The Impact of Atmospheric Cadmium Exposure on Colon Cancer and the Invasiveness of Intestinal Stents in the Cancerous Colon.

BACKGROUND: Inhalation exposure to carcinogenic metals such as cadmium (Cd) is a significant global health concern linked to various cancers. However, the precise carcinogenic mechanism underlying inhalation exposure remains elusive. METHODS: In this study, CT26 mouse colon cancer (CC) cells were implanted into BALB/c mice to establish CC mouse models. Some of the CC mice were implanted with intestinal stents. The mice were exposed to atomized oxygen and nitrogen (O2/N2) gas containing Cd. RESULTS: Atmospheric Cd intensified inflammation in CC cells and heightened Nicotinamide Adenine Dinucleotide Phosphate (NADPH) Oxidase 1 (NOX1) activity, which is an indirect measurement of increased reactive oxygen species (ROS) production. This escalated ROS production triggered abnormal Wnt protein secretion, activated the Wnt/ß-catenin signaling pathway, and stimulated CC cell proliferation. No discernible body weight effect was seen in the CC mice, possibly due to the later-stage tumor weight gain, which masked the changes in body weight. Cd facilitated colon tumor restructuring and cell migration at the later stage. The implantation of intestinal stents inhibited the expression of Superoxide Dismutase 1 (SOD1) in the colon tumors of the CC mice, with no evident effects on the expression levels of NOX1, SOD2, and Catalase (CAT) enzymes. Elevated ROS levels, indirectly reflected by enzyme activity, did not substantially impact the Wnt/ß-catenin signaling pathway and even contributed to slowing its imbalance. Stent implantation eased the inflammation occurring in colon tumors by reducing CC cell proliferation but it induced discomfort in the mice, leading to a reduction in food intake and weight. CONCLUSIONS: Cd partially fosters CC tumorigenesis via the ROS-mediated Wnt/ß-catenin signaling pathway. The effect of Cd on the invasive effect of intestinal stents in the cancerous colon is not significant.

Insights into the mechanism of transcription factors in Pb2+-induced apoptosis.

The health risks associated with exposure to heavy metals, such as Pb2+, are increasingly concerning the public. Pb2+ can cause significant harm to the human body through oxidative stress, autophagy, inflammation, and DNA damage, disrupting cellular homeostasis and ultimately leading to cell death. Among these mechanisms, apoptosis is considered crucial. It has been confirmed that transcription factors play a central role as mediators during the apoptosis process. Interestingly, these transcription factors have different effects on apoptosis depending on the concentration and duration of Pb2+ exposure. In this article, we systematically summarize the significant roles of several transcription factors in Pb2+-induced apoptosis. This information provides insights into therapeutic strategies and prognostic biomarkers for diseases related to Pb2+ exposure.

Effect of N2 and CO2 on the Explosion Properties of High Equivalence Ratios of Hydrogen.

The explosion characteristics of premixed gases under different equivalence ratios (1.0-3.0) and inert gas addition (5-20%) are experimentally investigated, and sensitivity analysis of the radical reactions is carried out using the USC Mech II model to analyze the molar fraction of radicals. The results show that at high equivalence ratios, inert gas has little effect on flame stability. The addition of an inert gas reduces the tensile rate in the early stage of flame growth. At high equivalence ratios, CO2 inhibits explosive flame propagation twice as effectively as N2. Due to the large heat capacity and chemical kinetic effects, CO2 has a stronger inhibitory effect on the explosion pressure than N2, and the inhibition efficiency on the explosion strength is nearly twice that high. To further analyze the effect of different inert gas addition ratios on chemical kinetics, sensitivity analysis, and molar fraction simulations were performed. The thermal and chemical kinetic effects of CO2 cause later generation of H and OH radicals and the partial chain reaction involving CO2 causes a lower peak of H radicals than the peak of H radicals generated under an N2 atmosphere. However, CO2 is a direct reactant and the third body to produce a small chemical kinetic effect.

