The maintenance of energy balance is regulated by complex homeostatic mechanisms, including those emanating from adipose tissue. The main function of the adipose tissue is to store the excess of metabolic energy in the form of fat. The energy stored as fat can be mobilized during periods of energy deprivation . The adipose tissue has also a homeostatic role regulating energy balance and functioning as endocrine organ that secretes substances that control body homeostasis. Two adipose tissues have been identified: white and brown adipose tissues (WAT and BAT) with different phenotype, function and regulation. WAT stores energy, while BAT dissipates energy as heat. Brown and white adipocytes have different ontogenetic origin and lineage and specific markers of WAT and BAT have been identified. “Brite” or beige adipose tissue has been identified in WAT with some properties of BAT. Thyroid hormones exert pleiotropic actions, regulating the differentiation process in many tissues including the adipose tissue. Adipogenesis gives raise to mature adipocytes and is regulated by several transcription factors  that coordinately activate specific genes, resulting in the adipocyte phenotype. T3 regulates several genes involved in lipid mobilization and storage and in thermogenesis. Both WAT and BAT are targets of thyroid hormones, which regulate genes crucial for their proper function: lipogenesis, lipolysis, thermogenesis, mitochondrial function, transcription factors, the availability of nutrients. T3 acts directly through specific TREs in the gene promoters, regulating transcription factors. The deiodinases D3, D2, and D1 regulate the availability of T3. D3 is activated during proliferation, while D2 is linked to the adipocyte differentiation program, providing T3 needed for lipogenesis and thermogenesis. We examine the differences between BAT, WAT and brite/beige adipocytes and the process that lead to activation of UCP1 in WAT and the presence of BAT in humans and its relevance. Thyroid hormones regulate multiple physiological systems in many tissues and are of maximal importance during developmental processes. T3 regulates the development of many tissues Bernal,  by actinThe adipose tissue is one important target of thyroid hormones. The adipose tissue is the main place for lipid storage, besides its function in lipid transport, synthesis and mobilization. The adipose tissue stores energy in the form of fat, so that this metabolic energy can be used in times of hunger or illness. In addition, adipose tissue works as a homeostatic mechanism regulating energy reserves and releasing many substances that keep the homeostasis of the organism, some of them, like leptin, act as adipostats regulating the amount of fat stored.Mammals have two types of adipose tissue: white and brown adipose tissue (WAT and BAT), with different phenotype, function and regulation. The white adipose tissue (WAT) was considered for many years a site for lipid storage. White adipocytes have a characteristic large lipid droplet that fills the cellular space, while the cellular structures  are placed near the cellular membrane. WAT is distributed in different anatomical locations that have been grossly divided into subcutaneous and visceral fat o intra-abdominal fat. Both locations have different lipolytic sensitivity in response to hormones and its abundance is associated to a different health risk, because an increase in visceral fat is associated to insulin resistance, metabolic syndrome and cardiovascular diseases  is responsible for the adaptive or facultative thermogenesis. BAT is activated in response to cold exposure or fat diets providing extra heat in demanding situations to maintain energy balance. BAT is abundant in small rodents, hibernating animals and specially in newborns  or beige adipocytes. They are multilocular and express UCP-1, Cidea (Cell death activator CIDE-A) and other markers of brown adipocytes as PGC1α (PPARγ Coactivator 1α). They are more frequently in certain anatomical locations, e.g., the inguinal fat. “Brite” adipocytes seem to come from different embryonic precursors than brown adipocytes and express distinct gene signatures   were identified later on as critical for the adipocyte phenotype, as will be review later on.Pluripotential stem cells give rise to preadipocytes, a mesenchymal cell predetermined to be adipocyte. It is not clear which are the specific factors that trigger the transition from pluripotential stem cells into predetermined preadipocytes. A common mesenchymal stem cell produces adipocytes, myoblasts and osteoblasts  of the adipose tissue. These precursor cells allowed to set primary cultures of preadipocytes, which proliferate and differentiated in culture . The specific growth factors governing proliferation of white preadipocytes require further research. White preadipocytes require only T3, insulin and transferrin to proliferate in serum-free medium . Differentiation was induced using dexamethasone and IBMX, an agent that increase cAMP levels. T3 was also included in the “differentiation cocktail.” So, we do not know if the effects observed are due to the action of the T3 added or the process of differentiation itself. During adipocyte differentiation the transcription of specific genes and the synthesis of numerous proteins increase, specially the lipogenic enzymes GPD, FAS and ME, and many others as described above  belong to the basic leucine zipper family. The C/EBP family  recognizes a common DNA-binding element and has tissue-specific expression patterns. C/EBPα is expressed in brown and white adipose tissues, placenta and liver and is a master regulator of adipose tissue development. C/EBPα overexpression induces the differentiation of 3T3-L1 preadipocytes. It works as antimitotic inducing growth arrest (proteins GADD45 and p21)  have C/EBP binding domains in their promoters and are activated together during adipogenesis  die shortly after birth due to hypoglycemia, defective hepatic glycogen storage and gluconeogenesis , PPARδ and PPARγ, quite specific of adipose tissue. PPARs activate the PPAR response elements (PPRE) present in the promoter of specific target genes, and form heterodimers with the X receptor of retinoic acid (RXR). FAS, aP2, PEPCK, LPL, SCD have PPREs in their promoters. The PPRE