In the world of epsilon-near-zero (ENZ) materials, the plasma is unique for its natural ENZ properties at the plasma frequency (wp). However, for the air plasma during femtosecond laser filamentation with wp in terahertz (THz) band, which is also known as a broadband THz emitter, the possible ENZ effect has long been neglected. In this work, interactions between the laser plasma in air and the radiated THz waves were investigated, and the THz resonance absorption at the ENZ point, which gave rise to the generation of surface plasmon waves, has been theoretically and experimentally demonstrated for the first time, to the best of our knowledge. Specifically, this ENZ effect was accompanied with THz modulations along the plasma filament in multiple domains, including the linear-to-elliptical THz polarization conversion and the multi-ring pattern of far-field THz profiles, etc. Thanks to these novel ENZ-induced phenomena, the understanding of this important plasma-based THz source has been enriched. Moreover, by extending the laser plasma to the role of ENZ material, it is promising to expedite related applications benefiting from the ENZ nature, e.g., the strong spatial confinement of THz waves inside the ENZ region between the bi-filaments array, which realized all-optical time-domain integration of broadband THz pulses as we recently displayed in [arXiv].
Helicobacter pylori infection is a well-established etiological factor for gastric inflammation and a significant risk factor for the development of gastric cancer. However, the precise relationship between dietary zinc intake and seropositivity for Helicobacter pylori remains uncertain.This cross-sectional observational study utilized data from the United States National Health and Nutrition Examination Survey conducted between 1999 and 2000. The study cohort comprised 2,884 adults aged 20 years or older who provided comprehensive 24-h dietary recall data. The presence of Helicobacter pylori infection was confirmed using serum analysis and lgG protein enzyme-linked immunosorbent assay (ELISA). Multivariable logistic regression models and generalized additive model (GAM) were employed to explore the potential association between dietary zinc intake and Helicobacter pylori seropositivity.Additionally, subgroup analysis was performed to evaluate the robustness of the primary findings. Of the 1,281 participants, 47.8% were male and the average age was 49.5 years. In the fully adjusted model, a statistically significant inverse association between dietary zinc intake and Helicobacter pylori seropositivity was observed [quartile variable, Q4 vs. Q1, odds ratio (OR): 0.72, 95% confidence interval (CI): 0.57-0.91, p = 0.007]. Furthermore, the relationship between dietary zinc intake and Helicobacter pylori seropositivity exhibited an L-shaped pattern, indicating a saturation effect. The results of sensitivity analysis remained consistent and reliable.Therefore, this study suggests that higher dietary zinc intake may be associated with a lower prevalence of Helicobacter pylori seropositivity. Notably, this association follows an L-shaped pattern, with a threshold point estimated at 24.925 mg/day.
Bayesian optimization (BO) is widely used to optimize expensive-to-evaluate black-box functions.BO first builds a surrogate model to represent the objective function and assesses its uncertainty. It then decides where to sample by maximizing an acquisition function (AF) based on the surrogate model. However, when dealing with high-dimensional problems, finding the global maximum of the AF becomes increasingly challenging. In such cases, the initialization of the AF maximizer plays a pivotal role, as an inadequate setup can severely hinder the effectiveness of the AF. This paper investigates a largely understudied problem concerning the impact of AF maximizer initialization on exploiting AFs' capability. Our large-scale empirical study shows that the widely used random initialization strategy often fails to harness the potential of an AF. In light of this, we propose a better initialization approach by employing multiple heuristic optimizers to leverage the historical data of black-box optimization to generate initial points for the AF maximize. We evaluate our approach with a range of heavily studied synthetic functions and real-world applications. Experimental results show that our techniques, while simple, can significantly enhance the standard BO and outperform state-of-the-art methods by a large margin in most test cases.
Abstract Background and objectives: The analysis of clustering characteristics of disease risk factors makes for the formulation of corresponding prevention and control policies, but the risk factors for non-suicidal self-injury (NSSI) behaviors in adolescents is not covered, so this study is intended to explore the clustering characteristics of risk factors for NSSI behaviors in adolescents in the multi-center primary and secondary schools in western China. Methods: Utilizing stratified and cluster sampling methods, a total of 13,784 primary and secondary school students who met the research standards were randomly selected as the survey subjects from January 2020 to January 2021, and the clustering situation of the seven risk factors (depression, anxiety, stress, low social support, tolerance, avoidance, and emotional venting) among the students was analyzed. The characteristics of the respondents with a high clustering degree of risk factors for NSSI behaviors were also identified with the hierarchical logistic regression analysis. Results: 4.2% of the adolescents in western China were detected with NSSI behaviors in the past year; the risk factors were grouped into 4 clusters, ranging from level 0 to level 3, with each level including 7692 (55.8%), 3847 (27.9 %), 1303 (9.5%) and 941 (6.8%) of the survey subjects, respectively. The results of the Cochran-Armitage trend test analysis showed that there existed a linear trend between the clustering degree of risk factors and the detection rate of NSSI behaviors (P<0.000); according to the hierarchical Logistic regression analysis, the clustering degree of risk factors for NSSI behaviors was higher in the adolescents whose parents divorced and remarried 1.21（0.016~0.373）and whose fathers received only primary school education or below 1.23（0.005~0.404）. By contrast, the degree was lower in the adolescents who are male 0.93（-0.132~-0.003） and had never attended boarding school 0.83（-0.286~-0.096）, whose parents were not divorced 0.80（-0.367~-0.072）, and whose fathers were farmers 0.87（-0.271~0.006）. Conclusion : The risk factors for NSSI behaviors in adolescents are in clusters. As the risk factors continue to cluster, NSSI behaviors can be detected more easily in adolescents. With respect to the endeavors to prevent and control NSSI behaviors in adolescents, more attention should be focused on the mental health of the adolescents who are female and attend boarding schools, whose parents have broken marriages, and whose fathers have low literacy.
