Again LLD appeared effective for source control and had better outcome than a laparoscopic HP. Interesting, they treated 5 cases of stage IV disease with LLD

combined with laparoscopic closure of the sigmoid colon perforation. Most recently the Dutch have reviewed their experience with LLD check details in 38 patients and reported notably less impressive outcomes [28]. In 31 patients the LLD controlled the sepsis. These patients had low mortality (1 died), acceptable morbidity and relatively rapid recovers. However, in the remaining 7 patients LLD did not control abdominal sepsis, two died of multiple organ failure (MOF) and 5 required further surgical interventions (3 HPs, 1 diverting stoma and 1 perforation closure). One of these died from Selumetinib cell line aspiration and the remaining four experienced prolonged complicated recoveries. These authors concluded that patient selection is of utmost importance. PD0325901 They believe it is contraindicated in stage IV disease. Additionally they noted that patients with stage III disease who have multiple co-morbidities, immunosuppression, a high C reactive protein level and/or a high Mannheim Peritonitis Index are at high risk of failure and concluded that a HP as a first step is the best option in these patients. Figure 1 Experience with laporoscopic lavage and drainage. Table 2 Laparoscopic lavage

and drainage (LLD) compared to laparoscopic hatman’s procedure (LHP)   LLD LHP p value # of patient 47 41   OR time (minutes) 100 ± 40 182 ± 55 0.001 Conversion 2% 15% 0.05 Complications 4% 13% 0.05 Mortality 0% 2.4% ns Hospital stay (days) 6.6 ± 2.4 16.6 ± 10 0.01 Colostomy closure na 72% na Elective resection 45% na na Nonoperative management (NOM) More recently, Costi et al. added more controversy to management options when they reported their experience with NOM of 39 hemodynamically stable patients with Aprepitant stage III diverticulitis [31]. Three (8%) required an emergency operation because of clinical deterioration and underwent an HP. Seven (18%) required later CT-guided PCD of abscesses, while amazingly

29 (74%) required no early operative intervention and hospital mortality was zero. Half of the discharged patients underwent a delayed elective sigmoid resection and of the remaining half, five had recurrent diverticulitis successfully treated medically (with later elective resection). Of note, patients who underwent delayed elective resection experienced higher than expected morbidity leading the authors to conclude that perhaps delayed resection is not necessary and causes more harm than good. It is surmised with resolution of an acute perforation; local fibrosis prevents the recurrent perforation of the diverticulum. Dr Costi has cautioned that it is imperative to differentiate stage III from stage IV disease.

A.1.13.1) vitamin B 12 transport protein. The topological prediction was performed with the WHAT program. Blue lines denote Hydropathy; Red lines

denote Amphipathicity; Orange bars mark transmembrane segments as predicted by HMMTOP. Figure 5 Red lettering indicates the TMSs (TM1-10) as also indicated by the Volasertib order helical structures above the sequence. Numbers at the beginning of each line refer to the residue numbers in the protein. TMSs within BtuC revealed by x-ray crystallography. The GAP program was run for TMSs 1–4 of gi288941543 aligning with TMSs 6–10 of gi150017008. GSK621 mouse The result, shown in Figure 6, gave a comparison score of 13.6 S.D. with 42.1% similarity and 31.0% identity. These results clearly show the presence of two BAY 80-6946 purchase internal repeats. Figure 6 TMSs 1–4 of gi288941543 aligned with TMSs 6–10 of gi150017008, giving a comparison score

of 13.6 S.D. with 42.1% similarity and 31.0% identity. The numbers at the beginning of each line refer to the residue numbers in each of the proteins. TMSs are indicated in red lettering. Vertical lines indicate identities; colons indicate close similarities, and periods indicate more distant similarities. We were able to demonstrate an internal repeat for a twenty TMS transporter, FhuB (TC# 3.A.1.14.3), a protein that catalyzes the transport of iron hydroxamates across the cytoplasmic membrane [27]. Its TMSs 1–10 aligned with TMSs 11–20, as shown in Additional file 1: Figure S5. The comparison score calculated was 33 S.D. with 44.8% similarity and 31.5% identity, demonstrating that TMSs 1–10 and TMS 11–20 resulted from a relatively recent intragenic duplication event. Evolutionary relationships among uptake porters with differing numbers of TMSs In this section, we aim to understand how the ABC uptake porters predicted to contain different numbers of TMSs relate to one another. Understanding the relationships between putative five PAK5 and six TMS transporters The five

