MicroRNA-124a (miR-124a) is one of the most abundantly expressed microRNAs in the central nervous system and is encoded in mammals by the three genomic loci miR-124a-1/2/3; however, its in vivo roles ...in neuronal development and function remain ambiguous. In the present study, we investigated the effect of miR-124a loss on neuronal differentiation in mice and in embryonic stem (ES) cells. Since miR-124a-3 exhibits only background expression levels in the brain and we were unable to obtain miR-124a-1/2/3 triple knockout (TKO) mice by mating, we generated and analyzed miR-124a-1/2 double knockout (DKO) mice. We found that these DKO mice exhibit perinatal lethality. RNA-seq analysis demonstrated that the expression levels of proneural and neuronal marker genes were almost unchanged between the control and miR-124a-1/2 DKO brains; however, genes related to neuronal synaptic formation and function were enriched among downregulated genes in the miR-124a-1/2 DKO brain. In addition, we found the transcription regulator Tardbp/TDP-43, loss of which leads to defects in neuronal maturation and function, was inactivated in the miR-124a-1/2 DKO brain. Furthermore, Tardbp knockdown suppressed neurite extension in cultured neuronal cells. We also generated miR-124a-1/2/3 TKO ES cells using CRISPR-Cas9 as an alternative to TKO mice. Phase-contrast microscopic, immunocytochemical, and gene expression analyses showed that miR-124a-1/2/3 TKO ES cell lines were able to differentiate into neurons. Collectively, these results suggest that miR-124a plays a role in neuronal maturation rather than neurogenesis in vivo and advance our understanding of the functional roles of microRNAs in central nervous system development.
The Thermal and Near Infrared Sensor for Carbon Observation (TANSO)–Fourier Transform Spectrometer (FTS) on board the Greenhouse Gases Observing Satellite (GOSAT) has been observing carbon dioxide ...(CO2) concentrations in several atmospheric layers in the thermal infrared (TIR) band since its launch. This study compared TANSO-FTS TIR version 1 (V1) CO2 data and CO2 data obtained in the Comprehensive Observation Network for TRace gases by AIrLiner (CONTRAIL) project in the upper troposphere and lower stratosphere (UTLS), where the TIR band of TANSO-FTS is most sensitive to CO2 concentrations, to validate the quality of the TIR V1 UTLS CO2 data from 287 to 162 hPa. We first evaluated the impact of considering TIR CO2 averaging kernel functions on CO2 concentrations using CO2 profile data obtained by the CONTRAIL Continuous CO2 Measuring Equipment (CME), and found that the impact at around the CME level flight altitudes (∼ 11 km) was on average less than 0.5 ppm at low latitudes and less than 1 ppm at middle and high latitudes. From a comparison made during flights between Tokyo and Sydney, the averages of the TIR upper-atmospheric CO2 data were within 0.1 % of the averages of the CONTRAIL CME CO2 data with and without TIR CO2 averaging kernels for all seasons in the Southern Hemisphere. The results of comparisons for all of the eight airline routes showed that the agreements of TIR and CME CO2 data were worse in spring and summer than in fall and winter in the Northern Hemisphere in the upper troposphere. While the differences between TIR and CME CO2 data were on average within 1 ppm in fall and winter, TIR CO2 data had a negative bias up to 2.4 ppm against CME CO2 data with TIR CO2 averaging kernels at the northern low and middle latitudes in spring and summer. The negative bias at the northern middle latitudes resulted in the maximum of TIR CO2 concentrations being lower than that of CME CO2 concentrations, which led to an underestimate of the amplitude of CO2 seasonal variation.