sequence of a given gene can bind different isoforms in different tissues, e.g., PPARα in the liver and PPARγ in adipose tissue. PPARs play important roles in adipogenesis, inflammation, atherogenesis, glucose homeostasis and cancer.During adipogenesis PPARγ is activated , is a triacylglycerol lipase strongly upregulated by T3 in rat and human white and brown adipocytes  important for Glut4 expression, both are up regulated by T3 in brown adipocytes; other T3 actions include the regulations of gluconeogenesis and glycolysis Figure . T3 alsoIn white adipocytes or 3T3-L1 adipocytes the differentiation process is tested by the increase in lipids, measuring the increase in lipid droplets or increases in lipogenic enzymes. The differentiation in BAT includes an increased thermogenic capacity, measured as UCP-1 increases.BAT function is the production of heat under cold exposure (facultative thermogenesis). This function is accomplished by the mitochondrial uncoupling protein (UCP-1), which uncouples the oxidative phosphorylation. After activation of the sympathetic nervous system (SNS), NE is released  that govern the differentiation of adipocytes. T3 regulates many of the enzymes involved in the process of adipogenesis, either directly through the interaction of its nuclear receptors (TRs) with TREs or through the interaction with other nuclear receptors as PPARs or coactivators. The deiodinases, especially D2, play a crucial role producing the T3 required or limiting its levels. D3 increases during proliferation, while D2 plays a crucial role in adipogenesis, thermogenesis and lipid metabolism. The number of genes regulated by T3 in adipocytes continues to grow, not only for lipid metabolism and carbohydrates but also regulating other process unknown to be important for the biology of the adipocyte. Several genes have been identified as markers of brown, white and “beige/brite” adipocytes, establishing that they are distinct cells. “Browning” occurs in some WAT depots under specific conditions or drugs and specific markers of “beige/brite” adipocytes have been identified. Additionally, BAT has been identified in humans and its presence and regulation is being actively studied. The reactivation of BAT and the induction of beige/“brite” adipocytes in humans could represent a therapeutic option to fight obesity.The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


A 69-year-old man, with severe refractory Crohn's disease, presented with acute coronary syndrome that required angioplasty. He developed severe tirofiban-induced thrombocytopenia (TIT) heralded by type I allergic reaction that required steroids and a combination of antihistamine H1 and antihistamine H2 for symptomatic management. The thrombocytopenia spontaneously resolved uneventfully in 48 hours thereafter. This case report suggests a possible association between TIT and inflammatory bowel disease. Therefore, strict monitoring of the platelet count is required in patients who develop allergic reactions to tirofiban. Glycoprotein IIb/IIIa (GP IIb/IIIa) receptor is a platelet surface protein that leads to platelet aggregation via cross-linking of fibrinogen and von Willebrand factor. Therefore, it has been considered as a primary target for the treatment of acute coronary syndrome and used as an adjunct to coronary interventions . Althoug3 with normal peripheral blood smear. The patient received two pools of platelets at 12 hours apart. Tirofiban, ticagrelor, enoxaparin, and aspirin were stopped. Two days later, the platelet count increased to 47000/mm3. The patient was discharged three days later with normal hematologic test results.A 69-year-old man without previous medical history except for a refractory Crohn's disease was referred to the Cardiology Department for the management of an acute coronary syndrome. His labs were normal except for an increased level of cardiac biomarkers. The patient received aspirin 100 mg PO and enoxaparin 30 mg IV before undergoing an urgent coronary angiogram. The angiogram revealed 95% stenosis of a dominant marginal branch requiring stenting. The patient therefore received enoxaparin 25 mg IV, ticagrelor 180 mg PO, and tirofiban 34 mcg/Kg/min followed by 0.1 mcg/kg/min over 24 hours. The rest of the angioplasty was uneventful. One day later, the patient complained of palpitations, dyspnea, chills, and minor urticaria. The patient was symptomatically treated with methylprednisolone 60 mg IV STAT and was started on desloratadine 5 mg PO q12h and ranitidine 150 mg IV q12h. One day later, the patient complained of repetitive episodes of rectal bleeding. The blood exam was only relevant for severe thrombocytopenia at 2000/mm3) within 12 hours of exposure, acute within 12 hours of second exposure, severe or not 5 to 7 days after any type of exposure, and pseudothrombocytopenia [Since Andreas Gruntziq first introduced coronary angioplasty in 1977, clinicians have been driven to lower the risks of stent thrombosis and introduced anticoagulants and antiaggregants to their procedures. Clinical studies have proved a significant benefit for these adjunctions but with a relatively acceptable risk of bleeding and thrombocytopenia . In the Overall, drug-induced immune thrombocytopenia (DITP) is a form of immune thrombocytopenia (ITP) that occurs 5 to 14 days after initiation of a new drug (commonly quinine or antibiotics). This delay is equivalent to the time for the patient to become sensitized to the drug and to constitute antibodies against his platelets . In contThe comparison of the incidence of thrombocytopenia across the different GP IIb/IIIa inhibitors has been recently reported in one meta-analysis of 29 large placebo-controlled randomized trials [Our patient developed thrombocytopenia during the first 24 hours after his presentation to the hospital. The variations in the kinetics of the platelet count upon withdrawal of all antiaggregants seem to relate to TIT even though aspirin, ticagrelor, and enoxaparin are plausible etiologies for thrombocytopenia. Effectively, our patient being naïve to heparin would have developed HIT after five days. Moreover, aspirin and ticagrelor were never reported to cause such severe thrombocytopenia.The time pattern of the TIT of our patient suggests the presence of naturally occurring antibodies that would destroy platelets coated with IIb/IIIa antagonists. Tirofiban may act as an antigen or may expose a platelet epitope that would be recognized by specific antibodies . Our pat