TMS porter investigated in this part of our study is HisM (TC# 3.A.1.3.1), involved in mediating histidine uptake. The hydropathy plot is shown in Additional file 1: Figure S6. A hundred non-redundant homologues of HisM were obtained via BLAST, and the average hydropathy plot, based on the multiple alignment, was derived using the AveHAS program (Additional file 1: Figure S7). The results confirm that HisM is indeed a 5 TMS protein. To demonstrate the relationship between the five TMS HisM and the six TMS MalG protein, their sequences were aligned. As seen from the alignment shown in Additional file 1: Figure S8, TMSs 2–6 of a MalG homologue, gi239931681, aligned with TMSs 1–5 of a HisM homologue (gi116248748), resulting in a comparison score of 17.5 S.D. (39.2% similarity and 27.9% identity). The extra TMS in MalG, not present in HisM, is therefore TMS1. TMSs 1–4 of a ten TMS porter, BtuC (TC# 3.A.1.13.1) homologue, gi87122087, aligned with TMSs 1–4 of the six TMS porter, MalG (TC# 3.A.1.1.

After generation of RACE-Ready cDNA, a PCR and a nested PCR were performed by using the inrR-specific primer 95,156rv plus the Universal Primer A (UPM, Clontech), HKI-272 and the

inrR primer 95,677rv plus the Nested Universal Primer A (NUP), respectively. Both PCR products were sequenced using a further inrR specific primer 95,790rv in the BigDye Terminator v3.1 cycle sequencing kit (Applied Biosystems), and were separated on ABI PRISM 3100 Genetic Analyzer (Applied Biosystems). A further successful mapping was deployed with 5′RACE on the transcript starting upstream of the most distal ICEclc ORF101284. 5′RACE reactions for the regions upstream of ORFs 58432, 66202, 73676, 81655, 88400, and 89746 did not produce specific fragments. Digoxigenin-labeled probe synthesis DNA regions of between 126 and 560 bp of 21 selected ORFs from the clc element’s core region (Figure 1) were amplified by PCR for probe synthesis (Additional file 1, Table S3). One of the PCR primers

(reverse complementary to the targeted ORF) included the sequence for the promoter region this website of T7 RNA polymerase. Antisense digoxigenin-labeled RNA probes were then synthesized from ~1 μg of purified PCR product by using T7 RNA polymerase according to instructions of the suppliers (Roche Applied Science). Northern hybridization 20 μg of total RNA were incubated in 20 μl (total volume) of denaturation buffer (containing 1 M glyoxal, 25% v/v learn more dimethylsulfoxide, 10 mM sodium phosphate, pH 7.0) for 1 h at 50°C. 100 ng of a digoxigenin-labeled RNA molecular weight marker I (0.3 — 6.9 kb, Roche Diagnostics)

was treated similarly. A volume of 0.2 μl of a 10 mg/ml ethidium bromide solution and 1 μl loading buffer (containing 50% sucrose, 15 mg/ml bromophenol blue in DEPC-treated H2O) were added to the samples at the end of the incubation period and mixed. Fragments were separated at 50 V on a 1% agarose gel in 10 mM sodium phosphate buffer (pH 7.0). RNA was subsequently transferred from gel Selleck Staurosporine onto Hybond N+ nylon membrane (Amersham Biosciences) in 10 × concentrated SSC solution (containing 3 M NaCl and 0.3 M sodium citrate dissolved in demineralized H2O) with the help of the VacuGene XL system (Amersham Biosciences) for 3.5 h at a vacuum of 50 mbar. After transfer, RNA was fixed to the membrane with a UV crosslinker (CX-2000, UVP) at a dose of 0.3 J per cm2. Immediately before hybridization, the membrane was rinsed with 20 mM Tris-HCl (pH 8.0) at 65°C for 10 min to remove glyoxal. The hybridization was performed in DIG Hybridization buffer (Roche Diagnostics) for 15 h at 68°C. The washing steps and the immuno-chemiluminescent detection were done according to the supplier’s instructions (Roche Diagnostics) using alkaline-phosphatase-conjugated anti-digoxigenin Fab fragments and CSPD as reagent for the chemiluminescence reaction. Light emission was detected on Hyperfilm ECL (Amersham Biosciences).

