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0.406388 | e12ec3869d884cf4a59e6c40c73d1d5c | Changes in lactic acid concentrations during the 14-day aerobic cultivation of Mucor species in 100 mL yogurt acid whey at 30 °C and 200 rpm agitation. The bars show the means of biological triplicates, and the error bars refer to one standard error from the mean. On each day, the bars denoted with different letters are significantly different from each other. MC = M. circinelloides; MG = M. genevensis; +E = with lactase addition; NH = without lactase addition. | PMC10177860 | foods-12-01784-g004.jpg |
0.404844 | b7ee49b9a2bc49c1b5896da8dd747d72 | Dried fungal biomass production during the aerobic cultivations of Mucor species at 30 °C and 200 rpm agitation in 100 mL yogurt acid whey. The markers show the means of biological triplicates, and the error bars refer to one standard error from the mean. MC = M. circinelloides; MG = M. genevensis; +E = lactase addition; NH = no lactase addition. | PMC10177860 | foods-12-01784-g005.jpg |
0.46764 | 3f4314052a734baba3602b24155ddcb9 | Lipid mass fraction (%) in the dried Mucor biomass produced from the aerobic cultivations at 30 °C and 200 rpm agitation in 100 mL yogurt acid whey. The bars show the means of biological triplicates, and the error bars refer to one standard error from the mean. On each day, the bars denoted with different letters are significantly different from each other. MC = M. circinelloides; MG = M. genevensis; +E = with lactase addition; NH = without lactase addition. | PMC10177860 | foods-12-01784-g006.jpg |
0.406333 | d1334ae36c7b40478cedd8567fc90f2e | Yogurt acid whey cultures on day 8 of the aerobic cultivation of Mucor species at 30 °C and 200 rpm agitation. Left to right: M. circinelloides with lactase addition (MC+E); M. genevensis with lactase addition (MG+E); M. genevensis without lactase addition (MGNH); and M. circinelloides without lactase addition (MCNH). Hyphal aggregation and pelletization occurred in the latter two cultures. | PMC10177860 | foods-12-01784-g007.jpg |
0.455 | fded308ce551455da0a4ae690d15f0fc | Positions and areas of the body at risk for pressure ulcers. | PMC10178524 | healthcare-11-01222-g001a.jpg |
0.427003 | d889d294abdf47878bea3114e2ee777c | The Stages of Pressure Ulcer. | PMC10178524 | healthcare-11-01222-g002.jpg |
0.49884 | fb12eae88e2b43fa92facaf4d43d3d87 | Applications of deep learning algorithms for medical images. | PMC10178524 | healthcare-11-01222-g003.jpg |
0.469507 | bcb0a1fa7c054130a8d7bc52240a92be | Architecture diagram for YOLOv5, adapted from [74]. YOLOv5 introduced a new architecture that includes a scaled YOLOv3 backbone and a novel neck design, which consists of SPP and PAN modules. | PMC10178524 | healthcare-11-01222-g004.jpg |
0.410932 | e3e2b683573f4e17883f66ed267fc087 | Bar chart showing the distribution of pressure ulcer stages and non-pressure ulcers in the dataset. | PMC10178524 | healthcare-11-01222-g005.jpg |
0.388589 | f8692893c1b24816aef4dfed1307ec2b | The training results. | PMC10178524 | healthcare-11-01222-g006.jpg |
0.427476 | 7d04dabda53f43b8a8febed04e02e85c | Precision confidence curve. | PMC10178524 | healthcare-11-01222-g007.jpg |
0.465144 | deb0b6ec743845deac5bb0f5b2772a9e | Recall confidence curve. | PMC10178524 | healthcare-11-01222-g008.jpg |
0.466319 | 965a5b53d930451e849bf5ca91361c06 | Precision–recall curve. | PMC10178524 | healthcare-11-01222-g009.jpg |
0.464569 | 5515fa44f4b2495f83ca0bf61dc751cb | F1 score curve. | PMC10178524 | healthcare-11-01222-g010.jpg |
0.421555 | 91dadf5178ae432d9610d85fb6c1517f | Confusion metrics. | PMC10178524 | healthcare-11-01222-g011.jpg |
0.400936 | 0a992fcee6444e50bd1322e936718023 | Representative Western blot detection of HNE conjugates of plasma proteins of control volunteers (C) and schizophrenia patients (P). Positions of molecular mass standards are indicated. Adapted from [21]. | PMC10178941 | ijms-24-07991-g001.jpg |
0.424181 | ac021d67d15c45c99915cb8cb7fed98a | Overview of mechanisms of mitochondrial dysfunction leading to neuroprogressive changes in schizophrenia. LDH—lactate dehydrogenase, OXPHOS—oxidative phosphorylation, ROS—reactive oxygen species, I–IV—enzyme complexes of OXPHOS. | PMC10178941 | ijms-24-07991-g002.jpg |
0.462304 | e67af424135741db801fcf7b6a14122a | Growth performance of mirror carp at different treatments fed with dies containing fishmeal (FM), soybean meal (SM), glycinin (FMG), B-conglycinin (FMc), AKG+glycinin (FMGA), AKG+B-conglycinin (FMcA) after eight weeks. (A) WG, weight gain (%); (B) SGR, specific growth rate (%/day); (C) SR, survival rate (%); (D) PE, protein effiency (%); (E) FCR, feed conversion ratio; Data are presented as mean + SE, (n = 3). a, b, c Mean values with different letters were significantly different (P<0.05). | PMC10179059 | fimmu-14-1140012-g001.jpg |
