In Situ Self-Cross-Linkable, Long-Term Stable Hyaluronic Acid Filler by Gallol Autoxidation for Tissue Augmentation and Wrinkle Correction

Copyright © 2019 American Chemical Society.Injectable fillers mainly aim to augment tissue volume and correct wrinkles in cosmetic and plastic reconstructions. However, the development of long-lasting, injectable fillers with minimal complications of pain, toxicity, and displacement has been challenging because of the absence of reliable cross-linking chemistry. Here, we report a novel cross-linker-free injectable hydrogel formulated by autoxidation as a highly biocompatible, easily injectable, and long-term volumetrically stable filler agent. Self-cross-linkable hyaluronic acid (SC-HA) with gallol moieties could form a hydrogel via autoxidation of gallols in vivo without additional cross-linking agents. The gelation of SC-HA in situ after injection is accelerated by the self-production of oxygen species and endogenous peroxidase in vivo. The SC-HA filler does not require a high injection force, thus minimizing pain, bleeding, and tissue damage-associated complications. In addition, improved tissue adhesiveness of the SC-HA hydrogel by oxidized gallols (shear strength; 2 kPa) prevented displacement of the filler constructs from the injection site. The SC-HA filler retained its mechanical properties in vivo (600-700 Pa) for wrinkle correction and volumetric augmentation up to 1 year after injection. Overall, the performance of the SC-HA hydrogel as an injectable dermal filler was superior to that of commercially available, chemically cross-linked biphasic HA filler composites in terms of injectability, tissue adhesiveness, and long-term volumetric augmentation. Our injectable HA hydrogel with no need of cross-linkers provides a long-lasting filler that has clinical utility for cosmetic applications11sciescopu

Adjuvant chemotherapy and survival among patients 70 years of age and younger with node-negative breast cancer and the 21-gene recurrence score of 26-30

BACKGROUND: The benefits of chemotherapy in node-negative, hormone receptor-positive, and human epidermal growth factor receptor 2 (HER2)-negative breast cancer patients with the 21-gene recurrence score (RS) of 18-30, particularly those with RS 26-30, are not known. METHODS: Using the Surveillance, Epidemiology, and End Results (SEER) data, we retrospectively identified 29,137 breast cancer patients with the 21-gene RS of 18-30 diagnosed between 2004 and 2015. Mortality risks according to the RS and chemotherapy use were compared by the Kaplan-Meier method and Cox\u27s proportional hazards model. RESULTS: Among the breast cancer patients with the RS 18-30, 21% of them had RS 26-30. Compared to breast cancer patients with RS 18-25, patients with RS 26-30 had more aggressive tumor characteristics and chemotherapy use and increased risk of breast cancer-specific mortality and overall mortality. In breast cancer patients who were aged ≤ 70 years and had RS of 26-30, chemotherapy administration was associated with a 32% lower risk of breast cancer-specific mortality (hazard ratio [HR], 0.68; 95% confidence interval [CI], 0.47-0.99) and a 42% lower risk of overall mortality (HR, 0.58; 95% CI, 0.44-0.76). Survival benefits were most pronounced in breast cancer patients who were younger or had grade III tumor. CONCLUSIONS: The 21-gene RS of 18-30 showed heterogeneous outcomes, and the RS 26-30 was a significant prognostic factor for an increased risk of mortality. Adjuvant chemotherapy could improve the survival of node-negative, hormone receptor-positive, and HER2-negative breast cancer patients with the 21-gene RS 26-30 and should be considered for patients, especially younger patients or patients with high-grade tumors

Histidine 454 plays an important role in polymerization of human glutamate dehydrogenase

AbstractAlthough previous chemical modification studies have suggested several residues to be involved in the maintenance of the quaternary structure of glutamate dehydrogenase (GDH), there are conflicting views for the polymerization process and no clear evidence has been reported yet. In the present study, cassette mutagenesis at seven putative positions (Lys333, Lys337, Lys344, Lys346, Ser445, Gly446, and His454) was performed using a synthetic human GDH gene to examine the polymerization process. Of the mutations at the seven different sites, only the mutagenesis at His454 results in depolymerization of the hexameric GDH into active trimers as determined by HPLC gel filtration analysis and native gradient polyacrylamide gel electrophoresis. The mutagenesis at His454 has no effects on expression or stability of the protein. The KM values for NADH and 2-oxoglutarate were 1.5-fold and 2.5-fold greater, respectively, for the mutant GDH than for wild-type GDH, indicating that substitution at position 454 had appreciable effects on the affinity of the enzyme for both NADH and 2-oxoglutarate. The Vmax values were similar for wild-type and mutant GDH. The kcat/KM value of the mutant GDH was reduced up to 2.8-fold. The decreased efficiency of the mutant, therefore, results from the increase in KM values for NADH and 2-oxoglutarate. The results with cassette mutagenesis and HPLC gel filtration analysis suggest that His454 is involved in the polymerization process of human GDH

