Exploring the natural chemiome to target interleukin-6 receptor (IL-6R) cytokines: an atomic scale investigation for novel rheumatoid arthritis drug discovery

<div><p>ABSTRACT Natural compounds are a gold mine for treating rheumatoid arthritis (RA). The etiology of this disease is linked to inflammation, where cytokines play an important role. Strategies have been drafted for targeting cytokines as a therapeutic option in patients with RA. Inhibiting cytokines with natural compounds has become a major focus for the development of drugs to treat RA. Here, a structure-based drug design approach was employed to identify novel leads to target the interleukin 6 receptor (IL-6R). A total of 48,531 compounds of natural origin were screened. Two of these compounds were shortlisted for molecular docking simulation and tested for inhibiting gp130 dimerization in human macrophages. The results show that Lead5 (CID5329098) significantly inhibited the release of gp130 in a dose-dependent manner, similar to the inhibitory effect of LMT-28 (p<0.005). This study provides an atomic scale outcome of a single natural compound that can be developed into a RA drug.</p></div

Image_2_Fatty acid metabolism is related to the immune microenvironment changes of gastric cancer and RGS2 is a new tumor biomarker.tif

BackgroundAlterations in lipid metabolism promote tumor progression. However, the role of lipid metabolism in the occurrence and development of gastric cancer have not been fully clarifiedMethodHere, genes that are related to fatty acid metabolism and differentially-expressed between normal and gastric cancer tissues were identified in the TCGA-STAD cohort. The intersection of identified differentially-expressed genes with Geneset was determined to obtain 78 fatty acid metabolism-related genes. The ConsensusClusterPlus R package was used to perform differentially-expressed genes, which yielded divided two gastric cancer subtypes termed cluster 1 and cluster 2.ResultsPatients in cluster 2 was found to display poorer prognosis than patients in cluster 1. Using machine learning method to select 8 differentially expressed genes among subtypes to construct fatty acid prognostic risk score model (FARS), which was found to display good prognostic efficacy. We also identified that certain anticancer drugs, such as bortezomib, elesclomol, GW843682X, and nilotinib, showed significant sensitivity in the high FARS score group. RGS2 was selected as the core gene upon an analysis of the gastric cancer single-cell, and Western blotting and immunofluorescence staining results revealed high level of expression of this gene in gastric cancer cells. The results of immunohistochemical staining showed that a large amount of RGS2 was deposited in the stroma in gastric cancer. A pan-cancer analysis also revealed a significant association of RGS2 with TMB, TIDE, and CD8+ T-cell infiltration in other cancer types as well. RGS2 may thus be studied further as a new target for immunotherapy in future studies on gastric cancer.ConclusionIn summary, the FARS model developed here enhances our understanding of lipid metabolism in the TME in gastric cancer, and provides a theoretical basis for predicting tumor prognosis and clinical treatment.</p

Image_1_Fatty acid metabolism is related to the immune microenvironment changes of gastric cancer and RGS2 is a new tumor biomarker.tif

BackgroundAlterations in lipid metabolism promote tumor progression. However, the role of lipid metabolism in the occurrence and development of gastric cancer have not been fully clarifiedMethodHere, genes that are related to fatty acid metabolism and differentially-expressed between normal and gastric cancer tissues were identified in the TCGA-STAD cohort. The intersection of identified differentially-expressed genes with Geneset was determined to obtain 78 fatty acid metabolism-related genes. The ConsensusClusterPlus R package was used to perform differentially-expressed genes, which yielded divided two gastric cancer subtypes termed cluster 1 and cluster 2.ResultsPatients in cluster 2 was found to display poorer prognosis than patients in cluster 1. Using machine learning method to select 8 differentially expressed genes among subtypes to construct fatty acid prognostic risk score model (FARS), which was found to display good prognostic efficacy. We also identified that certain anticancer drugs, such as bortezomib, elesclomol, GW843682X, and nilotinib, showed significant sensitivity in the high FARS score group. RGS2 was selected as the core gene upon an analysis of the gastric cancer single-cell, and Western blotting and immunofluorescence staining results revealed high level of expression of this gene in gastric cancer cells. The results of immunohistochemical staining showed that a large amount of RGS2 was deposited in the stroma in gastric cancer. A pan-cancer analysis also revealed a significant association of RGS2 with TMB, TIDE, and CD8+ T-cell infiltration in other cancer types as well. RGS2 may thus be studied further as a new target for immunotherapy in future studies on gastric cancer.ConclusionIn summary, the FARS model developed here enhances our understanding of lipid metabolism in the TME in gastric cancer, and provides a theoretical basis for predicting tumor prognosis and clinical treatment.</p