I2 = 97.5 %) for A(H1N1)pdm09 to 2.8 %  for A(H1N1). The pooled prevalence of influenza viruses in stool was 20.6 % , but their correlation with GI symptoms has rarely been explored. The presence of viral RNA in stools because of haematogenous dissemination to organs via infected lymphocytes is likely, but the potential to cause direct intestinal infection and faecal–oral transmission warrants further investigation. This review highlights the gaps in our knowledge, and the high degree of uncertainty about the prevalence and significance of GI symptoms in patients with influenza and their correlation with viral RNA positivity in stool because of the high level of heterogeneity among studies.This review provides for the first time an assessment of the current understanding about the occurrence and the clinical significance of gastrointestinal (GI) symptoms in influenza patients, and their correlation with the presence of human influenza viruses in stools of patients with confirmed influenza virus infection. Studies exploring how human influenza viruses spread to the patient’s GI tract after a primary respiratory infection have been summarized. We conducted a systematic search of published peer-reviewed literature up to June 2015 with regard to the above-mentioned aspects, focusing on human influenza viruses (A(H1N1), A(H1N1)pdm09, A(H3N2), and B). Forty-four studies were included in this systematic review and meta-analysis. The pooled prevalence of any digestive symptoms ranged from 30.9 %  contains supplementary material, which is available to authorized users. The avian influenza AH5N1) virus causes severe gastrointestinal (GI) symptoms and replicates in human intestinal tissues  virus ca, but theAlthough the main route of human influenza virus infection is respiratory, GI symptoms such as anorexia, diarrhea, vomiting, and abdominal pain are common manifestations –12, and The findings that faecal shedding of seasonal and pandemic influenza viruses could occur in patients with confirmed influenza raises the question of inadvertent human- human transmission, despite emphasis on droplet transmission and precautions for contact with respiratory secretions.Our objective was to outline the current understanding about the occurrence and clinical significance of GI symptoms and human influenza viruses in the stools of patients with confirmed influenza virus infection. Knowledge from studies exploring how human influenza viruses spread to the patient’s GI tract after a primary respiratory infection has been summarized.This review describes for the first time the current knowledge about the clinical significance and pathophysiology of human influenza virus in faecal samples, and, more importantly, highlights gaps in our knowledge and areas where research is warranted.Using PubMed, we searched the MEDLINE database for articles up to June 2015, without date restriction, using the terms ‘human influenza virus’, ‘faeces’, ‘diarrhea’, ‘stomach’, ‘faecal’, ‘intestinal cells’, ‘human intestinal’, ‘gut’, ‘viral load’, and ‘detection’. The terms were used alone or in combinations using Boolean operators. Only articles published in English were included and the search covered all years available in the MEDLINE database.We included studies according to the following eligibility criteria: (1) observational studies comparing clinical features between patients with influenza to estimate the prevalence of GI symptoms by influenza virus type and/or subtype; (2) case reports describing the occurrence of GI symptoms in patients with influenza; (3) observational studies regarding the detection and/or isolation of human influenza viruses in stools of patients with confirmed influenza by using upper and/or lower tract specimens; and (4) experimental studies on intestinal binding of human influenza viruses. The reference lists of all articles were reviewed for additional sources of data. All results were downloaded into an MS Word document and we searched for duplicate citations. Two investigators screened all articles by title and by abstract. All articles meeting the criteria were screened for information on study design, the time when the study was conducted, sample size, patient information, clinical presentation, nasopharyngeal and stool sample collection, number of virologically confirmed cases in nasopharyngeal specimens, influenza RNA detection and viral isolation from stool samples, method used for: viral detection, confirmation, and isolation.Our initial search yielded 143 articles, and after screening titles, abstracts and full-texts with inclusion criteria, 16 publications were selected. Twenty-six additional studies were retrieved by scanning the reference lists of articles selected , a random-effects model was used. Statistical analyses were performed using MedCalc for Windows, version 12.5 .We assessed the extent of the heterogeneity across studies of the prevalence of GI symptoms and the rate of detection of influenza virus in stools among influenza patients by using the I2 index . These t2 < 70 % . In studWe identified ten observational studies (six prospective and four retrospective) describing and comparing the occurrence of GI manifestation among patient mainly using reference methods: RT-PCR –12 and/oAs detailed in additional file Three of the ten studies reported that GI manifestations occurred more frequently in patients with confirmed influenza B virus infection than in those with confirmed infection with human influenza A (A(H1N1), A(H1N1)pdm09, and AH3N2)) virus infection [N2) virusI2 = 97.5 %) for influenza virus A(H1N1)pdm09 infection to 2.8 %  for influenza virus A(H1N1) infection. The most commonly reported individual symptom was vomiting, with pooled proportions ranging from 25.3 %  for influenza B virus infection to 21.9 %  for influenza A(H3N2) virus infection.Because the findings of the ten studies are apparently contradictory, we estimated the pooled prevalence of GI symptoms  by a meta-analysis of the types and/or subtypes of influenza virus infections Table ; Fig. 2.I2 = 96.7 %) for influenza virus A(H1N1)pdm09 infection to 31.6 %  for influenza