1
|
Wound Healing after Acellular Dermal Substitute Positioning in Dermato-Oncological Surgery: A Prospective Comparative Study. Life (Basel) 2023; 13:life13020463. [PMID: 36836820 PMCID: PMC9967245 DOI: 10.3390/life13020463] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Revised: 01/28/2023] [Accepted: 01/31/2023] [Indexed: 02/11/2023] Open
Abstract
BACKGROUND MatriDerm and Integra are both widely used collagenic acellular dermal matrices (ADMs) in the surgical setting, with similar characteristics in terms of healing time and clinical indication. The aim of the present study is to compare the two ADMs in terms of clinical and histological results in the setting of dermato-oncological surgery. METHODS Ten consecutive patients with medical indications to undergo surgical excision of skin cancers were treated with a 2-step procedure at our Dermatologic Surgery Unit. Immediately after tumor removal, both ADMs were positioned on the wound bed, one adjacent to the other. Closure through split-thickness skin grafting was performed after approximately 3 weeks. Conventional histology, immunostaining and ELISA assay were performed on cutaneous samples at different timepoints. RESULTS No significant differences were detected in terms of either final clinical outcomes or in extracellular matrix content of the neoformed dermis. However, Matriderm was observed to induce scar retraction more frequently. In contrast, Integra was shown to carry higher infectious risk and to be more slowly reabsorbed into the wound bed. Sometimes foreign body-like granulomatous reactions were also observed, especially in Integra samples. CONCLUSIONS Even in the presence of subtle differences between the ADMs, comparable global outcomes were demonstrated after dermato-oncological surgery.
Collapse
|
2
|
Ngema LM, Adeyemi SA, Marimuthu T, Choonara YE. A review on engineered magnetic nanoparticles in Non-Small-Cell lung carcinoma targeted therapy. Int J Pharm 2021; 606:120870. [PMID: 34245844 DOI: 10.1016/j.ijpharm.2021.120870] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Revised: 06/25/2021] [Accepted: 07/05/2021] [Indexed: 02/07/2023]
Abstract
There are growing appeals forthe design of efficacious treatment options for non-small-cell lung carcinoma (NSCLC) as it accrues to ~ 85% cases of lung cancer. Although platinum-based doublet chemotherapy has been the main therapeutic intervention in NSCLC management, this leads to myriad of problems including intolerability to the doublet regimens and detrimental side effects due to high doses. A new approach is therefore needed and warrants the design of targeted drug delivery systems that can halt tumor proliferation and metastasis by targeting key molecules, while exhibiting minimal side effects and toxicity. This review aims to explore the rational design of magnetic nanoparticles for the development of tumor-targeting systems for NSCLC. In the review, we explore the anticancer merits of conjugated linoleic acid (CLA) and provide a concise incursion into its application for the invention of functionalized magnetic nanoparticles in the targeted treatment of NSCLC. Recent nanoparticle-based targeted chemotherapies for targeting angiogenesis biomarkers in NSCLC will also be reviewed to further highlight versatility of magnetic nanoparticles. These developments through molecular tuning at the nanoscale and supported by comprehensive pre-clinical studies could lead to the establishment of precise nanosystems for tumor-homing cancer therapy.
Collapse
Affiliation(s)
- Lindokuhle M Ngema
- Wits Advanced Drug Delivery Platform Research Unit, Department of Pharmacy and Pharmacology, School of Therapeutic Sciences, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, 7 York Road, Parktown 2193, South Africa
| | - Samson A Adeyemi
- Wits Advanced Drug Delivery Platform Research Unit, Department of Pharmacy and Pharmacology, School of Therapeutic Sciences, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, 7 York Road, Parktown 2193, South Africa
| | - Thashree Marimuthu
- Wits Advanced Drug Delivery Platform Research Unit, Department of Pharmacy and Pharmacology, School of Therapeutic Sciences, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, 7 York Road, Parktown 2193, South Africa
| | - Yahya E Choonara
- Wits Advanced Drug Delivery Platform Research Unit, Department of Pharmacy and Pharmacology, School of Therapeutic Sciences, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, 7 York Road, Parktown 2193, South Africa.
