21 research outputs found
Semi-Supervised Domain Adaptation for Wildfire Detection
Recently, both the frequency and intensity of wildfires have increased
worldwide, primarily due to climate change. In this paper, we propose a novel
protocol for wildfire detection, leveraging semi-supervised Domain Adaptation
for object detection, accompanied by a corresponding dataset designed for use
by both academics and industries. Our dataset encompasses 30 times more diverse
labeled scenes for the current largest benchmark wildfire dataset, HPWREN, and
introduces a new labeling policy for wildfire detection. Inspired by CoordConv,
we propose a robust baseline, Location-Aware Object Detection for
Semi-Supervised Domain Adaptation (LADA), utilizing a teacher-student based
framework capable of extracting translational variance features characteristic
of wildfires. With only using 1% target domain labeled data, our framework
significantly outperforms our source-only baseline by a notable margin of 3.8%
in mean Average Precision on the HPWREN wildfire dataset. Our dataset is
available at https://github.com/BloomBerry/LADA.Comment: 16 pages, 5 figures, 22 table
Image-based Early Detection System for Wildfires
Wildfires are a disastrous phenomenon which cause damage to land, loss of
property, air pollution, and even loss of human life. Due to the warmer and
drier conditions created by climate change, more severe and uncontrollable
wildfires are expected to occur in the coming years. This could lead to a
global wildfire crisis and have dire consequences on our planet. Hence, it has
become imperative to use technology to help prevent the spread of wildfires.
One way to prevent the spread of wildfires before they become too large is to
perform early detection i.e, detecting the smoke before the actual fire starts.
In this paper, we present our Wildfire Detection and Alert System which use
machine learning to detect wildfire smoke with a high degree of accuracy and
can send immediate alerts to users. Our technology is currently being used in
the USA to monitor data coming in from hundreds of cameras daily. We show that
our system has a high true detection rate and a low false detection rate. Our
performance evaluation study also shows that on an average our system detects
wildfire smoke faster than an actual person.Comment: Published in Tackling Climate Change with Machine Learning workshop,
Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS
2022
The chromatin remodeler Ino80 mediates RNAPII pausing site determination
Background
Promoter-proximal pausing of RNA polymerase II (RNAPII) is a critical step for the precise regulation of gene expression. Despite the apparent close relationship between promoter-proximal pausing and nucleosome, the role of chromatin remodeler governing this step has mainly remained elusive.
Results
Here, we report highly confined RNAPII enrichments downstream of the transcriptional start site in Saccharomyces cerevisiae using PRO-seq experiments. This non-uniform distribution of RNAPII exhibits both similar and different characteristics with promoter-proximal pausing in Schizosaccharomyces pombe and metazoans. Interestingly, we find that Ino80p knockdown causes a significant upstream transition of promoter-proximal RNAPII for a subset of genes, relocating RNAPII from the main pausing site to the alternative pausing site. The proper positioning of RNAPII is largely dependent on nucleosome context. We reveal that the alternative pausing site is closely associated with the + 1 nucleosome, and nucleosome architecture around the main pausing site of these genes is highly phased. In addition, Ino80p knockdown results in an increase in fuzziness and a decrease in stability of the + 1 nucleosome. Furthermore, the loss of INO80 also leads to the shift of promoter-proximal RNAPII toward the alternative pausing site in mouse embryonic stem cells.
Conclusions
Based on our collective results, we hypothesize that the highly conserved chromatin remodeler Ino80p is essential in establishing intact RNAPII pausing during early transcription elongation in various organisms, from budding yeast to mouse.This work was supported by a National Research Foundation (NRF) of Korea Grant funded by the Ministry of Science and ICT (MSIT) (2018R1A5A1024261, SRC), and the Collaborative Genome Program for Fostering New Post-Genome Industry of the NRF funded by the MSIT (2018M3C9A6065070)
Dynamic modules of the coactivator SAGA in eukaryotic transcription
Gene activation: many modules make light work A protein that helps add epigenetic information to genome, SAGA, controls many aspects of gene activation, potentially making it a target for cancer therapies. To fit inside the tiny cell nucleus, the genome is tightly packaged, and genes must be unpacked before they can be activated. Known to be important in genome opening, SAGA has now been shown to also play many roles in gene activation. Daeyoup Lee at the KAIST, Daejeon, South Korea, and co-workers have reviewed recent discoveries about SAGA’s structure, function, and roles in disease. They report that SAGA’s complex (19 subunits organized into four modules) allows it to play so many roles, genome opening, initiating transcription, and efficiently exporting mRNAs. Its master role means that malfunction of SAGA may be linked to many diseases
Antioxidative and Analgesic Effects of Naringin through Selective Inhibition of Transient Receptor Potential Vanilloid Member 1