virus A(H3N2) infection. The most commonly reported individual symptom was vomiting, with pooled proportions ranging from 37.5 %  for influenza A(H3N2) virus to 25.6 %  for influenza B virus infection. Overall, heterogeneity across studies and/or wide confidence intervals were observed for the pooled prevalence of all types of GI symptoms analysed . Among the ten studies reporting faecal viral RNA in stools, six of them have conducted cell culture experiments viral RNA stool [There are ten reports of faecal viral RNA shedding after analysis of: (i) hospitalized adult and/ or paediatric patients –25, or nNA stool , 25, 26,NA stool , 22, 25 While influenza virus is likely to spread to the GI tract of patients after a primary respiratory infection, the route of dissemination remains unknown. Current knowledge explains the detection of human influenza viruses in faeces because of: (i) swallowing of influenza viruses from the upper respiratory tract; (ii) remnants of infected submucosal intestinal antigen-presenting immune cells; and (iii) virus replication in intestinal cells.A low pH environment, such as in the stomach, should render most influenza viruses non-infectious by inducing an irreversible conformational change of the viral haemagglutinin . For thi+ CD68+ dendritic cells, which are localized in the small and large intestine [+ CD68+ cells act as antigen-presenting cells and participate in the stimulation of immunity through T-cell activation [The faecal presence of influenza virus RNA may be related to the detection of human influenza viral RNA in remnants of infected intestinal antigen-presenting immune cells. Influenza virus could bind intestinal cells such as DC-SIGNntestine . These itivation . Antigentivation , and maytivation . The shetivation , 45, 46.in vitro [in vitro differentiated intestinal epithelial cells, suggesting that both avian and human influenza viruses have the potential to infect and replicate in human intestinal epithelial cells [Shu et al.  found thin vitro –50. Humain vitro . Human-ain vitro . Both tyal cells , 52. Indal cells . Intestial cells , 54.Escherichia coli (E.coli) in the intestinal tract increased, perhaps leading to intestinal immune injury. The hypothesis was Similar results were obtained when infecting mice with three different subtypes of respiratory influenza A viruses..A mouse model of respiratory influenza infection was used to explore the hypothesis that respiratory influenza virus can enter the GI tract and as a direct consequence of its replication cause immune injury at this site . IntranaE. coli strains, inducing the exposure of cellular receptors by intestinal cells [E. coli, thereby causing vomiting and diarrhea. These data suggest an increased number of E. coli as a consequence of influenza virus infection is the primary cause of intestinal injury during influenza virus infection.Influenza A virus significantly increases the adhesive properties of mucosa-associated al cells . The expal cells , and infAlthough the human respiratory tract is the main target of infection by influenza viruses, whether human influenza viruses are capable of local GI replication is unclear. This systematic review and meta-analysis shows that the present knowledge on the clinical significance and pathophysiology of human influenza viruses in the GI tract is scarce.The meta-analysis of the occurrence of GI symptoms among patients with influenza showed that they were inconsistent. First, the degree of heterogeneity among the ten studies included is so great that no specific GI symptoms can be described as typical for a patient with influenza. Therefore no comparison of the occurrence of GI symptoms among patients by types and/or subtypes of influenza viruses was possible. Second, the 95 % CIs of the prevalence rates were broad. The wide CIs could be related to the small number of studies included and to their small sample size. Moreover, the majority of studies used different criteria to define GI symptoms , different laboratory methodologies  and were mostly conducted in hospitalized patients.Similarly, studies reporting human cases with virological evidence of influenza virus in stools should be interpreted with caution because detection of viral RNA without additional virological evidence, such as culture or detection of anti-genomic RNA, does not necessary imply infection. Overall, in these studies, few clinical correlations were observed for viral RNA positivity and GI symptoms, and culture positivity was rare.E. coli strains, inducing the exposure of cellular receptors through replication in intestinal cells.The source of influenza viruses in faeces and how the viruses pass through the GI tract is poorly understood. On the one hand, the presence of viral RNA in stools may be a consequence of haematogenous dissemination to organs through infected lymphocytes, while on the other hand, influenza viruses were able to increase the adhesive behaviour of mucosa-associated Several methodological issues warrant discussion. The biggest challenge in extracting and compiling individual study data for this review was the variation in definitions of GI symptoms provided, the scarcity of data on the detection of RNA virus in stools, and the small sample size in the studies, providing little power for comparison between age classes or between types and subtypes of influenza viruses. Viral stool cultures from patients with respiratory infections (with and without GI symptoms) are infrequently required, and in the absence of standard methods for culturing influenza virus from stools, the true occurrence of infectious influenza virus in stools is unknown.Additional studies of large prospective cohorts, examining GI symptoms in patients of all ages with severe and mild influenza, with systematic detection and isolation of influenza virus and other respiratory and enteric viruses from the upper respiratory tract and in stools concomitantly, and measuring influenza viral loads at respiratory and non-respiratory sites may provide further insights into the role of human influenza viruses in the GI tract. Understanding the viral shedding profiles of human influenza viruses might provide helpful information for understanding virulence, cell tropism, and transmission dynamics, and for designing management policies.