0.456148 | 439c01619e054adbb316e4dc0e08fb1e | Antioxidative ability in the hepatopancreas of mirror carp at different treatment fed with diets containing fishmeal (FM), soybean meal (SM), glycinin (FMG), B-conglycinin (FMc), AKG+B-conglycinin (FMcA) after eight weeks. (A) T-SOD, total superoxide dismute (U/mg prot); (B) MDA, malondialdehyde (mmol/mg prot). (C) CAT, catalase (U/mg prot); (D) GSH, glutathione (umol/gprot); Data are presented as mean +SE, (n = 6) a, b, c Mean values with different letters were significantly different (P<0.05). | PMC10179059 | fimmu-14-1140012-g002.jpg |
0.390401 | 2f40d65b1729490b99d47eb3f7791961 | Relative expression levels of inflammatory cytokins in the intestine of mirror carp at different treatments fed with diets containing fishmeal (FM), soybeans meal (SM), glycinin (FMG), B-conglycinin (FMc), AKG+B-conglycinin (FMcA) after eight weeks. TNF-a, tumor necrosis factor alfa; TGF-B1, transforming growth factor beta; IL-1B, interleukin-1 beta. Data are presented as means + SE, (n = 3). a, b, c Mean values with different letters were significantly different (P<0.05). | PMC10179059 | fimmu-14-1140012-g003.jpg |
0.394211 | 844ca1ed3b054bfda6374b8ceaafa91c | Relative expression levels of junction protein in the intestine of mirror carp at different treatment fed with the diets containing fishmeal (FM), soybean meal (SM), glycinin (FMG), B-conglycinin (FMcA)< AKG+B-conglycinin (FMGA), AKG+B-conglycinin (FMcA) after eight weeks. Data are presented as means + SE, (n = 3). a, b, c Mean values with different letters were significantly different (P<0.05). | PMC10179059 | fimmu-14-1140012-g004.jpg |
0.413872 | 596d2999e51e4f918214370bc6a6f5b1 | Relative expression levels of apoptosis factors in the intestine of mirror carp at different treatments fed with diets containing fishmeal (FM), soybean meal (SM), glycinin (FMG), B-conglycinin (FMc), AKG+ glycinin (FMGA), AKG+B-conglycinin (FMcA) after eight weeks. Data are presented as means + SE, (n = 3). a, b, c Mean values with different letters were significantly different (P<0.05). | PMC10179059 | fimmu-14-1140012-g005.jpg |
0.409113 | 15e9158f16f7439da019f7fc0b5cf572 | Relative expression levels of AMPK/ACC and TOR signaling pathways in the intestine of mirror carp at different treatments fed with diets containing fishmeal (FM), soybean meal (SM), glycinin (FMG), B-conglycinin (FMc), AKG+ glycinin (FMGA), AKG+B-conglycinin (FMcA) after eight weeks. AMPKa, AMP-activated protein kinase gamma; ACC, acetyl-CoA carboxylase; TOR, target of rapamycin; 4E-BP, eIF4E-binding protein. Data are presented as means + SE, (n = 3). a, b, c Mean values with different letters were significantly different (P<0.05). | PMC10179059 | fimmu-14-1140012-g006.jpg |
0.478003 | 9318659071134e629c290fb4251db8ca | Morphology of the intestines of mirror carp at different treatments fed with diets containing fishmeal (FM), soybean meal (SM)m glycinin (FMG), B-conglycinin (FMc), AKG+ glycinin (FMGA), AKG+B-conglycinin (FMcA) after eight weeks. PI, proximal intestine; MI, mid intestine; DI, distal instestine. (A) villus height (um); (B) crypt depth (um); (C) mucosal thickness (um). Data are presented as means + SE, (n = 3). a, b, c Mean values with different letters were significantly different (P<0.05). | PMC10179059 | fimmu-14-1140012-g007.jpg |
0.43731 | a6520eed3c8244d6b61617719f7d8379 | Key enzymes in the tricarboxylic acid cycle and Na+/K+-ATPase in the intestine fed with diets containing fishmeal (FM), soybean meal (SM), glycinin (FMG). B-conglycinin (FMc), AKG+ glycinin (FMGA) AKG+B-conglycinin (FMcA) after eight weeks. PI, proximal intestine; MI, mid intestine; DI, distal intestine. (A) CS, Citrate synthase; (B) ICD, Isocitarte dehydrogenase; (pg/mL) (C) a-KGDHC, a-ketaglutarte dehydrogenase complex (pg/mL); (D) Na+/K+-ATPase (umol/L). Data are presented as means +SE, (n = 3). a, b, c Mean values with different letters were significantly different (P<0.05). | PMC10179059 | fimmu-14-1140012-g008.jpg |
0.374212 | 45131aa974f94adcaea3b06b8b9e8d14 | Example of TaCKX GFM and NAC2 expression profiles in 7 DAP spikes, seedling roots, and phenotypic traits in the maternal parent, paternal parent, and their six F2 progeny, from reciprocal cresses of S12B × S6C, C1 (A) and S6C × S12B, C2 (B). The data represent mean values with standard deviation. Black and red asterisks indicate statistical significance compared to the maternal parent or paternal parent, respectively (* 0.05 > p ≥ 0.01, ** 0.01 > p ≥ 0.001, *** p < 0.001) using the ANOVA test followed by the LSD post hoc test (STATISTICA 10, StatSoft). | PMC10179260 | ijms-24-08196-g001.jpg |
