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"Fu, Ying"
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Environmental Stimuli and Phytohormones in Anthocyanin Biosynthesis: A Comprehensive Review
Anthocyanin accumulation in plants plays important roles in plant growth and development, as well as the response to environmental stresses. Anthocyanins have antioxidant properties and play an important role in maintaining the reactive oxygen species (ROS) homeostasis in plant cells. Furthermore, anthocyanins also act as a “sunscreen”, reducing the damage caused by ultraviolet radiation under high-light conditions. The biosynthesis of anthocyanin in plants is mainly regulated by an MYB-bHLH-WD40 (MBW) complex. In recent years, many new regulators in different signals involved in anthocyanin biosynthesis were identified. This review focuses on the regulation network mediated by different environmental factors (such as light, salinity, drought, and cold stresses) and phytohormones (such as jasmonate, abscisic acid, salicylic acid, ethylene, brassinosteroid, strigolactone, cytokinin, and auxin). We also discuss the potential application value of anthocyanin in agriculture, horticulture, and the food industry.
Journal Article
Spin mapping of intralayer antiferromagnetism and field-induced spin reorientation in monolayer CrTe2
Intrinsic antiferromagnetism in van der Waals (vdW) monolayer (ML) crystals enriches our understanding of two-dimensional (2D) magnetic orders and presents several advantages over ferromagnetism in spintronic applications. However, studies of 2D intrinsic antiferromagnetism are sparse, owing to the lack of net magnetisation. Here, by combining spin-polarised scanning tunnelling microscopy and first-principles calculations, we investigate the magnetism of vdW ML CrTe
2
, which has been successfully grown through molecular-beam epitaxy. We observe a stable antiferromagnetic (AFM) order at the atomic scale in the ML crystal, whose bulk is ferromagnetic, and correlate its imaged zigzag spin texture with the atomic lattice structure. The AFM order exhibits an intriguing noncollinear spin reorientation under magnetic fields, consistent with its calculated moderate magnetic anisotropy. The findings of this study demonstrate the intricacy of 2D vdW magnetic materials and pave the way for their in-depth analysis.
In two dimensions magnetic order without magnetic anisotropy is forbidden, making 2D magnetic systems a rich playground for interesting physics. Here, Xian et al. fabricate monolayers of CrTe2, and demonstrate antiferromagnetic ordering, with spin reorientation at finite magnetic fields.
Journal Article
DeepKla: An attention mechanism‐based deep neural network for protein lysine lactylation site prediction
As a newly discovered protein posttranslational modification, lysine lactylation (Kla) plays a pivotal role in various cellular processes. High throughput mass spectrometry is the primary approach for the detection of Kla sites. However, experimental approaches for identifying Kla sites are often time‐consuming and labor‐intensive when compared to computational methods. Therefore, it is desirable to develop a powerful tool for identifying Kla sites. For this purpose, we presented the first computational framework termed as DeepKla for Kla sites prediction in rice by combining supervised embedding layer, convolutional neural network, bidirectional gated recurrent units, and attention mechanism layer. Comprehensive experiment results demonstrated the excellent predictive power and robustness of DeepKla. Based on the proposed model, a web‐server called DeepKla was established and is freely accessible at http://lin-group.cn/server/DeepKla. The source code of DeepKla is freely available at the repository https://github.com/linDing-group/DeepKla. We presented the first computational tool, termed DeepKla, to identify Kla sites in rice. Supervised embedding layer, convolutional neural network, bidirectional gated recurrent units, and attention mechanism layer were applied to train the model. A robust, generalized, and convenient web‐server of DeepKla was established at http://lin-group.cn/server/DeepKla. Highlights We presented the first computational tool, termed DeepKla, to identify Kla sites in rice. Supervized embedding layer, convolutional neural network, bidirectional gated recurrent units, and attention mechanism layer were applied to train the model. A robust, generalized, and convenient web‐server of DeepKla was established at http://lin-group.cn/server/DeepKla.
