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The Chinese urban regeneration movement underscores a "people-oriented" paradigm, aimed at addressing urban challenges stemming from rapid prior urbanization, while striving for high-quality and sustainable urban development. At the community level, fostering quality through a socially sustainable perspective (SSP) is a pivotal strategy for people-oriented urban regeneration. Nonetheless, explorations of community quality assessments grounded in an SSP have been notably scarce in recent scholarly discourse. This study pioneers a multidimensional quantitative model (MQM) for gauging community quality, leveraging diverse geospatial data sources from the SSP framework. The MQM introduces an evaluative framework with "Patency, Convenience, Comfort, and Safety" as primary indicators, integrating multi-sourced data encompassing the area of interest (AOI), Point of Interest (POI), Weibo check-ins, and Dianping data. The model's efficacy is demonstrated through a case study in the Gusu district, Suzhou. Furthermore, semantic analysis of the Gusu district's street view photos validates the MQM results. Our findings reveal the following: (1) AI-based semantic analysis accurately verifies the validity of MQM-generated community quality measurements, establishing its robust applicability with multi-sourced geospatial data; (2) the community quality distribution in Gusu district is notably correlated with the urban fabric, exhibiting lower quality within the ancient town area and higher quality outside it; and (3) communities of varying quality coexist spatially, with high- and low-quality communities overlapping in the same regions. This research pioneers a systematic, holistic methodology for quantitatively measuring community quality, laying the groundwork for informed urban regeneration policies, planning, and place making. The MQM, fortified by multi-sourced geospatial data and AI-based semantic analysis, offers a rigorous foundation for assessing community quality, thereby guiding socially sustainable regeneration initiatives and decision making at the community scale. [ABSTRACT FROM AUTHOR]

Simple Summary: Muscle growth is essential for the economic sustainability of the swine industry. Gaining a deeper understanding of pig muscle development is crucial for improving both the quantity and quality of pork production. This study employed RNA-seq technology to conduct a transcriptomic analysis of the longissimus dorsi muscle (LD) in three different pig breeds with varying body sizes and growth rates: Tibetan pigs (TP), Wujin pigs (WJ), and large white pigs (LW). Significant differences in gene expression were observed among the different breeds. We identified that myosin light chain 4 (MYL4) plays a role in influencing muscle growth. Experimental validation confirmed that MYL4 promotes skeletal muscle cell proliferation and inhibits degradation. These findings reveal the molecular mechanisms that control muscle growth and provide valuable insights for improving pig breeding practices, ultimately enhancing the efficiency and quality of meat production. Muscle growth stands as a pivotal economic trait within pig production, governed by a complex interplay of multiple genes, each playing a role in its quantitative manifestation. Understanding the intricate regulatory mechanisms of porcine muscle development is crucial for enhancing both pork yield and quality. This study used the GSE99749 dataset downloaded from the GEO database, conducting a detailed analysis of the RNA-seq results from the longissimus dorsi muscle (LD) of Tibetan pigs (TP), Wujin pigs (WJ) and large white pigs (LW) at 60 days of gestation, representing diverse body sizes and growth rates. Comparative analyses between TPvsWJ and TPvsLW, along with differential gene expression (DEG) analysis, functional enrichment analysis, and protein–protein interaction (PPI) network analysis, revealed 1048 and 1157 significantly differentially expressed genes (p < 0.001) in TPvsWJ and TPvsLW, respectively. With stricter screening criteria, 37 DEGs were found to overlap between the 2 groups. PPI analysis identified MYL5, MYL4, and ACTC1 as the three core genes. This article focuses on exploring the MYL4 gene. Molecular-level experimental validation, through overexpression and interference of the MYL4 gene combined with EDU staining experiments, demonstrated that overexpression of MYL4 significantly promoted the proliferation of porcine skeletal muscle satellite cells (PSMSC), while interference with MYL4 inhibited their proliferation. Furthermore, by examining the effects of overexpressing and interfering with the MYL4 gene on the muscle hypertrophy marker Fst gene and the muscle degradation marker FOXO3 gene, the pivotal role of the MYL4 gene in promoting muscle growth and preventing muscle degradation was further confirmed. These findings offer a new perspective on the molecular mechanisms behind porcine muscle growth and development, furnishing valuable data and insights for muscle biology research. [ABSTRACT FROM AUTHOR]

