The use of clamping grips and friction pads by tree frogs for climbing curved surfaces

Most studies on the adhesive mechanisms of climbing animals have addressed attachment against flat surfaces, yet many animals can climb highly curved surfaces, like twigs and small branches. Here we investigated whether tree frogs use a clamping grip by recording the ground reaction forces on a cylindrical object with either a smooth or anti-adhesive, rough surface. Furthermore, we measured the contact area of fore and hindlimbs against differently sized transparent cylinders and the forces of individual pads and subarticular tubercles in restrained animals. Our study revealed that frogs use friction and normal forces of roughly a similar magnitude for holding on to cylindrical objects. When challenged with climbing a non-adhesive surface, the compressive forces between opposite legs nearly doubled, indicating a stronger clamping grip. In contrast to climbing flat surfaces, frogs increased the contact area on all limbs by engaging not just adhesive pads but also subarticular tubercles on curved surfaces. Our force measurements showed that tubercles can withstand larger shear stresses than pads. SEM images of tubercles revealed a similar structure to that of toe pads including the presence of nanopillars, though channels surrounding epithelial cells were less pronounced. The tubercles' smaller size, proximal location on the toes and shallow cells make them probably less prone to buckling and thus ideal for gripping curved surfaces

Image restoration with point-spread function regularization and active learning

Large-scale astronomical surveys can capture numerous images of celestial objects, including galaxies and nebulae. Analysing and processing these images can reveal the intricate internal structures of these objects, allowing researchers to conduct comprehensive studies on their morphology, evolution, and physical properties. However, varying noise levels and point-spread functions can hamper the accuracy and efficiency of information extraction from these images. To mitigate these effects, we propose a novel image restoration algorithm that connects a deep-learning-based restoration algorithm with a high-fidelity telescope simulator. During the training stage, the simulator generates images with different levels of blur and noise to train the neural network based on the quality of restored images. After training, the neural network can restore images obtained by the telescope directly, as represented by the simulator. We have tested the algorithm using real and simulated observation data and have found that it effectively enhances fine structures in blurry images and increases the quality of observation images. This algorithm can be applied to large-scale sky survey data, such as data obtained by the Large Synoptic Survey Telescope (LSST), Euclid, and the Chinese Space Station Telescope (CSST), to further improve the accuracy and efficiency of information extraction, promoting advances in the field of astronomical research

Meta Architecture for Point Cloud Analysis

Recent advances in 3D point cloud analysis bring a diverse set of network architectures to the field. However, the lack of a unified framework to interpret those networks makes any systematic comparison, contrast, or analysis challenging, and practically limits healthy development of the field. In this paper, we take the initiative to explore and propose a unified framework called PointMeta, to which the popular 3D point cloud analysis approaches could fit. This brings three benefits. First, it allows us to compare different approaches in a fair manner, and use quick experiments to verify any empirical observations or assumptions summarized from the comparison. Second, the big picture brought by PointMeta enables us to think across different components, and revisit common beliefs and key design decisions made by the popular approaches. Third, based on the learnings from the previous two analyses, by doing simple tweaks on the existing approaches, we are able to derive a basic building block, termed PointMetaBase. It shows very strong performance in efficiency and effectiveness through extensive experiments on challenging benchmarks, and thus verifies the necessity and benefits of high-level interpretation, contrast, and comparison like PointMeta. In particular, PointMetaBase surpasses the previous state-of-the-art method by 0.7%/1.4/%2.1% mIoU with only 2%/11%/13% of the computation cost on the S3DIS datasets

MADS-Box Genes and Gibberellins Regulate Bolting in Lettuce (Lactuca sativa L.)

Bolting in lettuce is promoted by high temperature and bolting resistance is of great economic importance for lettuce production. But how bolting is regulated at the molecular level remains elusive. Here, a bolting resistant line S24 and a bolting sensitive line S39 were selected for morphological, physiological, transcriptomic and proteomic comparisons. A total of 12204 genes were differentially expressed in S39 vs S24. Line S39 was featured with larger leaves, higher levels of chlorophyll, soluble sugar, anthocyanin and auxin, consistent with its up-regulation of genes implicated in photosynthesis, oxidation-reduction and auxin actions. Proteomic analysis identified 30 differentially accumulated proteins in lines S39 and S24 upon heat treatment, and 19 out of the 30 genes showed differential expression in the RNA-Seq data. Exogenous gibberellins (GA) treatment promoted bolting in both S39 and S24, while 12 flowering promoting MADS-box genes were specifically induced in line S39, suggesting that although GA regulates bolting in lettuce, it may be the MADS-box genes, not GA, that plays a major role in differing the bolting resistance between these two lettuce lines

Spotting adversarial samples for speaker verification by neural vocoders

Automatic speaker verification (ASV), one of the most important technology for biometric identification, has been widely adopted in security-critical applications, including transaction authentication and access control. However, previous work has shown that ASV is seriously vulnerable to recently emerged adversarial attacks, yet effective countermeasures against them are limited. In this paper, we adopt neural vocoders to spot adversarial samples for ASV. We use the neural vocoder to re-synthesize audio and find that the difference between the ASV scores for the original and re-synthesized audio is a good indicator for discrimination between genuine and adversarial samples. This effort is, to the best of our knowledge, among the first to pursue such a technical direction for detecting adversarial samples for ASV, and hence there is a lack of established baselines for comparison. Consequently, we implement the Griffin-Lim algorithm as the detection baseline. The proposed approach achieves effective detection performance that outperforms all the baselines in all the settings. We also show that the neural vocoder adopted in the detection framework is dataset-independent. Our codes will be made open-source for future works to do comparison.Comment: Submitted to ASRU 202

