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Abstract Brainbow is a genetic cell-labeling technique that allows random colorization of multiple cells and real-time visualization of cell fate within a tissue, providing valuable insights into understanding complex biological processes. However, fluorescent proteins (FPs) in Brainbow have distinct excitation spectra with peak difference greater than 35 nm, which requires sequential imaging under multiple excitations and thus leads to long acquisition times. In addition, they are not easily used together with other fluorophores due to severe spectral bleed-through. Here, we report the development of a single-wavelength excitable Brainbow, UFObow, incorporating three newly developed blue-excitable FPs. We have demonstrated that UFObow enables not only tracking the growth dynamics of tumor cells in vivo but also mapping spatial distribution of immune cells within a sub-cubic centimeter tissue, revealing cell heterogeneity. This provides a powerful means to explore complex biology in a simultaneous imaging manner at a single-cell resolution in organs or in vivo.

In multicolor fluorescence microscopy, it is crucial to orient biological structures at a single-cell resolution based on precise anatomical annotations of cytoarchitecture images. However, during synchronous multicolor imaging, due to spectral mixing, the crosstalk from the blue signals of 4′,6-diamidino-2-phenylindole (DAPI)-stained cytoarchitecture images to the green waveband hinders the visualization and identification of green signals. Here, we proposed a deep learning-based framework named the crosstalk elimination and cytoarchitecture enhancement pipeline (CECEP) to simultaneously acquire crosstalk-free signals in the green channel and high-contrast DAPI-stained cytoarchitecture images during multicolor fluorescence imaging. For the CECEP network, we proposed an unsupervised learning algorithm named the cytoarchitecture enhancement network (CENet), which increased the signal-to-background ratio (SBR) of the cytoarchitecture images from 1.5 to 15.0 at a reconstruction speed of 25 Hz for 1800 × 1800 pixel images. The CECEP network is widely applicable to images of different quality, different types of tissues, and different multicolor fluorescence microscopy. In addition, the CECEP network can also facilitate various downstream analysis tasks, such as cell recognition, structure tensor calculation, and brain region segmentation. With the CECEP network, we simultaneously acquired two specific fluorescence-labeled neuronal distributions and their colocated high-SBR cytoarchitecture images without crosstalk throughout the brain. Experimental results demonstrate that our method could potentially facilitate multicolor fluorescence imaging applications in biology, such as revealing and visualizing different types of biological structures with precise locations and orientations.

Hard carbon is considered as the most commercially applicable anode for sodium-ion batteries. Lignin has the characteristics of sustainable, low cost, high carbon content (>60%) and abundant oxygen functional groups, which is expected to be used as a promising candidate precursor for low-cost hard carbons. The structure and electrochemical performances of hard carbons could be regulated by adjusting carbonization temperature. The microstructure and electrochemical performance of LDHC anode are highly dependent on the carbonization temperature. Increasing carbonization temperature could reduce specific surface area and improve initial coulombic efficiency. The slope and plateau capacity of the LDHC anode could also be adjusted by changing the carbonization temperature. The LDHC prepared at 1200 °C showed the best sodium-ion storage performance, with an initial coulombic efficiency of 78.9% and a reversible sodium-ion storage capacity of 284.7 mAh g−1.

Blue carbon sequestration is a nature-based solution to environmental problems caused by climate change and has a significant positive impact on the planet and human well-being. This paper bibliometrically and systematically analyzed 2,613 studies found in the Web of Science Core Collection (WoSCC) from 2003 to 2021 to explore the hotspots and trends of blue carbon research using the Bibliometrix package in R studio and VOSviewer software. The results based on network co-occurrence analysis indicated that mangroves, seagrasses, and salt marshes were the major blue carbon ecosystems (BCEs), and mangrove carbon sinks were the most popular central research area. Furthermore, phytoplankton and microalgae have essential roles in the marine carbon cycle and bioenergy utilization, as revealed by the high proportion of published literature, while the carbon transport mechanisms of seagrass and macroalgae was understudied. Thematic evolution analysis revealed that remote sensing was the most commonly used technology as an emerging research field for ecological monitoring and ecological investigation in blue carbon research in recent years. In addition, increasing carbon sinks by artificial approaches, fishery carbon sinks, and carbon sequestration by macroalgae have been potential hotspots for blue carbon research development. The findings from this study shed light on the trends of blue carbon in the past eighteen years, current research points in the field, and areas that need more research investment going forward.

How coral–Symbiodiniaceae mutualistic symbiosis is established, maintained, and disrupted is arguably the most fundamental and central area of coral research. The breakdown of this symbiosis, and consequent coral bleaching, have been frequently attributed to thermal stress, although microbial attack and pollution have also been blamed. Despite the perceived intense and broad research, it is unclear whether all the potential causes have been given adequate attention and whether some important areas have been overlooked. This work aims to comprehensively review the literature on coral and Symbiodiniaceae research and provide a portrait of the current coral research landscape, hence identifying areas that require more research effort. Data of publication output were extracted from the Web of Science (WoS) from 1986 to 2022 by using the keywords “coral” and “Symbiodiniaceae.” A total of 43,089 and 3,191 papers in the coral and Symbiodiniaceae were identified, mostly published after 2002. The journal Coral Reefs was ranked first regarding the total number of publications on coral or Symbiodiniaceae. The USA, Australia, and China were the top three countries in the number of publications. The network co-occurrence analysis of all keywords in coral and Symbiodiniaceae using VOSviewer showed that biodiversity, climate change, nutrient, and survival were the central research areas in coral and Symbiodiniaceae. Among them, climate change was the most invested research field, as revealed by the high proportion of published literature, while nutrient was the most understudied area. Thematic evolution analysis revealed that nutrient enrichment combined with elevated temperature was an emerging research field about coral and Symbiodiniaceae. Besides, nitrogen is currently the most studied nutrient. The findings from this study shed light on the trends of coral and Symbiodiniaceae research in the past 36 years, current research hotspots in the field, and areas that need more research investment going forward.

