Table_1_Pyrimidine metabolism regulator-mediated molecular subtypes display tumor microenvironmental hallmarks and assist precision treatment in bladder cancer.xls

BackgroundBladder cancer (BLCA) is a common urinary system malignancy with a significant morbidity and death rate worldwide. Non-muscle invasive BLCA accounts for over 75% of all BLCA cases. The imbalance of tumor metabolic pathways is associated with tumor formation and proliferation. Pyrimidine metabolism (PyM) is a complex enzyme network that incorporates nucleoside salvage, de novo nucleotide synthesis, and catalytic pyrimidine degradation. Metabolic reprogramming is linked to clinical prognosis in several types of cancer. However, the role of pyrimidine metabolism Genes (PyMGs) in the BLCA-fighting process remains poorly understood.MethodsPredictive PyMGs were quantified in BLCA samples from the TCGA and GEO datasets. TCGA and GEO provided information on stemness indices (mRNAsi), gene mutations, CNV, TMB, and corresponding clinical features. The prediction model was built using Lasso regression. Co-expression analysis was conducted to investigate the relationship between gene expression and PyM.ResultsPyMGs were overexpressed in the high-risk sample in the absence of other clinical symptoms, demonstrating their predictive potential for BLCA outcome. Immunological and tumor-related pathways were identified in the high-risk group by GSWA. Immune function and m6a gene expression varied significantly between the risk groups. In BLCA patients, DSG1, C6orf15, SOST, SPRR2A, SERPINB7, MYBPH, and KRT1 may participate in the oncology process. Immunological function and m6a gene expression differed significantly between the two groups. The prognostic model, CNVs, single nucleotide polymorphism (SNP), and drug sensitivity all showed significant gene connections.ConclusionsBLCA-associated PyMGs are available to provide guidance in the prognostic and immunological setting and give evidence for the formulation of PyM-related molecularly targeted treatments. PyMGs and their interactions with immune cells in BLCA may serve as therapeutic targets.</p

DataSheet_1_Pyrimidine metabolism regulator-mediated molecular subtypes display tumor microenvironmental hallmarks and assist precision treatment in bladder cancer.doc

BackgroundBladder cancer (BLCA) is a common urinary system malignancy with a significant morbidity and death rate worldwide. Non-muscle invasive BLCA accounts for over 75% of all BLCA cases. The imbalance of tumor metabolic pathways is associated with tumor formation and proliferation. Pyrimidine metabolism (PyM) is a complex enzyme network that incorporates nucleoside salvage, de novo nucleotide synthesis, and catalytic pyrimidine degradation. Metabolic reprogramming is linked to clinical prognosis in several types of cancer. However, the role of pyrimidine metabolism Genes (PyMGs) in the BLCA-fighting process remains poorly understood.MethodsPredictive PyMGs were quantified in BLCA samples from the TCGA and GEO datasets. TCGA and GEO provided information on stemness indices (mRNAsi), gene mutations, CNV, TMB, and corresponding clinical features. The prediction model was built using Lasso regression. Co-expression analysis was conducted to investigate the relationship between gene expression and PyM.ResultsPyMGs were overexpressed in the high-risk sample in the absence of other clinical symptoms, demonstrating their predictive potential for BLCA outcome. Immunological and tumor-related pathways were identified in the high-risk group by GSWA. Immune function and m6a gene expression varied significantly between the risk groups. In BLCA patients, DSG1, C6orf15, SOST, SPRR2A, SERPINB7, MYBPH, and KRT1 may participate in the oncology process. Immunological function and m6a gene expression differed significantly between the two groups. The prognostic model, CNVs, single nucleotide polymorphism (SNP), and drug sensitivity all showed significant gene connections.ConclusionsBLCA-associated PyMGs are available to provide guidance in the prognostic and immunological setting and give evidence for the formulation of PyM-related molecularly targeted treatments. PyMGs and their interactions with immune cells in BLCA may serve as therapeutic targets.</p

Additional file 1 of A multisectoral and multidisciplinary endeavor: a review of diabetes self-management apps in China

Additional file 1: Appendix A. Usability Scores of the Reviewed Diabetes Self-Management Apps (N=66). Appendix B. Comprehensiveness of the Reviewed Diabetes Self-Managed Apps (N=66)

Polymerization-Like Co-Assembly of Silver Nanoplates and Patchy Spheres

Highly anisometric nanoparticles have distinctive mechanical, electrical, and thermal properties and are therefore appealing candidates for use as self-assembly building blocks. Here, we demonstrate that ultra-anisometric nanoplates, which have a nanoscale thickness but a micrometer-scale edge length, offer many material design capabilities. In particular, we show that these nanoplates “copolymerize” in a predictable way with patchy spheres (Janus and triblock particles) into one- and two-dimensional structures with tunable architectural properties. We find that, on the pathway to these structures, nanoplates assemble into chains following the kinetics of molecular step-growth polymerization. In the same mechanistic framework, patchy spheres control the size distribution and morphology of assembled structures, by behaving as monofunctional chain stoppers or multifunctional branch points during nanoplate polymerization. In addition, both the lattice constant and the stiffness of the nanoplate assemblies can be manipulated after assembly. We see highly anisometric nanoplates as one representative of a broader class of dual length-scale nanoparticles, with the potential to enrich the library of structures and properties available to the nanoparticle self-assembly toolbox

Highly Stretchable and Transparent Thermistor Based on Self-Healing Double Network Hydrogel

An ultrastretchable thermistor that combines intrinsic stretchability, thermal sensitivity, transparency, and self-healing capability is fabricated. It is found the polyacrylamide/carrageenan double network (DN) hydrogel is highly sensitive to temperature and therefore can be exploited as a novel channel material for a thermistor. This thermistor can be stretched from 0 to 330% strain with the sensitivity as high as 2.6%/°C at extreme 200% strain. Noticeably, the mechanical, electrical, and thermal sensing properties of the DN hydrogel can be self-healed, analogous to the self-healing capability of human skin. The large mechanical deformations, such as flexion and twist with large angles, do not affect the thermal sensitivity. Good flexibility enables the thermistor to be attached on nonplanar curvilinear surfaces for practical temperature detection. Remarkably, the thermal sensitivity can be improved by introducing mechanical strain, making the sensitivity programmable. This thermistor with tunable sensitivity is advantageous over traditional rigid thermistors that lack flexibility in adjusting their sensitivity. In addition to superior sensitivity and stretchability compared with traditional thermistors, this DN hydrogel-based thermistor provides additional advantages of good transparency and self-healing ability, enabling it to be potentially integrated in soft robots to grasp real world information for guiding their actions