Transient receptor potential vanilloid member 1 (TRPV1) is activated in response to capsaicin, protons, temperature, and free reactive oxygen species (ROS) released from inflammatory molecules after exposure to harmful stimuli. The expression level of TRPV1 is elevated in the dorsal root ganglion, and its activation through capsaicin and ROS mediates neuropathic pain in mice. Its expression is high in peripheral and central nervous systems. Although pain is a response evolved for survival, many studies have been conducted to develop analgesics, but no clear results have been reported. Here, we found that naringin selectively inhibited capsaicin-stimulated inward currents in Xenopus oocytes using a two-electrode voltage clamp. The results of this study showed that naringin has an IC50 value of 33.3 μM on TRPV1. The amino acid residues D471 and N628 of TRPV1 were involved in its binding to naringin. Our study bridged the gap between the pain suppression effect of TRPV1 and the preventive effect of naringin on neuropathic pain and oxidation. Naringin had the same characteristics as a model selective antagonist, which is claimed to be ideal for the development of analgesics targeting TRPV1. Thus, this study suggests the applicability of naringin as a novel analgesic candidate through antioxidative and analgesic effects of naringin
The Association between Serum Uric Acid Levels and 10-Year Cardiovascular Disease Risk in Non-Alcoholic Fatty Liver Disease Patients
Non-alcoholic fatty liver disease (NAFLD) and serum uric acid (SUA) levels are risk factors for developing cardiovascular disease (CVD). Additionally, previous studies have suggested that high SUA levels increase the risk of having NAFLD. However, no study has investigated the relationship between SUA and CVD risk in NAFLD. This study analyzed the relationship between SUA and CVD in NAFLD. Data for this study used the 2016–2018 Korean National Health and Nutrition Examination Survey, which represents the Korean population. A total of 11,160 NAFLD patients were included. Participants with hepatic steatosis index ≥ 30 were considered to have NAFLD. Ten-year CVD risk was estimated using an integer-based Framingham risk score. Estimated 10-year CVD risk ≥ 20% was considered high risk. Multiple logistic regression was conducted to calculate the odds ratios (ORs) associated with SUA level and CVD risk. High CVD risk OR increases by 1.31 (95% CI 1.26–1.37) times per 1 mg/dL of SUA. After adjustment, SUA still had an increased risk (OR 1.44; 95% CI 1.38–1.51) of CVD. Compared with the lowest SUA quartile group, the highest quartile group showed a significantly higher risk of having CVD before (OR 2.76; 95% CI 2.34–3.25) and after (OR 4.01; 95% CI 3.37–4.78) adjustment. SUA is independently associated with CVS risk in NAFLD
The Effect of Mesenchymal Stem Cells on Dry Eye in Sjogren Syndrome Mouse Model
Sjögren’s syndrome (SS) is a systemic autoimmune disease delineated by chronic lymphocytic infiltrates into the lacrimal or salivary glands, leading to severe dry eye and dry mouth. Mesenchymal stem cells have been shown to be effective in treating numerous autoimmune diseases. This study aimed to illustrate the effects of mesenchymal stem cells on the attenuation of dry eyes (DE) through the inhibition of autophagy markers in a SS mouse model. NOD/ShiLtJ female mice with developed DE were treated with either subconjunctival or lacrimal gland injections of hMSCs (Catholic MASTER Cells). After maintenance for 14 days, clinical DE markers such as tear secretion and corneal staining were observed, as well as goblet cell counts in the conjunctiva, infiltration of inflammatory foci, B and T cells, and autophagy markers in the lacrimal glands. Proinflammatory cytokine expressions of the cornea and conjunctiva, as well as the lacrimal glands, were examined. Clinical markers, such as tear secretion and corneal stain scores, goblet cell counts in the conjunctiva, and foci infiltrations in the lacrimal glands were attenuated in mice treated with subconjunctival or lacrimal gland injections of hMSCs compared to the PBS-treated control group. B cell marker B220 decreased in the lacrimal glands of hMSCs-treated mice, as well as reduced proinflammatory cytokine expressions in the lacrimal glands and cornea. Notably, expression of autophagy markers ATG5 and LC3B-II, as well as HIF-1α and mTOR which play roles in the pathways of autophagy modulation, were shown to be attenuated in the lacrimal glands of hMSCs-treated mice compared to the PBS-treated control mice. Treatment with hMSCs by lacrimal gland or subconjunctival injection demonstrated the alleviation of DE through the repression of autophagy markers, suggesting the therapeutic potentials of hMSCs in a SS mouse model
Meta-Analysis of Randomized Clinical Trials Evaluating Effectiveness of a Multivitamin Supplementation against Oxidative Stress in Healthy Subjects
A meta-analysis has been widely applied to draw general conclusions using a set of studies with similar purposes and designs. This study aimed to perform a meta-analysis of six randomized placebo-controlled trials, independently conducted for the relationship between a plant-based multivitamin/mineral supplementation (PMS) and oxidative stress for 6 to 8 weeks, to provide overall estimates of those effects. In detail, linear mixed model analysis was first conducted on each study to obtain individual estimates; then, two types of meta-analysis were applied to combine the individual estimates from all available studies (overall meta-analysis) and region-specific studies (subgroup meta-analysis). In the meta-analysis, we selected 19 biomarker variables that overlapped in at least two studies and found 6 variables significant in at least one meta-analysis. The overall estimates of beta coefficients were 0.17 for vitamin C, 0.80 for vitamin B6, 0.46 for vitamin B12, 0.81 for folate, 0.36 for β-carotene, and −0.17 for oxidized LDL (ox-LDL). Subsequent association analysis revealed significant negative correlations between plasma free radical scavenging nutrients and plasma ox-LDL levels, indicating a general benefit of PMS in alleviating oxidative stress by providing exogenous oxidant scavengers