Evaluating vehicular exhaust and evaporative emissions via VOC measurement in an underground parking garage.

Vehicular emissions, including both tailpipe exhaust and evaporative emissions, are major anthropogenic sources of volatile organic compounds (VOCs) in urban cities. Current knowledge on vehicle tailpipe and evaporative emissions was mainly obtained via laboratory tests on very few vehicles under experimental conditions. Information on fleet gasoline vehicles emission features under real-world conditions is lacking. Here, VOC measurement was conducted in a large residential underground parking garage in Tianjin, China, to reveal the feature of the exhaust and evaporative emissions from real-world gasoline vehicle fleets. The VOC concentration in the parking garage was on average 362.7 ± 87.7 µg m-3, significantly higher than that in the ambient atmosphere at the same period (63.2 µg m-3). Aromatics and alkanes were the mainly contributors on both weekdays and weekends. A positive correlation between VOCs and traffic flow was observed, especially in the daytime. Source apportionment through the positive matrix factorization model (PMF) revealed that the tailpipe and evaporative emissions accounted for 43.2% and 33.7% of VOCs, respectively. Evaporative emission contributed 69.3% to the VOCs at night due to diurnal breathing loss from numerous parked cars. In contrast, tailpipe emission was most remarkable during morning rush hours. Based on the PMF results, we reconstructed a vehicle-related VOCs profile representing the combination of the tailpipe exhaust and evaporative emission from fleet-average gasoline vehicles, which could benefit future source apportionment studies.

Dark2Light: multi-stage progressive learning model for low-light image enhancement.

Due to severe noise and extremely low illuminance, restoring from low-light images to normal-light images remains challenging. Unpredictable noise can tangle the weak signals, making it difficult for models to learn signals from low-light images, while simply restoring the illumination can lead to noise amplification. To address this dilemma, we propose a multi-stage model that can progressively restore normal-light images from low-light images, namely Dark2Light. Within each stage, We divide the low-light image enhancement (LLIE) into two main problems: (1) illumination enhancement and (2) noise removal. Firstly, we convert the image space from sRGB to linear RGB to ensure that illumination enhancement is approximately linear, and design a contextual transformer block to conduct illumination enhancement in a coarse-to-fine manner. Secondly, a U-Net shaped denoising block is adopted for noise removal. Lastly, we design a dual-supervised attention block to facilitate progressive restoration and feature transfer. Extensive experimental results demonstrate that the proposed Dark2Light outperforms the state-of-the-art LLIE methods both quantitatively and qualitatively.

Somatic variant analysis suite: copy number variation clonal visualization online platform for large-scale single-cell genomics.

The recent advance of single-cell copy number variation (CNV) analysis plays an essential role in addressing intratumor heterogeneity, identifying tumor subgroups and restoring tumor-evolving trajectories at single-cell scale. Informative visualization of copy number analysis results boosts productive scientific exploration, validation and sharing. Several single-cell analysis figures have the effectiveness of visualizations for understanding single-cell genomics in published articles and software packages. However, they almost lack real-time interaction, and it is hard to reproduce them. Moreover, existing tools are time-consuming and memory-intensive when they reach large-scale single-cell throughputs. We present an online visualization platform, single-cell Somatic Variant Analysis Suite (scSVAS), for real-time interactive single-cell genomics data visualization. scSVAS is specifically designed for large-scale single-cell genomic analysis that provides an arsenal of unique functionalities. After uploading the specified input files, scSVAS deploys the online interactive visualization automatically. Users may conduct scientific discoveries, share interactive visualizations and download high-quality publication-ready figures. scSVAS provides versatile utilities for managing, investigating, sharing and publishing single-cell CNV profiles. We envision this online platform will expedite the biological understanding of cancer clonal evolution in single-cell resolution. All visualizations are publicly hosted at https://sc.deepomics.org.

SCYN: single cell CNV profiling method using dynamic programming.

