HIV associated cell death: Peptide-induced apoptosis restricts viral transmission.

The human immunodeficiency virus (HIV) is still a global pandemic and despite the successful use of anti-retroviral therapy, a well-established cure remains to be identified. Viral modulation of cell death has a significant role in HIV pathogenesis. Here we sought to understand the major mechanisms of HIV- induced death of lymphocytes and the effects on viral transmission. Flow cytometry analysis of lymphocytes from five latent HIV-infected patients, and HIV IIIB-infected MT2 cells demonstrated both necrosis and apoptosis to be the major mechanisms of cell death in CD4+ and CD4-/CD8- lymphocytes. Significantly, pro-apoptotic tumor necrosis factor (TNF) peptide (P13) was found to inhibit HIV-related cell death and reduced viral transmission. Whereas pro-necrotic TNF peptide (P16) had little effect on HIV-related cell death and viral transmission. Understanding mechanisms by which cell death can be manipulated may provide additional drug targets to reduce the loss of CD4+ cells and the formation of a viral reservoir in HIV infection

Can Large Language Models Understand Real-World Complex Instructions?

Large language models (LLMs) can understand human instructions, showing their potential for pragmatic applications beyond traditional NLP tasks. However, they still struggle with complex instructions, which can be either complex task descriptions that require multiple tasks and constraints, or complex input that contains long context, noise, heterogeneous information and multi-turn format. Due to these features, LLMs often ignore semantic constraints from task descriptions, generate incorrect formats, violate length or sample count constraints, and be unfaithful to the input text. Existing benchmarks are insufficient to assess LLMs' ability to understand complex instructions, as they are close-ended and simple. To bridge this gap, we propose CELLO, a benchmark for evaluating LLMs' ability to follow complex instructions systematically. We design eight features for complex instructions and construct a comprehensive evaluation dataset from real-world scenarios. We also establish four criteria and develop corresponding metrics, as current ones are inadequate, biased or too strict and coarse-grained. We compare the performance of representative Chinese-oriented and English-oriented models in following complex instructions through extensive experiments. Resources of CELLO are publicly available at https://github.com/Abbey4799/CELLO

The Influence of Sky View Factor on Daytime and Nighttime Urban Land Surface Temperature in Different Spatial-Temporal Scales: A Case Study of Beijing

Urban building morphology has a significant impact on the urban thermal environment (UTE). The sky view factor (SVF) is an important structure index of buildings and combines height and density attributes. These factors have impact on the land surface temperature (LST). Thus, it is crucial to analyze the relationship between SVF and LST in different spatial-temporal scales. Therefore, we tried to use a building vector database to calculate the SVF, and we used remote sensing thermal infrared band to retrieve LST. Then, we analyzed the influence between SVF and LST in different spatial and temporal scales, and we analyzed the seasonal variation, day–night variation, and the impact of building height and density of the SVF–LST relationship. We selected the core built-up area of Beijing as the study area and analyzed the SVF–LST relationship in four periods in 2018. The temporal experimental results indicated that LST is higher in the obscured areas than in the open areas at nighttime. In winter, the maximum mean LST is in the open areas. The spatial experimental results indicate that the SVF and LST relationship is different in the low SVF region, with 30 m and 90 m pixel scale in the daytime. This may be the shadow cooling effect around the buildings. In addition, we discussed the effects of building height and shading on the SVF–LST relationship, and the experimental results show that the average shading ratio is the largest at 0.38 in the mid-rise building area in winter

Effect and mechanism of magnesium on osteogenic differentiation in porcine aortic valve interstitial cells

Objective To explore the effect of magnesium ion on osteogenic differentiation of porcine aortic valve interstitial cells (AVICs) and its potential mechanism. Methods Porcine AVICs were isolated from fresh pig aortic valve samples through two-step digestion combined with type Ⅱ collagen, and then cultured and identified with immunofluorescence staining and flow cytometry for cell phenotypes. The cells were randomly divided into blank control group (Blank Group), osteogenic induction medium group (OIM Group) and magnesium treatment group (1, 2 and 3 mmol/L MgSO4 solution for 7 d). The expression of osteogenic differentiation markers, osteopontin (OPN) and Runt-related transcription factor 2 (RUNX2) were detected by Western blotting. Alizarin red staining was adopted to observe calcium deposition in the cells of each group. Subsequently, the changes in PI3K/Akt and MAPK/ERK1/2 signaling pathways were measured by Western blotting. Results Our obtained porcine AVICs had high expression of Vimentin, low expression of α-SMA, and no expression of CD31, with an ideal purity of porcine AVICs for subsequent experiments. Western blotting showed that the expression of osteogenic markers OPN and RUNX2 was significantly higher in the OIM Group than the Blank Group (P < 0.01), and these effects induced by OIM were obviously inhibited with 3 mmol/L magnesium treatment (P < 0.01). Alizarin red staining displayed that calcium salt deposition was remarkably increased in the OIM Group than the Blank Group, and this increment was inhibited after magnesium treatment. The results of Western blotting indicated that magnesium treatment resulted in decreased phosphorylation of PI3K/AKT and MAPK/ERK1/2 induced by OIM (P < 0.01). Conclusion Magnesium may partially inhibit the osteogenic differentiation of porcine AVICs induced by OIM in vitro through PI3K/AKT and MAPK/ERK1/2 signaling pathways

Monitoring Spatial Patterns and Changes of Ecology, Production, and Living Land in Chinese Urban Agglomerations: 35 Years after Reform and Opening Up, Where, How and Why?

