model predictive control  (MathWorks Inc)

Journal: Aging Cell

Article Title: Aging Triggers an Intestinal Energy Crisis and HDL3 Deficiency Disrupting Gut–Liver Axis Homeostasis

doi: 10.1111/acel.70445

Figure Lengend Snippet: Mitochondrial dysfunction‐mediated ATP deficiency suppresses HDL3 synthesis in aging intestinal cells. (a) Representative images (scale bar: 5 μm) of intestinal cell microstructure measured by TEM, n = 18 images from n = 3 independent experiments; (b) ileum ATP levels, n = 5; (c) representative images (scale bar: 5 μm) of IME microstructure measured by TEM, n = 18 images from n = 3 independent experiments; (d) IME ATP levels, n = 5; (e) glycolysis assay measured as cytoplasmic acidification, the fluorescence signal was enhanced with the increase of acidification degree, n = 4; (f) oxygen consumption, as mitochondrial respiration depletes the oxygen within the assay medium, quenching of the fluorescent dye is reduced, and the fluorescence signal increases proportionately, n = 4; (g, h) OXPHOS protein expression levels in the ileum, n = 3; and (i) exogenous ATPγS‐AM (50 μM) partially restored HDL3 synthesis in senescent IME cells, whereas native ATP (50 μM) had no significant effect, n = 5. Data are express as the mean ± SEM. * p < 0.05, ** p < 0.01. D‐Gal: D‐galactose; NC, normal control.

Article Snippet: In the normal control groups (10 replicates), the medium was replaced with complete DMEM, whereas in the model control groups (10 replicates), the medium was replaced with D‐galactose (200 mM, dissolved in complete DMEM) and cultured for 24 h. After successful establishment of the aging model, the medium was discarded, and the model control group (D‐Gal) (replaced with complete DMEM containing ApoA1 10 μg/mL), ATP intervention group (D‐Gal‐ATP) was replaced with complete DMEM containing ApoA1 10 μg/mL and ATP 50 μM, ATPγS‐AM intervention group (D‐Gal‐ATPγS‐AM) was replaced with complete DMEM containing ApoA1 10 μg/mL and ATPγS‐AM 50 μM, NMN intervention group (D‐Gal‐NMN) was replaced with complete DMEM containing ApoA1 10 μg/mL and NMN 5 μM, the agonist CS‐6253 (MedChem Express, Shanghai, China) intervention group (D‐GAL‐CS‐6253) was replaced with complete DMEM containing ApoA1 10 μg/mL and CS‐6253 1 μM; and the NMN and CS‐6253 synergistic group (D‐Gal‐NMN‐CS‐6253) was replaced with complete DMEM containing ApoA1 10 μg/mL, NMN 5 μM, and CS‐6253 1 μM.

Techniques: Fluorescence, Expressing, Control

Journal: Aging Cell

Article Title: Aging Triggers an Intestinal Energy Crisis and HDL3 Deficiency Disrupting Gut–Liver Axis Homeostasis

doi: 10.1111/acel.70445

Figure Lengend Snippet: ABCA1 downregulation limits HDL3 synthesis in aging. (a) Relative mRNA expression of ABCA1 , ApoA1 , LPL , and ANGPTL3 in ileum, n = 5; (b, c) representative images (scale bar: 50 μm) and quantitative analysis of ABCA1, ApoA1, LPL, and ANGPTL3, measured by IHC staining, n = 3; and (d) activation of ABCA1 expression combined with ATPγS‐AM supplementation enhances cellular HDL3 synthesis capacity n = 5. Data are express as the mean ± SEM. ** p < 0.01. ABCA1, ATP‐binding cassette transporter 1; ANGPTL3, angiopoietin‐like3; CS‐6253, ABCA1 activators; D‐Gal, D‐galactose; HDL3, high‐density lipoprotein 3; IHC, immunohistochemistry; IME, intestinal mucosa epithelial; LPL, lipoprotein lipase; NC, normal control.