Table_1_Fatty acid metabolism is related to the immune microenvironment changes of gastric cancer and RGS2 is a new tumor biomarker.xlsx

BackgroundAlterations in lipid metabolism promote tumor progression. However, the role of lipid metabolism in the occurrence and development of gastric cancer have not been fully clarifiedMethodHere, genes that are related to fatty acid metabolism and differentially-expressed between normal and gastric cancer tissues were identified in the TCGA-STAD cohort. The intersection of identified differentially-expressed genes with Geneset was determined to obtain 78 fatty acid metabolism-related genes. The ConsensusClusterPlus R package was used to perform differentially-expressed genes, which yielded divided two gastric cancer subtypes termed cluster 1 and cluster 2.ResultsPatients in cluster 2 was found to display poorer prognosis than patients in cluster 1. Using machine learning method to select 8 differentially expressed genes among subtypes to construct fatty acid prognostic risk score model (FARS), which was found to display good prognostic efficacy. We also identified that certain anticancer drugs, such as bortezomib, elesclomol, GW843682X, and nilotinib, showed significant sensitivity in the high FARS score group. RGS2 was selected as the core gene upon an analysis of the gastric cancer single-cell, and Western blotting and immunofluorescence staining results revealed high level of expression of this gene in gastric cancer cells. The results of immunohistochemical staining showed that a large amount of RGS2 was deposited in the stroma in gastric cancer. A pan-cancer analysis also revealed a significant association of RGS2 with TMB, TIDE, and CD8+ T-cell infiltration in other cancer types as well. RGS2 may thus be studied further as a new target for immunotherapy in future studies on gastric cancer.ConclusionIn summary, the FARS model developed here enhances our understanding of lipid metabolism in the TME in gastric cancer, and provides a theoretical basis for predicting tumor prognosis and clinical treatment.</p

Patterned Manipulated Surface Based on Femtosecond Laser with Adjustable Wetting Speed and Directional Fluid Delivery

Recently, due to the crucial roles of multifunctional liquid manipulation surfaces in biomedical transportation, microfluidics, and chemical engineering, the demand for controllable and functional aspects of directed liquid transportation has increased significantly. However, designing an intelligent manipulation surface that is easy to manufacture and fully functional remains an immense challenge. To address this challenge, a smart surface that can regulate the rate of liquid transport within a patterned channel by temperature is reported. A synergistically controlled approach of poly(N-isopropylacrylamide) and micropillar shape-memory polymers (SMPs) was used to modulate the wetting rate of liquids on surfaces. By femtosecond laser direct writing, temperature-responsive composite surfaces are embedded in the microstructure of shape-memory polymers (SMPs) in a patterned manner, resulting in the preparation of novel programmable liquid manipulation surfaces incorporating boundaries possessing asymmetric wettability. Since the smart surface is based on SMP, the superhydrophobic part in the superhydrophobic/controllable wettability patterning platform is also programmed for droplet directional transport, which takes advantage of the difference in wettability between the rewritable indentation track and the periphery to allow droplets to flow into the temperature-controlled velocity track, enriching the functionality of the surface. In addition, based on its excellent controllability and patterning, the surface has been shown to be used in microfluidic circuit chips with self-cleaning properties, which provides new ideas for circuit timing control. This study provides promising prospects for the effective development of multifunctional liquid steering surfaces, lab-on-a-chip, and microfluidic devices