0.559193 | a055ab2025534ca2bde420a37be1b2e2 | Models of up- (↑) or down-regulation (↓) of TaCKX GFMs and NAC2 in low-yielding maternal parent crossed with higher-yielding paternal parent and their F2 progeny. | PMC10179260 | ijms-24-08196-g002.jpg |
0.455384 | e6983c37569a499eb89702b200dcf653 | Regulation of yield-related traits by TaCKX GFMs and NAC2 in the high-yielding progeny of F2 based on correlation coefficients. | PMC10179260 | ijms-24-08196-g003.jpg |
0.387029 | 15126d8d85c14694864a72977c68761c | Diffraction patterns of the precursor powder calcined at 800 °C, 1000 °C, and 1200 °C. | PMC10179874 | molecules-28-03932-g001.jpg |
0.486988 | f7a2fff1c1b74332b266c49b94165086 | SEM images of the (A) precursor powder and (B) calcined powder at 1200 °C. | PMC10179874 | molecules-28-03932-g002.jpg |
0.428337 | 8cf69f8722e04272bcb29ae711504038 | TEM images of the precursor powder calcined at 1200 °C. | PMC10179874 | molecules-28-03932-g003.jpg |
0.504829 | d2bc51b2ac014eeaaad74ca00795a759 | (A) Full XPS spectrum of the h-YMnO3 powders. Narrow scan of (B) Y 3d, (C) Mn 2p, and (D) O 1s levels. | PMC10179874 | molecules-28-03932-g004.jpg |
0.406183 | b2c1fae8b70b43d68e0494e216bbdcdd | (A) UV-Vis absorbance spectrum of the h-YMnO3 powders. (B) Tauc plot was used to determine the band gap. | PMC10179874 | molecules-28-03932-g005.jpg |
0.429993 | de5fae093fc94b66a8519be886b1b13f | Conduction band (CB) and valence band (VB) positions for h-YMnO3. | PMC10179874 | molecules-28-03932-g006.jpg |
0.462733 | 57c5415f81de4daa847813717e96a293 | Diagram of the setup for the photocurrent test. | PMC10179874 | molecules-28-03932-g007.jpg |
0.39122 | 6f530184cf9c4b50b455f52aeaf1c4ac | (A) Spectrum of the violet LED. (B) A plot of the photocurrent using violet light, with 2 min on/off cycles at the fixed optical power of 100 mW/cm2. | PMC10179874 | molecules-28-03932-g008.jpg |
0.43259 | 1c296631cf8146319e22c450316f81c6 | Photoelectric response at λ = 405 nm, using optical powers ranging from 20 to 100 mW/cm2, with on/off cycles of 2 min. | PMC10179874 | molecules-28-03932-g009.jpg |
0.373963 | 6f9f1dc198304f5394bbb4cbd11bf702 | (A) Spectrum of the red LED. (B). A plot of the photocurrent using red light with 2 min on/off cycles at the fixed optical power of 100 mW/cm2. | PMC10179874 | molecules-28-03932-g010.jpg |
0.414484 | b5d50284f7e543a0869b853f0a18dc30 | Photoelectric response at λ = 642 nm, using optical powers in the range of 10 to 100 mW/cm2, with on/off cycles of 2 min. | PMC10179874 | molecules-28-03932-g011.jpg |
0.42003 | d2fca3d8b69f4733a734c1ad1e8fba42 | Photocurrent plot of Y2O3 pellet using violet light (λ = 405 nm), with 2 min on/off cycles at Ee = 100 mW/cm2. | PMC10179874 | molecules-28-03932-g012.jpg |
0.466709 | 2947ce7bcb0847f6a1bbbb4e48803b3d | (A) UV-Vis absorbance spectrum of malachite green solutions containing h-YMnO3 as a photocatalyst after exposure to violet light. (B) Percentage degradation. (C) Linear fit corresponds to the modified Freundlich kinetic model. | PMC10179874 | molecules-28-03932-g013.jpg |
0.44725 | 222ff068627d42dfa07d5af8cdc98636 | Diffraction pattern of the h-YMnO3 powders after being used as photocatalysts. | PMC10179874 | molecules-28-03932-g014.jpg |
0.457614 | ecc60031cd304bceb93a7548c3c46dc4 | Narrow scan of Mn 2p and O 1s from the h-YMnO3 powders after being used as a photocatalysts. (A) Mn XPS spectrum; (B) O XPS spectrum. | PMC10179874 | molecules-28-03932-g015.jpg |
0.534128 | c51748c34d024045a890fa23f36b56b0 | Effect of ISPA, p-BZQ, and EDTA scavengers on the photodegradation of the MG dye using h-YMnO3 as the photocatalyst and violet light with an Ee = 100 mW/cm2. | PMC10179874 | molecules-28-03932-g016.jpg |
0.472545 | fd3d298165db4c5bababb054a6868d71 | Contribution of pH to the photodegradation of the MG dye. | PMC10179874 | molecules-28-03932-g017.jpg |
0.479108 | cc7c3f2d95ea447daf39bf451978cd07 | Photocatalytic degradation mechanism for the MG dye using h-YMnO3 as the photocatalyst under visible light exposure (λ = 405 nm). | PMC10179874 | molecules-28-03932-g018.jpg |
0.394504 | f94587331fd245919d3f06e8ec93bf97 | Bars represent at least three independent experiments and are plotted as mean ± SD. Significantly differences are depicted by *** indicate p < 0.0001. | PMC10179874 | molecules-28-03932-g019.jpg |