CO2 observations in the free troposphere can be useful for constraining CO2 source and sink estimates at the surface since they represent CO2 concentrations away from point source emissions. The ...thermal infrared (TIR) band of the Thermal and Near Infrared Sensor for Carbon Observation (TANSO) Fourier transform spectrometer (FTS) on board the Greenhouse Gases Observing Satellite (GOSAT) has been observing global CO2 concentrations in the free troposphere for about 8 years and thus could provide a dataset with which to evaluate the vertical transport of CO2 from the surface to the upper atmosphere. This study evaluated biases in the TIR version 1 (V1) CO2 product in the lower troposphere (LT) and the middle troposphere (MT) (736–287 hPa), on the basis of comparisons with CO2 profiles obtained over airports using Continuous CO2 Measuring Equipment (CME) in the Comprehensive Observation Network for Trace gases by AIrLiner (CONTRAIL) project. Bias-correction values are presented for TIR CO2 data for each pressure layer in the LT and MT regions during each season and in each latitude band: 40–20° S, 20° S–20° N, 20–40° N, and 40–60° N. TIR V1 CO2 data had consistent negative biases of 1–1.5 % compared with CME CO2 data in the LT and MT regions, with the largest negative biases at 541–398 hPa, partly due to the use of 10 µm CO2 absorption band in conjunction with 15 and 9 µm absorption bands in the V1 retrieval algorithm. Global comparisons between TIR CO2 data to which the bias-correction values were applied and CO2 data simulated by a transport model based on the Nonhydrostatic ICosahedral Atmospheric Model (NICAM-TM) confirmed the validity of the bias-correction values evaluated over airports in limited areas. In low latitudes in the upper MT region (398–287 hPa), however, TIR CO2 data in northern summer were overcorrected by these bias-correction values; this is because the bias-correction values were determined using comparisons mainly over airports in Southeast Asia, where CO2 concentrations in the upper atmosphere display relatively large variations due to strong updrafts.
CO.sub.2 observations in the free troposphere can be useful for constraining CO.sub.2 source and sink estimates at the surface since they represent CO.sub.2 concentrations away from point source ...emissions. The thermal infrared (TIR) band of the Thermal and Near Infrared Sensor for Carbon Observation (TANSO) Fourier transform spectrometer (FTS) on board the Greenhouse Gases Observing Satellite (GOSAT) has been observing global CO.sub.2 concentrations in the free troposphere for about 8 years and thus could provide a dataset with which to evaluate the vertical transport of CO.sub.2 from the surface to the upper atmosphere. This study evaluated biases in the TIR version 1 (V1) CO.sub.2 product in the lower troposphere (LT) and the middle troposphere (MT) (736-287 hPa), on the basis of comparisons with CO.sub.2 profiles obtained over airports using Continuous CO.sub.2 Measuring Equipment (CME) in the Comprehensive Observation Network for Trace gases by AIrLiner (CONTRAIL) project. Bias-correction values are presented for TIR CO.sub.2 data for each pressure layer in the LT and MT regions during each season and in each latitude band: 40-20° S, 20° S-20° N, 20-40° N, and 40-60° N. TIR V1 CO.sub.2 data had consistent negative biases of 1-1.5 % compared with CME CO.sub.2 data in the LT and MT regions, with the largest negative biases at 541-398 hPa, partly due to the use of 10 µm CO.sub.2 absorption band in conjunction with 15 and 9 µm absorption bands in the V1 retrieval algorithm. Global comparisons between TIR CO.sub.2 data to which the bias-correction values were applied and CO.sub.2 data simulated by a transport model based on the Nonhydrostatic ICosahedral Atmospheric Model (NICAM-TM) confirmed the validity of the bias-correction values evaluated over airports in limited areas. In low latitudes in the upper MT region (398-287 hPa), however, TIR CO.sub.2 data in northern summer were overcorrected by these bias-correction values; this is because the bias-correction values were determined using comparisons mainly over airports in Southeast Asia, where CO.sub.2 concentrations in the upper atmosphere display relatively large variations due to strong updrafts.
The Thermal and Near Infrared Sensor for Carbon Observation (TANSO)-Fourier Transform Spectrometer (FTS) on board the Greenhouse Gases Observing Satellite (GOSAT) has been observing carbon dioxide ...(CO.sub.2) concentrations in several atmospheric layers in the thermal infrared (TIR) band since its launch. This study compared TANSO-FTS TIR version 1 (V1) CO.sub.2 data and CO.sub.2 data obtained in the Comprehensive Observation Network for TRace gases by AIrLiner (CONTRAIL) project in the upper troposphere and lower stratosphere (UTLS), where the TIR band of TANSO-FTS is most sensitive to CO.sub.2 concentrations, to validate the quality of the TIR V1 UTLS CO.sub.2 data from 287 to 162â¯hPa. We first evaluated the impact of considering TIR CO.sub.2 averaging kernel functions on CO.sub.2 concentrations using CO.sub.2 profile data obtained by the CONTRAIL Continuous CO.sub.2 Measuring Equipment (CME), and found that the impact at around the CME level flight altitudes (â¼â¯11â¯km) was on average less than 0.5â¯ppm at low latitudes and less than 1â¯ppm at middle and high latitudes. From a comparison made during flights between Tokyo and Sydney, the averages of the TIR upper-atmospheric CO.sub.2 data were within 0.1â¯% of the averages of the CONTRAIL CME CO.sub.2 data with and without TIR CO.sub.2 averaging kernels for all seasons in the Southern Hemisphere. The results of comparisons for all of the eight airline routes showed that the agreements of TIR and CME CO.sub.2 data were worse in spring and summer than in fall and winter in the Northern Hemisphere in the upper troposphere. While the differences between TIR and CME CO.sub.2 data were on average within 1â¯ppm in fall and winter, TIR CO.sub.2 data had a negative bias up to 2.4â¯ppm against CME CO.sub.2 data with TIR CO.sub.2 averaging kernels at the northern low and middle latitudes in spring and summer. The negative bias at the northern middle latitudes resulted in the maximum of TIR CO.sub.2 concentrations being lower than that of CME CO.sub.2 concentrations, which led to an underestimate of the amplitude of CO.sub.2 seasonal variation.
The Thermal and Near Infrared Sensor for Carbon Observation (TANSO)-Fourier Transform Spectrometer (FTS) on board the Greenhouse Gases Observing Satellite (GOSAT) has been observing carbon dioxide ...(CO2) concentrations in several atmospheric layers in the thermal infrared (TIR) band since its launch. This study compared TANSO-FTS TIR version 1 (V1) CO2 data and CO2 data obtained in the Comprehensive Observation Network for TRace gases by AIrLiner (CONTRAIL) project in the upper troposphere and lower stratosphere (UTLS), where the TIR band of TANSO-FTS is most sensitive to CO2 concentrations, to validate the quality of the TIR V1 UTLS CO2 data from 287 to 162-hPa. We first evaluated the impact of considering TIR CO2 averaging kernel functions on CO2 concentrations using CO2 profile data obtained by the CONTRAIL Continuous CO2 Measuring Equipment (CME), and found that the impact at around the CME level flight altitudes ( -11-km) was on average less than 0.5-ppm at low latitudes and less than 1-ppm at middle and high latitudes. From a comparison made during flights between Tokyo and Sydney, the averages of the TIR upper-atmospheric CO2 data were within 0.1-% of the averages of the CONTRAIL CME CO2 data with and without TIR CO2 averaging kernels for all seasons in the Southern Hemisphere. The results of comparisons for all of the eight airline routes showed that the agreements of TIR and CME CO2 data were worse in spring and summer than in fall and winter in the Northern Hemisphere in the upper troposphere. While the differences between TIR and CME CO2 data were on average within 1-ppm in fall and winter, TIR CO2 data had a negative bias up to 2.4-ppm against CME CO2 data with TIR CO2 averaging kernels at the northern low and middle latitudes in spring and summer. The negative bias at the northern middle latitudes resulted in the maximum of TIR CO2 concentrations being lower than that of CME CO2 concentrations, which led to an underestimate of the amplitude of CO2 seasonal variation.
CO2 observations in the free troposphere can be useful for constraining CO2 source and sink estimates at the surface since they represent CO2 concentrations away from point source emissions. The ...thermal infrared (TIR) band of the Thermal and Near Infrared Sensor for Carbon Observation (TANSO) Fourier transform spectrometer (FTS) on board the Greenhouse Gases Observing Satellite (GOSAT) has been observing global CO2 concentrations in the free troposphere for about 8 years and thus could provide a dataset with which to evaluate the vertical transport of CO2 from the surface to the upper atmosphere. This study evaluated biases in the TIR version 1 (V1) CO2 product in the lower troposphere (LT) and the middle troposphere (MT) (736–287 hPa), on the basis of comparisons with CO2 profiles obtained over airports using Continuous CO2 Measuring Equipment (CME) in the Comprehensive Observation Network for Trace gases by AIrLiner (CONTRAIL) project. Bias-correction values are presented for TIR CO2 data for each pressure layer in the LT and MT regions during each season and in each latitude band: 40–20∘ S, 20∘ S–20∘ N, 20–40∘ N, and 40–60∘ N. TIR V1 CO2 data had consistent negative biases of 1–1.5 % compared with CME CO2 data in the LT and MT regions, with the largest negative biases at 541–398 hPa, partly due to the use of 10 µm CO2 absorption band in conjunction with 15 and 9 µm absorption bands in the V1 retrieval algorithm. Global comparisons between TIR CO2 data to which the bias-correction values were applied and CO2 data simulated by a transport model based on the Nonhydrostatic ICosahedral Atmospheric Model (NICAM-TM) confirmed the validity of the bias-correction values evaluated over airports in limited areas. In low latitudes in the upper MT region (398–287 hPa), however, TIR CO2 data in northern summer were overcorrected by these bias-correction values; this is because the bias-correction values were determined using comparisons mainly over airports in Southeast Asia, where CO2 concentrations in the upper atmosphere display relatively large variations due to strong updrafts.
In Japan, pregnant women are diagnosed as obese if the prepregnancy body mass index (BMI) is ≥ 25 kg/m2. However, this is different from other countries. The Institute of Medicine (IOM) classifies ...prepregnancy BMI as underweight (BMI < 18.5 kg/m2), normal weight (BMI 18.5-24.9 kg/m2), overweight (BMI 25.0-29.9 kg/m2), and obese (BMI ≥ 30 kg/m2). In addition to these four categories, the American College of Obstetricians and Gynecologists (ACOG) classifies prepregnancy BMI as obesity class I (BMI 30.0-34.9 kg/m2), obesity class II (BMI 35.0-39.9 kg/m2), and obesity class III (BMI ≥ 40 kg/m2). We conducted a retrospective cohort study to compare obstetric outcomes by the three different categorizations in 6,066 pregnant women who gave birth between 2010 and 2019. According to Japanese classification, 668 (11%) pregnant women were classified as obese, and significant odds ratios (OR) were observed for hypertensive disorders of pregnancy (HDP; 3.32), gestational diabetes mellitus (GDM; 3.39), large for gestational age (LGA; 2.91), and macrosomia (4.01). According to the classification of IOM, 474 (7.8%) and 194 (3.1%) were classified as overweight and obese pregnant women, respectively. Specifically, a high OR was observed in obese pregnant women for HDP (5.85) and GDM (5.0). ACOG classification categorized 474 (7.8%) pregnant women as overweight, 141 (2.3%) as obesity class I, 41 (0.6%) as obesity class II, and 12 (0.2%) as obesity class III. In obesity class III, a significantly high OR was observed for HDP (12.89), GDM (8.37), and LGA (5.74). The Japanese classification may be useful for low-risk pregnancies, whereas IOM classification may be applicable to identify high-risk pregnancies. ACOG criteria may be useful for step-wise assessments of HDP and GDM risks in Japanese pregnant women; however, the number of class II and III obese pregnant women was small.
A New Approach to Reversible Watermarking Ito, Toshiki; Sugimura, Ryo; Hyunho Kang ...
2014 Tenth International Conference on Intelligent Information Hiding and Multimedia Signal Processing,
2014-Aug.
Conference Proceeding
A general digital watermarking application could not prevent the distortion of some sensitive content, like medical or military images. Since such changing of medical images is not acceptable, a ...reversible watermarking technique must be used to completely restore the original image after the watermark information has been extracted. The use of such a technique also enables the embedding of multiple watermarks. This paper survey recent watermarking methods and identifies research trends. A combination of two particular methods is shown to achieve the highest embedding capacity and best image quality. The reason for this is discussed and proposed as a new method.
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