Copy number and gene expression differences between African American and Caucasian American prostate cancer

<p>Abstract</p> <p>Background</p> <p>The goal of our study was to investigate the molecular underpinnings associated with the relatively aggressive clinical behavior of prostate cancer (PCa) in African American (AA) compared to Caucasian American (CA) patients using a genome-wide approach.</p> <p>Methods</p> <p>AA and CA patients treated with radical prostatectomy (RP) were frequency matched for age at RP, Gleason grade, and tumor stage. Array-CGH (BAC SpectralChip2600) was used to identify genomic regions with significantly different DNA copy number between the groups. Gene expression profiling of the same set of tumors was also evaluated using Affymetrix HG-U133 Plus 2.0 arrays. Concordance between copy number alteration and gene expression was examined. A second aCGH analysis was performed in a larger validation cohort using an oligo-based platform (Agilent 244K).</p> <p>Results</p> <p>BAC-based array identified 27 chromosomal regions with significantly different copy number changes between the AA and CA tumors in the first cohort (Fisher's exact test, P < 0.05). Copy number alterations in these 27 regions were also significantly associated with gene expression changes. aCGH performed in a larger, independent cohort of AA and CA tumors validated 4 of the 27 (15%) most significantly altered regions from the initial analysis (3q26, 5p15-p14, 14q32, and 16p11). Functional annotation of overlapping genes within the 4 validated regions of AA/CA DNA copy number changes revealed significant enrichment of genes related to immune response.</p> <p>Conclusions</p> <p>Our data reveal molecular alterations at the level of gene expression and DNA copy number that are specific to African American and Caucasian prostate cancer and may be related to underlying differences in immune response.</p

Comparison of machine learning and deep learning models for evaluating suitable areas for premium teas in Yunnan, China.

BackgroundTea is an important economic crop in Yunnan, and the market price of premium teas such as Lao Banzhang is significantly higher than ordinary teas. For planting lands to promote, the tea industry to develop and minority lands' economies to prosper, it is vital to evaluate and analyze suitable areas for premium tea cultivation.MethodsClimate, terrain, soil, and green cropping system in the premium tea planting areas were used as evaluation variables. The suitability of six machine learning models for predicting suitable areas of premium teas were evaluated.ResultFA+ResNet demonstrated the best performance with an accuracy score of 0.94 and a macro-F1 score of 0.93. The suitable areas of premium teas were mainly located in the southern catchment of LancangJiang River, south-central part of Dehong, a few areas in the mid-west of Lincang, central scattered areas of Pu'er, most of the southern western part of Xishuangbanna and the southern edge of Honghe. Annual mean temperature, annual mean precipitation, mist belt, annual mean relative humidity, soil type and elevation were the key components in evaluating the suitable areas of premium teas in Yunnan

A Multilayered and Multifactorial Health Assessment Method for Launch Vehicle Engine under Vibration Conditions

Sixty percent of the failures of launch vehicles in the ascending phase occur in the propulsion system. Among them, the vibration generated by the engine is an important factor in the occurrence of failure. At present, health assessment methods in the aerospace field are mostly for specific equipment, and scholars mostly assess the real-time health status of launch vehicle engines which can only reflect the current health status of the launch vehicle. Existing methods cannot be applied to different equipment, and there is a lack of research on health assessments of fuzzy and complex mechanical systems. In this article, we propose a multi-layer and multi-factor predictive evaluation method for a fuzzy and complex system and conduct experiments on real vibration data of rockets. First, we divide the health assessment level according to the vibration data that affect the normal operation of the rocket. Secondly, we obtain the future trend of vibration signals based on five data prediction methods and calculate the health status interval of the rocket engine’s working conditions based on the boxplot method. At the same time, we calculate the single health evaluation set of every vibration signal. We obtain the weights of each level and factor for the health value based on an analytic hierarchy process (AHP). The optimization of this step avoids an over-reliance on expert experience. Finally, we complete a fuzzy comprehensive evaluation of the engine system from the bottom up to obtain the final health value. The minimum evaluation error is 0.0193% on the test data of the Long March series launch vehicle engine, which shows that the proposed method can successfully predict and evaluate the launch vehicle engine