0.421442 | ac87bdbc8a13477eb4cb77a420010f60 | Intake, absorption, and transportation of iron in the body. Orally administered heme-Fe is absorbed via heme carrier protein (HCP-1) in the small intestine. Non-heme Fe is primarily in the form of Fe3+ and is reduced to Fe2+ by ferrireductase (FR), such as duodenal cytochrome b, or by ascorbic acid in food. Thereafter, Fe2+ is transported via divalent metal transporter (DMT1). The absorption is influenced by phosphate, phytate, Zn2+, and Cu2+ in food. Some of the absorbed Fe2+ is transported to the liver and stored in ferritin as Fe3+ or exported via ferroportin (FPN). The Fe2+ is oxidized to Fe3+ by ferroxidase (FRO), such as ceruloplasmin, binds to transferrin (TF) or citrate in the blood, and is transported. | PMC10180548 | nutrients-15-02067-g001.jpg |
0.469675 | 9e7a23d641ec45a0a7e4272f08158464 | Characteristics of amyloidogenic proteins and the link with trace elements. (a) Amyloid precursor protein (APP) and ß-amyloid protein (AßP). The expression of APP is regulated by the level of Fe through the iron-responsive element-iron responsive protein (IRE-IRP) pathway. Al3+ and/or Mn3+ can influence the IRE-IRP pathway. APP possesses Cu and/or Zn binding domains and reduces Cu2+ to Cu+. APP also regulates Fe2+ efflux by stabilizing ferroportin (FPN). AßP, which is derived from APP by the enzymatic cleavage of ß-secretase and γ-secretase. The primate AßP possesses the ability to bind metals such as Al, Zn, Cu, Fe, and Mn, although rodent AßP does not. The primary sequences of primate AßP and rodent AßP differ by only three metal-binding amino acids (Arg5, Tyr10, and His13; shown in Italic and Bold form). (b) Prion protein (PrPC). The expression of PrP is regulated by the level of Fe through the IRE-IRP pathway as well as APP. PrPC can bind Cu2+, Zn2+, Mn2+, and other metal ions. Four Cu atoms can bind to the octarepeat domain in PrPC, and two Cu bind to other His residues (His96 and His111). PrP106-126, which is a neurotoxic fragment peptide, can bind to Cu and other metal ions. PrPC possesses the ferrireductase activity that converts Fe3+ to Fe2+. (c) α-Synuclein. The expression of α-synuclein is regulated by the level of Fe through the IRE-IRP pathway as well as APP and PrPC. α-Synuclein reportedly binds Cu2+, Zn2+, Mn2+, and other metal ions in its N-terminal and C-terminal domains. α-Synuclein possesses the ferrireductase activity that converts Fe3+ to Fe2+, similar to PrPC. | PMC10180548 | nutrients-15-02067-g002.jpg |
0.441775 | e003e591c4cd4f3ebe4a3cca8dee14f3 | Hypothetical scheme of the roles of trace elements in synapses: Overview of the entry of trace elements and its roles in synapses. APP is primarily localized to the presynaptic membrane. PrPC is localized to the postsynaptic membrane. α-Synuclein is mainly localized to the presynaptic domain and membranes of synaptic vesicles. Orally administered Fe is absorbed in the gastrointestinal tract and transported in the blood as Fe3+ by binding to transferrin (TF) or citrate. TF-bound Fe3+ can enter neurons or glial cells via its receptors (TF-R). Thereafter, Fe3+ is converted to Fe2+ by ferrireductases (FR). α-Synuclein acts as a ferrireductase in the presynaptic domain and functions to provide bioavailable Fe2+ to enzymes requiring it in mitochondria and other organelles. PrPC acts as a ferrireductase in the postsynaptic domain, and the converted Fe2+ is transported into cells by the complex of ZIP14 and divalent metal transporter 1 (DMT1). Fe3+ binding with citrate is also reduced to Fe2+ by FR and enters cells via DMT1. Excess intracellular Fe2+ is exported via ferroportin (FPN). APP stabilizes FPN and regulates Fe2+ efflux from cells. α-Synuclein and FPN coexist in presynaptic vesicles and control Fe homeostasis in the vesicles. Excess synaptic Fe2+ is oxidized to Fe3+ by ferroxidase (FRO) and turns into circulation. Meanwhile, Fe controls the expressions of these proteins. Mn can influence this IRE-IRP pathway and affect the expressions. Orally administered Zn and Cu enter into the neurons or glial cells, accumulate in synaptic vesicles, and are activity-dependently released to the synaptic clefts. Secreted Zn as well as Cu bind to NMDA-type glutamate receptors or other receptors, and control neuronal excitability. Synaptic Zn is translocated into postsynaptic neurons through voltage-dependent Ca2+ channels (VDCC), NMDA-type glutamate receptor, and Ca2+-permeable APMA receptor as well as Ca2+. PrPC acts as a Zn sensor and transports Zn to postsynaptic neurons. Zn transporters such as ZnT1 and ZIP4 contribute to regulating Zn levels in the synaptic clefts. NMDA-R, NMDA-type glutamate receptor; AMPA-R, AMPA-type glutamate receptor; FPN, ferroportin; TF, transferrin; VDCC; voltage-dependent calcium channel, colored circles represent Zn, Cu, Fe, Mn, Ca, and glutamate. | PMC10180548 | nutrients-15-02067-g003.jpg |