Chinese urban agglomeration (UA) has gradually become a new world economic center and the strategic region of the “The Belt and Road Initiatives”. The spatial patterns and variations of ecology–production–living land (EPL) profoundly affect UA’s development and its ecological environment. Unfortunately, scientific understanding about the trajectories, patterns and drivers of EPL changes in Chinese urban agglomerations (UAs) since reform and opening up is still very limited. The aim of this paper was to monitor those characteristics during the last 35 years. Here, we proposed a new classification system of EPL, including ecology land (EL), industrial production land (IPL), agricultural production land (APL), urban living land (ULL) and rural living land (RLL) due to Chinese urban–rural dual structure. Then, we extracted EPL land from the Chinese LUCC product, which is the recently released remote sensing data product of high resolution spatial land use data in China at national level. Furthermore, we analyzed the spatial-temporal trajectories and driving factors of EPL for Chinese UAs during 1980–2015. The results showed that: (1) ULL and IPL in Chinese UAs were increased rapidly, while EL and APL were seriously decreased. (2) The growth patterns of ULL and IPL had shown a spatial heterogeneity. As to different regional UAs, the expansion rates of ULL and IPL ranked from high to low were as follows: eastern, central, western, and northeastern UAs. (3) National policies, population, and economy dominated the spatial-temporal changes of EPL in Chinese UAs. (4) The multi-planning integration in the structure of land use should be strengthened at UA-scale

A DC vaccine and its preparation method and applications: CN103495157B

DC vaccine and its preparation method and applications of the present invention relates to a gastric cancer or breast cancer, according to the amino acid sequence of a tumor antigen construct a recombinant fusion protein of overlapping peptides, polypeptides from a series of overlapping peptide fusion protein composed of 15 amino acids, two adjacent there are 11 amino acid polypeptide is the same complete overlap between the overlapping peptides connected by the same enzyme sites li-key, the overlapping peptide fusion recombinant protein gene by restriction sites NdeI and BamH subcloned into pET28 vector, recombinant overlapping peptide fusion protein was purified by the E. coli expressed, in vitro human blood isolated from PBMC with GM-CSF and recombinant fusion proteins were co-cultured overlapping peptides, recombinant peptides overlapping by the fusion protein and then the DC endocytosis, intracellular generating digested a series of overlapping peptides uncertain phenotype containing CTL and / or Th phenotype of MHC bind to DC? I and MHC? II molecules of the DC maturation, DC vaccine obtained according to the present invention with the DC in vitro method for stimulating the synthesis of each peptide compared to DC to stimulate fast and low cost-effectiveness

Integrating Aerial LiDAR and Very-High-Resolution Images for Urban Functional Zone Mapping

This study presents a new approach for Urban Functional Zone (UFZ) mapping by integrating two-dimensional (2D) Urban Structure Parameters (USPs), three-dimensional (3D) USPs, and the spatial patterns of land covers, which can be divided into two steps. Firstly, we extracted various features, i.e., spectral, textural, geometrical features, and 3D USPs from very-high-resolution (VHR) images and light detection and ranging (LiDAR) point clouds. In addition, the multi-classifiers (MLCs), i.e., Random Forest, K-Nearest Neighbor, and Linear Discriminant Analysis classifiers were used to perform the land cover mapping by using the optimized features. Secondly, based on the land cover classification results, we extracted 2D and 3D USPs for different land covers and used MLCs to classify UFZs. Results for the northern part of Brooklyn, New York, USA, show that the approach yielded an excellent accuracy of UFZ mapping with an overall accuracy of 91.9%. Moreover, we have demonstrated that 3D USPs could considerably improve the classification accuracies of UFZs and land covers by 6.4% and 3.0%, respectively

Monitoring changes in the impervious surfaces of urban functional zones using multisource remote sensing data: a case study of Tianjin, China

Previous research on urban impervious surface monitoring has ignored the differences, spatial patterns, and driving factors of impervious surfaces among the various functional zones in cities. In this paper, we extracted the impervious surface coverage of Tianjin in 1990, 1995, 2000, 2005, 2010, and 2015 based on the Classification and Regression Tree model. Then, using the methods of quantitative geography, we systematically analyzed the spatiotemporal variations of impervious surface coverage among the functional zones in Tianjin from 1990 to 2015. Additionally, the driving mechanisms of impervious surface growths among different functional zones were investigated. The results showed that (1) the growth of impervious surfaces shows two spatially separate core areas of growth. The core functional zone (CFZ) had the highest impervious surface coverage, and the ecological conservation zone (ECZ) had the lowest impervious surface coverage. (2) High-high aggregation regions of impervious surface coverage were mainly located in CFZ, while low-low aggregation regions of impervious surface coverage area were mainly located in ECZ. (3) Influences of social-economic factors on area growths of impervious surface are stronger in urban function expanded zone, coastal city key development zone, Beijing–Tianjin coordinated development zone, and urban-rural coordinated development zone than those in CFZ. Our results can provide a point of reference for decision-making regarding urban planning management