Patterned Manipulated Surface Based on Femtosecond Laser with Adjustable Wetting Speed and Directional Fluid Delivery

Recently, due to the crucial roles of multifunctional liquid manipulation surfaces in biomedical transportation, microfluidics, and chemical engineering, the demand for controllable and functional aspects of directed liquid transportation has increased significantly. However, designing an intelligent manipulation surface that is easy to manufacture and fully functional remains an immense challenge. To address this challenge, a smart surface that can regulate the rate of liquid transport within a patterned channel by temperature is reported. A synergistically controlled approach of poly(N-isopropylacrylamide) and micropillar shape-memory polymers (SMPs) was used to modulate the wetting rate of liquids on surfaces. By femtosecond laser direct writing, temperature-responsive composite surfaces are embedded in the microstructure of shape-memory polymers (SMPs) in a patterned manner, resulting in the preparation of novel programmable liquid manipulation surfaces incorporating boundaries possessing asymmetric wettability. Since the smart surface is based on SMP, the superhydrophobic part in the superhydrophobic/controllable wettability patterning platform is also programmed for droplet directional transport, which takes advantage of the difference in wettability between the rewritable indentation track and the periphery to allow droplets to flow into the temperature-controlled velocity track, enriching the functionality of the surface. In addition, based on its excellent controllability and patterning, the surface has been shown to be used in microfluidic circuit chips with self-cleaning properties, which provides new ideas for circuit timing control. This study provides promising prospects for the effective development of multifunctional liquid steering surfaces, lab-on-a-chip, and microfluidic devices

Patterned Manipulated Surface Based on Femtosecond Laser with Adjustable Wetting Speed and Directional Fluid Delivery

Recently, due to the crucial roles of multifunctional liquid manipulation surfaces in biomedical transportation, microfluidics, and chemical engineering, the demand for controllable and functional aspects of directed liquid transportation has increased significantly. However, designing an intelligent manipulation surface that is easy to manufacture and fully functional remains an immense challenge. To address this challenge, a smart surface that can regulate the rate of liquid transport within a patterned channel by temperature is reported. A synergistically controlled approach of poly(N-isopropylacrylamide) and micropillar shape-memory polymers (SMPs) was used to modulate the wetting rate of liquids on surfaces. By femtosecond laser direct writing, temperature-responsive composite surfaces are embedded in the microstructure of shape-memory polymers (SMPs) in a patterned manner, resulting in the preparation of novel programmable liquid manipulation surfaces incorporating boundaries possessing asymmetric wettability. Since the smart surface is based on SMP, the superhydrophobic part in the superhydrophobic/controllable wettability patterning platform is also programmed for droplet directional transport, which takes advantage of the difference in wettability between the rewritable indentation track and the periphery to allow droplets to flow into the temperature-controlled velocity track, enriching the functionality of the surface. In addition, based on its excellent controllability and patterning, the surface has been shown to be used in microfluidic circuit chips with self-cleaning properties, which provides new ideas for circuit timing control. This study provides promising prospects for the effective development of multifunctional liquid steering surfaces, lab-on-a-chip, and microfluidic devices

Patterned Manipulated Surface Based on Femtosecond Laser with Adjustable Wetting Speed and Directional Fluid Delivery