Article Snippet: In the normal control groups (10 replicates), the medium was replaced with complete DMEM, whereas in the model control groups (10 replicates), the medium was replaced with D‐galactose (200 mM, dissolved in complete DMEM) and cultured for 24 h. After successful establishment of the aging model, the medium was discarded, and the model control group (D‐Gal) (replaced with complete DMEM containing ApoA1 10 μg/mL), ATP intervention group (D‐Gal‐ATP) was replaced with complete DMEM containing ApoA1 10 μg/mL and ATP 50 μM, ATPγS‐AM intervention group (D‐Gal‐ATPγS‐AM) was replaced with complete DMEM containing ApoA1 10 μg/mL and ATPγS‐AM 50 μM, NMN intervention group (D‐Gal‐NMN) was replaced with complete DMEM containing ApoA1 10 μg/mL and NMN 5 μM, the agonist CS‐6253 (MedChem Express, Shanghai, China) intervention group (D‐GAL‐CS‐6253) was replaced with complete DMEM containing ApoA1 10 μg/mL and CS‐6253 1 μM; and the NMN and CS‐6253 synergistic group (D‐Gal‐NMN‐CS‐6253) was replaced with complete DMEM containing ApoA1 10 μg/mL, NMN 5 μM, and CS‐6253 1 μM.

Techniques: Expressing, Immunohistochemistry, Activation Assay, Binding Assay, Control

Journal: Aging Cell

Article Title: Aging Triggers an Intestinal Energy Crisis and HDL3 Deficiency Disrupting Gut–Liver Axis Homeostasis

doi: 10.1111/acel.70445

Figure Lengend Snippet: Aging impairs ABCA1‐mediated cholesterol efflux and reduces HDL3 synthesis. (a, b) Representative images (scale bar: 100 μm) of ABCA1 measured by IF staining in ileum and IME, n = 6 images from n = 3 independent experiments; and (c, d) efficiency of cholesterol efflux to ApoA‐1 and HDL, n = 5. Data are expressed as the mean ± SEM. ** p < 0.01. ABCA1, ATP‐binding cassette transporter 1; CS‐6253, ABCA1 activators; D‐Gal, D‐galactose; IF, immunofluorescence; IME, intestinal mucosa epithelial; NC, normal control.

Article Snippet: In the normal control groups (10 replicates), the medium was replaced with complete DMEM, whereas in the model control groups (10 replicates), the medium was replaced with D‐galactose (200 mM, dissolved in complete DMEM) and cultured for 24 h. After successful establishment of the aging model, the medium was discarded, and the model control group (D‐Gal) (replaced with complete DMEM containing ApoA1 10 μg/mL), ATP intervention group (D‐Gal‐ATP) was replaced with complete DMEM containing ApoA1 10 μg/mL and ATP 50 μM, ATPγS‐AM intervention group (D‐Gal‐ATPγS‐AM) was replaced with complete DMEM containing ApoA1 10 μg/mL and ATPγS‐AM 50 μM, NMN intervention group (D‐Gal‐NMN) was replaced with complete DMEM containing ApoA1 10 μg/mL and NMN 5 μM, the agonist CS‐6253 (MedChem Express, Shanghai, China) intervention group (D‐GAL‐CS‐6253) was replaced with complete DMEM containing ApoA1 10 μg/mL and CS‐6253 1 μM; and the NMN and CS‐6253 synergistic group (D‐Gal‐NMN‐CS‐6253) was replaced with complete DMEM containing ApoA1 10 μg/mL, NMN 5 μM, and CS‐6253 1 μM.

Techniques: Staining, Binding Assay, Immunofluorescence, Control

Journal: Aging Cell

Article Title: Aging Triggers an Intestinal Energy Crisis and HDL3 Deficiency Disrupting Gut–Liver Axis Homeostasis

doi: 10.1111/acel.70445

Figure Lengend Snippet: NMN modulates mitochondrial function to boost ATP production in the aging intestine. (a, b) NADH levels and NAD + /NADH ratio in ileum, n = 3; (c) relative telomere length in ileum (T/S), n = 5; (d, e) DAO and D‐LA levels in serum, n = 5; (f) ileum relative mRNA expression of Occludin and Claudin‐1 , n = 6; (g, h) representative images (scale bar: 100 μm) and quantitative analysis of Occludin and Claudin‐1 measured by IF staining, n = 6 images from n = 3 independent experiments; (i, k) representative images (scale bar: 5 μm, scale bar: 1 μm) of ileum and IME cell structure measured by TEM, n = 18 images from n = 3 independent experiments; (j, l) ATP levels in ileum and IME cell, n = 5; (m) glycolysis assay measured as cytoplasmic acidification, the fluorescence signal was enhanced with the increase of acidification degree, n = 4; (n) oxygen consumption, as mitochondrial respiration depletes the oxygen within the assay medium, quenching of the fluorescent dye is reduced, and the fluorescence signal increases proportionately, n = 4; and (o, p) OXPHOS protein expression levels in the ileum, n = 3. Data are express as the mean ± SEM. * p < 0.05, ** p < 0.01. DAO, diamine oxidase; D‐Gal, D‐galactose; D‐LA, D‐lactic acid; IF, immunofluorescence; IME, intestinal mucosa epithelial; NC, normal control.

