| 1 | Comparison of bacterial quantities in left and right colon biopsies and faeces显示文摘AIM:To compare quantities of predominant and pathogenic bacteria in mucosal and faecal samples.METHODS:Twenty patients undergoing diagnostic colonoscopy with endoscopically and histologically normal mucosa were recruited to the study,14 subjects of which also supplied faecal(F) samples between 15 d to 105 d post colonoscopy.Mucosal biopsies were taken from each subject from the midportion of the ascending colon(right side samples,RM) and the sigmoid(left side samples,LM).Predominant intestinal and mucosal bacteria including clostridial 16S rRNA gene clusters Ⅳ and ⅩⅣab,Bacteroidetes,Enterobacteriaceae,Bifidobacterium spp.,Akkermansia muciniphila(A.muciniphila),Veillonella spp.,Collinsella spp.,Faecalibacterium prausnitzii(F.prausnitzii) and putative pathogens such asEscherichia coli(E.coli),Clostridium difficile(C.difficile),Helicobacter pylori(H.pylori) and Staphylococcus aureus(S.aureus) were analysed by quantitative polymerase chain reaction(qPCR).Host DNA was quantified from the mucosal samples with human glyceraldehyde 3-phosphate dehydrogenase gene targeting qPCR.Paired t tests and the Pearson correlation were applied for statistical analysis.RESULTS:The most prominent bacterial groups were clostridial groups Ⅳ and ⅩⅣa+b andBacteroidetes and bacterial species F.prausnitzii in both sample types.H.pylori and S.aureus were not detected and C.difficile was detected in only one mucosal sample and three faecal samples.E.coli was detected in less than half of the mucosal samples at both sites,but was present in all faecal samples.All detected bacteria,except Enterobacteriaceae,were present at higher levels in the faeces than in the mucosa,but the different locations in the colon presented comparable quantities(RM,LM and F followed byP 1 for RMvs F,P 2 for LMvs F andP 3 for RM vs LM:4.17 ± 0.60 log 10 /g,4.16 ± 0.56 log 10 /g,5.88 ± 1.92 log 10 /g,P 1 = 0.011,P 2 = 0.0069,P 3 = 0.9778 forA.muciniphila;6.25 ± 1.3 log 10 /g,6.09 ± 0.81 log 10 /g,8.84 ± 1.38 log 10 /g,P 1 < 0.0001,P 2 = 0.0002,P 3 = 0.6893 forBacteroidetes;5.27 ± 1.68 log 10 /g,5.38 ± 2.06 log 10 /g,8.20 ± 1.14 log 10 /g,P 1 < 0.0001,P 2 ≤ 0.0001,P 3 = 0.7535 forBifidobacterium spp.;6.44 ± 1.15 log 10 /g,6.07 ±1.45 log 10 /g,9.74 ±1.13 log 10 /g,P 1 < 0.0001,P 2 ≤ 0.0001,P 3 = 0.637 forClostridium cluster Ⅳ;6.65 ± 1.23 log 10 /g,6.57 ± 1.52 log 10 /g,9.13 ± 0.96 log 10 /g,P 1 < 0.0001,P 2 ≤ 0.0001,P 3 = 0.9317 forClostridium cluster ⅩⅣa;4.57 ± 1.44 log10/g,4.63 ± 1.34 log10/g,7.05 ± 2.48 log 10 /g,P 1 = 0.012,P 2 = 0.0357,P 3 = 0.7973 for Collinsella spp.;7.66 ± 1.50 log 10 /g,7.60 ± 1.05 log 10 /g,10.02 ± 2.02 log 10 /g,P 1 ≤ 0.0001,P 2 = 0.0013,P 3 = 0.9919 forF.prausnitzsii;6.17 ± 1.3 log 10 /g,5.85 ± 0.93 log 10 /g,7.25 ± 1.01 log 10 /g,P 1 = 0.0243,P 2 = 0.0319,P 3 = 0.6982 for Veillonella spp.;4.68 ± 1.21 log 10 /g,4.71 ± 0.83 log 10 /g,5.70 ± 2.00 log 10 /g,P 1 = 0.1927,P 2 = 0.0605,P 3 = 0.6476 forEnterobacteriaceae).TheBifidobacterium spp.counts correlated significantly between mucosal sites and mucosal and faecal samples(Pearson correlation coefficients 0.62,P = 0.040 and 0.81,P = 0.005 between the right mucosal sample and faeces and the left mucosal sample and faeces,respectively).CONCLUSION:Non-invasive faecal samples do not reflect bacterial counts on the mucosa at the individual level,except for bifidobacteria often analysed in probiotic intervention studies. | Anna Lyra Sofia Forssten Peter Rolny Yvonne Wettergren Sampo J Lahtinen Krista Salli Lennart Cedgrd Elisabeth Odin Bengt Gustavsson Arthur C Ouwehand | 2012 | World Journal of Gastroenterology2012，18，32： | 2 |
| 6 | Wood substitution potential in greenhouse gas emission reduction–review on current state and application of displacement factors显示文摘Background:Replacing non-renewable materials and energy with wood offers a potential strategy to mitigate climate change if the net emissions of ecosystem and technosystem are reduced in a considered time period.Displacement factors(DFs)describe an emission reduction for a wood-based product or fuel which is used in place of a non-wood alternative.The aims of this review were to map and assess DFs from scientific literature and to provide findings on how to harmonise practices behind them and to support coherent application.Results:Most of the reviewed DFs were positive,implying decreasing fossil GHG emissions in the technosystem.The vast majority of the reviewed DFs describe avoided fossil emissions either both in processing and use of wood or only in the latter when wood processing emissions were considered separately.Some of the reviewed DFs included emissions avoided in post-use of harvested wood products(HWPs).Changes in forest and product carbon stocks were not included in DFs except in a few single cases.However,in most of the reviewed studies they were considered separately in a consistent way along with DFs.DFs for wood energy,construction and material substitution were widely available,whereas DFs for packaging products,chemicals and textiles were scarce.More than half of DFs were calculated by the authors of the reviewed articles while the rest of them were adopted from other articles.Conclusions:Most of the reviewed DFs describe the avoided fossil GHG emissions.These DFs may provide insights on the wood-based products with a potential to replace emissions intensive alternatives but they do not reveal the actual climate change mitigation effects of wood use.The way DFs should be applied and interpreted depends on what has been included in them.If the aim of DFs is to describe the overall climate effects of wood use,DFs should include all the relevant GHG flows,including changes in forest and HWP carbon stock and post-use of HWPs,however,based on this literature review this is not a common practice.DFs including only fossil emissions should be applied together with a coherent assessment of changes in forest and HWP carbon stocks,as was the case in most of the reviewed studies.To increase robustness and transparency and to decrease misuse,we recommend that system boundaries and other assumptions behind DFs should be clearly documented. | Tanja Myllyviita Sampo Soimakallio Jáchym Judl Jyri Seppälä | 2021 | Forest Ecosystems2021，8，3： | 1 |
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