4B). In the other binding QNZ model (designated hereinafter as model B in Fig. 4C), Emodin entered into the middle of the tunnel C near the catalytic site, and located in the hydrophobic pocket consisting of residues Ile20, Leu21, Pro22, His23, Gly79, Phe83, Ile98, Val99 and Phe101. Ring A extended to the bottom of the tunnel and was stacked between

residues Pro22 and Ile98, ring B interacted with residue Val99, while ring C bound to residues His23 and Phe101 through hydrophobic interactions. Additional hydrophobic interactions between 3′-methyl of ring A and residues Ile20 and Phe83, and hydrogen bond interactions between 6′-hydroxyl of ring C and water molecules of W12 and W402 which formed find more H-bonds to Oε1 and Oε2 of Glu72 respectively stabilized Emodin in the right place (Fig. 4D). Figure 3 Stereo view of the omit electron density map contoured at 1.0σ around Emodin. Monomers A/B, C/D and Emodin are colored

yellow/magenta, blue/orange and wheat, respectively. Residues interacted with Emodin are shown as sticks. Figure 4 Schematic diagram of Emodin binding models against HpFabZ. The electrostatic surface of the active tunnel is rendered by a color ramp from red to blue. Emodin and surrounding critical residues are shown as Panobinostat mw sticks; water molecules that interact with Emodin are shown as red sphere. Hydrogen bonds are shown as yellow dashes. Emodin is colored wheat, and residues are colored in yellow, magenta, blue and orange for monomers A, B, C and D, respectively. The diagram was produced by the program Pymol. (A) Binding model A of Emodin around the entrance of tunnel B. Emodin binds to the entrance of tunnel B linearly through hydrophobic interactions, and is stacked between residues Tyr100 and Pro112′. (B) The interactions between Emodin

and residues nearby (as well as some water molecules) in Coproporphyrinogen III oxidase model A are indicated. Ring A of Emodin is stacked between Tyr100 and Pro112′ forming a sandwich structure. 3′-methyl of ring A and C forms hydrophobic interactions with residues near the tunnel entrance. In addition, 6′-hydroxyl of ring C interacts with water molecule W466 through hydrogen bond. (C) Binding model B of Emodin near the catalytic site of tunnel C. Emodin extents to the bottom of the tunnel and is located in the hydrophobic pocket. (D) The interactions between Emodin and residues nearby (as well as some water molecules) in model B are indicated. The whole molecule of Emodin hydrophobic interacts with residues near by as well as hydrogen bonded interacts with waters W12 and W402 through its 6′-hydroxyl of ring C. Discussion It is known that Emodin shows a wide range of pharmacological properties including anticancer, anti-inflammatory, antiproliferation, vasorelaxant and anti-H. pylori activities. However, to date no targeting information has been revealed regarding Emodin’s anti-H. pylori activity.

All authors read an approved the final draft.”
“Background The Gram-negative Epsilonproteobacterium Campylobacter

jejuni, which is due to recent epidemiological data the most leading cause for bacterial gastroenteritis and Guillain-Barré-syndrome (GBS) worldwide, shows a high genetic diversity #this website randurls[1|1|,|CHEM1|]# among its isolates [1]. As consequence of this genetic and phenotypic diversity several C. jejuni subpopulations could be identified on the basis of the presence of non-ubiquitous genes [2]. In a previous study we could identify six C. jejuni groups combining selleck products multilocus sequence typing (MLST) with six genetic markers: ansB, dmsA, ggt, cj1585c, cj1365c and dimeric tlp7 (Tlp7m + Tlp7c) [2]. Here we could in particular demonstrate that the genes ansB, dmsA, ggt occur together in a specific cj1585c- and cj1365c–negative isolate group [2]. Several

studies were able to correlate further genetic markers with clinical parameters. Thus, the question was addressed how a sialylated lipoologosaccharide (LOS) affects the severity of the Campylobacter-trigged diarrhea [3–5]. It was demonstrated that a sialylated LOS of the Campylobacter cell wall is associated with an increased occurrence of bloody diarrhea and a longer duration of symptoms [3–5]. Champion and coworkers made a further interesting finding. They demonstrated that 55.7% of C. jejuni isolates from human faeces belong to a non-livestock

clade that misses the flagellin O-glycosylation cluster encoded by the genes cj1321-cj1326[6]. Cj1321-cj1326-negative strains originate mostly from asymptomatic carriers and the environment. Thus, flagellin O-glycosylation may Sirolimus purchase play as well a role in cell invasion, and in consequence for the virulence in humans. Another study of Feodoroff and coworkers identified a C. jejuni-subpopulation in which they were able to detect the gamma-glytamyl-transpeptidase gene (ggt) but not the fucose permease gene (fucP), the phospholipase A gene (pldA) and the enterochelin-uptake-binding-protein gene (ceuE) using pldA- and ceuE-primers derived from the NCTC 11168 genome sequence (The corresponding genes are designated in the following as pldA 11168 and ceuE 11168) [7]. These isolates could be associated with a higher rate of hospitalizations and bloody diarrhea [7].