Journal Article
Genetics of the human circadian clock and sleep homeostat
Timing and duration of sleep are controlled by the circadian system, which keeps an ~24-h internal rhythm that entrains to environmental stimuli, and the sleep homeostat, which rises as a function of time awake. There is a normal distribution across the population in how the circadian system aligns with typical day and night resulting in varying circadian preferences called chronotypes. A portion of the variation in the population is controlled by genetics as shown by the single-gene mutations that confer extreme early or late chronotypes. Similarly, there is a normal distribution across the population in sleep duration. Genetic variations have been identified that lead to a short sleep phenotype in which individuals sleep only 4–6.5 h nightly. Negative health consequences have been identified when individuals do not sleep at their ideal circadian timing or are sleep deprived relative to intrinsic sleep need. Whether familial natural short sleepers are at risk of the health consequences associated with a short sleep duration based on population data is not known. More work needs to be done to better assess for an individual’s chronotype and degree of sleep deprivation to answer these questions.
Journal Article
Observation of topological states residing at step edges of WTe2
Topological states emerge at the boundary of solids as a consequence of the nontrivial topology of the bulk. Recently, theory predicts a topological edge state on single layer transition metal dichalcogenides with 1
T
’ structure. However, its existence still lacks experimental proof. Here, we report the direct observations of the topological states at the step edge of WTe
2
by spectroscopic-imaging scanning tunneling microscopy. A one-dimensional electronic state residing at the step edge of WTe
2
is observed, which exhibits remarkable robustness against edge imperfections. First principles calculations rigorously verify the edge state has a topological origin, and its topological nature is unaffected by the presence of the substrate. Our study supports the existence of topological edge states in 1
T
’-WTe
2
, which may envision in-depth study of its topological physics and device applications.
Two-dimensional topological insulators support edge conduction electrons but its realization in real materials is rare. Here, Peng et al. report the direct observation of topological states at the step edge of WTe
2
.
Journal Article
Predicting breast cancer 5-year survival using machine learning: A systematic review
Accurately predicting the survival rate of breast cancer patients is a major issue for cancer researchers. Machine learning (ML) has attracted much attention with the hope that it could provide accurate results, but its modeling methods and prediction performance remain controversial. The aim of this systematic review is to identify and critically appraise current studies regarding the application of ML in predicting the 5-year survival rate of breast cancer.
In accordance with the PRISMA guidelines, two researchers independently searched the PubMed (including MEDLINE), Embase, and Web of Science Core databases from inception to November 30, 2020. The search terms included breast neoplasms, survival, machine learning, and specific algorithm names. The included studies related to the use of ML to build a breast cancer survival prediction model and model performance that can be measured with the value of said verification results. The excluded studies in which the modeling process were not explained clearly and had incomplete information. The extracted information included literature information, database information, data preparation and modeling process information, model construction and performance evaluation information, and candidate predictor information.
Thirty-one studies that met the inclusion criteria were included, most of which were published after 2013. The most frequently used ML methods were decision trees (19 studies, 61.3%), artificial neural networks (18 studies, 58.1%), support vector machines (16 studies, 51.6%), and ensemble learning (10 studies, 32.3%). The median sample size was 37256 (range 200 to 659820) patients, and the median predictor was 16 (range 3 to 625). The accuracy of 29 studies ranged from 0.510 to 0.971. The sensitivity of 25 studies ranged from 0.037 to 1. The specificity of 24 studies ranged from 0.008 to 0.993. The AUC of 20 studies ranged from 0.500 to 0.972. The precision of 6 studies ranged from 0.549 to 1. All of the models were internally validated, and only one was externally validated.
Overall, compared with traditional statistical methods, the performance of ML models does not necessarily show any improvement, and this area of research still faces limitations related to a lack of data preprocessing steps, the excessive differences of sample feature selection, and issues related to validation. Further optimization of the performance of the proposed model is also needed in the future, which requires more standardization and subsequent validation.
