Isolation and characterisation of human gingival margin-derived STRO-1/MACS+ and MACS− cell populations

Recently, gingival margin-derived stem/progenitor cells isolated via STRO-1/magnetic activated cell sorting (MACS) showed remarkable periodontal regenerative potential in vivo. As a second-stage investigation, the present study's aim was to perform in vitro characterisation and comparison of the stem/progenitor cell characteristics of sorted STRO-1-positive (MACS+) and STRO-1-negative (MACS−) cell populations from the human free gingival margin. Cells were isolated from the free gingiva using a minimally invasive technique and were magnetically sorted using anti-STRO-1 antibodies. Subsequently, the MACS+ and MACS− cell fractions were characterized by flow cytometry for expression of CD14, CD34, CD45, CD73, CD90, CD105, CD146/MUC18 and STRO-1. Colony-forming unit (CFU) and multilineage differentiation potential were assayed for both cell fractions. Mineralisation marker expression was examined using real-time polymerase chain reaction (PCR). MACS+ and MACS− cell fractions showed plastic adherence. MACS+ cells, in contrast to MACS− cells, showed all of the predefined mesenchymal stem/progenitor cell characteristics and a significantly higher number of CFUs (P<0.01). More than 95% of MACS+ cells expressed CD105, CD90 and CD73; lacked the haematopoietic markers CD45, CD34 and CD14, and expressed STRO-1 and CD146/MUC18. MACS− cells showed a different surface marker expression profile, with almost no expression of CD14 or STRO-1, and more than 95% of these cells expressed CD73, CD90 and CD146/MUC18, as well as the haematopoietic markers CD34 and CD45 and CD105. MACS+ cells could be differentiated along osteoblastic, adipocytic and chondroblastic lineages. In contrast, MACS− cells demonstrated slight osteogenic potential. Unstimulated MACS+ cells showed significantly higher expression of collagen I (P<0.05) and collagen III (P<0.01), whereas MACS− cells demonstrated higher expression of osteonectin (P<0.05; Mann–Whitney). The present study is the first to compare gingival MACS+ and MACS− cell populations demonstrating that MACS+ cells, in contrast to MACS− cells, harbour stem/progenitor cell characteristics. This study also validates the effectiveness of the STRO-1/MACS+ technique for the isolation of gingival stem/progenitor cells. Human free gingival margin-derived STRO-1/MACS+ cells are a unique renewable source of multipotent stem/progenitor cells

2017 update of the WSES guidelines for emergency repair of complicated abdominal wall hernias

Emergency repair of complicated abdominal wall hernias may be associated with worsen outcome and a significant rate of postoperative complications. There is no consensus on management of complicated abdominal hernias. The main matter of debate is about the use of mesh in case of intestinal resection and the type of mesh to be used. Wound infection is the most common complication encountered and represents an immense burden especially in the presence of a mesh. The recurrence rate is an important topic that influences the final outcome. A World Society of Emergency Surgery (WSES) Consensus Conference was held in Bergamo in July 2013 with the aim to define recommendations for emergency repair of abdominal wall hernias in adults. This document represents the executive summary of the consensus conference approved by a WSES expert panel. In 2016, the guidelines have been revised and updated according to the most recent available literature.Peer reviewe

Burnout among surgeons before and during the SARS-CoV-2 pandemic: an international survey

Background: SARS-CoV-2 pandemic has had many significant impacts within the surgical realm, and surgeons have been obligated to reconsider almost every aspect of daily clinical practice. Methods: This is a cross-sectional study reported in compliance with the CHERRIES guidelines and conducted through an online platform from June 14th to July 15th, 2020. The primary outcome was the burden of burnout during the pandemic indicated by the validated Shirom-Melamed Burnout Measure. Results: Nine hundred fifty-four surgeons completed the survey. The median length of practice was 10&nbsp;years; 78.2% included were male with a median age of 37&nbsp;years old, 39.5% were consultants, 68.9% were general surgeons, and 55.7% were affiliated with an academic institution. Overall, there was a significant increase in the mean burnout score during the pandemic; longer years of practice and older age were significantly associated with less burnout. There were significant reductions in the median number of outpatient visits, operated cases, on-call hours, emergency visits, and research work, so, 48.2% of respondents felt that the training resources were insufficient. The majority (81.3%) of respondents reported that their hospitals were included in the management of COVID-19, 66.5% felt their roles had been minimized; 41% were asked to assist in non-surgical medical practices, and 37.6% of respondents were included in COVID-19 management. Conclusions: There was a significant burnout among trainees. Almost all aspects of clinical and research activities were affected with a significant reduction in the volume of research, outpatient clinic visits, surgical procedures, on-call hours, and emergency cases hindering the training. Trial registration: The study was registered on clicaltrials.gov "NCT04433286" on 16/06/2020

