Search

Anti‐cancer peptides (ACPs) represent a promising potential for cancer treatment, although their mechanisms need to be further elucidated to improve their application in cancer therapy. Lycosin‐I, a linear amphipathic peptide isolated from the venom of Lycosa singorensis, shows significant anticancer potential. Herein, it is found that Lycosin‐I, which can self‐assemble into a nanosphere structure, has a multimodal mechanism of action involving lipid binding for the selective and effective treatment of leukemia. Mechanistically, Lycosin‐I selectively binds to the K562 cell membrane, likely due to its preferential interaction with negatively charged phosphatidylserine, and rapidly triggers membrane lysis, particularly at high concentrations. In addition, Lycosin‐I induces apoptosis, cell cycle arrest in the G1 phase and ferroptosis in K562 cells by suppressing the PI3K‐AKT‐mTOR signaling pathway and activating cell autophagy at low concentrations. Furthermore, intraperitoneal injection of Lycosin‐I inhibits tumor growth of K562 cells in a nude mouse xenograft model without causing side effects. Collectively, the multimodal effect of Lycosin‐I can provide new insights into the mechanism of ACPs, and Lycosin‐I, which is characterized by high potency and specificity, can be a promising lead for the development of anti‐leukemia drugs. [ABSTRACT FROM AUTHOR]

In our previous work on broadband photometric reverberation mapping (PRM), we proposed the interpolated cross-correlation function (ICCF)-Cut process to obtain the time lags of the H α emission line from two broadband lightcurves via subtracting the continuum emission from the line band. Extending the work, we enlarge our sample to the Zwicky Transient Facility (ZTF) database. We adopt two criteria to select 123 type 1 active galactic nuclei (AGNs) with sufficient variability and smooth light curves from 3537 AGNs at z < 0.09 with more than 100 epoch observations in the g and r bands from the ZTF database. We calculate the H α time lags for 23 of them that have previous spectroscopic reverberation mapping (SRM) results using the ICCF-Cut, Just Another Vehicle for Estimating Lags In Nuclei (JAVELIN), and χ 2 methods. Our obtained H α time lags are slightly larger than the H β time lags, which is consistent with the previous SRM results and the theoretical model of the AGN broad-line region. The comparisons between the SRM and PRM lag distributions and between the subtracted emission line light curves indicate that after selecting AGNs with the two criteria, combining the ICCF-Cut, JAVELIN, and χ 2 methods provides an efficient way to get the reliable H α lags from the broadband PRM. Such techniques can be used to estimate the black hole masses of a large sample of AGNs in large multiepoch photometric sky surveys such as the Legacy Survey of Space and Time and the survey from the Wide Field Survey Telescope in the near future. [ABSTRACT FROM AUTHOR]

In the Synthetic Aperture Radar (SAR) remote sensing imagery of complicated scenes (especially urban scenes), there are a large number of lines and surfaces, such as roads in urban areas and the surfaces of buildings. These microwave-signal-scattering features have strong directivity. Traditional SAR acquires the scattering information of a scene from a single observation, and traditional imaging algorithms are based on the point target model, which makes the main features of the lines and surfaces in traditional SAR images appear as a series of strong scattering points rather than line-scattering and surface-scattering features. This outcome ultimately causes the target to be discontinuous in the SAR image, thus making the SAR image difficult to interpret. Therefore, in this study, we conducted an in-depth and meticulous investigation of the SAR imaging mechanism for lines and surfaces by establishing a parametric echo model of typical lines and triangular surfaces. Based on the proposed parametric model, we performed parametric imaging of these lines and surfaces. Based on our results, we propose a parametric imaging method, in which the typical lines and surfaces are classified and determined based on Bayesian theory and the proposed parametric model. Then, an SAR image can be obtained that effectively characterizes the scattering features of the line and surface targets by visual imaging, which effectively facilitates SAR image interpretation. The results of our numerical simulation experiments verify the validity of the proposed method.