In Amacayacu, mushroom communities differed between forests on terra firme and regularly flooded forests (i.e. várzea). A EPZ004777 ic50 putative ectomycorrhizal forest type dominated by Pseudomonotes tropenbosii yielded some candidate ectomycorrhizal species. A recently cleared

patch of forest gave a high number of dead wood-inhabiting CRT0066101 purchase fungi. The forests patches studied differed in macrofungal and plant species composition, suggesting complex spatial–temporal relationships between fungal biodiversity and vegetation, plant diversity and soils. The question remains whether it is possible to get a reliable total estimate of macrofungal diversity in such tropical habitats as even after 20 years of intense sampling in a European forest macrofungal Momelotinib cell line species new to the plots still appeared (Straatsma et al. 2001; Egli et al. 2006). An increased future sampling effort is needed to further confirm the differences observed in the

species distributions in the different forest plots. Acknowledgments The authors are greatly grateful to NWO-WOTRO for the financial support of the project (WOTRO grants 895.100.014 and WB 84-525). Logistic support was given by Tropenbos Colombia and we thank Dr. Carlos Rodriguez for this. C.L-Q and A.E.F.M. thank the University of Antioquia for giving time to collect in the Amazonas. Further financial support from the Studienstiftung Mykologie and the CBS-KNAW is greatly appreciated. Finally, we want to thank the indigenous people in Araracuara and Araracuara-Peña Roja and the workers in the Parque Natural Nacional Amacayacu for their willingness to allow us to perform the studies described. Open Access This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the

original author(s) and the source are credited. Electronic supplementary material Below is the link to the electronic supplementary material. Supplementary material 1 (XLS 149 Amylase kb) Supplementary material 2 (DOC 997 kb) References Alexander I, Selosse MA (2009) Mycorrhizas in tropical forests: a neglected research imperative. New Phytol 182:14–16PubMedCrossRef Alexopoulos CJ, Mims CW, Blackwell M (1996) Introductory mycology, 4th edn. Wiley, New York Braga-Neto R, Luizão RCC, Magnusson WE, Zuquim G, de Castilho CV (2008) Leaf litter fungi in a Central Amazonian forest: the influence of rainfall, soil and topography on the distribution of fruiting bodies. Biodivers Conserv 17:2701–2712CrossRef Brown N, Bhagwat S, Watkinson S (2006) Macrofungal diversity in fragmented and disturbed forests of the Western Ghats of India. J Appl Ecol 43:11–17CrossRef Colwell RK (2006) EstimateS: Statistical estimation of species richness and shared species from samples. Version 8.

The TtgABC homologue in Escherichia coli, AcrAB-TolC, is also involved in extrusion of quorum sensing signals and in regulation of population entering into stationary phase. Namely, it has been shown that acrAB-deficient strain can grow to higher cell density in stationary phase than the wild-type E. coli [39] indicating that its cell division is less inhibited c-Met inhibitor by stationary phase factors.

In case of P. putida, JNK-IN-8 research buy However, we found no evidence that inactivation of TtgABC pump could affect the growth of bacterial culture in stationary phase, as judged by optical density measurements (data not shown). Nevertheless, flow cytometry analysis of the phenol-exposed P. putida ttgC mutant revealed population structure indicative of more active cell division than that

of the wild-type. However, at this stage of studies we cannot distinguish whether less arrested cell division is a reason for the increased phenol tolerance of the ttgC mutant or, vice versa, increased phenol tolerance results in less-inhibited cell division. In our previous study, G418 purchase where we showed that the colR-deficient P. putida is less tolerant to phenol than its parental strain, we argued that membrane permeability of the colR mutant to phenol may be increased [8]. However, results of the current study suggest that the phenol entry into the colR-deficient strain is not increased. The latter was supported by the assay which measured the ability of glucose-grown cells to survive in the presence of 50 mM phenol. Unexpectedly, no differences in cell survival between Rutecarpine the wild-type and the colR-deficient strain