0.462071 | cbdaaf60cee04dea8c537c1a1371878d | Hypothetical scheme of the roles of trace elements in synapses: Detailed cross-talk of trace elements and amyloidogenic proteins at synaptic clefts. Zn and Cu are secreted to the synaptic clefts during neuronal excitation and transmit the information of neuronal firing to neighboring synapses by binding to NMDA-type glutamate receptors and other receptors. It is suggested that both Zn and Cu contribute to synaptic plasticity. In postsynaptic membranes, PrPC binds to Cu, Zn, and Fe. PrPC acts as a Zn2+ sensor and contributes to the uptake of Zn by AMPA-type glutamate receptors. Additionally, PrPC acts as a ferrireductase and controls Fe influx via ZIP14/DMT1. Other Zn transporters (ZnT1 and ZIP4) also localize at the postsynaptic domain and maintain Zn2+ levels in the synaptic clefts. ZnT1 also regulates NMDA-R and Ca2+ channels. APP binds to Cu and/or Zn in the presynaptic membranes. Considering the narrowness of the synaptic clefts (approximately 20 nm), PrPC may provide Cu2+ to APP, and APP converts Cu2+ to Cu+ and may provide Cu+ to copper transporter 1 (CTR1) for re-uptake into presynaptic vesicles. Zn2+ and Cu2+ influence the secretion of AβP from APP by binding with presenilins (PS), and γ-secretases. Metallotionein3 (MT3) and carnosine (Car) also exist in synaptic clefts and regulate the homeostasis of Zn and Cu. In pathological conditions, AβP and other amyloidogenic proteins form pore-like structures on membranes. The amyloid pores cause Ca2+ dyshomeostasis and trigger various neurodegenerative processes. Trace elements can contribute to the formation of amyloid pores by accelerating the oligomerization of amyloidogenic proteins. NMDA-R, NMDA-type glutamate receptor; AMPA-R, AMPA-type glutamate receptor; FPN, ferroportin; PS, presenilins; VDCC, voltage-dependent calcium channel; colored circles represent Fe, Zn, Cu, Fe, Mn, Al, and glutamate. | PMC10180548 | nutrients-15-02067-g004.jpg |
0.65858 | ac44b6880f7541a29d4cfe8dd81ae866 | Experimental design. | PMC10180667 | nutrients-15-02065-g001.jpg |
0.575643 | c1e1ff19c291470fae50dcdef947d49d | Venn diagram of the action targets of four active components of FS and the targets of cholestasis disease. | PMC10180667 | nutrients-15-02065-g002.jpg |
0.431736 | 8dc6f7a4bf59409ca187f1d55493c175 | Network pharmacology research results of FS in the treatment of cholestasis. (a) “components-targets” network; (b) PPI network of four active components of FS in the treatment of cholestasis; (c) Network topology analysis of PPI network; (d) Top 25 results of KEGG pathway enrichment analysis; (e) Top 25 results of GO biological process enrichment analysis. | PMC10180667 | nutrients-15-02065-g003.jpg |
0.391118 | 3e106691081f4ec7b5fb82212a60a249 | “Components-targets-pathways” network. | PMC10180667 | nutrients-15-02065-g004.jpg |
0.40292 | 4cb64bbdd7354bc6a437789849c166b8 | Effect of FS on toll-like receiver signaling pathway. | PMC10180667 | nutrients-15-02065-g005.jpg |
0.448341 | 66b72ab6f27e472885462dc9fafd3ac2 | Network pharmacology research results of forsythoside A (FTA) in the treatment of cholestasis. (a) PPI network of targets for FTA treatment of cholestasis; (b) Network topology analysis of PPI network; (c) Top 20 results of KEGG pathway enrichment analysis; (d) Top 20 results of GO biological process enrichment analysis. | PMC10180667 | nutrients-15-02065-g006.jpg |
0.504771 | 5c0c92cec24447529c389125e9b81720 | Conformation of ligand and receptor binding. The binding conformation and interaction force between FTA and MMP-2 (a), TLR4 (b), MYD88 (c), and NFKB1 (d). | PMC10180667 | nutrients-15-02065-g007.jpg |
0.398373 | 60de45a7be234b57bcf8a1a2315692b7 | FTA alleviated DDC-induced liver injury and fibrosis. (a) HE staining. Black arrow: neutrophil infiltration; Blue arrow: pigment deposition; Green arrow: duct proliferation. (b,c) Serum AST and ALT levels measured by biochemical kits. (d) Masson staining. (e,f) Protein expression and quantitative analysis of MMP-2. (g) Liver MMP-2 mRNA expression was detected by RT-qPCR. (h,i) Protein expression and quantitative analysis of α-SMA. (j) α-SMA was detected by immunohistochemistry. ## p < 0.01 vs. Control group, * p < 0.05 vs. 0.1% DDC group, ** p < 0.01 vs. 0.1% DDC group. | PMC10180667 | nutrients-15-02065-g008.jpg |
