doxorubicin and siRNA

IntroductionOsteosarcoma tumors are the most common malignant bone tumors in children and adolescents. Their treatment usually requires surgical removal of all detectable cancerous tissue and multidrug chemotherapy; however, the prognosis for patients with unresectable or recurrent osteosarcoma is unfavorable. To make chemotherapy safer and more effective for osteosarcoma patients, biomimetic nanoparticles (NPs) camouflaged by mesenchymal stem cell membranes (MSCMs) were synthesized to induce osteosarcoma cell apoptosis by co-delivering the anticancer drug doxorubicin hydrochloride(DOX) and a small interfering RNA (siRNA). Importantly, these NPs have high biocompatibility and tumor-homing ability. This study aimed to improve the efficacy of osteosarcoma therapy by using the synergistic combination of DOX and an siRNA targeting the apoptosis suppressor gene survivin.MethodsBiomimetic NPs (DOX/siSUR-PLGA@MSCM NPs) were synthesized by coloading DOX and survivin siRNA (siSUR) into poly (lactide-co-glycolide acid) (PLGA) via a double-emulsion solvent evaporation method. The NPs were camouflaged by MSCMs to deliver both DOX and survivin-targeting siRNA and characterized and evaluated in terms of cellular uptake, in vitro release, in vitro and in vivo antitumor effects, and biosafety.ResultsDOX/siSUR-PLGA@MSCM NPs had good tumor-homing ability due to the MSCMs modification. The drug-laden biomimetic NPs had good antitumor effects in homozygous MG63 tumor-bearing mice due to the synergistic effect of the drug combination.ConclusionDOX/siSUR-PLGA@MSCM NPs can show improved therapeutic effects in osteosarcoma patients due to the combination of a chemotherapeutic drug and gene therapy based on their good tumor targeting and biosafety

Displacive phase transitions in infinite-layer nickelates from first- and second-principles calculations.

peer reviewedPDR Promospa

Association between serum potassium and Parkinson’s disease in the US (NHANES 2005–2020)

BackgroundEvaluating the correlation between serum potassium and Parkinson’s disease (PD) in US adults.MethodsA cross-sectional study was conducted on 20,495 adults aged 40 years or older using NHANES data from 2005 to 2020. The study utilized one-way logistic regression and multifactorial logistic regression to examine the correlation between serum potassium levels and PD. Additionally, a smoothed curve fitting approach was employed to assess the concentration-response relationship between serum potassium and PD. Stratified analyses were carried out to investigate potential interactions between serum potassium levels and PD with variables such as age, sex, race, marital status, education, BMI, smoking and medical conditions like coronary, stroke, diabetes, hypertension, and hypercholesterolemia.ResultsIn this study, a total of 20,495 participants, comprising 403 PD and 20,092 non-PD individuals, were included. After adjusted for covariates, multivariable logistic regression revealed that high serum potassium level was an independent risk factor for PD (OR:1.86, 95% CI:1.45 ~ 2.39, p < 0.01).The linear association between serum potassium and PD was described using fitted smoothing curves. Age, sex, race, education, marital, BMI, coronary, stroke, diabetes, hypertension and hypercholesterolemia were not significantly correlated with this positive connection, according to subgroup analysis and interaction testing (P for interaction >0.05).ConclusionSerum potassium levels are elevated in patients with Parkinson's disease compared to non-PD patients. Additional prospective studies are required to explore the significance of serum potassium levels in individuals with Parkinson's disease

Cdon is essential for organ left-right patterning by regulating dorsal forerunner cells clustering and Kupffer’s vesicle morphogenesis

Cdon and boc are members of the cell adhesion molecule subfamily III Ig/fibronectin. Although they have been reported to be involved in muscle and neural development at late developmental stage, their early roles in embryonic development remain unknown. Here, we discovered that in zebrafish, cdon, but not boc, is expressed in dorsal forerunner cells (DFCs) and the epithelium of Kupffer’s vesicle (KV), suggesting a potential role for cdon in organ left-right (LR) patterning. Further data showed that liver and heart LR patterning were disrupted in cdon morphants and cdon mutants. Mechanistically, we found that loss of cdon function led to defect in DFCs clustering, reduced KV lumen, and defective cilia, resulting in randomized Nodal/spaw signaling and subsequent organ LR patterning defects. Additionally, predominant distribution of a cdon morpholino (MO) in DFCs caused defects in DFC clustering, KV morphogenesis, cilia number/length, Nodal/spaw signaling, and organ LR asymmetry, similar to those observed in cdon morphants and cdon−/− embryos, indicating a cell-autonomous role for cdon in regulating KV formation during LR patterning. In conclusion, our data demonstrate that during gastrulation and early somitogenesis, cdon is essential for proper DFC clustering, KV formation, and normal cilia, thereby playing a critical role in establishing organ LR asymmetry