Table_1_Application of multiple machine learning approaches to determine key pyroptosis molecules in type 2 diabetes mellitus.xlsx

ObjectivePyroptosis, a lytic and inflammatory programmed cell death, has been implicated in type 2 diabetes mellitus (T2DM) and its complications. Nonetheless, it remains elusive exactly which pyroptosis molecule exerts an essential role in T2DM, and this study aims to solve such issue.MethodsTranscriptional profiling datasets of T2DM, i.e., GSE20966, GSE95849, and GSE26168, were acquired. Four machine learning models, namely, random forest, support vector machine, extreme gradient boosting, and generalized linear modeling, were built based on pyroptosis genes. A nomogram of key pyroptosis genes was also generated, and the clinical value was appraised via calibration curves and decision curve analysis. Immune infiltration was inferred utilizing CIBERSORT. Drug–druggable target relationships were acquired from the Drug Gene Interaction Database. Through WGCNA, key pyroptosis-relevant genes were selected.ResultsMost pyroptosis genes exhibited upregulation in T2DM relative to controls, indicating the activity of pyroptosis in T2DM. The SVM model composed of BAK1, CHMP2B, NLRP6, PLCG1, and TIRAP exhibited the best performance in T2DM diagnosis, with AUC = 1. The nomogram can predict the risk of T2DM for clinical practice. NK cells resting exhibited a lower abundance in T2DM versus normal specimens, with a higher abundance of neutrophils. NLRP6 was positively linked with neutrophils. Drugs (keracyanin, 9,10-phenanthrenequinone, diclofenac, phosphomethylphosphonic acid adenosyl ester, acetaminophen, cefixime, aspirin, ustekinumab) potentially targeted the key pyroptosis genes. Additionally, CHMP2B-relevant genes were determined.ConclusionAltogether, this work proposes the key pyroptosis genes in T2DM, which might become possible molecules for the management and treatment of T2DM and its complications.</p

Table_2_Application of multiple machine learning approaches to determine key pyroptosis molecules in type 2 diabetes mellitus.xlsx

ObjectivePyroptosis, a lytic and inflammatory programmed cell death, has been implicated in type 2 diabetes mellitus (T2DM) and its complications. Nonetheless, it remains elusive exactly which pyroptosis molecule exerts an essential role in T2DM, and this study aims to solve such issue.MethodsTranscriptional profiling datasets of T2DM, i.e., GSE20966, GSE95849, and GSE26168, were acquired. Four machine learning models, namely, random forest, support vector machine, extreme gradient boosting, and generalized linear modeling, were built based on pyroptosis genes. A nomogram of key pyroptosis genes was also generated, and the clinical value was appraised via calibration curves and decision curve analysis. Immune infiltration was inferred utilizing CIBERSORT. Drug–druggable target relationships were acquired from the Drug Gene Interaction Database. Through WGCNA, key pyroptosis-relevant genes were selected.ResultsMost pyroptosis genes exhibited upregulation in T2DM relative to controls, indicating the activity of pyroptosis in T2DM. The SVM model composed of BAK1, CHMP2B, NLRP6, PLCG1, and TIRAP exhibited the best performance in T2DM diagnosis, with AUC = 1. The nomogram can predict the risk of T2DM for clinical practice. NK cells resting exhibited a lower abundance in T2DM versus normal specimens, with a higher abundance of neutrophils. NLRP6 was positively linked with neutrophils. Drugs (keracyanin, 9,10-phenanthrenequinone, diclofenac, phosphomethylphosphonic acid adenosyl ester, acetaminophen, cefixime, aspirin, ustekinumab) potentially targeted the key pyroptosis genes. Additionally, CHMP2B-relevant genes were determined.ConclusionAltogether, this work proposes the key pyroptosis genes in T2DM, which might become possible molecules for the management and treatment of T2DM and its complications.</p

Table_3_Application of multiple machine learning approaches to determine key pyroptosis molecules in type 2 diabetes mellitus.xlsx

ObjectivePyroptosis, a lytic and inflammatory programmed cell death, has been implicated in type 2 diabetes mellitus (T2DM) and its complications. Nonetheless, it remains elusive exactly which pyroptosis molecule exerts an essential role in T2DM, and this study aims to solve such issue.MethodsTranscriptional profiling datasets of T2DM, i.e., GSE20966, GSE95849, and GSE26168, were acquired. Four machine learning models, namely, random forest, support vector machine, extreme gradient boosting, and generalized linear modeling, were built based on pyroptosis genes. A nomogram of key pyroptosis genes was also generated, and the clinical value was appraised via calibration curves and decision curve analysis. Immune infiltration was inferred utilizing CIBERSORT. Drug–druggable target relationships were acquired from the Drug Gene Interaction Database. Through WGCNA, key pyroptosis-relevant genes were selected.ResultsMost pyroptosis genes exhibited upregulation in T2DM relative to controls, indicating the activity of pyroptosis in T2DM. The SVM model composed of BAK1, CHMP2B, NLRP6, PLCG1, and TIRAP exhibited the best performance in T2DM diagnosis, with AUC = 1. The nomogram can predict the risk of T2DM for clinical practice. NK cells resting exhibited a lower abundance in T2DM versus normal specimens, with a higher abundance of neutrophils. NLRP6 was positively linked with neutrophils. Drugs (keracyanin, 9,10-phenanthrenequinone, diclofenac, phosphomethylphosphonic acid adenosyl ester, acetaminophen, cefixime, aspirin, ustekinumab) potentially targeted the key pyroptosis genes. Additionally, CHMP2B-relevant genes were determined.ConclusionAltogether, this work proposes the key pyroptosis genes in T2DM, which might become possible molecules for the management and treatment of T2DM and its complications.</p