Abstract. Observations of atmospheric CO2 molar fraction and its 13C isotope composition (δ13C) in urban airsheds provide constraints on the roles of anthropogenic and natural sources in local and regional C cycles. In this study, we report observations of these quantities in Nanjing at hourly intervals from March 2013 to August 2015 using a laser-based optical instrument. Nanjing is the second largest city located in the highly industrialized Yangtze River Delta (YRD), Eastern China. The mean CO2 molar fraction and 13C were 439.7 ppm and −8.48 ‰ over this observational period. The peak monthly mean δ13C (−7.44 ‰, July 2013) was 1.03 ‰ higher than that observed at the Mauna Loa Observatory. The highly enriched 13C signal was attributed to the influence of cement production in the region. By applying the Keeling plot and the Miller–Tans method to midnight and midday observations, respectively, we showed that the 13C signal of C sources in the Nanjing Municipality was 0.48 ‰ lower than that in the YRD. Flux partitioning calculations revealed that natural ecosystems in the YRD were a negligibly small sink of atmospheric CO2, consistent with the Carbon Tracker inverse modeling result.
Abstract Src homology region 2 domain-containing phosphatase-2 (SHP-2) is a key node in the RAS signaling pathway. Allosteric inhibition of SHP2 phosphatase is a potential therapeutic strategy for cancers harboring oncogenic mutations in the KRAS pathway. SHP2 also participates in the signal transduction downstream of regulatory immunoreceptors, and it has been shown in preclinical models that SHP2 inhibition drives anti-tumor immunity through modulation of both innate and adaptive mechanism. BPI-442096 is a potent, selective, and orally bioavailable small molecule SHP2 inhibitor. It exhibited significant anti-proliferation activities against multiple KRAS mutant cancer cell lines, including those from NSCLC, PDAC, CRPC, etc. BPI-442096 dose-dependently inhibited SHP2 phosphatase and downstream ERK phosphorylation in cancer cells, as well as NFAT reporter gene expression downstream of PD-1/PD-L1 signaling in immune cells. In vivo, BPI-442096 demonstrated strong tumor growth inhibition in KRASG12C, KRASG12D, and KRASG12V mutant xenograft mouse models. BPI-442096 also exhibited anti-tumor immunity in the MC38 syngeneic model, as a single agent or in combination with anti-PD1/PD-L1 drugs. Moreover, BPI-442096 combining with KRASG12C inhibitor may reverse intrinsic and acquired resistance to KRASG12C inhibition. Adequate oral exposure across multiple pre-clinical species and good ADME properties ensured the druggability of BPI-442096. In conclusion, BPI-442096 exhibits a robust anti-tumor effect in multiple KRAS mutant models and enhanced anti-cancer immunity in syngeneic mouse models, and it shows multiple combination potentials to overcome drug resistance. Phase 1 clinical trial is planned in early 2022. Citation Format: Ling Li, Bang Fu, Han Han, Zhongxin Sun, Xiangdong Zhao, Xuepeng Jv, Jun Tong, Jiayu Zhao, Zhengyao Zou, Haibo Chen, Xiaoyun Liu, Wei Ren, Yinlong Li, Wenmao Wu, Jing Guo, Dan Yan, Xiangyong Liu, Hong Lan, Hao Wu, Lieming Ding, Jiabing Wang. BPI-442096: A potent and selective inhibitor of SHP2 for the treatment of multiple cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5463.
Optical microscopy is indispensable to biomedical research and clinical investigations. As all molecules absorb light, optical-resolution photoacoustic microscopy (PAM) is an important tool to image molecules at high resolution without labeling. However, due to tissue-induced optical aberration, the imaging quality degrades with increasing imaging depth. To mitigate this effect, we develop an imaging method, called acoustic-feedback wavefront-adapted PAM (AWA-PAM), to dynamically compensate for tissue-induced aberration at depths. In contrast to most existing adaptive optics assisted optical microscopy, AWA-PAM employs acoustic signals rather than optical signals to indirectly determine the optimized wavefront. To demonstrate this technique, we imaged zebrafish embryos and mouse ears in vivo. Experimental results show that compensating for tissue-induced aberration in live tissue effectively improves both signal strength and lateral resolution. With this capability, AWA-PAM reveals fine structures, such as spinal cords and microvessels, that were otherwise unidentifiable using conventional PAM. We anticipate that AWA-PAM will benefit the in vivo imaging community and become an important tool for label-free optical imaging in the quasi-ballistic regime.
Remote sensing images are widely used in various fields, such as geographic information systems, environmental monitoring, and agricultural management. However, remote sensing images are often corrupted by various noises during acquisition, transmission, and storage, which degrade the image quality and affect the image analysis and utilization. Therefore, de-noising remote sensing images is an important step to improve the image quality and application performance. In this paper, we propose a remote sensing image de-noising method based on wavelet packet decomposition and information entropy threshold function. The proposed method uses wavelet packet decomposition to perform multiresolution analysis on remote sensing images, and combines information entropy threshold function to adaptively suppress noises. The experimental results show that the proposed method can effectively remove Gaussian noise and salt-andpepper noise, and preserve the edge and detail information of remote sensing images. The proposed method outperforms the existing methods in terms of peak signal-to-noise ratio, structural similarity index, and visual quality.
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