Journal Article
Emerging Role of Immunity in Cerebral Small Vessel Disease
Cerebral small vessel disease (CSVD) is one of the main causes of vascular dementia in older individuals. Apart from risk containment, efforts to prevent or treat CSVD are ineffective due to the unknown pathogenesis of the disease. CSVD, a subtype of stroke, is characterized by recurrent strokes and neurodegeneration. Blood-brain barrier (BBB) impairment, chronic inflammatory responses, and leukocyte infiltration are classical pathological features of CSVD. Understanding how BBB disruption instigates inflammatory and degenerative processes may be informative for CSVD therapy. Antigens derived from the brain are found in the peripheral blood of lacunar stroke patients, and antibodies and sensitized T cells against brain antigens are also detected in patients with leukoaraiosis. These findings suggest that antigen-specific immune responses could occur in CSVD. This review describes the neurovascular unit features of CSVD, the immune responses to specific neuronal and glial processes that may be involved in a distinct mechanism of CSVD, and the current evidence of the association between mechanisms of inflammation and interventions in CSVD. We suggest that autoimmune activity should be assessed in future studies; this knowledge would benefit the development of effective therapeutic interventions in CSVD.
Journal Article
The intricate dance of post-translational modifications in the rhythm of life
Clock proteins are controlled by multiple post-translational modifications during the circadian cycle. In this Review, the authors examine how post-translational modifications influence the stability, interactions and activity of mammalian clock proteins and how they contribute to proper clock function or are altered in circadian disorders.
Endogenous biological rhythms with approximately 24-h periodicity are generated by the circadian clock, in which clock genes coordinate with one another and form a transcriptional–translational negative feedback loop. The precision of the circadian clock is further regulated by multiple post-translational modifications (PTMs), including phosphorylation, ubiquitination, acetylation and SUMOylation. Here, we review current understanding of the regulatory mechanisms of the core clock proteins by PTMs in the mammalian circadian clock.
Journal Article
Single‐Layered MoS2 Fabricated by Charge‐Driven Interlayer Expansion for Superior Lithium/Sodium/Potassium‐Ion‐Battery Anodes
Single‐layered MoS2 is a promising anode material for lithium‐ion batteries (LIBs), sodium‐ion batteries (SIBs), and potassium‐ion batteries (PIBs) due to its high capacity and isotropic ion transport paths. However, the low intrinsic conductivity and easy‐agglomerated feature hamper its applications. Here, a charge‐driven interlayer expansion strategy that Co2+ replaces Mo4+ in the doping form to endow MoS2 layers with negative charges, thus inducing electrostatic repulsion, together with the insertion of gaseous groups, to drive interlayer expansion which once breaks the confinement of interlayer van der Waals force, single‐layered MoS2 is obtained and uniformly dispersed into carbon matrix arising from the transformation of carbonaceous gaseous groups under high vapor pressure, is proposed. Co atom doping helps enhance the intrinsic conductivity of single‐layered MoS2. Carbon matrix effectively prevents agglomeration of single‐layered MoS2. The doped Co atoms can be fully transformed into ultrasmall Co nanoparticles during conversion reaction, which enables strong spin‐polarized surface capacitance and thus significantly boosts ion transport and storage. Consequently, the prepared material delivers superb Li/Na/K‐ion storage performances, which are best in the reported MoS2‐based anodes. The proposed charge‐driven interlayer expansion strategy provides a novel perspective for preparing single‐layered MoS2, which shows huge potential for energy storage. Single‐layered MoS2 has great potential in energy storage but suffers from low intrinsic conductivity and easy‐agglomerated feature. Here, a charge‐driven interlayer expansion strategy is proposed. The interlayer electrostatic repulsion induced by Co doping breaks the interlayer van der Waals force to fabricate Co‐doped single‐layered MoS2, which uniformly disperses in carbon matrix and shows superior lithium/sodium/potassium‐ion transport and storage capability.
Journal Article