BackgroundA number of public health measures are required during the COVID-19 pandemic. To stop the spread of COVID-19, the Chinese government has adopted isolation policies, including closing non-essential businesses, public transportation and schools, moving students' face-to-face learning to online, and recommending the cancellation of all non-essential activities and outdoor activities. However, while this isolation strategy has reduced human-to-human transmission of COVID-19, it has led to dramatic changes in students' daily lives and learning styles, including reduced physical activity and increased sedentary time. Considering the potentially harmful effects of physical inactivity, this study hoped to explore the incidence and influencing factors of non-participation in home physical exercise among Chinese students aged 10–20 during the implementation of the COVID-19 isolation policy.MethodsThrough an online questionnaire platform, this study created an open-ended questionnaire (from March 1, 2020 to March 10, 2020) and distributed it to students in areas where isolation policies were enforced. The questionnaire was initially distributed by 10 recruited volunteers, and then the questionnaire was voluntarily forwarded and shared by the subjects or others, in a “snowball” way, to expand distribution. Finally, the survey data of 4,532 Chinese students aged 10–20 were collected. The incidence of respondents non-participating in home physical activity was determined using univariate analysis. Using odds ratios and 95% confidence intervals of a multivariate binary logistic regression model, factors influencing non-participation in home physical exercise were estimated.ResultsAmong the sample students, the incidence rate of non-participating in home physical exercise was 25.86% (24.06–27.15%). Exercise intentions, exercise habits, self-assessed health, beliefs in physical health, family exercise, family exercise recommendations, home exercise conditions, school exercise guidance, and health education programs had a negative impact on students non-participating in home physical exercise. Academic performance and electronic product use had a positive effect on non-participating in home physical exercise.ConclusionsA variety of forward leaning factors, enabling factors and demand factors have affected the occurrence of students” non-participating in home physical exercise. Future health isolation policies should take into account these influencing factors to reduce the occurrence of students” non-participating in home physical exercise and to promote students' independent participation in physical exercise.

Gravi-A nanoparticles, composed of retinyl propionate (RP) and hydroxypinacolone retinoate (HPR), were prepared by encapsulating the two using the high-pressure homogenization technique. The nanoparticles are effective in anti-wrinkle treatment with high stability and low irritation. We evaluated the effect of different process parameters on nanoparticle preparation. Supramolecular technology effectively produced nanoparticles with spherical shapes with an average size of 101.1 nm. The encapsulation efficiency was in the 97.98–98.35% range. The system showed a sustained release profile for reducing the irritation caused by Gravi-A nanoparticles. Furthermore, applying lipid nanoparticle encapsulation technology improved the transdermal efficiency of the nanoparticles, thereby allowing these to penetrate deep into the dermis layer to achieve precise and sustained release of active ingredients. Gravi-A nanoparticles can be extensively and conveniently used in cosmetics and other related formulations by direct application.

Objective: To explore the effects of using RPE exercise intensity monitoring methods and 12-week mid- and low-intensity team aerobic training on anxiety, depression and sleep quality of depressed middle school students after the COVID-19 epidemic.Methods: All study participants were all from a boarding middle school in Chongqing, China. All study participants were screened by the self-rating depression scale and reached the diagnostic criteria for depression. The study subjects were divided into a control group (N = 35) and an exercise group (N = 34). The exercise group performed 30-min night aerobic running four times a week. Use the Borg 6–20 rating of perceived exertion scale (RPE) as a monitoring tool for exercise intensity, and control the exercise intensity at RPE = 11–14. And the control group studied and lived normally. The experiment lasted 12 weeks in total. After the experiment, there were 34 people in the control group and 23 people in the exercise group. The subjects' anxiety, depression and Pittsburgh sleep quality were scored before and after the experiment.Results: After intervention, the depression index (p < 0.01) of the exercise group was significantly lower than that of the control group.Conclusion: Using the RPE exercise intensity monitoring method for 12 weeks of mid- and low-intensity team aerobic training can improve the depressive symptoms of depressed middle school students, and it is beneficial to improve the students' mental health.

The adaptive decomposition algorithm is a powerful tool for signal analysis, because it can decompose signals into several narrow-band components, which is advantageous to quantitatively evaluate signal characteristics. In this paper, we present a comparative study of four kinds of adaptive decomposition algorithms, including some algorithms deriving from empirical mode decomposition (EMD), empirical wavelet transform (EWT), variational mode decomposition (VMD) and Vold–Kalman filter order tracking (VKF_OT). Their principles, advantages and disadvantages, and improvements and applications to signal analyses in dynamic analysis of mechanical system and machinery fault diagnosis are showed. Examples are provided to illustrate important influence performance factors and improvements of these algorithms. Finally, we summarize applicable scopes, inapplicable scopes and some further works of these methods in respect of precise filters and rough filters. It is hoped that the paper can provide a valuable reference for application and improvement of these methods in signal processing.