Silver Linings Playbook) to 11.75% (Seinfeld) within individual clips. ISC’s were significantly greater than zero for 15 out of 16 clips, and fluctuations within the delta frequency band (i.e. 0-4 Hz) primarily contributed to response similarities across subjects. Interestingly, there was insufficient evidence to indicate that individuals with greater similarities in clip preference demonstrate greater similarities in cortical responses, suggesting a lack of association between ISC and clip preference. Overall these results demonstrate the utility of using ISC’s for prediction, and further characterize the relationship between ISC magnitudes and subjective reports.Cortical responses to complex natural stimuli can be isolated by examining the relationship between neural measures obtained while multiple individuals view the same stimuli. These inter-subject correlation’s (ISC’s) emerge from similarities in individual’s cortical response to the shared audiovisual inputs, which may be related to their emergent cognitive and perceptual experience. Within the present study, our goal is to examine the utility of using ISC’s for predicting which audiovisual clips individuals viewed, and to examine the relationship between neural responses to natural stimuli and subjective reports. The ability to predict which clips individuals viewed depends on the relationship of the EEG response across subjects and the nature in which this information is aggregated. We conceived of three approaches for aggregating responses, i.e. three assignment algorithms, which we evaluated in Experiment 1A. The aggregate correlations algorithm generated the highest assignment accuracy (70.83% chance = 33.33%) and was selected as the assignment algorithm for the larger sample of individuals and clips within Experiment 1B. The overall assignment accuracy was 33.46% within Experiment 1B (chance = 06.25%), with accuracies ranging from 52.9% ( Individuals experience a broad range of perceptual and cognitive events throughout the day. This complexity is approximated by the complexity of the experience of watching short movies or audiovisual clips, which may invoke a greater array of emotional and perceptual experiences than traditional cognitive experiments . HoweverCortical responses may emerge from natural stimuli as either evoked oscillations  from the stimuli, or phase entrainment (i.e. phase tracking) to the stimulus features ,5. TheseThe relationship between neural time series may be examined across individuals using Pearson’s correlation coefficient, or inter-subject correlation’s (ISC’s) –9. WithiSince ISC’s may emerge from similarities in the direct neural response to the audiovisual inputs, as well as similarities in their emergent perceptual experience ,11, we aThe relationship between ISC’s and valence and arousal appears mixed, however, with relationships demonstrated in some cases , but notThe nuanced relationship between subjective reports and ISC’s is further demonstrated by a recent study by Dmochowski et al., 2014. The authors examined the relationship between EEG ISC magnitudes  with the preference of the broad population and the preference of the individuals within the study. They found that the EEG response similarities explained 66% of the variance of population ratings, but only 26% of the variance of the individuals own preferences. Thus, EEG ISC’s appear better at predicting the preferences expressed by a broad audience than the preferences obtained directly from the individuals in which the ISC’s are measured .Within the present study, our primary goal is to examine the utility of using ISC’s for predicting which clips individuals viewed. Within Experiment 1A, we examine the prediction accuracy of three different assignment algorithms which emphasize different aspects of similarity across subjects. The algorithm is implemented within Experiment 1B in a larger sample viewing a diverse array of audiovisual clips. Within Experiment 1B, we recommend the best performing algorithm for future studies implementing EEG ISC’s for prediction. In order to understand the relationship between ISC’s and individual’s perceptual experience, within Experiment 1B we additionally examined whether ISC’s were related to individual preference. We were unable to demonstrate a statistical relationship between ISC’s and preference, which suggests that this measure of subjective experience is unrelated to cortical response similarities across subjects.algorithm selection sessions in order to select the assignment algorithm to predict which video clips subjects watched within the main experiment. Each individual had normal or corrected to normal vision and had no family history of mental illness. Both participants were enrolled in protocols approved by the University of New Mexico Institutional Review Board (HRRC/MCIRB), and provided informed written consent prior to the first session at the Mind Research Network.Two subjects  were recruited to participate in The video clips were presented on a computer using VLC media player. Participants were seated 56 cm from the computer screen, and the VLC media player window comprised 13.2 degree visual angle (dva) horizontally and 7.4 dva vertically. The audio was presented to the individual through speakers placed adjacent the monitor. On average, the audio intensity was ~ 90 decibels (db) across all clips, and the maximum intensity never exceeded ~95 db . Two individuals participated in four sessions each consisting of three ~4:56 min video clips  presenteEEG responses were collected with two 4 channel CamNtech Actiwave mobile EEG devices (sampling rate: 128 Hz). The eight electrodes where placed on the participant’s scalp using the standard 10–20 locations F3, Fz, F4, Cz, P3, P4, O1, and O2, with a left mastoid reference (e.g. see ). EEG anThe continuous EEG recordings were segmented into individual segments for each ~4:56 min video clip. The time-courses were visually inspected for each electrode and segment (i.e. clip) and artifactual time-courses were marked for removal before averaging across time series, as described in detail below. Artifactual segments typically contained multiple segments of large amplitude fluctuations. 