Automated geometric precise correction of medium remote sensing images based on ASTER global digital elevation model

Accurate and unified information from the increasingly remote sensing (RS) scenes is important for RS applications in multi-sectoral association services of natural resource management. However, these applications in mountain areas are limited by the challenging issues of random geometric distortions and erroneous spatial associations. The paper introduces digital elevation model (DEM) maps as a unified geographic reference to search and match homonymy ground points (HGPs). The proposed computer-based procedure was tested with Landsat TM, ETM and HJ-1B satellite images using ASTER global DEM in the Longitudinal Rang-gorge Valley Region of Southwest China. 1322, 3551 and 694 pairs of HGPs were identified and acquired the geometric accuracies with 43 m (TM), 14 m (ETM) and 123 m (HJ), respectively. The deviations are significantly reduced and the disjoint ground objects are matched. The study satisfies the application requirement of multispectral satellite imagery with less labour and time costs

Review of Launch Vehicle Engine PHM Technology and Analysis Methods Research

The reliability and safety of launch vehicle launch missions might be effectively increased thanks to the fault prediction and health management (PHM) technology of engines, which could also improve with problem diagnostics and decrease the cost of operation and maintenance overhaul. This paper combines the equipment characteristics and the current state of safeguarding for large, complex space systems, introduces the intelligent launch vehicle engine PHM technology methods that are being gradually implemented in space systems, and discusses and compares fault detection and health assessment techniques. Subsequently, analysis of the measurement signals from a rocket engine was performed using an example, and it was shown that the established comprehensive health assessment structure, which is based on the fault prediction algorithm method and the fuzzy comprehensive assessment method, could successfully realize the effectiveness of the rocket engine system health assessment, which had an outstanding application value

Response of Two Major Lakes in the Changtang National Nature Reserve, Tibetan Plateau to Climate and Anthropogenic Changes over the Past 50 Years

Areal changes in alpine lakes on the Tibetan Plateau (TP) are reliable indicators of climate change and anthropogenic disturbance. This study used long-term Landsat images and meteorological records to monitor the temporal evolution patterns of lakes within the Changtang National Nature Reserve between 1972 and 2021 and examine the climatic and anthropogenic impacts on lake area changes. The results revealed that the area of Lake LongmuCo and Lake Jiezechaqia significantly expanded by 12.81% and 12.88% from 1972 to 2021, respectively. After 1999, Lake LongmuCo and Lake Jiezechaqia entered into a period of rapid expansion. During 1972–2021, the annual mean temperature significantly increased at a rate of 0.05 °C/a, while the change in annual precipitation was not significant. The temperature change was a major contributor to the observed changes of Lake LongmuCo and Lake Jiezechaqia between 1972 and 2021, while human intervention also played a vital role during 2013–2021. The glaciers around these two lakes decreased by 21.81%, and the increase in water supply from warming-triggered glacier melting was a reason of expansion of Lake LongmuCo and Lake Jiezechaqia. The areas of the two artificial salt lakes affiliated with Lake LongmuCo and Lake Jiezechaqia were 0.24 km2 and 2.67 km2 in 2013 and rose to 0.51 km2 and 9.80 km2 in 2021, respectively. In particular, the continuous exploitations of salt lakes to extract lithium resources have retarded the rate of expansion of Lake LongmuCo and Lake Jiezechaqia. The dams constructed by industrial enterprises have blocked the expansion of Lake LongmuCo to the south. This paper sheds new light on the influences of recent human intervention and climatic variation on alpine lakes within the TP. Due to the importance of alpine lakes in the TP, we need more comprehensive and in-depth efforts to protect the lake ecosystems within the national nature reserves

Research on Discrete Fourier Transform-Based Phasor Measurement Algorithm for Distribution Network under High Frequency Sampling

