Global land surface temperature influenced by vegetation cover and PM2.5 from 2001 to 2016

Land surface temperature (LST) is an important parameter to evaluate environmental changes. In this paper, time series analysis was conducted to estimate the interannual variations in global LST from 2001 to 2016 based on moderate resolution imaging spectroradiometer (MODIS) LST, and normalized difference vegetation index (NDVI) products and fine particulate matter (PM2.5) data from the Atmospheric Composition Analysis Group. The results showed that LST, seasonally integrated normalized difference vegetation index (SINDVI), and PM2.5 increased by 0.17 K, 0.04, and 1.02 �g/m3 in the period of 2001–2016, respectively. During the past 16 years, LST showed an increasing trend in most areas, with two peaks of 1.58 K and 1.85 K at 72�N and 48�S, respectively. Marked warming also appeared in the Arctic. On the contrary, remarkable decrease in LST occurred in Antarctic. In most parts of the world, LST was affected by the variation in vegetation cover and air pollutant, which can be detected by the satellite. In the Northern Hemisphere, positive relations between SINDVI and LST were found; however, in the Southern Hemisphere, negative correlations were detected. The impact of PM2.5 on LST was more complex. On the whole, LST increased with a small increase in PM2.5 concentrations but decreased with a marked increase in PM2.5. The study provides insights on the complex relationship between vegetation cover, air pollution, and land surface temperature

Large AI Models in Health Informatics: Applications, Challenges, and the Future

Large AI models, or foundation models, are models recently emerging with massive scales both parameter-wise and data-wise, the magnitudes of which can reach beyond billions. Once pretrained, large AI models demonstrate impressive performance in various downstream tasks. A prime example is ChatGPT, whose capability has compelled people's imagination about the far-reaching influence that large AI models can have and their potential to transform different domains of our lives. In health informatics, the advent of large AI models has brought new paradigms for the design of methodologies. The scale of multi-modal data in the biomedical and health domain has been ever-expanding especially since the community embraced the era of deep learning, which provides the ground to develop, validate, and advance large AI models for breakthroughs in health-related areas. This article presents a comprehensive review of large AI models, from background to their applications. We identify seven key sectors in which large AI models are applicable and might have substantial influence, including 1) bioinformatics; 2) medical diagnosis; 3) medical imaging; 4) medical informatics; 5) medical education; 6) public health; and 7) medical robotics. We examine their challenges, followed by a critical discussion about potential future directions and pitfalls of large AI models in transforming the field of health informatics.Comment: This article has been accepted for publication in IEEE Journal of Biomedical and Health Informatic

MicroRNA-17-92 Regulates the Transcription Factor E2F3b during Myogenesis In Vitro and In Vivo

Myogenic differentiation, which occurs during muscle development, is a highly ordered process that can be regulated by E2F transcription factors. Available data show that E2F3b, but not E2F3a, is upregulated and required for myogenic differentiation. However, the regulation of E2F3b expression in myogenic differentiation is not well understood. To investigate whether E2Fb expression is controlled by miRNAs, we used bioinformatics to combine the database of microRNAs downregulated during myogenesis and those predicted to target E2F3. This identified miR-17 and miR-20a as miRNAs potentially involved in E2F3 regulation. We found that miR-17-92 controls the expression of E2F3b in C2C12 cells during myogenic differentiation. Moreover, we confirmed that miR-20a regulates the expression of E2F3b proteins in vivo using a muscle regeneration model

Highly selective and sensitive xylene sensors based on Nb-doped NiO nanosheets

It's demonstrated that doping of aliovalent atom can greatly influence the sensing performance of metal oxides-based gas sensors. In this work, Nb-doped nickel oxides with Nb contents in the range of 6.2-29.1 at% have been synthesized by a one-step hydrothermal method. The gas sensing test results indicates that the 20.2 at% Nb doped NiO possesses an ultrahigh response (335.1-100 ppm), excellent selectivity and theoretical ppb-level detection limit (2 ppb) to xylene at 370 degrees C, which is much better than that of pure NiO sensor. The higher specific surface area and the enhanced catalytic activity caused by higher ratio Ni3+/Ni2+ are considered as the main reasons for the enhanced gas sensor performance

De Novo Sequencing and Transcriptome Analysis Reveal Genes’ Specific Expression in Chinese Fir (Cunninghamia lanceolata) Callus

While the progress made in vitro culture of Chinese fir has produced satisfactory results, further improvements are warranted. To understand the mechanism of somatic embryogenesis (SE) in Chinese fir, we conducted phenotypic observations, physiological and biochemical measurements, and transcriptome analysis of embryonic (EC) and non-embryogenic callus (NEC) to provide a scientific basis for SE in this species. We found that EC and NEC showed significant morphological and physiological-biochemical indicators differences. Compared with NEC, EC had higher levels of soluble protein and proline and lower levels of malondialdehyde (MDA), peroxidase (POD), superoxide dismutase (SOD), and catalase (CAT). Callus transcriptome sequencing assembled 152,229 unigenes, and 438 differentially expressed genes (DEGs) were screened, including transcription factor-related (TFs), DNA methylation-related, cell wall component protein, signal transduction-related, and stress response-related. GO and KEGG enrichment analyses of DEGs identified starch and sucrose, glutathione, and cysteine and methionine metabolism as the most representative pathways significantly enriched in EC and NEC genes and were associated with cell proliferation and embryogenesis. For the first time, the specific patterns of gene expression in Chinese fir callus were found through transcriptome comparison between callus, 16-year-old Chinese fir cambium, and drought-stressed tissue culture seedlings. In Chinese fir callus, 75.1% of genes were co-expressed in 16-year-old Chinese fir cambium and drought-stressed tissue culture seedlings, and 24.9% were only specifically expressed in callus. DEGs from EC and NEC indicated that 68.2 and 31.8% were co-expressed and specifically expressed, respectively. These results provided a basis for Chinese fir rapid propagation, which is expected to have theoretical and practical significance.Forestry, Faculty ofNon UBCForest and Conservation Sciences, Department ofReviewedFacultyResearche