Characterization of the psoRPM1 gene for resistance to root-knot nematodes in wild myrobalan plum (Prunus sogdiana)

Several root-knot nematode (Meloidogyne spp.) resistance genes have been discovered in different stone fruit crops. However, none of them has yet been cloned and they were only located on the chromosomes. In this study, a candidate root-knot nematode resistance gene (designated as psoRPM1) was isolated from the individual plant of Xinjiang wild myrobalan plum (Prunus sogdiana) by degenerate PCR amplification combined with the RACE technique. The gene had a typical NBS-LRR structure and high homology with Mi-1.2 (root-knot nematode resistance genes in tomato). The expression of psoRPM1 gene increased in the roots of resistant wild myrobalan plum material 12, 24 and 48 h after inoculation with root-knot nematodes and the expression of psoRPM1 gene was maximum 12 h after inoculation. But in susceptible plant, the psoRPM1 gene expression remained low both before and after inoculation. This result suggested that the psoRPM1 gene was constitutively expressed gene in the wild myrobalan plum. In-situ hybridization results showed that the psoRPM1 gene mainly expressed in both phloem and cortex parenchyma of root 12 h after inoculation in resistant plant. Furthermore, the psoRPM1 gene only expressed in phloem 48 h after inoculation in resistant plant. The result suggested that the psoRPM1 gene played a role in keeping nematodes off the cortex when nematodes began to infect the plant’s roots. After root-knot nematodes entering into cortex parenchyma, the psoRPM1 gene mainly played defense function in phloem of pericycle. Using the gene gun bombarding into onion epidermal cells, the result was that psoRPM1 protein was located in cytomembrane and might be interacted with other proteins in cytomembrane to locateKey words: Xingjiang wild myrobalan plum (Prunus sogdiana), root-knot nematodes (Meloidogyne incognita), gene, in-situ, gene location

COVID-19 spreading patterns in family clusters reveal gender roles in China

Unfolding different gender roles is preceding the efforts to reduce gender inequality. This paper analyzes COVID-19 family clusters outside Hubei Province in mainland China during the 2020 outbreak, revealing significant differences in spreading patterns across gender and family roles. Results show that men are more likely to be the imported cases of a family cluster, and women are more likely to be infected within the family. This finding provides new supportive evidence of the men as breadwinner and women as homemaker (MBWH) gender roles in China. Further analyses reveal that the MBWH pattern is stronger in eastern than in western China, stronger for younger than for elder people. This paper offers not only valuable references for formulating gender-differentiated epidemic prevention policies but also an exemplification for studying group differences in similar scenarios.Comment: 13 pages, 5 figures, 2 table

Mean-squared displacement and variance for confined Brownian motion

For one-dimension Brownian motion in the confined system with the size $L$, the mean-squared displacement(MSD) defined by $\left \langle (x-x_0)^2 \right\rangle$ should be proportional to $t^{\alpha(t)}$. The power $\alpha(t)$ should range from $1$ to $0$ over time, and the MSD turns from $2Dt$ to $c L^2$, here the coefficient $c$ independent of $t$, $D$ being the diffusion coefficient. The paper aims to quantitatively solve the MSD in the intermediate confinement regime. The key to this problem is how to deal with the propagator and the normalization factor of the Fokker-Planck equation(FPE) with the Dirichlet Boundaries. Applying the Euler-Maclaurin approximation(EMA) and integration by parts for the small $t$, we obtain the MSD being $2Dt(1-\frac{2\sqrt{\xi} }{3\pi\sqrt{\pi}})$, with $t_{ch}=\frac{L^2}{4\pi^2D},\xi\equiv \frac{t}{t_{ch}}$, and the power $\alpha(t)$ being $\frac{1-0.18\sqrt{\xi}}{1-0.12\sqrt{\xi}}$. Further, we analysis the MSD and the power for the $d$-dimension system with $\gamma$-dimension confinement. In the case of $\gamma< d$, there exists the sub-diffusive behavior in the intermediate time. The universal description is consistent with the recent experiments and simulations in the micro-nano systems. Finally, we calculate the position variance(PV) meaning $\left\langle (x-\left\langle x \right\rangle)^2 \right\rangle$. Under the initial condition referring to the different probability density function(PDF) being $p_{0}(x)$, MSD and PV should exhibit different dependencies on time, which reflect corresponding diffusion behaviors.As examples, the paper discusses the representative initial PDFs reading $p_{0}(x)=\delta(x-x_0)$, with the midpoint $x_0=\frac{L}{2}$ and the endpoint $x_0=\epsilon$(or $0^+$).The MSD(equal to PV) reads $2Dt(1-\frac{5\pi^3 Dt}{L^2})$,and $\frac{4}{\pi}(2Dt)[1+\frac{2\sqrt{\pi Dt}}{L}]$for the small $t$,respectively.Comment: 18 pages, 4 figure

Linezolid and Rifampicin Combination to Combat cfr-Positive Multidrug-Resistant MRSA in Murine Models of Bacteremia and Skin and Skin Structure Infection.