Recently, due to the crucial roles of multifunctional liquid manipulation surfaces in biomedical transportation, microfluidics, and chemical engineering, the demand for controllable and functional aspects of directed liquid transportation has increased significantly. However, designing an intelligent manipulation surface that is easy to manufacture and fully functional remains an immense challenge. To address this challenge, a smart surface that can regulate the rate of liquid transport within a patterned channel by temperature is reported. A synergistically controlled approach of poly(N-isopropylacrylamide) and micropillar shape-memory polymers (SMPs) was used to modulate the wetting rate of liquids on surfaces. By femtosecond laser direct writing, temperature-responsive composite surfaces are embedded in the microstructure of shape-memory polymers (SMPs) in a patterned manner, resulting in the preparation of novel programmable liquid manipulation surfaces incorporating boundaries possessing asymmetric wettability. Since the smart surface is based on SMP, the superhydrophobic part in the superhydrophobic/controllable wettability patterning platform is also programmed for droplet directional transport, which takes advantage of the difference in wettability between the rewritable indentation track and the periphery to allow droplets to flow into the temperature-controlled velocity track, enriching the functionality of the surface. In addition, based on its excellent controllability and patterning, the surface has been shown to be used in microfluidic circuit chips with self-cleaning properties, which provides new ideas for circuit timing control. This study provides promising prospects for the effective development of multifunctional liquid steering surfaces, lab-on-a-chip, and microfluidic devices

Patterned Manipulated Surface Based on Femtosecond Laser with Adjustable Wetting Speed and Directional Fluid Delivery

Recently, due to the crucial roles of multifunctional liquid manipulation surfaces in biomedical transportation, microfluidics, and chemical engineering, the demand for controllable and functional aspects of directed liquid transportation has increased significantly. However, designing an intelligent manipulation surface that is easy to manufacture and fully functional remains an immense challenge. To address this challenge, a smart surface that can regulate the rate of liquid transport within a patterned channel by temperature is reported. A synergistically controlled approach of poly(N-isopropylacrylamide) and micropillar shape-memory polymers (SMPs) was used to modulate the wetting rate of liquids on surfaces. By femtosecond laser direct writing, temperature-responsive composite surfaces are embedded in the microstructure of shape-memory polymers (SMPs) in a patterned manner, resulting in the preparation of novel programmable liquid manipulation surfaces incorporating boundaries possessing asymmetric wettability. Since the smart surface is based on SMP, the superhydrophobic part in the superhydrophobic/controllable wettability patterning platform is also programmed for droplet directional transport, which takes advantage of the difference in wettability between the rewritable indentation track and the periphery to allow droplets to flow into the temperature-controlled velocity track, enriching the functionality of the surface. In addition, based on its excellent controllability and patterning, the surface has been shown to be used in microfluidic circuit chips with self-cleaning properties, which provides new ideas for circuit timing control. This study provides promising prospects for the effective development of multifunctional liquid steering surfaces, lab-on-a-chip, and microfluidic devices

Patterned Manipulated Surface Based on Femtosecond Laser with Adjustable Wetting Speed and Directional Fluid Delivery

Recently, due to the crucial roles of multifunctional liquid manipulation surfaces in biomedical transportation, microfluidics, and chemical engineering, the demand for controllable and functional aspects of directed liquid transportation has increased significantly. However, designing an intelligent manipulation surface that is easy to manufacture and fully functional remains an immense challenge. To address this challenge, a smart surface that can regulate the rate of liquid transport within a patterned channel by temperature is reported. A synergistically controlled approach of poly(N-isopropylacrylamide) and micropillar shape-memory polymers (SMPs) was used to modulate the wetting rate of liquids on surfaces. By femtosecond laser direct writing, temperature-responsive composite surfaces are embedded in the microstructure of shape-memory polymers (SMPs) in a patterned manner, resulting in the preparation of novel programmable liquid manipulation surfaces incorporating boundaries possessing asymmetric wettability. Since the smart surface is based on SMP, the superhydrophobic part in the superhydrophobic/controllable wettability patterning platform is also programmed for droplet directional transport, which takes advantage of the difference in wettability between the rewritable indentation track and the periphery to allow droplets to flow into the temperature-controlled velocity track, enriching the functionality of the surface. In addition, based on its excellent controllability and patterning, the surface has been shown to be used in microfluidic circuit chips with self-cleaning properties, which provides new ideas for circuit timing control. This study provides promising prospects for the effective development of multifunctional liquid steering surfaces, lab-on-a-chip, and microfluidic devices