This paper proposes a phasor measurement algorithm that is suitable for a distribution network. Under the condition of fixed interval and high frequency sampling, the algorithm uses a dynamic calibration factor to correct the traditional Discrete Fourier Transform (DFT) algorithm, which solves the shortcomings of the rapid decline in traditional algorithm measurement accuracy under the condition of power system frequency deviation or dynamic measurement. Under the high sampling rate of the international distribution network waveform data, the conventional phasor is used to represent the theoretical phasor, and the value of the conventional phasor is compensated to make the result closer to the theoretical value. Finally, the phasor measurement software simulation platform is built in Matlab/Simulink, based on the principle of the algorithm, providing a simulation environment for researchers to verify the phasor measurement algorithm of the distribution network and the fault location, state estimation, or other advanced applications

Response of Two Major Lakes in the Changtang National Nature Reserve, Tibetan Plateau to Climate and Anthropogenic Changes over the Past 50 Years

Areal changes in alpine lakes on the Tibetan Plateau (TP) are reliable indicators of climate change and anthropogenic disturbance. This study used long-term Landsat images and meteorological records to monitor the temporal evolution patterns of lakes within the Changtang National Nature Reserve between 1972 and 2021 and examine the climatic and anthropogenic impacts on lake area changes. The results revealed that the area of Lake LongmuCo and Lake Jiezechaqia significantly expanded by 12.81% and 12.88% from 1972 to 2021, respectively. After 1999, Lake LongmuCo and Lake Jiezechaqia entered into a period of rapid expansion. During 1972&ndash;2021, the annual mean temperature significantly increased at a rate of 0.05 &deg;C/a, while the change in annual precipitation was not significant. The temperature change was a major contributor to the observed changes of Lake LongmuCo and Lake Jiezechaqia between 1972 and 2021, while human intervention also played a vital role during 2013&ndash;2021. The glaciers around these two lakes decreased by 21.81%, and the increase in water supply from warming-triggered glacier melting was a reason of expansion of Lake LongmuCo and Lake Jiezechaqia. The areas of the two artificial salt lakes affiliated with Lake LongmuCo and Lake Jiezechaqia were 0.24 km2 and 2.67 km2 in 2013 and rose to 0.51 km2 and 9.80 km2 in 2021, respectively. In particular, the continuous exploitations of salt lakes to extract lithium resources have retarded the rate of expansion of Lake LongmuCo and Lake Jiezechaqia. The dams constructed by industrial enterprises have blocked the expansion of Lake LongmuCo to the south. This paper sheds new light on the influences of recent human intervention and climatic variation on alpine lakes within the TP. Due to the importance of alpine lakes in the TP, we need more comprehensive and in-depth efforts to protect the lake ecosystems within the national nature reserves

Spatial Pattern and Environmental Driving Factors of Treeline Elevations in Yulong Snow Mountain, China

The southwestern region of China is a global biodiversity hotspot. Understanding the environmental mechanisms behind treeline formation in high-altitude areas is crucial for predicting ecosystem changes, such as the upward movement of the treeline due to climate warming and the disappearance of high-altitude rocky beach and shrub ecosystems. Globally, observations show that growing seasonal temperatures at treelines are typically 6–7 °C, but trees do not always reach the predicted elevations. Spatial heterogeneity exists in the deviation (Dtreeline) between actual treeline elevation and the thermal treeline; however, the main driving factors for Dtreeline in many areas remain unclear. This study uses Yulong Snow Mountain as an example, employing machine learning methods like Support Vector Machine (SVM) to precisely identify actual treeline elevation and Extreme Gradient Boosting Tree (XGBoost) to explore the main environmental factors driving the spatial heterogeneity of Dtreeline. Our research found that (1) more than half of the treelines deviated from the thermal treeline, with the average elevation of the thermal treeline (3924 ± 391 m) being about 56 m higher than the actual treeline (3863 ± 223 m); (2) Dtreeline has a complex relationship with environmental factors. In addition to being highly correlated with temperature, precipitation and wind speed also significantly influence the treeline in this region; and (3) the influence of individual variables such as precipitation and wind speed on the spatial variation of Dtreeline is limited, often nonlinear, and involves threshold effects. This knowledge is essential for developing comprehensive protection strategies for Yunnan’s high-altitude ecological systems in response to climate warming. Furthermore, it plays a significant role in understanding the changes in biological communities and the response of high-altitude areas to climate change