0.393255 | 6f6e06b0ba0243c1ab1cc33999dd5cd6 | FTA alleviated DDC-induced cholestatic liver injury by inhibiting the release of inflammatory factors and the TLR4/MYD88/NF-κB signaling pathway. (a–c) Serum TNF-α, IL-6, and IL-1β levels measured by ELISA kits. (d–f) Liver TNF-α, IL-6, and IL-1β mRNAs expression detected by RT-qPCR. (g) F4/80 detected by immunohistochemistry. (h) Quantitative analysis of F4/80. (i) Liver F4/80 mRNA expression detected by RT-qPCR. (j–o) Proteins expression and quantitative analysis of TLR4, MYD88, and ratio of p-NF-κB p65/NF-κB p65. (p) p-NF-κB p65 detected by immunohistochemistry. # p < 0.05 vs. Control group, ## p < 0.01 vs. Control group, * p < 0.05 vs. 0.1% DDC group, ** p < 0.01 vs. 0.1% DDC group. | PMC10180667 | nutrients-15-02065-g009.jpg |
0.409594 | bd516a3187944909b611cb959a842253 | Experimental flow and molecular mechanism diagram in this study. | PMC10180667 | nutrients-15-02065-g010.jpg |
0.427736 | 9cad0fb6ceb64a59a74f764c3b216bfb | Ferritin level in patients on regular RBCX. aRBCX: Automated red blood cells exchange, MET: Manual exchange transfusion; Y-axis demonstrate the serum ferritin level (ug/L) among each patient, X-axis demonstrates the session in which the ferritin was measured among the two groups. Each vertical line represents a different patient with his recorded ferritin readings throughout the follow-up period; 11 patients were on aRBCX, while 9 patients were on MET. Chelation therapy began at ferritin level ≥1000 ug/L | PMC10180797 | AJTS-17-91-g001.jpg |
0.480124 | 67267568ba24403c9e7c1203df6b5713 | Adsorption of cobalt ions on nanocellulose at 20 °C. | PMC10180900 | polymers-15-02143-g001.jpg |
0.456907 | 585b8e83b55b4b18aa53e166c8579d15 | Adsorption rate of cobalt ions on nanocellulose at Co = 200 ppm and varying stirrer speeds. | PMC10180900 | polymers-15-02143-g002.jpg |
0.455173 | 345d9a60911c4f18af89afe9e5c7f28c | Adsorption rate of cobalt ions on nanocellulose at 200 rpm and varying initial concentrations. | PMC10180900 | polymers-15-02143-g003.jpg |
0.427358 | 7a1c68f3f3a748e6850ba797e89b8d9b | TEM of the nanocellulose (200,000×). | PMC10180900 | polymers-15-02143-g004.jpg |
0.494709 | 8f7e311619d4493fa7a8c5692713598f | FT-IR spectrum of nanocellulose. Peak 1 (1027 cm−1): C-O stretching in cellulose. Peak 2 (1164 cm−1): C-O stretching in cellulose and hemicellulose. Peak 3 (1730 cm−1): C=O stretching in hemicellulose. Peak 4 (3000–3399 cm−1): CH stretching in cellulose, hemicellulose. | PMC10180900 | polymers-15-02143-g005.jpg |
0.501422 | 74929d45ec2a4f8ea606dc8df7cb20e5 | Nitrogen adsorption–desorption isotherms. | PMC10180900 | polymers-15-02143-g006.jpg |
0.427718 | afa3f288aa33423880f4d646d675b520 | Variation of zeta potential versus pH for the nanocellulose. | PMC10180900 | polymers-15-02143-g007.jpg |
0.507905 | 9f8b38c2b1d6474a938ed5a5e396f5c9 | XRD for nanocellulose. | PMC10180900 | polymers-15-02143-g008.jpg |
0.397376 | 624f994469534c73825ff5a9e55e9829 | Langmuir isotherm fitting the experimental data of cobalt ion adsorption onto nanocellulose. | PMC10180900 | polymers-15-02143-g009.jpg |
0.464535 | 50189cfcb9bf424ba68d8200b2a9b954 | Freundlich isotherm fitting the experimental data of cobalt-ion adsorption onto nanocellulose. | PMC10180900 | polymers-15-02143-g010.jpg |
0.382935 | f1d0e62326e8440d87cd4c825bcf83a0 | Plots of pseudo-first-order model for adsorption of cobalt ions on nanocellulose at different agitation speeds. | PMC10180900 | polymers-15-02143-g011.jpg |
0.437306 | 008cf1ce49af4b819c81eaa74bf9f333 | Plots of pseudo-first-order model for adsorption of cobalt ions on nanocellulose at different initial concentrations. | PMC10180900 | polymers-15-02143-g012.jpg |
0.502396 | 5ce7eb01cf7b422486825897e926419f | Graphs of the pseudo-second-order model for cobalt ions adsorption on nanocellulose at various agitation speeds. | PMC10180900 | polymers-15-02143-g013.jpg |
0.428198 | 2bd28b96a21f4626a8a802f81382eb2a | Graphs of the pseudo-second-order model for cobalt ions adsorption on nanocellulose at different initial concentrations. | PMC10180900 | polymers-15-02143-g014.jpg |
0.468919 | c33969096477478493efcb667770432f | Plots of the Elovich model for adsorption of cobalt ions on nanocellulose at different agitation speeds. | PMC10180900 | polymers-15-02143-g015.jpg |
0.410835 | fb5362a28f564911a4699811c9ac4f8e | Plots of the Elovich model for adsorption of cobalt ions on nanocellulose at different initial concentrations. | PMC10180900 | polymers-15-02143-g016.jpg |
