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With the development of artificial intelligence, path planning of Autonomous Mobile Robot (AMR) has been a research hotspot in recent years. This paper proposes the improved A* algorithm combined with the greedy algorithm for a multi-objective path planning strategy. Firstly, the evaluation function is improved to make the convergence of A* algorithm faster. Secondly, the unnecessary nodes of the A* algorithm are removed, meanwhile only the necessary inflection points are retained for path planning. Thirdly, the improved A* algorithm combined with the greedy algorithm is applied to multi-objective point planning. Finally, path planning is performed for five target nodes in a warehouse environment to compare path lengths, turn angles and other parameters. The simulation results show that the proposed algorithm is smoother and the path length is reduced by about 5%. The results show that the proposed method can reduce a certain path length.

Background Periodontitis is a chronic inflammatory disease that leads to the destruction of periodontal tissues and diabetes is a metabolic disease characterized by hyperglycemia. Both of these diseases affect many people worldwide. Epidemiological data have revealed a close relationship between periodontitis and diabetes. In particular, the high-glucose microenvironment plays an important role in the relationship between these two chronic inflammatory diseases, which makes it difficult to mitigate the progression of periodontitis and restore periodontal tissue in diabetic patients. Anti-inflammatory and regenerative processes are of fundamental importance for periodontal treatment and are mediated by diverse cell populations, including macrophages, T cells, neutrophils, stem cells, and fibroblasts that reside within periodontal tissues. Main body This review summarizes the interaction between diabetes mellitus and periodontitis, and illustrates that the high-glucose microenvironment aggravates periodontal homeostasis. Furthermore, the mechanism by which the high-glucose microenvironment regulates the involvement of various cells in the destruction of periodontal tissue, leading to the significant inhibition of tissue regeneration and recovery, is discussed. On this basis, the current therapeutic strategies that can be used to target cells are summarized to improve the regeneration and repair processes in the high-glucose microenvironment. Conclusion In this review, we assess how metabolic dysregulation mediated by a high-glucose microenvironment exacerbates inflammatory damage and inhibits tissue repair. A deeper understanding of the effects of a high-glucose microenvironment on periodontal tissue cells is essential for developing new therapeutic strategies to restore the structure and function of periodontal tissue.

Sarcina ventriculi is a bacterium with a specific histological morphology and infection can present with symptoms such as abdominal pain, nausea, vomiting and occasionally fatal complications. Delayed gastric emptying is regarded as the most significant risk factor for infection. Its pathogenicity is currently unknown and treatment options are inconsistent. Here we report a case of gastric bezoars secondary to a mixed infection of Sarcina ventriculi and G + bacilli, which is diagnosed by a pathological biopsy.

Roots are fundamentally important for growth and development, anchoring the plant to its growth substrate, facilitating water and nutrient uptake from the soil, and sensing and responding to environmental signals such as biotic and abiotic stresses. Understanding the molecular mechanisms controlling root architecture is essential for improving nutrient uptake efficiency and crop yields. In this review, we describe the progress being made in the identification of genes and regulatory pathways involved in the development of root systems in rice (Oryza sativa L.), including crown roots, lateral roots, root hairs, and root length. Genes involved in the adaptation of roots to the environmental nutrient status are reviewed, and strategies for further study and agricultural applications are discussed. The growth and development of rice roots are controlled by both genetic factors and environmental cues. Plant hormones, especially auxin and cytokinin, play important roles in root growth and development. Understanding the molecular mechanisms regulating root architecture and response to environmental signals can contribute to the genetic improvement of crop root systems, enhancing their adaptation to stressful environmental conditions.