4.87 out of 24 (3 clips × 8 electrodes) segments were removed on average.Our goal was to assign a particular EEG segment measured with a given individual to 1 of the 3 video clips. To illustrate this specifically, consider determining which video clip an individual watched while we recorded 1 of the 3 [8 channels × 37940 samples] EEG segments in an individual session. The general approach was to assign this segment, which we refer to as the withheld segment, to one of the three clips using the segments recorded in the other sessions (i.e. sessions 2–8), when subjects watched each of the three clips. In this example, we refer to the segments from sessions 2–8 as the reference segments.The relationship between the withheld segment and the reference segments were examined by calculating the electrode-wise Pearson correlation coefficient between the time series. We conceived of three potential ways in which the time series may be related across subjects, which motivated the three assignment algorithms that were evaluated within Experiment 1A . The algIn the separate time series approach  electrodWithin the aggregate time series approach  electrodIn the aggregate correlations approach  correlatWithin each of the three approaches, assignments were computed for each of the 24 withheld segments, and assignment accuracy was evaluated by determining the percentage of segments which were correctly assigned. The algorithm with the highest assignment accuracy was then used to predict which of the 16 video clips corresponded to each segment within the main experiment.Fourteen, 13, and 17 of the EEG segments were correctly assigned to 1 of 3 clips using the separate time series , aggregaEighteen subjects  between the ages 20 and 35 were recruited to participate. One individual was excluded due to artifactual EEG, bringing the total number of participants to 17. Each individual had normal or corrected to normal vision and had no family history of mental illness. All participants were enrolled in protocols approved by the University of New Mexico Institutional Review Board (HRRC/MCIRB), and provided informed written consent prior to the first session at the Mind Research Network.The viewing distance and audio levels were identical to Experiment 1A. Eighteen individuals viewed sixteen clips  within aThe continuous EEG recordings were acquired (see Experiment 1A) and segmented into ~ 4:00 min intervals for each video clip. Segments were preprocessed as described in Experiment 1A (section 2.1.3). In order to determine the frequency that contributes to ISC’s, the EEG time series were decomposed into time-frequency representations using the discrete wavelet transform (DWT) prior to ISC calculations. We chose multiresolution analysis (MRA) ,16 by DWFive levels of DWT were implemented using the wavedec and wrcoef functions in matlab with a biorthogonal spline wavelet . Each level of decomposition returns two time-frequency representations with half the frequency band of the input, a course representation (i.e. the approximation A), and a high frequency representation . With a 128 Hz signal, the first level of decomposition returns an approximation A containing ~0–32 Hz and its associated detail, D encompassing ~32–64 Hz. At the second level, the approximation AA is ~0–16 Hz and the detail AD is ~16–32 Hz. Following this convention, we focus analysis on the following details and approximations which approximately overlap with the characteristic EEG frequencies: delta , theta , alpha , beta , gamma (DA: ~32–48).Individual [8 channels × 30721 samples] segments were assigned to 1 of the 16 video clips using the aggregate correlations algorithm , i.e. thThe assignment accuracy likely depends on the number of subjects that contribute to the reference segments in the assignment. We evaluated the nature of this dependence when N = 1, 2, 3 … 16 subjects were used as reference. When N < 16, an individual withheld segment is assigned to a particular video clip using all of the unique combinations of subjects from the pool of 16. For example, in the instance where 2 subjects are used as reference, there are 120 unique combinations of the 16 subjects available. The average and standard deviation of these assignment accuracies were examined for each unique combination of subjects, generated with N = 1, 2, 3, … 16 subjects in the assignment.Statistical tests were conducted to determine whether ISC’s were significantly greater than zero for each of the 16 clips (16 permutation tests). Additional tests (Pearson’s r) were conducted to determine whether there was a relationship between ISC magnitudes and individual clip preferences, and ISC magnitudes and assignment accuracy. Statistical tests are reported as significant if p < 0.0028, which conservatively corrects for the 18 tests .The EEG signals were filtered with DWT in order to determine which frequencies contributed to ISC’s. For a given wavelet frequency and electrode, ISC’s were computed for each pair of segments that correspond to matching clips and non-matching clips. For example, for a given pair of subjects, 16 correlations were computed among matching segment pairs (16 movies) and 120 correlations were computed among unique non-matching segment pairs. The 2048 matching correlations (16 clips × 8 electrodes × 16 remaining subjects) were averaged for each individual, and the distribution of individual averages is indicated in The overall average ISC increased from .0035 with the broadband EEG signal (0–50 Hz) to .0064 with the signal filtered between 0–4 Hz . The othIndividual ISC’s (N = 17) were computed for each clip by averaging the correlations computed among 128 segment pairs (8 electrodes × 16 remaining subjects). The distribution of individual average ISC’s is indicated in The spatial distribution of ISC’s were examined by computing the average ICS  separately for each electrode. The highest ISC’s were observed at electrode Cz (r = 0.0083) and electrode 02 (r = 0.0081). The ISC’s were 0.0055, 0.0054, 0.0073, 0.0060, 0.0065, and 0.0044 within electrodes