High-speed intravascular photoacoustic imaging of lipid-laden atherosclerotic plaque enabled by a 2-kHz barium nitrite raman laser

Lipid deposition inside the arterial wall is a key indicator of plaque vulnerability. An intravascular photoacoustic (IVPA) catheter is considered a promising device for quantifying the amount of lipid inside the arterial wall. Thus far, IVPA systems suffered from slow imaging speed (~50 s per frame) due to the lack of a suitable laser source for high-speed excitation of molecular overtone vibrations. Here, we report an improvement in IVPA imaging speed by two orders of magnitude, to 1.0 s per frame, enabled by a custom-built, 2-kHz master oscillator power amplifier (MOPA)-pumped, barium nitrite [Ba(NO3)2] Raman laser. This advancement narrows the gap in translating the IVPA technology to the clinical setting

Protective Effect of Chlorogenic Acid and Its Analogues on Lead-Induced Developmental Neurotoxicity Through Modulating Oxidative Stress and Autophagy

Lead (Pb) is among the deleterious heavy metal and has caused global health concerns due to its tendency to cause a detrimental effect on the development of the central nervous system (CNS). Despite being a serious health concern, treatment of Pb poisoning is not yet available, reflecting the pressing need for compounds that can relieve Pb-induced toxicity, especially neurotoxicity. In the quest of exploring protective strategies against Pb-induced developmental neurotoxicity, compounds from natural resources have gained increased attention. Chlorogenic acid (CGA) and its analogues neochlorogenic acid (NCGA) and cryptochlorogenic acid (CCGA) are the important phenolic compounds widely distributed in plants. Herein, utilizing zebrafish as a model organism, we modeled Pb-induced developmental neurotoxicity and investigated the protective effect of CGA, NCGA, and CCGA co-treatment. In zebrafish, Pb exposure (1,000 μg/L) for 5 days causes developmental malformation, loss of dopaminergic (DA) neurons, and brain vasculature, as well as disrupted neuron differentiation in the CNS. Additionally, Pb-treated zebrafish exhibited abnormal locomotion. Notably, co-treatment with CGA (100 µM), NCGA (100 µM), and CCGA (50 µM) alleviated these developmental malformation and neurotoxicity induced by Pb. Further underlying mechanism investigation revealed that these dietary phenolic acid compounds may ameliorate Pb-induced oxidative stress and autophagy in zebrafish, therefore protecting against Pb-induced developmental neurotoxicity. In general, our study indicates that CGA, NCGA, and CCGA could be promising agents for treating neurotoxicity induced by Pb, and CCGA shows the strongest detoxifying activity

Functional Role of Cyclin-Dependent Kinase 5 in the Regulation of Melanogenesis and Epidermal Structure

The mammalian integumentary system plays important roles in body homeostasis, and dysfunction of melanogenesis or epidermal development may lead to a variety of skin diseases, including melanoma. Skin pigmentation in humans and coat color in fleece-producing animals are regulated by many genes. Among them, microphthalmia-associated transcription factor (MITF) and paired-box 3 (PAX3) are at the top of the cascade and regulate activities of many important melanogenic enzymes. Here, we report for the first time that cyclin-dependent kinase 5 (Cdk5) is an essential regulator of MITF and PAX3. Cdk5 knockdown in mice causes a lightened coat color, a polarized distribution of melanin and hyperproliferation of basal keratinocytes. Reduced expression of Keratin 10 (K10) resulting from Cdk5knockdown may be responsible for an abnormal epidermal structure. In contrast, overexpression of Cdk5 in sheep (Ovis aries) only produces brown patches on a white background, with no other observable abnormalities. Collectively, our findings show that Cdk5 has an important functional role in the regulation of melanin production and transportation and in normal development of the integumentary system

Impact of GLP-1 Receptor Agonists on Major Gastrointestinal Disorders for Type 2 Diabetes Mellitus: A Mixed Treatment Comparison Meta-Analysis

Aim. We aimed to integrate evidence from all randomized controlled trials (RCTs) and assess the impact of different doses of exenatide or liraglutide on major gastrointestinal adverse events (GIAEs) in type 2 diabetes (T2DM). Methods. RCTs evaluating different doses of exenatide and liraglutide against placebo or an active comparator with treatment duration ≥4 weeks were searched and reviewed. A total of 35, 32 and 28 RCTs met the selection criteria evaluated for nausea, vomiting, and diarrhea, respectively. Pairwise random-effects meta-analyses and mixed treatment comparisons (MTC) of all RCTs were performed. Results. All GLP-1 dose groups significantly increased the probability of nausea, vomiting and diarrhea relative to placebo and conventional treatment. MTC meta-analysis showed that there was 99.2% and 85.0% probability, respectively, that people with exenatide 10 μg twice daily (EX10BID) was more vulnerable to nausea and vomiting than those with other treatments. There was a 78.90% probability that liraglutide 1.2 mg once daily (LIR1.2) has a higher risk of diarrhea than other groups. A dose-dependent relationship of exenatide and liraglutide on GIAEs was observed. Conclusions. Our MTC meta-analysis suggests that patients should be warned about these GIAEs in early stage of treatment by GLP-1s, especially by EX10BID and LIR1.2, to promote treatment compliance