Maximal Quantum Fisher Information in a Mach-Zehnder Interferometer without initial parity

Mach-Zehnder interferometer is a common device in quantum phase estimation and the photon losses in it are an important issue for achieving a high phase accuracy. Here we thoroughly discuss the precision limit of the phase in the Mach-Zehnder interferometer with a coherent state and a superposition of coherent states as input states. By providing a general analytical expression of quantum Fisher information, the phase-matching condition and optimal initial parity are given. Especially, in the photon loss scenario, the sensitivity behaviors are analyzed and specific strategies are provided to restore the phase accuracies for symmetric and asymmetric losses.Comment: 10 pages, 3 figure

Electric-field Control of Magnetism with Emergent Topological Hall Effect in SrRuO3 through Proton Evolution

Ionic substitution forms an essential pathway to manipulate the carrier density and crystalline symmetry of materials via ion-lattice-electron coupling, leading to a rich spectrum of electronic states in strongly correlated systems. Using the ferromagnetic metal SrRuO3 as a model system, we demonstrate an efficient and reversible control of both carrier density and crystalline symmetry through the ionic liquid gating induced protonation. The insertion of protons electron-dopes SrRuO3, leading to an exotic ferromagnetic to paramagnetic phase transition along with the increase of proton concentration. Intriguingly, we observe an emergent topological Hall effect at the boundary of the phase transition as the consequence of the newly-established Dzyaloshinskii-Moriya interaction owing to the breaking of inversion symmetry in protonated SrRuO3 with the proton compositional film-depth gradient. We envision that electric-field controlled protonation opens a novel strategy to design material functionalities

Oral microbiota–host interaction: the chief culprit of alveolar bone resorption

There exists a bidirectional relationship between oral health and general well-being, with an imbalance in oral symbiotic flora posing a threat to overall human health. Disruptions in the commensal flora can lead to oral diseases, while systemic illnesses can also impact the oral cavity, resulting in the development of oral diseases and disorders. Porphyromonas gingivalis and Fusobacterium nucleatum, known as pathogenic bacteria associated with periodontitis, play a crucial role in linking periodontitis to accompanying systemic diseases. In periodontal tissues, these bacteria, along with their virulence factors, can excessively activate the host immune system through local diffusion, lymphatic circulation, and blood transmission. This immune response disruption contributes to an imbalance in osteoimmune mechanisms, alveolar bone resorption, and potential systemic inflammation. To restore local homeostasis, a deeper understanding of microbiota–host interactions and the immune network phenotype in local tissues is imperative. Defining the immune network phenotype in periodontal tissues offers a promising avenue for investigating the complex characteristics of oral plaque biofilms and exploring the potential relationship between periodontitis and associated systemic diseases. This review aims to provide an overview of the mechanisms underlying Porphyromonas gingivalis- and Fusobacterium nucleatum-induced alveolar bone resorption, as well as the immunophenotypes observed in host periodontal tissues during pathological conditions

YY1 directly interacts with myocardin to repress the triad myocardin/SRF/CArG box-mediated smooth muscle gene transcription during smooth muscle phenotypic modulation

Yin Yang 1 (YY1) regulates gene transcription in a variety of biological processes. In this study, we aim to determine the role of YY1 in vascular smooth muscle cell (VSMC) phenotypic modulation both in vivo and in vitro. Here we show that vascular injury in rodent carotid arteries induces YY1 expression along with reduced expression of smooth muscle differentiation markers in the carotids. Consistent with this finding, YY1 expression is induced in differentiated VSMCs in response to serum stimulation. To determine the underlying molecular mechanisms, we found that YY1 suppresses the transcription of CArG box-dependent SMC-specific genes including SM22α, SMα-actin and SMMHC. Interestingly, YY1 suppresses the transcriptional activity of the SM22α promoter by hindering the binding of serum response factor (SRF) to the proximal CArG box. YY1 also suppresses the transcription and the transactivation of myocardin (MYOCD), a master regulator for SMC-specific gene transcription by binding to SRF to form the MYOCD/SRF/CArG box triad (known as the ternary complex). Mechanistically, YY1 directly interacts with MYOCD to competitively displace MYOCD from SRF. This is the first evidence showing that YY1 inhibits SMC differentiation by directly targeting MYOCD. These findings provide new mechanistic insights into the regulatory mechanisms that govern SMC phenotypic modulation in the pathogenesis of vascular diseases

Reversible manipulation of the magnetic state in SrRuO3 through electric-field controlled proton evolution

Ionic substitution forms an essential pathway to manipulate the structural phase, carrier density and crystalline symmetry of materials via ion-electron-lattice coupling, leading to a rich spectrum of electronic states in strongly correlated systems. Using the ferromagnetic metal SrRuO3 as a model system, we demonstrate an efficient and reversible control of both structural and electronic phase transformations through the electric-field controlled proton evolution with ionic liquid gating. The insertion of protons results in a large structural expansion and increased carrier density, leading to an exotic ferromagnetic to paramagnetic phase transition. Importantly, we reveal a novel protonated compound of HSrRuO3 with paramagnetic metallic as ground state. We observe a topological Hall effect at the boundary of the phase transition due to the proton concentration gradient across the film-depth. We envision that electric-field controlled protonation opens up a pathway to explore novel electronic states and material functionalities in protonated material systems

Long noncoding RNA NEAT1 (nuclear paraspeckle assembly transcript 1) is critical for phenotypic switching of vascular smooth muscle cells

