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The incorporation of physical environmental performance as a primary consideration in building design can facilitate the harmonization of the built environment with the surrounding site and climate, enhance the building's environmental adaptability and environmental friendliness, and contribute to the achievement of energy-saving and emission-reduction objectives through the integration of natural lighting and ventilation. General computational fluid dynamics (CFD) can help architects make accurate predictions and effectively control the building's wind environment. However, CFD integration into the design workflow in the preliminary stages is frequently challenging due to program uncertainty, intricate parameter settings, and substantial computational expenses. This study offers a methodology and framework based on machine learning to overcome the complexity and computational cost barriers in simulating outdoor wind environments of buildings. In this framework, the machine learning model is trained using an automated CFD simulation system based on Butterfly and implemented within the Rhino and Grasshopper environment. This framework provides real-time simulation feedback within the design software and exhibits promising accuracy, with a Structural Similarity Index Measure (SSIM) ranging from 90–97% on a training dataset of 1200 unique urban geometries in Xinjiekou Area of Nanjing, China. Furthermore, we programmatically integrate various parts of the simulation and computation process to automate multiscenario CFD simulations and computations. This automation saves a significant amount of time in producing machine-learning training sets. Finally, we demonstrate the effectiveness and accuracy of the proposed working framework in the design process through a case study. Although our approach cannot replace CFD simulation computation in the later design stages, it can support architects in making design decisions in the preliminary stages with minimal effort and immediate performance feedback. [ABSTRACT FROM AUTHOR]

Based on five periods of Landsat remote sensing data from 1980 to 2020, this study constructs a landscape ecological risk-ecosystem service value evaluation model and integrates it with a geodetector model to analyse the environmental benefits of the development of the "production–living–ecological space" pattern and its driving factors in the Xuzhou planning area. The results of the study are as follows: (1) Over the past 40 years, the expansion of living spaces has significantly encroached upon adjacent agricultural production areas and ecological spaces, such as forests and grasslands. Specifically, the areas of agricultural land, forests, and grassland have been diminished by 277.39 km2, 23.8 km2 and 12.93 km2, respectively; in contrast, urban and rural living spaces have increased by 238.62 km2 and 58.92 km2, alongside a rise in industrial production areas, water bodies, and other ecological spaces. (2) Throughout the 40-year period, both the landscape ecological risk (ERI) and ecosystem service value (ESV) in the study area have shown a decreasing trend. The proportion of high- and medium-high-risk areas of the ERI have decreased by 5.19% and 7.50%, respectively, while low, lower, and medium ecological risk areas have increased by 6.40%, 3.22% and 3.07%, respectively. In addition, low-ESV areas have increased by 14.22%, while the proportion of high- and medium-high-ESV areas have decreased by 1.16%. (3) There is a significant positive spatial correlation between the ERI and ESV. Regions with dense ecological spaces comprising forests, water bodies, and grasslands, particularly in the northeastern part of the Jiawang District and the southeastern part of the Tongshan District, demonstrate superior regional ecosystem service quality. The ERI and ESV are dominated by "high–high" and "low–high" aggregation. Conversely, in the southwestern part of the study area, the expansion of living space has led to the transformation of some agricultural land, forest land, and grassland into less risky construction land, resulting in a decline in the quality of regional ecosystem services. The local spatial correlation between the ERI and ESV changed from "high–high", "low–low", "low–high" agglomeration to "low–low" agglomeration. (4) Key factors influencing the spatial differentiation of the "production–living–ecological space" include the GDP, population density, soil type, and the distance to towns and roads. Among these, the interaction between population density and soil type has the most significant effect on the changes in the pattern of the "production–living–ecological space". [ABSTRACT FROM AUTHOR]