Fz, O1, F3, F4, P3, and P4, respectively . Thus, tThe similarity in preferences between each subject pair was calculated by computing the Spearman rank correlation coefficient between their rankings for the 16 video clips. If ISC’s are related to individual preferences, then subjects with similar preferences, as reflected by larger Spearman’s rho values, would demonstrate a greater similarity in their EEG response to the clips, as reflected in larger ISC’s. The Spearman’s rho and average delta-band ISC’s (i.e. across the 16 movies and 8 electrode) values were uncorrelated across the subject pairs (r(135) = -0.08; p = 0.34), indicating insufficient evidence to demonstrate a relationship between these two variables .EEG segments were DWT filtered within the delta band, since this frequency primarily contributed to ISC’s, and were assigned to 1 of the 16 clips in Experiment 1B using the aggregate correlations assignment algorithm . The aggSilver Linings Playbook) to 11.75% (Seinfeld). In general, there appear to be qualitative differences in the assignment accuracies across the clips, and there is a significant relationship between delta ISC’s (in The assignment accuracies are indicated for each of the separate clips in ISC’s in  and assiISC’s in  (r(15) =We examined which spatial locations were most informative for prediction by determining the percentage of correct assignments for each electrode. The best predicting electrode was electrode Cz, with 26 out of 91 (28.57%) correct predictions derived from this mid central spatial location. Electrodes Fz, O1, F3, F4, O2, P3, and P4 contributed to 10.99%, 01.10%, 10.99%, 02.20%, 17.58%, 26.37% and 02.20% of the correct predictions.We examined assignment accuracy with the aggregate correlations approach when N = 1, 2, 3, … 16 subjects were used as reference. Assignment accuracy monotonically increased from 11.94% with N = 1, up to 33.46% with N = 16, as indicated in In the present study, our primary goal was to implement and evaluate different assignment algorithms for predicting which audiovisual clips individuals viewed. The aggregate correlations algorithm  outperfoIt is important to note that the assignment accuracy monotonically increased as the number of subjects increased. This finding suggests that further increases in assignment accuracy, from the peak at 33.46%, would likely be observed with further increases in sample size. Additional studies with a larger sample size could potentially characterize the nature of this assignment accuracy increase, revealing the subject sample that may result in a plateau in prediction accuracy. A greater sample size could additionally enhance the ability to examine whether individual differences, such as gender and the individuals prior exposure to the clip, are related to differences in ISC magnitude across clips.There was insufficient evidence to support our hypothesis that individuals with similar clip preferences would have similar EEG responses (i.e. greater ISC’s). There are a few reasons why individual preferences would potentially diverge from EEG responses to the stimuli. In general, ISC magnitudes and assignment accuracies appeared to differ across the clips. These differences may be related to many aspects of the clip content, including the spectral characteristics of the auditory signals, low level characteristics of the audiovisual content and differences in attentional and emotional engagement toward the different clips. A subset of these characteristics may be related to individual’s preferences. Thus, individuals preference ratings may represent an aggregate measure of their subjective and perceptive response to the video, which may be not necessarily be related to the characteristics that lead to cortical engagement toward the stimuli, as expressed by EEG ISC magnitudes. This is consistent with previous studies demonstrating the recruitment of neural responses toward behaviorally relevant ecological events, irrespective of whether or not the content is subjectively pleasing . The divThe majority of ISC studies have been conducted using BOLD fMRI measures ,29,36–50Previous studies demonstrate that fMRI ISC increases correspond to segments of the clip that display content consistent with the functional properties of the region ,48,56–58EEG responses arise primarily from the cortex, and the specific cortical regions of activity are difficult to localize compared to fMRI. Thus, EEG ISC’s are ill suited toward determining the functional properties of different spatial locations. Instead, EEG ISC’s emerge from a tight coupling (i.e. phase locking) of the evoked response across individuals at a given location of the clip . These cEye movements are coherent across subjects when viewing natural scenes  and eye EOG responses were not measured in the present study due to the limited coverage of the mobile EEG system and individual’s eye movements were not constrained to a central fixation point. However, the spatial topography of ISC’s and our choice of video size help alleviate concerns that the results of the present study are influenced primarily by eye movements. For example, the peak ISC was not observed within the electrodes which are predominantly influenced by eye movements . Instead, the peak ISC location (electrode Cz) is consistent with the topographic locations in which cognitive ERP peaks are often observed (e.g. the P300 ). AdditiThe smaller video size may have contributed to the small ISC values (i.e. r < .01) reported in the present study. These low correlations indicate that the evoked response to shared audiovisual inputs explains only a small portion of the EEG signal variance, which is expected given that the variability of single-trial evoked potentials and their low magnitude against background EEG . Previous studies have implemented spectral decomposition and canonical correlations analysis (CCA) and have reported ISC values up to 0.3. As in the present study, these studies demonstrate that ISC’s emerge from activity within the delta band (0–4 Hz), with few significant correlations observed within the higher frequencies ,65. MultThe general approach for EEG