171 research outputs found
The global landscape and research trend of phase separation in cancer: a bibliometric analysis and visualization
BackgroundCancer as a deathly disease with high prevalence has impelled researchers to investigate its causative mechanisms in the search for effective therapeutics. Recently, the concept of phase separation has been introduced to biological science and extended to cancer research, which helps reveal various pathogenic processes that have not been identified before. As a process of soluble biomolecules condensed into solid-like and membraneless structures, phase separation is associated with multiple oncogenic processes. However, there are no bibliometric characteristics for these results. To provide future trends and identify new frontiers in this field, a bibliometric analysis was conducted in this study.MethodsThe Web of Science Core Collection (WoSCC) was used to search for literature on phase separation in cancer from 1/1/2009 to 31/12/2022. After screening the literature, statistical analysis and visualization were carried out by the VOSviewer software (version 1.6.18) and Citespace software (Version 6.1.R6).ResultsA total of 264 publications, covering 413 organizations and 32 countries, were published in 137 journals, with an increasing trend in publication and citation numbers per year. The USA and China were the two countries with the largest number of publications, and the University of Chinese Academy of Sciences was the most active institution based on the number of articles and cooperations. Molecular Cell was the most frequent publisher with high citations and H-index. The most productive authors were Fox AH, De Oliveira GAP, and Tompa P. Overlay, whilst few authors had a strong collaboration with each other. The combined analysis of concurrent and burst keywords revealed that the future research hotspots of phase separation in cancer were related to tumor microenvironments, immunotherapy, prognosis, p53, and cell death.ConclusionPhase separation-related cancer research remained in the hot streak period and exhibited a promising outlook. Although inter-agency collaboration existed, cooperation among research groups was rare, and no author dominated this field at the current stage. Investigating the interfaced effects between phase separation and tumor microenvironments on carcinoma behaviors, and constructing relevant prognoses and therapeutics such as immune infiltration-based prognosis and immunotherapy might be the next research trend in the study of phase separation and cancer
Understanding thermal induced escape mechanism of optically levitated sphere in vacuum
The escape phenomenon, mainly caused by thermal effects, is known as an
obstacle to the further practical application of optical levitation system in
vacuum. Irregular photophoresis induced by thermal effects can act as an
amplifier of Brownian motion. Studies on this topic provide interpretation for
particle escaping phenomenon during the pressure decreasing process, as well as
valuable insights into the micro- and nanoscale thermal effects in optical trap
in vacuum. In this paper, we derive and test a dynamic model for the motion of
an optically levitated particle in a non-equilibrium state and demonstrate the
escaping mechanism of heated particles. The result of theoretical
investigations is consistent with experimental escape at 0.1mbar. This work
reveals and provides a theoretical basis for the stable operation of laser
levitated oscillator in high vacuum and pave the way for the practicability of
ultra-sensitive sensing devices
Inconsistent Matters: A Knowledge-guided Dual-consistency Network for Multi-modal Rumor Detection
Rumor spreaders are increasingly utilizing multimedia content to attract the
attention and trust of news consumers. Though quite a few rumor detection
models have exploited the multi-modal data, they seldom consider the
inconsistent semantics between images and texts, and rarely spot the
inconsistency among the post contents and background knowledge. In addition,
they commonly assume the completeness of multiple modalities and thus are
incapable of handling handle missing modalities in real-life scenarios.