Abstract Background The tumor suppressor gene CDKN2A generates at least three different transcriptional variants, each of which is thought to encode a tumor suppressor. However, the inhibitory activities of these variants have not yet been compared in the same cells. Protein therapy is known to have several advantages over gene therapy. Thus, investigation of the exogenous protein molecule of the most effective suppressor may yield meaningful information regarding protein-based cancer therapy. Methods The inhibitory effects of p16INK4a, p14ARF and p12 were studied in the human lung cancer cell line A549 which lacks the CDKN2A locus. The eukaryotic expression plasmids of the three transcriptional variants were constructed and stably transfected into the cells. RNA and protein expression by the plasmids was confirmed using RT-PCR and fluorescence immunocytochemistry, respectively. Cell growth inhibition and cell-cycle redistribution after transfection were investigated based on growth curve and flow cytometry analyses. An exogenous His-tag fusion p16INK4a protein was obtained and purified by affinity chromatography. Cell growth inhibition and cell cycle arrest induced by the expression of p16INK4a protein were measured in A549 cells transduced with the exogenous protein. Results While all three variants suppressed cell growth, p16INK4a had the strongest effect. Marked G1-phase accumulation and S-phase inhibition were induced by p16INK4a and p14ARF but not by p12. Exogenous p16INK4a protein was successfully expressed and purified and transduction of the fusion protein into A549 cells inhibited cell growth by G1→S arrest. Conclusions Among the three transcript variants, p16INK4a has a greater inhibitory effect than p14ARF and p12; exogenous p16INK4a protein should be further investigated for use in cancer therapy as a protein agent.

SOD2 (superoxide dismutase 2) is one of the endogenous antioxidant enzymes that protect against reactive oxygen species. While explorations of SOD2 expression regulation are mainly focused on transcriptional and post-translational activation, there are few reports about the post-transcriptional regulation of SOD2. MicroRNAs (miRNAs) are 21nt-25nt (nucleotide) small noncoding RNAs that have emerged as indispensable regulators of gene expression. Here we show that miR-146a, a widely expressed miRNA, is up-regulated by H2O2-induced stress. By sequence analysis we found a binding site for miR-146a in the sod2 mRNA 3′UTR, and a luciferase reporter assay confirmed that miR-146a can interact with this sod2 regulatory region. Our results further show that miR-146a could down-regulate the SOD2 protein expression, and antisense-miR-146a could reverse the decrease of both the SOD2 level and cell viability in H2O2 treated PC12 cells. In conclusion, here we have identified a novel function of miR-146a in the post-transcriptional regulation of SOD2 expression. [ABSTRACT FROM AUTHOR]

The circadian clock controls the physiological functions of many tissues including the liver via an autoregulatory transcriptional-translational feedback loop, of which CLOCK is a core positive component. In addition, many studies have indicated that microRNAs (miRNAs) regulate liver function. However, how CLOCK-regulated miRNAs are linked to liver function remains largely unknown. In this study, miRNAs expression profiles were performed in the liver of Clock Δ19 mutant mice. Compared to wild type mice, totals of 61 and 57 putative CLOCK-regulated miRNAs were differentially expressed (fold change absolute value ≥2) at zeitgeber time 2 and zeitgeber time 14, respectively. According to the pathway analyses, the target genes of differentially expressed miRNAs were mainly involved in pathways in cancer, the PI3K-Akt signaling pathway and the MAPK signaling pathway. Protein-protein interaction analyses revealed that the hub genes were primarily associated with pathway in cancer and circadian rhythms. Expression validation showed that while the expression levels of miR-195 and miR-340 were up-regulated, the rhythms of these two miRNAs were always maintained. The expression level of nr1d2 mRNA was down-regulated. We identified a number of prospective CLOCK-regulated miRNAs that play roles in the various physiological processes of the liver, providing a reference to better understanding the potential regulatory mechanisms in the liver., Competing Interests: The authors declare that they have no competing interests., (© 2019 Wang et al.)

Circadian locomotor output cycles kaput protein (CLOCK) is a core transcription factor of complex integrated feedback loops in mammalian circadian clock. More genes have been reported to be regulated by CLOCK, however little is known about the role of CLOCK-mediated miRNAs. To dissect this, we used microarray analysis to measure miRNAs expression in suprachiasmatic nuclei (SCN) of wild-type (WT) and Clock Δ19 mutant mice at two different time points. We found that miRNAs regulation in two time points was extensive (nearly 75% of the miRNAs expressed at each time point), and very little overlap, with only six miRNAs in common. Besides this, the predicted CLOCK regulated miRNAs at two time points participated in extremely diverse pathways. We validated nine miRNAs (miR-125a-3p, miR-144, miR-199a-5p, miR-199b*, miR-200a, miR-200b, miR-203, miR-449a, and miR-96), which were involved in the same signaling pathway-hippo signaling pathway. The rhythms of these miRNAs showed a broad distribution of phase, amplitude, and waveform in Clock mutation. And further analysis indicated that there may be three models of miRNA-mediated circadian rhythms and hippo signaling pathway. MiRNA, the small player, may play a hub role in connecting circadian rhythms and other pathways via its multiple target genes networks., (© 2018 The Author(s).)