In the rapid process of urbanization, crucial habitats for mid-sized felids such as bobcats are increasingly compromised. This study employs Geographic Information System (GIS) tools and Machine Learning to investigate the subtle impacts of urbanization on bobcat habitats. Focused on the San Jose area, our extensive geospatial analysis has developed a complex ecological model for bobcat habitats. Our findings emphasize the significant influence of factors like vegetation cover, water body distribution, road traffic volume, and intersection density on the suitability of habitats for bobcats. Specifically, we discovered that while vegetation cover typically supports habitat suitability, its proximity to busy roads significantly undermines this advantage, indicating a need for strategic urban planning that incorporates wildlife mobility. By synthesizing natural and urban elements, we offer fresh insights into urban ecosystem management and propose specific conservation tactics: identifying optimal wildlife crossings, integrating corridors with urban infrastructure, and placing fencing and signage strategically to facilitate wildlife movement safely. These measures aim to reduce road-related threats and enhance the integrity of natural habitats, strengthening bobcat conservation efforts. More than its direct implications for bobcat conservation, this study offers actionable insights for urban wildlife conservation and introduces innovative methods for assessing and mitigating the broader ecological impacts of urbanization. [ABSTRACT FROM AUTHOR]

In modern cities, urban public spaces, such as parks, gardens, plazas, and streets, play a big role in people's social activities, physical activities, mental health, and overall well-being. However, the traditional post-occupancy evaluation (POE) process for public spaces such as large urban parks is extremely difficult, especially for long-term user experiences through observations, surveys, and interviews. On the other hand, social media has emerged as a major media outlet recording millions of user experiences to the public, which provides opportunities to inform how public space is used and perceived by users. Furthermore, unlike previous research that primarily presented descriptive characters of park programs, our study employs a network model to elucidate the interactive relationships and intensities among reported park elements, human activities, and experiences. This approach enables us to track the sources within the space that impact people's perceptions, such as weather conditions, food options, and notable landmarks. The utilization of this network model opens avenues for future research to comprehensively investigate the factors shaping people's perceptions in public open spaces. This study uses Bryant Park as an example and presents a new analytical framework, POSE (post-occupancy social media evaluation), to support long-term POE studies for large public spaces. Methods such as data automation, descriptive statistics, and social network analysis were used. The identification and quantification of meaningful park activities, scenes, and sentiments as well as their relationships will help optimize the design and management of park programs. [ABSTRACT FROM AUTHOR]

Wearable electronic sensors that can perform real-time, continuous, and high-fidelity monitoring of diverse biophysical signals from the human body are burgeoning and exhibit great potential to transform traditional clinical healthcare. However, such emerging devices often suffer from strict requirements of special precursor materials and sophisticated fabrication procedures. Here, we present a new paradigm of a self-powered, skin-attachable, and multifunctional sensing platform that can be fully created just at home with daily necessities. Its operating mechanism is based on mechanical/thermal regulation of the potential difference output of a primary electrochemical cell. This proposed sensing platform is totally self-powered and can be conformally attached to the skin for continuous monitoring of both mechanical and thermal stimulations. A wide spectrum of vital physiological signs of the human body, including body temperature, heart/pulse rate, respiratory rate, coughing, and body motions, can be continuously monitored and analyzed with this home-made sensing platform. This study demonstrates that the lab-conducted professional and expensive scientific research can also be accomplished at home, opening up new opportunities for home-centered healthcare in low-resource environments. Moreover, this work can serve as a handy and cost-efficient prototype for classroom education and clinical training purposes.

Objective: This paper sets out to investigate the miR-205 and HMGB1 expressions in chronic periodontitis (PO) patients and their associations with the inflammatory factors., Methods: From February 2016 to May 2018, 68 PO patients treated in our hospital were recruited for the study and placed in a patient group (PG), and 60 healthy volunteers were also recruited and placed in a healthy group (HG). Serum samples were collected from both groups for the identification of miR-205 using qPCR, as well as to determine the HMGB1 and inflammatory factor (IL-1β, IL-6, TNF-α) expression levels using ELISA. The correlations of the miR-205 and HMGB1 expression levels with the periodontal clinical indicators and the inflammatory factors were analyzed using a correlation analysis., Results: In comparison with the HG expression, the serum miR-205 expression was lower, and the HMGB1 was elevated in PG (P < 0.05). An ROC curve analysis showed that the areas under the curve (AUCs) of the serum miR-205 and HMGB1 expressions in diagnosing PO were 0.936 and 0.955 respectively. However, the serum miR-205 expression in PG increased while the HMGB1 expression decreased post treatment (P < 0.05). A correlation analysis revealed an inverse association between the serum miR-205 expression levels and the periodontal clinical indicators [bleeding index (BI), probing depth (PD), plaque index (PLI), and attachment loss (AL)], and the inflammatory factors [interleukin-1β (IL-1β), IL-6, and tumor necrosis factor-α (TNF-α)], but there was a positive association between the HMGB1 expression level and these parameters., Conclusions: miR-205 and HMGB1 are closely related to the progression of PO, and may be candidate biomarkers for the diagnosis and treatment of PO., Competing Interests: None., (AJTR Copyright © 2021.)