Article Snippet: In the normal control groups (10 replicates), the medium was replaced with complete DMEM, whereas in the model control groups (10 replicates), the medium was replaced with D‐galactose (200 mM, dissolved in complete DMEM) and cultured for 24 h. After successful establishment of the aging model, the medium was discarded, and the model control group (D‐Gal) (replaced with complete DMEM containing ApoA1 10 μg/mL), ATP intervention group (D‐Gal‐ATP) was replaced with complete DMEM containing ApoA1 10 μg/mL and ATP 50 μM, ATPγS‐AM intervention group (D‐Gal‐ATPγS‐AM) was replaced with complete DMEM containing ApoA1 10 μg/mL and ATPγS‐AM 50 μM, NMN intervention group (D‐Gal‐NMN) was replaced with complete DMEM containing ApoA1 10 μg/mL and NMN 5 μM, the agonist CS‐6253 (MedChem Express, Shanghai, China) intervention group (D‐GAL‐CS‐6253) was replaced with complete DMEM containing ApoA1 10 μg/mL and CS‐6253 1 μM; and the NMN and CS‐6253 synergistic group (D‐Gal‐NMN‐CS‐6253) was replaced with complete DMEM containing ApoA1 10 μg/mL, NMN 5 μM, and CS‐6253 1 μM.

Techniques: Expressing, Staining, Fluorescence, Immunofluorescence, Control

Journal: Aging Cell

Article Title: Aging Triggers an Intestinal Energy Crisis and HDL3 Deficiency Disrupting Gut–Liver Axis Homeostasis

doi: 10.1111/acel.70445

Figure Lengend Snippet: NMN enhances intestinal HDL3 synthesis in the aging intestine. (a, b) NMN enhanced HDL3 synthesis capacity in the ileum and IME cells, n = 5; (c–e) NMN increased the relative expression of ABCA1 mRNA and protein in the ileum. n = 3; (f, h) representative images (scale bar: 100 μm) of ABCA1 localization to the cell membrane measured by IF staining, n = 6 images from n = 3 independent experiments; (g) NMN increased the relative expression of ABCA1 mRNA in the IME cells. n = 3; and (i, j) NMN enhanced cholesterol efflux to ApoA‐1 and HDL in aging cells, n = 5. Data are expressed as the mean ± SEM. ** p < 0.01. ABCA1, ATP‐binding cassette transporter 1; D‐Gal, D‐galactose; HDL, high‐density lipoprotein; IF, immunofluorescence; IME, intestinal mucosa epithelial; NC, normal control.

Article Snippet: In the normal control groups (10 replicates), the medium was replaced with complete DMEM, whereas in the model control groups (10 replicates), the medium was replaced with D‐galactose (200 mM, dissolved in complete DMEM) and cultured for 24 h. After successful establishment of the aging model, the medium was discarded, and the model control group (D‐Gal) (replaced with complete DMEM containing ApoA1 10 μg/mL), ATP intervention group (D‐Gal‐ATP) was replaced with complete DMEM containing ApoA1 10 μg/mL and ATP 50 μM, ATPγS‐AM intervention group (D‐Gal‐ATPγS‐AM) was replaced with complete DMEM containing ApoA1 10 μg/mL and ATPγS‐AM 50 μM, NMN intervention group (D‐Gal‐NMN) was replaced with complete DMEM containing ApoA1 10 μg/mL and NMN 5 μM, the agonist CS‐6253 (MedChem Express, Shanghai, China) intervention group (D‐GAL‐CS‐6253) was replaced with complete DMEM containing ApoA1 10 μg/mL and CS‐6253 1 μM; and the NMN and CS‐6253 synergistic group (D‐Gal‐NMN‐CS‐6253) was replaced with complete DMEM containing ApoA1 10 μg/mL, NMN 5 μM, and CS‐6253 1 μM.