Linezolid resistance mediated by the cfr gene in MRSA represents a global concern. We investigated relevant phenotype differences between cfr-positive and -negative MRSA that contribute to pathogenesis, and the efficacy of linezolid-based combination therapies in murine models of bacteremia and skin and skin structure infection (SSSI). As a group, cfr-positive MRSA exhibited significantly reduced susceptibilities to the host defense peptides tPMPs, human neutrophil peptide-1 (hNP-1), and cathelicidin LL-37 (P &lt; 0.01). In addition, increased binding to fibronectin (FN) and endothelial cells paralleled robust biofilm formation in cfr-positive vs. -negative MRSA. In vitro phenotypes of cfr-positive MRSA translated into poor outcomes of linezolid monotherapy in vivo in murine bacteremia and SSSI models. Importantly, rifampicin showed synergistic activity as a combinatorial partner with linezolid, and the EC50 of linezolid decreased 6-fold in the presence of rifampicin. Furthermore, this combination therapy displayed efficacy against cfr-positive MRSA at clinically relevant doses. Altogether, these data suggest that the use of linezolid in combination with rifampicin poses a viable therapeutic alternative for bacteremia and SSSI caused by cfr-positive multidrug resistant MRSA

N-{N-[N-(1,1-Dimethyl­ethoxy­carbon­yl)-l-leuc­yl]-N-methyl-l-leuc­yl}-N-methyl-l-leucine benzyl ester

The tripeptide title compound, C32H53N3O6, synthesized in 80% yield by coupling of N-methyl-l-leucine benzyl ester with tert-butoxy­carbonyl-l-leucyl-N-methyl-l-leucine at 273 K, conjugates through two amide linkages and includes two protecting groups: a tert-butyl­oxycarbonyl group at the C-tip and a benzyl group at the N-tip. A classical inter­molecular N—H⋯O hydrogen bond and a weak non-conventional inter­molecular C—H⋯O contact connect the mol­ecules, forming layers parallel to (001)

PanopticNeRF-360: Panoramic 3D-to-2D Label Transfer in Urban Scenes

Training perception systems for self-driving cars requires substantial annotations. However, manual labeling in 2D images is highly labor-intensive. While existing datasets provide rich annotations for pre-recorded sequences, they fall short in labeling rarely encountered viewpoints, potentially hampering the generalization ability for perception models. In this paper, we present PanopticNeRF-360, a novel approach that combines coarse 3D annotations with noisy 2D semantic cues to generate consistent panoptic labels and high-quality images from any viewpoint. Our key insight lies in exploiting the complementarity of 3D and 2D priors to mutually enhance geometry and semantics. Specifically, we propose to leverage noisy semantic and instance labels in both 3D and 2D spaces to guide geometry optimization. Simultaneously, the improved geometry assists in filtering noise present in the 3D and 2D annotations by merging them in 3D space via a learned semantic field. To further enhance appearance, we combine MLP and hash grids to yield hybrid scene features, striking a balance between high-frequency appearance and predominantly contiguous semantics. Our experiments demonstrate PanopticNeRF-360's state-of-the-art performance over existing label transfer methods on the challenging urban scenes of the KITTI-360 dataset. Moreover, PanopticNeRF-360 enables omnidirectional rendering of high-fidelity, multi-view and spatiotemporally consistent appearance, semantic and instance labels. We make our code and data available at https://github.com/fuxiao0719/PanopticNeRFComment: Project page: http://fuxiao0719.github.io/projects/panopticnerf360/. arXiv admin note: text overlap with arXiv:2203.1522

Ion-exchange voltammetry at polymer film-coated nanoelectrode ensembles.

Ensembles of nanoscopic disk-shaped electrodes have been shown to offer enhancements in electroanalytical detection limits relative to electrodes of macroscopic dimensions (e.g., disk electrodes with diameters of 1 mm). Enhancements in electroanalytical detection limits have also been observed at macroscopic electrodes that have been coated with films of ion-exchange polymers. In this paper we combine these two concepts. We demonstrate that a nanoelectrode ensemble (NEE) that has been coated with a thin film of the Kodak ion-exchange polymer AQ 55 shows enhanced electroanalytical detection limits relative to the uncoated NEE and to the coated macroscopic electrode. To our knowledge, this is the first investigation of the electrochemistry, and the electroanalytical advantages, of polymer film-coated NEEs

Panoptic NeRF: 3D-to-2D Label Transfer for Panoptic Urban Scene Segmentation

Large-scale training data with high-quality annotations is critical for training semantic and instance segmentation models. Unfortunately, pixel-wise annotation is labor-intensive and costly, raising the demand for more efficient labeling strategies. In this work, we present a novel 3D-to-2D label transfer method, Panoptic NeRF, which aims for obtaining per-pixel 2D semantic and instance labels from easy-to-obtain coarse 3D bounding primitives. Our method utilizes NeRF as a differentiable tool to unify coarse 3D annotations and 2D semantic cues transferred from existing datasets. We demonstrate that this combination allows for improved geometry guided by semantic information, enabling rendering of accurate semantic maps across multiple views. Furthermore, this fusion process resolves label ambiguity of the coarse 3D annotations and filters noise in the 2D predictions. By inferring in 3D space and rendering to 2D labels, our 2D semantic and instance labels are multi-view consistent by design. Experimental results show that Panoptic NeRF outperforms existing semantic and instance label transfer methods in terms of accuracy and multi-view consistency on challenging urban scenes of the KITTI-360 dataset.Comment: Project page: https://fuxiao0719.github.io/projects/panopticnerf