In response to vascular injury, vascular smooth muscle cells (VSMCs) may switch from a contractile to a proliferative phenotype thereby contributing to neointima formation. Previous studies showed that the long noncoding RNA (lncRNA) NEAT1 is critical for paraspeckle formation and tumorigenesis by promoting cell proliferation and migration. However, the role of NEAT1 in VSMC phenotypic modulation is unknown. Herein we showed that NEAT1 expression was induced in VSMCs during phenotypic switching in vivo and in vitro. Silencing NEAT1 in VSMCs resulted in enhanced expression of SM-specific genes while attenuating VSMC proliferation and migration. Conversely, overexpression of NEAT1 in VSMCs had opposite effects. These in vitro findings were further supported by in vivo studies in which NEAT1 knockout mice exhibited significantly decreased neointima formation following vascular injury, due to attenuated VSMC proliferation. Mechanistic studies demonstrated that NEAT1 sequesters the key chromatin modifier WDR5 (WD Repeat Domain 5) from SM-specific gene loci, thereby initiating an epigenetic "off" state, resulting in down-regulation of SM-specific gene expression. Taken together, we demonstrated an unexpected role of the lncRNA NEAT1 in regulating phenotypic switching by repressing SM-contractile gene expression through an epigenetic regulatory mechanism. Our data suggest that NEAT1 is a therapeutic target for treating occlusive vascular diseases

Antifungal mechanisms of the antagonistic bacterium Bacillus mojavensis UTF-33 and its potential as a new biopesticide

Biological control has gradually become the dominant means of controlling fungal disease over recent years. In this study, an endophytic strain of UTF-33 was isolated from acid mold (Rumex acetosa L.) leaves. Based on 16S rDNA gene sequence comparison, and biochemical and physiological characteristics, this strain was formally identified as Bacillus mojavensis. Bacillus mojavensis UTF-33 was sensitive to most of the antibiotics tested except neomycin. Moreover, the filtrate fermentation solution of Bacillus mojavensis UTF-33 had a significant inhibitory effect on the growth of rice blast and was used in field evaluation tests, which reduced the infestation of rice blast effectively. Rice treated with filtrate fermentation broth exhibited multiple defense mechanisms in response, including the enhanced expression of disease process-related genes and transcription factor genes, and significantly upregulated the gene expression of titin, salicylic acid pathway-related genes, and H2O2 accumulation, in plants; this may directly or indirectly act as an antagonist to pathogenic infestation. Further analysis revealed that the n-butanol crude extract of Bacillus mojavensis UTF-33 could retard or even inhibit conidial germination and prevent the formation of adherent cells both in vitro and in vivo. In addition, the amplification of functional genes for biocontrol using specific primers showed that Bacillus mojavensis UTF-33 expresses genes that can direct the synthesis of bioA, bmyB, fenB, ituD, srfAA and other substances; this information can help us to determine the extraction direction and purification method for inhibitory substances at a later stage. In conclusion, this is the first study to identify Bacillus mojavensis as a potential agent for the control of rice diseases; this strain, and its bioactive substances, have the potential to be developed as biopesticides

Spatiotemporal Dynamics of Cultivated Land and Its Influences on Grain Production Potential in Hunan Province, China

Understanding the impact of changes in cultivated land in terms of structure, distribution, and quantity on grain production potential (GPP) is essential for a sustainable land utilization strategy and food security. Cultivated land balance (CLB), as a critical policy aiming at protecting farmland in China, has greatly restricted the loss of cultivated land. However, changes in cultivated land were largely generated due to the land-use activities led by the CLB policy. To clarify how the spatiotemporal dynamics of cultivated land led by the CLB policy affects the GPP, this work discusses the impact mechanism of cultivated land changes on GPP and provides an empirical analysis in Hunan Province, China. This study shows that the activities that merely aim at restricting the loss of cultivated land under CLB cannot stop the decline in GPP in China, since it requires the government to reclaim a certain amount of cultivated land that is equal to that occupied for non-cultivated land use. Furthermore, the distribution of cultivated land changed after the implementation of CLB and, as a result, contributed to the decrease in the quality of cultivated land and GPP. Quantity, productivity, and other elements that may potentially facilitate cultivated land protection are greatly advocated to be considered to enrich the connotation of the CLB policy in China. It also found that less developed regions located in central and western Hunan Province, among other areas, observed a higher sensitivity of GPP to cultivated land change. More attention should be paid to protecting cultivated land in these regions and addressing issues such as the abandonment of high-quality cultivated land

A Local–Global Framework for Semantic Segmentation of Multisource Remote Sensing Images

Recently, deep learning has been widely used in the segmentation tasks of remote sensing images. However, the existing deep learning method most focus on local contextual information and has limited field of perception, which makes it difficult to capture the long-range contextual feature of objects at large scales form very-high-resolution (VHR) images. In this paper, we present a novel Local–global Framework consisting of the dual-source fusion network and local–global transformer modules, which efficiently utilize features extracted from multiple sources and fully capture features of local and global regions. The dual-source fusion network is an encoder designed to extract features from multiple sources such as spectra, synthetic aperture radar, and elevations, which selective fuse features from multiple sources and reduce the interference of redundant features. The local–global transformer module is proposed to capture fine-grained local features and coarse-grained global features, which enables the framework to focus on recognizing multiple-scale objects from the local and global regions. Moreover, we propose a pixelwise contrastive loss, which could encourage that the prediction is pulled closer to the ground truth. The Local–global Framework achieves state-of-the-art performance with 90.45% mean f1 score on the ISPRS Vaihingen dataset and 93.20% mean f1 score on the ISPRS Potsdam dataset