were recorded after phenol-shock, indicating similar membrane permeability to phenol in the colR-deficient and the wild-type cells. As phenol is known to cause membrane permeabilization [40] we therefore tested whether population of phenol-exposed colR-deficient strain could contain more cells with PI permeable membrane. However, as judged by flow cytometry analysis of gluconate-grown bacteria, also the membrane permeabilizing effect of phenol is similar to the wild-type and the colR mutant (Fig. 5). Thus, other reasons than enhanced phenol entry or increased membrane permeability should underlie behind the lowered phenol tolerance of the colR mutant. Interestingly, population analysis at single cell level revealed that compared to the wild-type, phenol more efficiently enhanced the relative amount of subpopulations with higher DNA content in case of the colR mutant, suggesting that cell division of the colR mutant is more sensitive to phenol inhibition than that of the wild-type (Fig. 5). However, it is hard to distinguish whether it occurs due to lowered phenol tolerance or reflects some sort of specific response.

g. flagellin (FliC/FlaA) and type IV pilin types (PilA)). Transcriptomic analyses are able to quantitate gene expression accurately up to 4.7 orders

of magnitude [76], however proteomic strategies such as iTRAQ only achieve measurement of around 2 orders of magnitude. Technical limitations of the iTRAQ method may lead to an underestimation of the magnitude of change [77], while many proteins are below the limit of detection by 2-DE. Clear examples of iTRAQ ratio underestimation are seen in proteins that are unique to a particular strain, such as AES_7165 (unique to AES-1R), which despite being absent in PAO1 and PA14 only achieved measured ratios of 4.15 and 4.90, respectively. Conclusions A complementary proteomic approach combining gel-based (2-DE) and gel-free (2-DLC-MS/MS with

check details iTRAQ tags) techniques was employed to quantitatively compare the proteomes of P. aeruginosa strains PAO1, PA14 and AES-1R (an acute, transmissible CF isolate). Proteins associated with AES-1R belonged to a variety of functional groups including Wortmannin virulence factors, antibiotic resistance, LPS and fatty acid biosynthesis, and several MS-275 mouse hypothetical proteins. Proteins involved in the acquisition of iron were elevated in AES-1R compared to PAO1, while being decreased compared to PA14. These results confirm that CF-associated P. aeruginosa strains express a unique protein profile indicative of phenotypic adaptations to their environment and that provide traits conferring an advantage in colonization of the CF lung micro-environment. Identification of the proteins used by transmissible strains will aid in the elucidation of novel intervention strategies to reduce the burden of P. aeruginosa infection in CF patients. Acknowledgements This work was supported by the National Health and Medical Research Council of Australia (NHMRC 632788 to S.J.C.). N.J.H. is the recipient of an NHMRC Dora Lush Biomedical Research Scholarship and a stipend

from the Australian Cystic Fibrosis Research Trust (ACFRT). N.S. is the recipient of an Australian Postgraduate Award. The authors wish to thank Dr. Torsten Seemann from the Victorian Bioinformatics Consortium for assistance with annotation of the AES-1R genome sequence and bioinformatics Tyrosine-protein kinase BLK support for proteomics data searches. Electronic supplementary material Additional file 1: Growth curves for P. aeruginosa AES-1R, PAO1 and PA14 grown to stationary phase in LB medium. Dotted line and *, harvest time for PAO1 and PA14; #, for AES-1R. (JPEG 348 KB) Additional file 2: Table containing identification of differentially abundant proteins in P. aeruginosa AES-1R compared to PAO1 and PA14 using 2-DE. (PDF 143 KB) Additional file 3: Table containing identification of differentially abundant proteins in P.

All authors read and approved the final manuscript.”
“Background Lactic Acid Bacteria (LAB) are a group of functionally and genetically related bacteria known for the fermentation of

sugars to the metabolic end-product, lactic acid [1]. LAB belong to the order of Lactobacillales, which includes the genera Lactobacillus, Lactococcus, Leuconostoc, Oenococcus, Pediococcus, Streptococcus, among others [2]. LAB, including lactobacilli, are very diverse and are commonly found in many different environments. Lactobacilli are naturally associated with many foods, including fruits, vegetables, cereal grains, wine, milk and meats. In addition, buy GDC-0068 several species of Lactobacillus, such as Lactobacillus gasseri, are considered to be indigenous to the gastrointestinal tract (GIT) and other mucosal surfaces, including the mouth and vagina [3, 4]. The Lactobacillus AG-881 cost genus has been explored for their probiotic potential due to the ability of specific strains to survive passage through the human GIT and exert benefits to general health and wellness to the host [5]. Probiotics have been defined as live microorganisms that,