Background Numerous studies have demonstrated significant variations in the plant growth-promoting effects among different species of arbuscular mycorrhizal fungi (AMF). However, the underlying mechanisms remain incompletely understood, particularly regarding how distinct AMF species regulate the rhizosphere microbiome. Results Five AMF species ( Funneliformis mosseae , Diversispora versiformis , Clariodeoglous etunicatum , Rhizophagus intraradices , and Acaulospora delicate ) were inoculated to investigate their effects on tobacco seedling growth and rhizosphere microecological regulation. The results showed that all AMF inoculations significantly increased shoot and root biomass, N/P/K uptake, morphological traits (height, stem diameter, leaf area), chlorophyll content (SPAD), and root architecture (length, surface area, volume, diameter) of tobacco seedlings. Among them, the treatment inoculated with R. intraradices showed the most outstanding growth-promoting effect in all growth indicators. Metagenomic analysis indicated that AMF inoculation significantly altered the diversity and community structure of rhizosphere substrate microorganisms. Among them, R. intraradices inoculation yielded the highest microbial diversity, with an associated network exhibiting enhanced complexity. KEGG functional annotation revealed metabolic pathways (IAA biosynthesis, iron-siderophore transport regulation, exopolysaccharide production, and nutrient cycling) consistently associated with tobacco growth promotion in all AMF inoculations. However, species-specific mechanisms were observed: F. mosseae promotes tobacco seedling growth by enhancing IAA synthesis through the recruitment of beneficial microorganisms such as Nostoc , Flavisolibacter , Frateuria , and Sphingomonas . D. versiformis enhanced carbon fixation via the hydroxypropionate-hydroxybutyrate cycle, driven by the proliferation of Glaciecola , Pedococcus , Phycicoccus , and Hephaestia . C. etunicatum facilitated phosphorus/iron accumulation through organic phosphorus mineralization, phosphate transport, and iron acquisition accompanied by the recruitment of, Hartmannibacter , Lysobacter , Moheibacter , and Pseudolabrys . R. intraradices improved nitrogen assimilation through augmented nitrogen transport and assimilatory nitrate reduction (ANRA), correlated with the recruitment of Azospirillum , Sphingobium , Mesorhizobium , Paracoccus , and Parafilimonas . A. delicate stimulated plant growth via polyphosphate degradation and exopolysaccharide biosynthesis, associated with the enrichment of Segetibacter , Ferruginibacter , Hyphomicrobium and Pseudomonas . Notably, this study revealed that functional divergence in rhizosphere microbiomes associated with the five tested fungal species was primarily reflected in the abundance rather than the composition of functional genes. Conclusion In summary, AMF inoculation significantly enhanced tobacco seedling biomass and agronomic traits by improving mineral nutrient assimilation efficiency and restructuring the rhizosphere microbial community. Different AMF species exhibited distinct microecological regulation patterns. This study elucidated the growth-promoting mechanisms of AMF from a microbial interaction perspective, providing a theoretical basis for establishing a sustainable tobacco cultivation system.

Objective: The purpose of this study was to explore the impact of disability on dyadic quality of life (QoL) among stroke survivors and to examine the mediating role of social support in this process. Methods: Outcome measures were collected at four time points: baseline, 1 month, 3 months, and 6 months post-discharge. The Actor–Partner Interdependence Mediation Model was used to analyze the dyadic data. Results: A significant association was observed between a higher degree of disability and more severe depressive symptoms in stroke survivors (β = 0.626) and their spouses (β = 0.426). Survivors’ disability had a negative impact on their own physical health (β = −3.731) and indirectly affected the physical health of the spouse caregiver through the spouse caregiver’s depression (β = −0.198). In addition, disability affects the survivor’s own mental health through depression and social support (β = −0.231) and indirectly through the spouse caregiver’s depression and their own social support (β = −0.156). Conclusions: Survivor disability has a major impact on depression and QoL in couples with stroke. It is recommended that healthcare providers should identify disability early in stroke survivors and then target interventions to improve the QoL of couples affected by stroke who are at high risk of negative emotions.

In plants, sensing the levels of external and internal nutrients is essential for reprogramming the transcriptome and adapting to the fluctuating environment. Phosphate (Pi) is a key plant nutrient, and a large proportion of Pi starvation-responsive genes are under the control of PHOSPHATE STARVATION RESPONSE REGULATOR 1 (PHR1) in Arabidopsis (AtPHR1) and its homologs, such as Oryza sativa (Os)PHR2 in rice. AtPHR1 and OsPHR2 expression is not very responsive to Pi starvation, raising the question as to how plants sense changes in cellular Pi levels to activate the central regulator. SPX [named after SYG1 (suppressor of yeast gpa1 ), Pho81 (CDK inhibitor in yeast PHO pathway), and XPR1 (xenotropic and polytropic retrovirus receptor)] proteins that harbor only the SPX domain are reported to be involved in the negative regulation of Pi starvation responses. Here, we show that the nuclear localized SPX proteins SPX1 and SPX2 are Pi-dependent inhibitors of the activity of OsPHR2 in rice. Indeed, SPX1 and SPX2 proteins interact with PHR2 through their SPX domain, inhibiting its binding to P1BS (the PHR1-binding sequence: GNATATNC). In vivo data, as well as results from in vitro experiments using purified SPX1, SPX2, and OsPHR2 proteins, showed that SPX1 and SPX2 inhibition of OsPHR2 activity is Pi-dependent. These data provide evidence to support the involvement of SPX1 and SPX2 in the Pi-sensing mechanism in plants. Significance Phosphate (Pi) is a primary nutrient for plant growth. Because of the low availability of soil Pi, the Pi starvation signaling in plants is gaining great interest. Arabidopsis AtPHR1 and its rice homologue OsPHR2 are known to be central transcription factors in Pi homeostasis; however, the mechanism of how plants sense external Pi fluctuation to regulate the activity of AtPHR1/OsPHR2 has been elusive. Here, we identify rice SPX1 and SPX2 as Pi-dependent inhibitors of PHR2, implicating SPX1 and SPX2 in the Pi-sensing mechanism. We also show that the SPX domain of SPX1 and SPX2 is critical for repressing PHR2 binding to cis elements by protein interaction. The discovery of cellular nutrient concentration-dependent fine-tuning sheds light on a novel mechanism of plant adaption to environmental cues.