New 1,2,3-Triazole-Coumarin-Glycoside Hybrids and Their 1,2,4-Triazolyl Thioglycoside Analogs Targeting Mitochondria Apoptotic Pathway: Synthesis, Anticancer Activity and Docking Simulation

Toxicity and resistance to newly synthesized anticancer drugs represent a challenging phenomenon of intensified concern arising from variation in drug targets and consequently the prevalence of the latter concern requires further research. The current research reports the design, synthesis, and anticancer activity of new 1,2,3-triazole-coumarin-glycosyl hybrids and their 1,2,4-triazole thioglycosides as well as acyclic analogs. The cytotoxic activity of the synthesized products was studied against a panel of human cancer cell lines. Compounds 8, 10, 16 and 21 resulted in higher activities against different human cancer cells. The impact of the hybrid derivative 10 upon different apoptotic protein markers, including cytochrome c, Bcl-2, Bax, and caspase-7 along with its effect on the cell cycle was investigated. It revealed a mitochondria-apoptotic effect on MCF-7 cells and had the ability to upregulate pro-apoptotic Bax protein and downregulate anti-apoptotic Bcl-2 protein and thus implies the apoptotic fate of the cells. Furthermore, the inhibitory activities against EGFR, VEGFR-2 and CDK-2/cyclin A2 kinases for 8, 10 and 21 were studied to detect the mechanism of their high potency. The coumarin-triazole-glycosyl hybrids 8 and 10 illustrated excellent broad inhibitory activity (IC50= 0.22 &plusmn; 0.01, 0.93 &plusmn; 0.42 and 0.24 &plusmn; 0.20 &mu;M, respectively, for compound 8), (IC50 = 0.12 &plusmn; 0.50, 0.79 &plusmn; 0.14 and 0.15&plusmn; 0. 60 &mu;M, respectively, for compound 10), in comparison with the reference drugs, erlotinib, sorafenib and roscovitine (IC50 = 0.18 &plusmn; 0.05, 1.58 &plusmn; 0.11 and 0.46 &plusmn; 0.30 &mu;M, respectively). In addition, the docking study was simulated to afford better rationalization and put insight into the binding affinity between the promising derivatives and their targeted enzymes and that might be used as an optimum lead for further modification in the anticancer field

Estimation of Potato Water Footprint Using Machine Learning Algorithm Models in Arid Regions

Precise assessment of water footprint to improve the water consumption and crop yield for irrigated agricultural efficiency is required in order to achieve water management sustainability. Although Penman-Monteith is more successful than other methods and it is the most frequently used technique to calculate water footprint, however, it requires a significant number of meteorological parameters at different spatio-temporal scales, which are sometimes inaccessible in many of the developing countries such as Egypt. Machine learning models are widely used to represent complicated phenomena because of their high performance in the non-linear relations of inputs and outputs. Therefore, the objectives of this research were to (1) develop and compare four machine learning models: support vector regression (SVR), random forest (RF), extreme gradient boost (XGB), and artificial neural network (ANN) over three potato governorates (Al-Gharbia, Al-Dakahlia, and Al-Beheira) in the Nile Delta of Egypt and (2) select the best model in the best combination of climate input variables. The available variables used for this study were maximum temperature (Tmax), minimum temperature (Tmin), average temperature (Tave), wind speed (WS), relative humidity (RH), precipitation (P), vapor pressure deficit (VPD), solar radiation (SR), sown area (SA), and crop coefficient (Kc) to predict the potato blue water footprint (BWF) during 1990–2016. Six scenarios (Sc1–Sc6) of input variables were used to test the weight of each variable in four applied models. The results demonstrated that Sc5 with the XGB and ANN model gave the most promising results to predict BWF in this arid region based on vapor pressure deficit, precipitation, solar radiation, crop coefficient data, followed by Sc1. The created models produced comparatively superior outcomes and can contribute to the decision-making process for water management and development planners. Full text: CC BY License</p