sj-docx-1-pid-10.1177_09544070221128173 – Supplemental material for Comparative analysis of AEB effectiveness based on typical and atypical scenarios of electric two-wheeler accidents in China

Supplemental material, sj-docx-1-pid-10.1177_09544070221128173 for Comparative analysis of AEB effectiveness based on typical and atypical scenarios of electric two-wheeler accidents in China by Di Pan, Yong Han, Qianqian Jin, He Wu, Bingyu Wang, Hongwu Huang and Koji Mizuno in Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering</p

pH-dependent synthesis of a cadmium coordination compound from a compound based on Hpytz ligand [Hpytz = 5-(4-pyridyl)tetrazole]

<div><p>Reactions of CdSO₄·6H₂O and Hpytz [Hpytz = 5-(4-pyridyl)tetrazole] under high pH values produced a known compound, [Cd(pytz)₂(H₂O)₄]·2H₂O (<b>1</b>), which can be used to prepare [Cd(Hpytz)(SO₄)(H₂O)₂] (<b>2</b>) by adjusting the pH to a lower level using sulfuric acid under hydrothermal conditions. These compounds were characterized by elemental analysis, IR spectroscopy, and single-crystal diffraction. X-ray analysis reveals that <b>1</b> features a mononuclear structure, while <b>2</b> affords a 1-D polymeric chain structure. Compound <b>1</b> displays a 2-D network, while <b>2</b> shows a 3-D network by hydrogen bonding interactions. Furthermore, the luminescent properties were investigated at room temperature in the solid state.</p></div

Reaction of C₆₀ with Inactive Secondary Amines and Aldehydes and the Cu(OAc)₂‑Promoted Regioselective Intramolecular C–H Functionalization of the Generated Fulleropyrrolidines

The thermal reaction of C₆₀ with aromatic aldehydes and inactive secondary amines for the stereoselective synthesis of <i>trans</i>-1,2,5-trisubstituted fulleropyrrolidines has been developed. Moreover, when an <i>o</i>-hydroxyl group was located at the phenyl ring of the generated fulleropyrrolidines, the Cu­(OAc)₂-promoted regioselective intramolecular C–O coupling reaction occurred to generate unique tricycle-fused fullerene derivatives

Data_Sheet_1_Apolipoprotein E Deficiency Exacerbates Spinal Cord Injury in Mice: Inflammatory Response and Oxidative Stress Mediated by NF-κB Signaling Pathway.pdf

<p>Spinal cord injury (SCI) is a severe neurological trauma that involves complex pathological processes. Inflammatory response and oxidative stress are prevalent during the second injury and can influence the functional recovery of SCI. Specially, Apolipoprotein E (APOE) induces neuronal repair and nerve regeneration, and the deficiency of Apoe impairs spinal cord-blood-barrier and reduces functional recovery after SCI. However, the mechanism by which Apoe mediates signaling pathways of inflammatory response and oxidative stress in SCI remains largely elusive. This study was designed to investigate the signaling pathways that regulate Apoe deficiency-dependent inflammatory response and oxidative stress in the acute stage of SCI. In the present study, Apoe^−/− mice retarded functional recovery and had a larger lesion size when compared to wild-type mice after SCI. Moreover, deficiency of Apoe induced an exaggerated inflammatory response by increasing expression of interleukin-6 (IL-6) and interleukin-1β (IL-1β), and increased oxidative stress by reducing expression of Nrf2 and HO-1. Furthermore, lack of Apoe promoted neuronal apoptosis and decreased neuronal numbers in the anterior horn of the spinal cord after SCI. Mechanistically, we found that the absence of Apoe increased inflammation and oxidative stress through activation of NF-κB after SCI. In contrast, an inhibitor of nuclear factor-κB (NF-κB; Pyrrolidine dithiocarbamate) alleviates these changes. Collectively, these results indicate that a critical role for activation of NF-κB in regulating Apoe-deficiency dependent inflammation and oxidative stress is detrimental to recovery after SCI.</p