A geographically and temporally weighted regression (GTWR) model is an effective tool for dealing with spatial heterogeneity and temporal non-stationarity simultaneously. As an important characteristic of spatiotemporal data, spatiotemporal autocorrelation should be considered when constructing spatiotemporally varying coefficient models. The proposed local autoregressive geographically and temporally weighted regression (GTWRLAR) model can simultaneously handle spatiotemporal autocorrelations among response variables and the spatiotemporal heterogeneity of regression relationships. The two-stage weighted least squares (2SLS) estimation can effectively reduce computational complexity. However, the weighted least squares estimation is essentially a Nadaraya–Watson kernel-smoothing approach for nonparametric regression models, and it suffers from a boundary effect. For spatiotemporally varying coefficient models, the three-dimensional spatiotemporal coefficients (longitude, latitude, and time) inherently exhibit larger boundaries than one-dimensional intervals. Therefore, the boundary effect of the 2SLS estimation of GTWRLAR will be more serious. A local–linear geographically and temporally weighted 2SLS (GTWRLAR-L) estimation is proposed to correct the boundary effect in both the spatial and temporal dimensions of GTWRLAR and simultaneously improve parameter estimation accuracy. The simulation experiment shows that the GTWRLAR-L method reduces the root mean square error (RMSE) of parameter estimates compared to the standard GTWRLAR approach. Empirical analyses of carbon emissions in China’s Yellow River Basin (2017–2021) show that GTWRLAR-L enhances the adjusted R2 from 0.888 to 0.893.

Three polyimides (PIs) were prepared from a diamine containing biphenyl ester group as a side chain and a corresponding dianhydride chosen from 1,2,3,4-cyclobutanetetracarboxylic dianhydride (PI-1), 4,4′-(hexafluoroisopropylidene) diphthalic anhydride (PI-2) or pyromellitic dianhydride (PI-3). Chemical structures of the resulting PIs were confirmed by Fourier transform infrared spectroscopy (FT-IR) and 1H NMR spectroscopy. While PI-3 was insoluble in any of organic solvents after the imidization process, PI-1 and PI-2 showed good solubility in polar aprotic solvents. Especially, PI-2 exhibited remarkable solubility even in chloroform and tetrahydrofuran. Liquid crystal (LC) alignment layers were prepared from these PIs by conventional rubbing processes, and subjected to fabricate LC cells for the characterization of alignment properties. In all cases, a uniform alignment was observed as confirmed by angle dependence polarizing microscopic technique. LC alignment directors of these polymer films were found to be perpendicular to the rubbing direction due to the perpendicularly attached biphenyl moiety to the main chain. LC pretilt angle and electro-optical properties of these LC cells were also investigated.

Two draft sequences of Gossypium hirsutum, the most widely cultivated cotton species, provide insights into genome structure, genome rearrangement, gene evolution and cotton fiber biology. Upland cotton is a model for polyploid crop domestication and transgenic improvement. Here we sequenced the allotetraploid Gossypium hirsutum L. acc. TM-1 genome by integrating whole-genome shotgun reads, bacterial artificial chromosome (BAC)-end sequences and genotype-by-sequencing genetic maps. We assembled and annotated 32,032 A-subgenome genes and 34,402 D-subgenome genes. Structural rearrangements, gene loss, disrupted genes and sequence divergence were more common in the A subgenome than in the D subgenome, suggesting asymmetric evolution. However, no genome-wide expression dominance was found between the subgenomes. Genomic signatures of selection and domestication are associated with positively selected genes (PSGs) for fiber improvement in the A subgenome and for stress tolerance in the D subgenome. This draft genome sequence provides a resource for engineering superior cotton lines.