Techniques: Expressing, Membrane, Staining, Binding Assay, Immunofluorescence, Control

Journal: PLOS One

Article Title: Research on self-adaptive height adjustment control of shearer based on deep deterministic policy gradient

doi: 10.1371/journal.pone.0329347

Figure Lengend Snippet: The block diagram of the height adjustment control system for the shearer.

Article Snippet: This includes the selection of action space and state space, the establishment of the height adjustment system Simulink model, the creation of the RL Agent model, and the design and selection of the reward function.

Techniques: Blocking Assay, Control

Journal: PLOS One

Article Title: Research on self-adaptive height adjustment control of shearer based on deep deterministic policy gradient

doi: 10.1371/journal.pone.0329347

Figure Lengend Snippet: Transfer function block diagram of the self-adaptive height adjustment control system.

Article Snippet: This includes the selection of action space and state space, the establishment of the height adjustment system Simulink model, the creation of the RL Agent model, and the design and selection of the reward function.

Techniques: Blocking Assay, Control

Journal: PLOS One

Article Title: Research on self-adaptive height adjustment control of shearer based on deep deterministic policy gradient

doi: 10.1371/journal.pone.0329347

Figure Lengend Snippet: Simplified schematic diagram of shearer height adjustment hydraulic system.

Article Snippet: This includes the selection of action space and state space, the establishment of the height adjustment system Simulink model, the creation of the RL Agent model, and the design and selection of the reward function.

Techniques:

Journal: PLOS One

Article Title: Research on self-adaptive height adjustment control of shearer based on deep deterministic policy gradient

doi: 10.1371/journal.pone.0329347

Figure Lengend Snippet: 3D solid model of shearer height adjustment mechanism.

Article Snippet: This includes the selection of action space and state space, the establishment of the height adjustment system Simulink model, the creation of the RL Agent model, and the design and selection of the reward function.

Techniques:

Journal: PLOS One

Article Title: Research on self-adaptive height adjustment control of shearer based on deep deterministic policy gradient

doi: 10.1371/journal.pone.0329347

Figure Lengend Snippet: Algorithm architecture of the hydraulic height adjustment system for the shearer based on DDPG.

Article Snippet: This includes the selection of action space and state space, the establishment of the height adjustment system Simulink model, the creation of the RL Agent model, and the design and selection of the reward function.

Techniques:

Journal: PLOS One

Article Title: Research on self-adaptive height adjustment control of shearer based on deep deterministic policy gradient

doi: 10.1371/journal.pone.0329347

Figure Lengend Snippet: Simulink model of height adjustment system.

Article Snippet: This includes the selection of action space and state space, the establishment of the height adjustment system Simulink model, the creation of the RL Agent model, and the design and selection of the reward function.

Techniques:

Journal: PLOS One

Article Title: Research on self-adaptive height adjustment control of shearer based on deep deterministic policy gradient

doi: 10.1371/journal.pone.0329347

Figure Lengend Snippet: The DDPG-based self-adaptive hydraulic height adjustment system model for the shearer (Model I).

Article Snippet: This includes the selection of action space and state space, the establishment of the height adjustment system Simulink model, the creation of the RL Agent model, and the design and selection of the reward function.

Techniques:

Journal: PLOS One

Article Title: Research on self-adaptive height adjustment control of shearer based on deep deterministic policy gradient

doi: 10.1371/journal.pone.0329347

Figure Lengend Snippet: The AMEsim model of the hydraulic system of the shearer electro-hydraulic proportional height adjustment.

Article Snippet: This includes the selection of action space and state space, the establishment of the height adjustment system Simulink model, the creation of the RL Agent model, and the design and selection of the reward function.

Techniques:

Journal: PLOS One

Article Title: Research on self-adaptive height adjustment control of shearer based on deep deterministic policy gradient

doi: 10.1371/journal.pone.0329347

Figure Lengend Snippet: Self-adaptive hydraulic height adjustment model of shearer based on DDPG (Model II).

Article Snippet: This includes the selection of action space and state space, the establishment of the height adjustment system Simulink model, the creation of the RL Agent model, and the design and selection of the reward function.

Techniques:

Journal: PLOS One

Article Title: Research on self-adaptive height adjustment control of shearer based on deep deterministic policy gradient

doi: 10.1371/journal.pone.0329347

Figure Lengend Snippet: Self-adaptive height adjustment test system platform.

Article Snippet: This includes the selection of action space and state space, the establishment of the height adjustment system Simulink model, the creation of the RL Agent model, and the design and selection of the reward function.

Techniques: