Relative coefficient of grain carbon emission. by Xidong Zhang (6336488)

“…Henan and Anhui have consistently maintained a high level of net agricultural carbon output, the net agricultural carbon output decreased from 35.54 million tons in 2015 to 25.68 million tons in 2021. …”

Relative coefficient of meat carbon emission. by Xidong Zhang (6336488)

“…Henan and Anhui have consistently maintained a high level of net agricultural carbon output, the net agricultural carbon output decreased from 35.54 million tons in 2015 to 25.68 million tons in 2021. …”

Relative coefficient of grain carbon emission. by Xidong Zhang (6336488)

“…Henan and Anhui have consistently maintained a high level of net agricultural carbon output, the net agricultural carbon output decreased from 35.54 million tons in 2015 to 25.68 million tons in 2021. …”

Carbon emissions from grain. by Xidong Zhang (6336488)

“…Henan and Anhui have consistently maintained a high level of net agricultural carbon output, the net agricultural carbon output decreased from 35.54 million tons in 2015 to 25.68 million tons in 2021. …”

Conversion factor of food consumption. by Xidong Zhang (6336488)

“…Henan and Anhui have consistently maintained a high level of net agricultural carbon output, the net agricultural carbon output decreased from 35.54 million tons in 2015 to 25.68 million tons in 2021. …”

Spatial variations of ET and WY. by Hao Yang (328526)

“…<p>Maps displaying the slope of ET and WY by linear trend estimation: (a) ET and (b) WY. K > 0 and K < 0 in any pixels indicate increasing and decreasing trends over time, respectively.…”

Supplementary Material for: Structural and Functional Proteomics of Intracytoplasmic Membrane Assembly in <b><i>Rhodobacter sphaeroides</i></b> by Woronowicz K. (4137052)

“…The results of a detailed structural and functional proteomic analysis of intracytoplasmic membrane (ICM) assembly in the model purple phototrophic bacterium <i>Rhodobacter sphaeroides</i> are reviewed in this report. …”

Image_1_Understanding Ciprofloxacin Failure in Pseudomonas aeruginosa Biofilm: Persister Cells Survive Matrix Disruption.JPEG by Anaïs Soares (7858007)

“…Biofilms were analyzed using confocal laser scanning microscopy (CLSM), and the expression of genes involved in stringent response, toxin-antitoxin HigB/HigA, and type 3 secretion system (T3SS) was quantified by RT-qPCR in untreated and treated biofilms. …”

Alteration of <em>POLDIP3</em> Splicing Associated with Loss of Function of TDP-43 in Tissues Affected with ALS by Atsushi Shiga (144249)

“…Moreover, we found an increment of <em>POLDIP3</em> variant-2 mRNA in motor cortex, spinal cord and spinal motor neurons collected by laser capture microdissection with ALS. Our results suggest a loss of TDP-43 function in tissues affected with ALS, supporting the hypothesis that a loss of function of TDP-43 underlies the pathogenesis of ALS.…”

Table_1_Understanding Ciprofloxacin Failure in Pseudomonas aeruginosa Biofilm: Persister Cells Survive Matrix Disruption.DOCX by Anaïs Soares (7858007)

“…Biofilms were analyzed using confocal laser scanning microscopy (CLSM), and the expression of genes involved in stringent response, toxin-antitoxin HigB/HigA, and type 3 secretion system (T3SS) was quantified by RT-qPCR in untreated and treated biofilms. …”

Video 1_Immunoassay–mass spectrometry to identify Brucella melitensis.mp4 by Amirreza Sharif (20667197)

“…<p>Two factors frequently impede accurate bacterial identification using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS): inadequate bacterial abundance in real samples and bacterial combinations. …”

Image_2_Understanding Ciprofloxacin Failure in Pseudomonas aeruginosa Biofilm: Persister Cells Survive Matrix Disruption.JPEG by Anaïs Soares (7858007)

“…Biofilms were analyzed using confocal laser scanning microscopy (CLSM), and the expression of genes involved in stringent response, toxin-antitoxin HigB/HigA, and type 3 secretion system (T3SS) was quantified by RT-qPCR in untreated and treated biofilms. …”

Table_1_Potential of Pectins to Beneficially Modulate the Gut Microbiota Depends on Their Structural Properties.docx by Nadja Larsen (253461)

“…Both general and pectin-specific changes were observed in relative abundances of numerous bacterial taxa in a time-dependent way. Bacterial populations associated with human health, such as Faecalibacterium prausnitzii, Coprococcus, Ruminococcus, Dorea, Blautia, Oscillospira, Sutterella, Bifidobacterium, Christensenellaceae, Prevotella copri, and Bacteroides spp. were either increased or decreased depending on the substrate, suggesting that these bacteria can be controlled using structurally different pectins. …”

Image_1_Potential of Pectins to Beneficially Modulate the Gut Microbiota Depends on Their Structural Properties.tiff by Nadja Larsen (253461)

“…Both general and pectin-specific changes were observed in relative abundances of numerous bacterial taxa in a time-dependent way. Bacterial populations associated with human health, such as Faecalibacterium prausnitzii, Coprococcus, Ruminococcus, Dorea, Blautia, Oscillospira, Sutterella, Bifidobacterium, Christensenellaceae, Prevotella copri, and Bacteroides spp. were either increased or decreased depending on the substrate, suggesting that these bacteria can be controlled using structurally different pectins. …”

DataSheet_1_Study on molecular mechanism of volatiles variation during Bupleurum scorzonerifolium root development based on metabolome and transcriptome analysis.zip by Dan Yu (214174)

“…<p>Bupleurum scorzonerifolium Willd. is a medicinal herb. Its root has a high content of volatile oil (BSVO), which shows a variety of biological activities. …”

Table_3_Potential of Pectins to Beneficially Modulate the Gut Microbiota Depends on Their Structural Properties.docx by Nadja Larsen (253461)

“…Both general and pectin-specific changes were observed in relative abundances of numerous bacterial taxa in a time-dependent way. Bacterial populations associated with human health, such as Faecalibacterium prausnitzii, Coprococcus, Ruminococcus, Dorea, Blautia, Oscillospira, Sutterella, Bifidobacterium, Christensenellaceae, Prevotella copri, and Bacteroides spp. were either increased or decreased depending on the substrate, suggesting that these bacteria can be controlled using structurally different pectins. …”

DataSheet1_Evaluation of Water Resources Utilization Efficiency in Guangdong Province Based on the DEA–Malmquist Model.xlsx by Lifen Cheng (12135903)

“…Furthermore, spatial heterogeneity exhibited a decreasing tendency in the future owing to the rapid water utilization efficiency increase in the Western and Eastern Guangdong. …”

Data_Sheet_1_Effects of Social Participation and Its Diversity, Frequency, and Type on Depression in Middle-Aged and Older Persons: Evidence From China.doc by Jiahui Wang (746367)

“…All types of SP had a significantly positive effect (p < 0.001), and participating in community activities had the largest effect (β = −1.549 to −1.788, p < 0.001). …”

Table_2_Potential of Pectins to Beneficially Modulate the Gut Microbiota Depends on Their Structural Properties.docx by Nadja Larsen (253461)

“…Both general and pectin-specific changes were observed in relative abundances of numerous bacterial taxa in a time-dependent way. Bacterial populations associated with human health, such as Faecalibacterium prausnitzii, Coprococcus, Ruminococcus, Dorea, Blautia, Oscillospira, Sutterella, Bifidobacterium, Christensenellaceae, Prevotella copri, and Bacteroides spp. were either increased or decreased depending on the substrate, suggesting that these bacteria can be controlled using structurally different pectins. …”

Clustering and PCA analysis of basal gene expression reveals <i>MITF</i> expression and gene regulation separates melanoma cell lines. by Brian J. Capaldo (800144)

“…Cluster IV genes were analyzed using Ingenuity Pathway Analysis revealing the cluster contains <i>MITF</i> as a regulatory hub and its target genes (B). Principal component plot of basal expression across the twelve cell lines (C) separates cells according to <i>MITF</i> expression along the first principal component (i.e., decreasing <i>MITF</i> expression going from left to right) and Bliss score across the second principal component.…”