0.531793 | 601ac1e9d0f743f6b3cade1d9d0c2b45 | The plot of the intraparticle diffusion model for adsorption of cobalt ions on nanocellulose at different agitation speeds. | PMC10180900 | polymers-15-02143-g017.jpg |
0.475573 | 827e356553e04877b4d1b4083084c8a8 | The plot of the intraparticle diffusion model for adsorption of cobalt ions on nanocellulose at different initial concentrations. | PMC10180900 | polymers-15-02143-g018.jpg |
0.438369 | 2026c8f47c454c1b92bde70fd8d07ba3 | The plot of log Dp against log agitation speed for adsorption of cobalt ions on nanocellulose at different agitation speeds. | PMC10180900 | polymers-15-02143-g019.jpg |
0.455267 | 3c9fc9c7ab8e40cd87f47e5660f5d926 | The plot of log Dp against log initial concentration for adsorption of cobalt ions on nanocellulose at different initial concentrations. | PMC10180900 | polymers-15-02143-g020.jpg |
0.442309 | 8d99f81018c646dca315fb0d77d3b62f | An illustration of IF neuron-based gradient BP framework. (1) Forward pass: The total input current is the weighted sum of pre-spike trains from the pre-layer, then transmitted to the next neuron.The activation of the IF neuron is sent to the post-layers to calculate the loss. (2) Backward pass: The surrogate gradient trick is used to approximately formulate the activation function of the IF neuron. The gradients of the loss function are propagated backward down to the input layer through the hidden layers using the recursive chain rule, and the weights are updated using the gradient descent algorithm. | PMC10181528 | sensors-23-04532-g001.jpg |
0.482968 | d6119465cd0244e0a15d670a45b82d81 | SpikeConvFlowNet architecture. (A) shows the topology of the method, including four parts: RGB stream, optical flow stream, merging block, and fully-connected layers; (B) and (C) show the structure of the SpikeConv Block and the merging block, respectively. | PMC10181528 | sensors-23-04532-g002.jpg |
0.434073 | 15302ed3ca4c4a06b3a079fdd2ac70ba | The histogram shows the average spiking activity in each block on four testing datasets. For each pair, the left denotes the number of pixels in the output of the block-layers, while the right denotes the number of spikes fired in the block-layers. | PMC10181528 | sensors-23-04532-g003.jpg |
0.38869 | 0adde21cfc0542a19973d3898d6fc550 | Different input paradigms between SpikeConvFlowNet and existing models. Most existing models commonly extract features from video segments, while SpikeConvFlowNet processes the frames from videos one by one, which reduces memory consumption. | PMC10181528 | sensors-23-04532-g004.jpg |
0.441833 | 0642bbb16738485f950449ae16062ec3 | The typical scenes in four datasets. The videos in the Crowd Violence and RWF2000 datasets include more crowd and complex real-life scenes than the first two. | PMC10181528 | sensors-23-04532-g005.jpg |
0.422537 | 67d7d8cab1564315b11c8922e8ade162 | Confusion matrix of experimental results on four datasets using SpikeConvFlowNet. | PMC10181528 | sensors-23-04532-g006.jpg |
0.437622 | 12b0e029b1744002b9ce5eb7c68ce7f9 | Samples from the feature maps in hidden layers. (A–C) denote SpikeConvBlock1, SpikeConvBlock2, and SpikeConvBlock3 in the RGB stream. As for each heatmap pair, the above is before operating through the IF neuron, while the below is for the spiking activity after the IF neuron. It shows that the output of each layer is a sparse matrix. | PMC10181528 | sensors-23-04532-g007.jpg |
0.456028 | 8f877902b7f841158cc28e567f0e2a37 | Temperature dependence of the spectral line strength S(T), the gas-density-corrected line strength S(T)/T and the first derivative of S(T)/T, as well as the relative temperature coefficient δ S(T)/T δ T/(S(T)/T)⋅100 [16] in the temperature window between 293 and 473 K for the used H2O spectral line at 7299.43 cm−1. | PMC10181621 | sensors-23-04345-g001.jpg |
0.431762 | 809129e16d6f46cc9594dea0e9b6c454 | (a) CAD rendering of the CMPAC with laser beam. (b) Plot of the normalized sample weights of the beam path in our CMPAC configuration over the radius of the cell. The laser beam does not reach/measure in an inner circle of 8.5 mm radius. This we termed “dark zone”. | PMC10181621 | sensors-23-04345-g002.jpg |
0.423716 | 3d2986e0fee2417d88477daec4f6b325 | CAD rendering of the dynH2O setup with cut-through of the flow section, showing: ① the optics unit of the open-path reference dTDLAS hygrometer with the CMPAC, ② pressure sensors, ③ spatially scanned sampling line of the extractive SEALDH-II dTDLAS hygrometer, ④ automated positioning unit for the extractive gas probe, ⑤ gas extraction probe with critical orifice, ⑥ optical measurement plane, ⑦ aluminum honeycomb and ⑧ glass sinter filter to smooth the spatial flow profile, ⑨ injector plate, ⑩ base-flow gas mixing/switching/preparation unit and ⑪ stationary temperature sensors (fast thermocouple plus accurate platinum thermometer, PT100). | PMC10181621 | sensors-23-04345-g003.jpg |