BACKGROUND: Copy number variation is crucial in deciphering the mechanism and cure of complex disorders and cancers. The recent advancement of scDNA sequencing technology sheds light upon addressing intratumor heterogeneity, detecting rare subclones, and reconstructing tumor evolution lineages at single-cell resolution. Nevertheless, the current circular binary segmentation based approach proves to fail to efficiently and effectively identify copy number shifts on some exceptional trails. RESULTS: Here, we propose SCYN, a CNV segmentation method powered with dynamic programming. SCYN resolves the precise segmentation on in silico dataset. Then we verified SCYN manifested accurate copy number inferring on triple negative breast cancer scDNA data, with array comparative genomic hybridization results of purified bulk samples as ground truth validation. We tested SCYN on two datasets of the newly emerged 10x Genomics CNV solution. SCYN successfully recognizes gastric cancer cells from 1% and 10% spike-ins 10x datasets. Moreover, SCYN is about 150 times faster than state of the art tool when dealing with the datasets of approximately 2000 cells. CONCLUSIONS: SCYN robustly and efficiently detects segmentations and infers copy number profiles on single cell DNA sequencing data. It serves to reveal the tumor intra-heterogeneity. The source code of SCYN can be accessed in https://github.com/xikanfeng2/SCYN .

Landscape change patterns at three stages of the construction and operation of the TGP.

Analyses of landscape change patterns that are based on elevation and slope can not only provide reasonable interpretations of landscape patterns but can also help to reveal evolutionary laws. However, landscape change patterns and their model in different landforms of the typical watershed in the Three Gorges Reservoir Area (TGRA) has not been quantified and assessed effectively. As a complex geographical unit, the ecological environment in the middle reach of the Yangtze River has experienced great changes due to the construction of the Three Gorges Project (TGP) and its associated human activities. Here, based mainly on a digital elevation model (DEM) and remotely sensed images from 1986, 2000, 2010, and 2017 and by using GIS technology, speeds/ trends of landscape change, the index of landscape type change intensity, landscape pattern indices, and landscape ecological security index, the spatial and temporal evolution characteristics of different elevations, slopes, and buffer landscape types were analyzed in typical watersheds, as well as an evolutionary model of the landscape pattern. The results indicated that (1) the landscape types along with the land classification and buffer zone that were influenced by the TGR construction have undergone a phased change, with the period 2000-2010 being the most dramatic period of landscape evolution during the impoundment period; (2) landscape type shifts from human-dominated farmland to nature-driven forestland and shrub-land as elevations, slopes and buffer distances increased. The landscape has shifted from diversity to relative homogeneity; (3) land types and buffer zones played essential roles in the landscape pattern index, which is reflected in the differences in landscape type indices for spatial extension and temporal characteristics. The results of this paper illustrate the spatial-temporal characteristics of various landscape types at three distinct stages in the construction of the TGR. These findings indicate that the landscape ecological security of the watershed is improving year by year. The follow-up development of the TGRA needs to consider the landscape change patterns of different landforms.

Effect of Inert Gas CO2 on Deflagration Pressure of CH4/CO.

To study the effect of CO2 on the explosion characteristics of CH4/CO, the explosion experiments of the effect of different volume fractions of CO2 on CH4/CO deflagration were carried out by using the self-developed pipeline gas explosion experimental platform. The explosion characteristics of premixed gas are studied from the aspects of explosion peak pressure and time of reaching the peak pressure. The results show that the effect of CO on the deflagration of methane with a different volume fraction is the result of the interaction of the elementary reaction and the oxygen content in the reaction system. Two percent of the CO promoted the methane explosion in the oxygen-rich state, while it showed a damping effect in the oxygen-poor state. CO2 has different inhibitory effects on different volume fractions of methane. Experiments show that the addition of 20% CO2 can effectively inhibit the deflagration of methane. The addition of CO2 has a stronger inhibitory effect on the mixed gas of CH4/CO under the condition of poor oxygen but less on the mixed gas under the condition of rich oxygen.