when administered in adequate amounts, confer a health benefit to the host [6]. Some of these benefits include a positive influence on the normal microbiota present in the GIT, the competitive exclusion of AZD5363 solubility dmso pathogens, and the stimulation or adjustment of mucosal immunity [7]. Lactobacilli can utilize a variety this website of carbohydrates which reflects the nutrient availability in their respective environments. In many lactobacilli, PTS (phosphotransferase system) transporters are the dominant carbohydrate transporters [8]. For example, the L. plantarum genome revealed 25 PTS transporters which correlate with its broad carbohydrate utilization profile [9]. Analysis of the L. johnsonii, L. acidophilus and L. gasseri genomes further substantiate these observations since they contain a preponderance of PTS transporters [10]. The PTS functions by the transfer of a phosphate group from phosphoenolpyruvate (PEP) to the incoming sugar through a series of sequential steps that involve the different components of the PTS. The PTS consists of cytoplasmic components, which lack

sugar specificity, and membrane-associated enzymes, which are specific for a few sugars, at most. The cytoplasmic components are enzyme I (EI) and histidine-phosphorylatable protein (HPr). The membranous component of the PTS system, enzyme II (EII), is made up of three to four subunits: IIA, IIB, IIC and sometimes IID [11]. In reference to the human GIT, lactobacilli are the predominant species in the ileum [12]. The carbohydrate utilization profile of lactobacilli isolated from porcine ileal contents reflects the carbohydrate content of the diet [13]. For example, the relative percentage of lactobacilli that can utilize starch increases after weaning, whereas the relative percentage of lactobacilli that can utilize lactose decreases after weaning.

Additional subboundaries give their contributions to the diffusion flow after 20 to 30 cycles of γ-α-γ transformations. Diffusion

coefficients were too high – more than 103 times higher compared to the values obtained by extrapolation to high temperature data at temperatures below 0.5 of melting point. Data in this work also show high diffusion transparency of fragments’ subboundaries of nanoscale level (nanofragments) due to dislocation nature of small-angle boundaries. We might probably determine the effect of dislocations and additional subboundaries in reverted f.c.c. austenite and b.c.c. martensite onto the total diffusion flow if we studied alloy diffusion characteristics after different numbers of γ-α-γ cycles. It is known that dislocation density increases by three orders after the first γ-α-γ transformation. With increased number of such cycles, dislocation density remains almost unchanged although the total #BIIB057 mw randurls[1|1|,|CHEM1|]# length of additional see more subboundaries significantly increases [17, 18]. The up-to-date ability to create ultrafine and

nanocrystalline structures of metallic materials opens new prospects for further intensification methods of chemical and thermal treatment (carburizing, nitriding, metallization) due to a significant acceleration of diffusion. Thus, it follows from this work that temperature of the surface metallization of metastable iron-nickel alloy can be reduced by several hundred degrees. Previously, it has been found [6] that anomalies of grain-boundary diffusion occur in new classes of nanostructured materials created by means of severe plastic deformations. This means that diffusion coefficients increase by several orders and diffusion energy activation is reduced almost by half. Grain-boundary diffusion Sclareol plays a significant role in the formation of structure-sensitive properties. The authors of [6] believe that this type of diffusion determines significantly the course

of diffusion-controlled processes such as recrystallization, high-temperature plastic deformation, superplastic fluidity, temperature-dependent internal friction, and grain-boundary deformation under conditions of fatigue. Diffusion mobility increase of substitution atoms in reverted austenite as the result of multiple martensitic transformation is comparable with the one which occurs as the result of severe plastic deformation. Conclusions As the result of multiple martensitic γ-α-γ transformations, diffusion mobility of nickel and iron atoms in reverted austenite of Fe-31.7%Ni-0.06%C alloy is significantly increased. The diffusion coefficients increased, and at the temperature of 400°C, they corresponded to stationary diffusion coefficients at 900°C. Two factors influenced the diffusion acceleration: a three-order increase of the dislocation density that reached the value of 5 × 1011 cm-2, and additional low-angle subboundaries of disoriented nanofragments with deformation twins subboundaries formed as the result of γ-α-γ cycles.