Motivated by the intuition that rumors in social media are more likely to have
inconsistent semantics, a novel Knowledge-guided Dual-consistency Network is
proposed to detect rumors with multimedia contents. It uses two consistency
detection subnetworks to capture the inconsistency at the cross-modal level and
the content-knowledge level simultaneously. It also enables robust multi-modal
representation learning under different missing visual modality conditions,
using a special token to discriminate between posts with visual modality and
posts without visual modality. Extensive experiments on three public real-world
multimedia datasets demonstrate that our framework can outperform the
state-of-the-art baselines under both complete and incomplete modality
conditions. Our codes are available at https://github.com/MengzSun/KDCN
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Editorial: Biofuels and Bioenergy
Editorial on the research topic of biofuels and bioenergy
Perspectives and challenges of applying the water-food-energy nexus approach to lake eutrophication modelling
Embargo until August 4, 2023The water-food-energy (WFE) nexus is about balancing competing interests to secure the sustainability of services provided by interconnected sectors. Ignoring the interconnections could cause serious consequences. For example, eutrophication caused by overemphasizing on food production maximization could threaten water security. Worldwide eutrophication intensification is one of the most important causes of the lake water quality deteriorations. Water quality models are usually important decision making tools for policy makers. This study attempts to explore the possibilities of applying the WFE nexus concept into water quality models. We propose the most significant challenge is lack of a common modelling framework to streamline connections between up- and downstream models. As the most important water quality issue, eutrophication modeling should increase its visibility in the United Nations Sustainable Develop Goals.acceptedVersio
Detect Depression from Social Networks with Sentiment Knowledge Sharing
Social network plays an important role in propagating people's viewpoints,
emotions, thoughts, and fears. Notably, following lockdown periods during the
COVID-19 pandemic, the issue of depression has garnered increasing attention,
with a significant portion of individuals resorting to social networks as an
outlet for expressing emotions. Using deep learning techniques to discern
potential signs of depression from social network messages facilitates the
early identification of mental health conditions. Current efforts in detecting
depression through social networks typically rely solely on analyzing the
textual content, overlooking other potential information. In this work, we
conduct a thorough investigation that unveils a strong correlation between
depression and negative emotional states. The integration of such associations
as external knowledge can provide valuable insights for detecting depression.
Accordingly, we propose a multi-task training framework, DeSK, which utilizes
shared sentiment knowledge to enhance the efficacy of depression detection.
Experiments conducted on both Chinese and English datasets demonstrate the
cross-lingual effectiveness of DeSK
Energy deficiency promotes rhythmic foraging behavior by activating neurons in paraventricular hypothalamic nucleus
BackgroundDysregulation of feeding behavior leads to a variety of pathological manifestations ranging from obesity to anorexia. The foraging behavior of animals affected by food deficiency is not fully understood.MethodsHome-Cage system was used to monitor the behaviors. Immunohistochemical staining was used to monitor the trend of neuronal activity. Chemogenetic approach was used to modify neuronal activity.ResultsWe described here a unique mouse model of foraging behavior and unveiled that food deprivation significantly increases the general activities of mice with a daily rhythmic pattern, particularly foraging behavior. The increased foraging behavior is potentiated by food cues (mouthfeel, odor, size, and shape) and energy deficit, rather than macronutrient protein, carbohydrate, and fat. Notably, energy deficiency increases nocturnal neuronal activity in paraventricular hypothalamic nucleus (PVH), accompanying a similar change in rhythmic foraging behavior. Activating neuronal activity in PVH enhances the amplitude of foraging behavior in mice. Conversely, inactivating neuronal activity in PVH decreases the amplitude of foraging behavior and impairs the rhythm of foraging behavior.DiscussionThese results illustrate that energy status and food cues regulate the rhythmic foraging behavior via PVH neuronal activity. Understanding foraging behavior provides insights into the underlying mechanism of eating-related disorders
Plant biosystems design research roadmap 1.0
Human life intimately depends on plants for food, biomaterials, health, energy, and a sustainable environment. Various plants have been genetically improved mostly through breeding, along with limited modification via genetic engineering, yet they are still not able to meet the ever-increasing needs, in terms of both quantity and quality, resulting from the rapid increase in world population and expected standards of living. A step change that may address these challenges would be to expand the potential of plants using biosystems design approaches. This represents a shift in plant science research from relatively simple trial-and-error approaches to innovative strategies based on predictive models of biological systems. Plant biosystems design seeks to accelerate plant genetic improvement using genome editing and genetic circuit engineering or create novel plant systems through de novo synthesis of plant genomes. From this perspective, we present a comprehensive roadmap of plant biosystems design covering theories, principles, and technical methods, along with potential applications in basic and applied plant biology research. We highlight current challenges, future opportunities, and research priorities, along with a framework for international collaboration, towards rapid advancement of this emerging interdisciplinary area of research. Finally, we discuss the importance of social responsibility in utilizing plant biosystems design and suggest strategies for improving public perception, trust, and acceptance
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