| |
Collapse
|
3
|
Braga CP, Boone CHT, Grove RA, Adamcova D, Fernandes AAH, Adamec J, de Magalhães Padilha P. Liver Proteome in Diabetes Type 1 Rat Model: Insulin-Dependent and -Independent Changes. OMICS-A JOURNAL OF INTEGRATIVE BIOLOGY 2016; 20:711-726. [PMID: 27849439 DOI: 10.1089/omi.2016.0135] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Diabetes mellitus type 1 (DM1) is a major public health problem that continues to burden the healthcare systems worldwide, costing exponentially more as the epidemic grows. Innovative strategies and omics system diagnostics for earlier diagnosis or prognostication of DM1 are essential to prevent secondary complications and alleviate the associated economic burden. In a preclinical study design that involved streptozotocin (STZ)-induced DM1, insulin-treated STZ-induced DM1, and control rats, we characterized the insulin-dependent and -independent changes in protein profiles in liver samples. Digested proteins were subjected to LC-MSE for proteomic data. Progenesis QI data processing and analysis of variance were utilized for statistical analyses. We found 305 proteins with significantly altered abundance among the control, DM1, and insulin-treated DM1 groups (p < 0.05). These differentially regulated proteins were related to enzymes that function in key metabolic pathways and stress responses. For example, gluconeogenesis appeared to return to control levels in the DM1 group after insulin treatment, with the restoration of gluconeogenesis regulatory enzyme, FBP1. Insulin administration to DM1 rats also restored the blood glucose levels and enzymes of general stress and antioxidant response systems. These observations are crucial for insights on DM1 pathophysiology and new molecular targets for future clinical biomarkers, drug discovery, and development. Additionally, we underscore that proteomics offers much potential in preclinical biomarker discovery for diabetes as well as common complex diseases such as cancer, dementia, and infectious disorders.
Collapse
Affiliation(s)
- Camila Pereira Braga
- 1 Department of Chemistry and Biochemistry, Institute of Bioscience, São Paulo State University , Botucatu, Brazil .,2 Redox Biology Center, Department of Biochemistry, University of Nebraska-Lincoln , Lincoln, NE, USA
| | - Cory H T Boone
- 2 Redox Biology Center, Department of Biochemistry, University of Nebraska-Lincoln , Lincoln, NE, USA
| | - Ryan A Grove
- 2 Redox Biology Center, Department of Biochemistry, University of Nebraska-Lincoln , Lincoln, NE, USA
| | - Dana Adamcova
- 2 Redox Biology Center, Department of Biochemistry, University of Nebraska-Lincoln , Lincoln, NE, USA
| | | | - Jiri Adamec
- 2 Redox Biology Center, Department of Biochemistry, University of Nebraska-Lincoln , Lincoln, NE, USA
| | - Pedro de Magalhães Padilha
- 1 Department of Chemistry and Biochemistry, Institute of Bioscience, São Paulo State University , Botucatu, Brazil
| |
Collapse
|
4
|
Ma J, Yang J, Zhou L, Zhang Z, Ma H, Xie X, Zhang F, Xiong X, Cui L, Yang H, Liu X, Duan Y, Xiao S, Ai H, Ren J, Huang L. Genome-wide association study of meat quality traits in a White Duroc×Erhualian F2 intercross and Chinese Sutai pigs. PLoS One 2013; 8:e64047. [PMID: 23724019 PMCID: PMC3665833 DOI: 10.1371/journal.pone.0064047] [Citation(s) in RCA: 50] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2012] [Accepted: 04/07/2013] [Indexed: 12/31/2022] Open
Abstract
Thousands of QTLs for meat quality traits have been identified by linkage mapping studies, but most of them lack precise position or replication between populations, which hinder their application in pig breeding programs. To localize QTLs for meat quality traits to precise genomic regions, we performed a genome-wide association (GWA) study using the Illumina PorcineSNP60K Beadchip in two swine populations: 434 Sutai pigs and 933 F2 pigs from a White Duroc×Erhualian intercross. Meat quality traits, including pH, color, drip loss, moisture content, protein content and intramuscular fat content (IMF), marbling and firmness scores in the M. longissimus (LM) and M. semimembranosus (SM) muscles, were recorded on the two populations. In total, 127 chromosome-wide significant SNPs for these traits were identified. Among them, 11 SNPs reached genome-wise significance level, including 1 on SSC3 for pH, 1 on SSC3 and 3 on SSC15 for drip loss, 3 (unmapped) for color a*, and 2 for IMF each on SSC9 and SSCX. Except for 11 unmapped SNPs, 116 significant SNPs fell into 28 genomic regions of approximately 10 Mb or less. Most of these regions corresponded to previously reported QTL regions and spanned smaller intervals than before. The loci on SSC3 and SSC7 appeared to have pleiotropic effects on several related traits. Besides them, a few QTL signals were replicated between the two populations. Further, we identified thirteen new candidate genes for IMF, marbling and firmness, on the basis of their positions, functional annotations and reported expression patterns. The findings will contribute to further identification of the causal mutation underlying these QTLs and future marker-assisted selection in pigs.
Collapse
Affiliation(s)
- Junwu Ma
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China
| | - Jie Yang
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China
| | - Lisheng Zhou
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China
| | - Zhiyan Zhang
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China
| | - Huanban Ma
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China
| | - Xianhua Xie
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China
| | - Feng Zhang
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China
| | - Xinwei Xiong
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China
| | - Leilei Cui
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China
| | - Hui Yang
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China
| | - Xianxian Liu
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China
| | - Yanyu Duan
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China
| | - Shijun Xiao
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China
| | - Huashui Ai
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China
| | - Jun Ren
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China
| | - Lusheng Huang
- Key Laboratory for Animal Biotechnology of Jiangxi Province and the Ministry of Agriculture of China, Jiangxi Agricultural University, Nanchang, China
- * E-mail:
| |
Collapse
|