Depression and suicide risk prediction models using blood-derived multi-omics data

More than 300 million people worldwide experience depression; annually, ~800,000 people die by suicide. Unfortunately, conventional interview-based diagnosis is insufficient to accurately predict a psychiatric status. We developed machine learning models to predict depression and suicide risk using blood methylome and transcriptome data from 56 suicide attempters (SAs), 39 patients with major depressive disorder (MDD), and 87 healthy controls. Our random forest classifiers showed accuracies of 92.6% in distinguishing SAs from MDD patients, 87.3% in distinguishing MDD patients from controls, and 86.7% in distinguishing SAs from controls. We also developed regression models for predicting psychiatric scales with R2 values of 0.961 and 0.943 for Hamilton Rating Scale for Depression???17 and Scale for Suicide Ideation, respectively. Multi-omics data were used to construct psychiatric status prediction models for improved mental health treatment

Pepper EST database: comprehensive in silico tool for analyzing the chili pepper (Capsicum annuum) transcriptome

<p>Abstract</p> <p>Background</p> <p>There is no dedicated database available for Expressed Sequence Tags (EST) of the chili pepper (<it>Capsicum annuum</it>), although the interest in a chili pepper EST database is increasing internationally due to the nutritional, economic, and pharmaceutical value of the plant. Recent advances in high-throughput sequencing of the ESTs of chili pepper cv. Bukang have produced hundreds of thousands of complementary DNA (cDNA) sequences. Therefore, a chili pepper EST database was designed and constructed to enable comprehensive analysis of chili pepper gene expression in response to biotic and abiotic stresses.</p> <p>Results</p> <p>We built the Pepper EST database to mine the complexity of chili pepper ESTs. The database was built on 122,582 sequenced ESTs and 116,412 refined ESTs from 21 pepper EST libraries. The ESTs were clustered and assembled into virtual consensus cDNAs and the cDNAs were assigned to metabolic pathway, Gene Ontology (GO), and MIPS Functional Catalogue (FunCat). The Pepper EST database is designed to provide a workbench for (i) identifying unigenes in pepper plants, (ii) analyzing expression patterns in different developmental tissues and under conditions of stress, and (iii) comparing the ESTs with those of other members of the <it>Solanaceae </it>family. The Pepper EST database is freely available at <url>http://genepool.kribb.re.kr/pepper/</url>.</p> <p>Conclusion</p> <p>The Pepper EST database is expected to provide a high-quality resource, which will contribute to gaining a systemic understanding of plant diseases and facilitate genetics-based population studies. The database is also expected to contribute to analysis of gene synteny as part of the chili pepper sequencing project by mapping ESTs to the genome.</p

Evaluation for Damaged Degree of Vegetation by Forest Fire Using LiDAR and Digital Aerial Photograph

The amount of vegetation physically damaged by forest fire can be evaluated using lidar (Light Detection And Ranging) data because the loss of canopy height and width by forest fire can be relevant to the number of points transmitted to the ground through the canopy of the damaged forest. On the other hand, the biological damage of vegetation caused by forest fire can be obtained from the Normalized Difference Vegetation Index (NDVI), which determines the vegetation vitality. In this study, the degree of physical damage from the lidar data was classified into serious physical damage (SPD) and light physical damage (LPD). The degree of biological damage using NDVI was likewise classified into serious biological damage (SBD) and light biological damage (LBD). Finally, the damaged area was graded into four categories: (a) SPD and SBD, (b) LPD and SBD, (c) SPD and LBD, and (d) LPD and LBD. The accuracy assessment for the area classified into four grades showed an overall accuracy of 0.74, and a kappa value of 0.61 which provides improvement over previous works