Aims Huanglongbing (citrus greening) is a plant disease putatively caused by the unculturable Gram-negative bacterium Candidatus Liberibacter asiaticus (CLas), and it has caused severe damage to citrus plantations worldwide. There are no definitive treatments for this disease, and conventional disease control techniques have shown limited efficacy. This work presents an in silico evaluation of using specifically targeting anti-microbial peptides (STAMPs) consisting of a targeting segment and an antimicrobial segment to inhibit citrus greening by inhibiting the BamA protein of CLas, which is an outer membrane protein crucial for bacterial viability. Methods and results Initially, a set of peptides with a high affinity toward BamA protein were screened and evaluated via molecular docking and molecular dynamics simulations and were verified in vitro via bio-layer interferometry (BLI). In silico studies and BLI experiments indicated that two peptides, HASP2 and HASP3, showed stable binding to BamA. Protein structures for STAMPs were created by fusing known anti-microbial peptides (AMPs) with the selected short peptides. The binding of STAMPs to BamA was assessed using molecular docking and binding energy calculations. The attachment of high-affinity short peptides significantly reduced the free energy of binding for AMPs, suggesting that it would make it easier for the STAMPs to bind to BamA. Efficacy testing in vitro using a closely related CLas surrogate bacterium showed that STAMPs had greater inhibitory activity than AMP alone. Conclusions In silico and in vitro results indicate that the STAMPs can inhibit CLas surrogate Rhizobium grahamii more effectively compared to AMPs, suggesting that STAMPs can achieve better inhibition of CLas, potentially via enhancing the site specificity of AMPs. [ABSTRACT FROM AUTHOR]

Accelerated urbanization has led to regional disruptions and exacerbated imbalances in spatial quality, social cohesion, and inequalities. Urban regeneration, as a mitigating strategy for these disruptions, faces significant social challenges, particularly at the community scale. This study addresses the existing research gap by comprehensively reviewing community regeneration (CR) from a socially sustainable perspective (SSP). Utilizing VOSviewer software, we synthesize and categorize relevant research trends and methods spanning from 2006 to 2023, retrieving 213 coded articles among 5002 relevant documents from Web of Science bibliometric datasets. The study explores the implementation trajectory of CR, considering novel scenario demands, emerging technologies, and new development paradigms and approaches. It delves into human-centric approaches to enhance the quality of life, precision, and diversification of community engagement and cultivate a sense of community equity and belonging. Moreover, the findings highlight densification as a synergistic and adaptive strategy for current regeneration actions. This scientometric review leverages new tools and innovative approaches for regeneration policy and planning decision-making, ultimately contributing to the improvement of livability. The study provides valuable insights into the challenges and opportunities associated with socially sustainable CR, offering a foundation for future research, and guiding practical urban planning and design interventions. [ABSTRACT FROM AUTHOR]

Aerosol pH is commonly used to characterize the acidity of aqueous aerosols and is of significant scientific interest due to its close relationship with atmospheric processes. Estimation of ambient aerosol pH usually relies on the thermodynamic modeling approach. In the existing chemical transport model and field observation studies, the temporal resolution of the input chemical and meteorological data into thermodynamic models varied substantially ranging from less than an hour to a year because of the inconsistency in the resolution of the original data and the aggregation of time-series data in some studies. Furthermore, the average value of aerosol pH has been represented by diverse metrics of central tendency in existing studies. This study attempts to evaluate the potential discrepancies in the calculated average aerosol pH arising from differences in both averaging metrics and temporal resolutions based on the ISORROPIA-II thermodynamic model and the example datasets prepared by the GEOS-Chem chemical transport model simulation. Overall, we find that the variation in the temporal resolutions of input data may lead to a change of up to more than two units in the average pH, and that the averaging metrics calculated based on the pH value of individual samples may be about two units higher than the averaging metrics calculated based on the activity of hydrogen ions. Accordingly, we recommend that the chosen averaging metrics and temporal resolutions should be stated clearly in future studies to ensure comparability of the average aerosol pH between models and/or observations. [ABSTRACT FROM AUTHOR]