0.455293 | 3697fafad2bb4ae8a342385f2ed22deb | The 2D planar gas temperature distribution (color-coded) 14.5 cm behind the optical measurement plane of the circular cell derived from 13 local T-measurements (black circles) along the Y- and Z-axis. The plots on the top and left show the temperature profile along the Y- and Z-axis, respectively, as a solid line. The dashed line indicates the maximum value for each point on the Y-axis along the Z-axis and vice versa. | PMC10181621 | sensors-23-04345-g004.jpg |
0.485623 | 1f9825592c2a41e9a714128da8c1b728 | (a) Plot of the maximum relative concentration difference at one sample point in the cross section 7 cm behind the optical measurement plane relative to the average concentration in the cross section at that time. The maximum difference is reached at 1.01 s. (b) Concentration distribution in the cross section 7 cm behind the optical measurement plane of the circular cell, 1.01 s after the concentration step was triggered. The plots on the top and left in (b) show the concentration profile along the Z- and Y-axis, respectively, as a solid line. The dashed line indicates the maximum value for each point on the Y-axis along the Z-axis and vice versa. | PMC10181621 | sensors-23-04345-g005.jpg |
0.505633 | ab4074cc393149d3a340061574247723 | (a) The 2D planar temperature distribution (color-coded) in the CMPAC, as described in Section 3.1, with the laser beam pattern (red lines), and the local sample points along the optical path (blue dots, only every 100th sample point is shown) superimposed. (b) Histogram of the local temperatures along the optical path (orange) compared to the local temperatures in the entire cross section (blue) derived from the interpolated gas temperature measurements (see Figure 4). | PMC10181621 | sensors-23-04345-g006.jpg |
0.518796 | 595a710a555e4b43b9aa9627aee4247f | Top: Simulated, integrated absorbance spectrum of the 7299.43 cm−1 H2O line along the CMPAC light path, taking into account in scenario (a) (in blue) the measured and interpolated spatial heterogeneities in gas temperature and H2O concentration and in scenario (b) (dashed orange) using the average concentration in the cross section and the temperature at the ring center as single “average” values for the entire optical path. The range in which the line area is determined by numeric integration is shown in green. Bottom: Residual between scenario (a) and (b). The relative difference in the peak absorption at the line peak between scenario (a) and (b) is 13.4%. | PMC10181621 | sensors-23-04345-g007.jpg |
0.445335 | 4a04d5f4081144e1a3cf2f492d58995d | (a) Set of six temperature profiles used to calculate the results shown in (b), with the temperature at the tube center shown on top of the profiles on the left and the average temperature across the full T profile shown as dashed line. (b) Relative difference between the line area calculated by integrating the temperature distributions shown in (a) along the optical path to the line area calculated with a single temperature value. The single temperature values used to evaluate the simulated absorption spectrum (see Figure 7) are (1) the average temperature along the optical path, (2) the average temperature in the full 2D cross section, (3) the temperature at the tube center and (4) the wall temperature (which was in the simulations fixed to 293 K). The pressure and concentration distributions for all those scenarios were identical and assumed to be homogeneous: p = 1 atm and H2O = 1000 ppm. | PMC10181621 | sensors-23-04345-g008.jpg |
0.448611 | c66b19a4f0a4440697c0409b5ed139c6 | Locations of 4678 PurpleAir indoor monitors in the three West Coast states. Shown are the 3500 PA-I (single sensor) and 1178 PA-II (double sensor) monitors. | PMC10181715 | sensors-23-04387-g001.jpg |
0.429414 | 923233ab86a94db8ae3cc77e96e6ea04 | Locations of regulatory sites in the three-state area. There are 261 unique regulatory monitors at 175 sites. | PMC10181715 | sensors-23-04387-g002.jpg |
0.462575 | 610c13338c7943318eeec180356b9391 | Improvement in outdoor PM2.5 with distance from the regulatory monitors. | PMC10181715 | sensors-23-04387-g003.jpg |
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