analysis with complex stimuli differs considerably from conventional EEG experiments, where responses are measured to repeated presentations of a stimulus and averaged, generating an ERP. EEG responses to complex audiovisual stimuli violate many of the assumptions for traditional ERP analysis. For example, audiovisual content is typically not repeated within an individual session, which precludes multiple measurements for event-related averaging. In addition, the audiovisual content overlap in time, which may result in the superposition of phase-locked EEG oscillations arising from the responses associated with the events and the emotional and cognitive response. In contrast to ERP analysis, the ISC approach shifts emphasis from the specific shape of the EEG response toward the commonalities in the response across subjects. Thus, ERP responses that are non-stationary and non-linear with respect to a stimulus within an individual subject will contribute to large ISC values as long as the characteristics of the non-stationary and non-linear response are preserved across subjects.It is important to note that the ISC approach may be useful for capturing complex stimulus-response characteristics that may result within conventional task-based paradigms, and thus, may complement traditional analyses of task data ,44–46,66Further studies may manipulate the content of audiovisual clips and the subject population to determine whether clinical populations demonstrate similar cortical responses to particular content. For example, clinical populations may demonstrate a greater commonality in their responses among themselves than among other populations. Individuals with autism demonstrate reduced ISC’s within multiple fMRI regions while watching social interactions , and demSilver Linings Playbook) to 11.75% (Seinfeld). ISC’s were significantly greater than zero for 15 out of 16 clips, and fluctuations within the delta frequency band (i.e. 0–4 Hz) primarily contributed to response similarities across subjects. There was insufficient evidence to indicate that individuals with greater similarities in clip preference demonstrate greater similarities in cortical responses, suggesting a lack of association between ISC and clip preference. These results demonstrate the utility of using ISC’s for prediction, and further characterize the relationship between ISC magnitudes and subjective reports.Within the present study, we examined the utility of using ISC’s for predicting which audiovisual clips individuals viewed, and their potential relationship to subjective reports. Three approaches were evaluated for aggregating responses across subjects for assignment within Experiment 1A. The aggregate correlations algorithm generated the highest assignment accuracy (70.83% chance = 33.33%) and was selected as the assignment algorithm for the larger sample of individuals and clips within Experiment 1B. The overall assignment accuracy was 33.46% within Experiment 1B (chance = 06.25%), with accuracies ranging from 52.9% . Individual average ISC’s were computed by averaging the ISC’s computed for the 3 clips and 3 electrodes for each unique session pair. The column “Video + Audio” indicates the distribution of individual ISC’s in Experiment 1A with video and audio. The column “Audio” indicates the distribution of individual ISC’s when the experiment was repeated with only audio . There was insufficient evidence of a different in ISC’s between the two conditions (T(10) = -0.09; p = 0.93). These results suggest that eye movements were not a strong contributor to ISC’s within the present study.(PNG)Click here for additional data file.S2 FigThe spatial distribution of ISC’s were examined by computing the average ICS  separately for each electrode. The 8 electrodes are indicated by their 10–20 label  with the average ISC indicated below each label. The highest ICS’s were observed over the mid central electrode (Cz) and the electrode located over occipital regions (O2).(PNG)Click here for additional data file.


SFRP promoter hypermethylation has often been identified in human cancers; however, the precise role of SFRPs in cutaneous squamous cell carcinoma (SCC) is unclear.The Wnt signaling pathway is abnormally activated in many human cancers. Secreted frizzled-related proteins (SFRPs) function as negative regulators of Wnt signaling and play an important role in carcinogenesis. SFRP family was analyzed in an age-and sex-matched case-control study, including 40 cutaneous SCC cases and 40 normal controls, using the MassARRAY EpiTYPER system.The methylation status of the SFRP1, SFRP2, SFRP4, and SFRP5 promoters was significantly higher in cutaneous SCC tissues than in adjacent tissue and normal skin samples.The methylation rate of Our manuscript mainly discussed the average methylation rate of SFRPs  promoters are significantly high in tumor tissue samples and the average CpG island methylation rate among different pathological levels of cutaneous SCC between these genes are different.SFRPs is associated with the development of carcinoma, and could be a useful tumor marker for cutaneous SCC and other types of cancers.Our findings suggest that promoter hypermethylation of  Non-melanoma skin carcinomas, comprising cutaneous squamous cell carcinoma (SCC) and basal cell carcinoma (BCC), are the most common malignancies in fair-skinned Caucasians . Unlike The Wnt family of proteins includes a wide range of secreted growth factors that regulate cell differentiation, proliferation, migration, and organogenesis during embryonic development . AberranSFRP family with tumorigenesis have only recently begun to be explored. Previous studies have reported SFRP downregulation in colorectal cancer, gastric cancer [SFRP family members, including SFRP1, SFRP2, SFRP4, and SFRP5 in different tissue samples from a Chinese population of the Xinjiang Uygur Autonomous Region.Although the involvement of Wnt signaling in carcinogenesis has been extensively studied, the associations of the c cancer , and invc cancer , 17. Addc cancer . Althougc cancer . In the SFRP family, we conducted an age- and gender- matched case-control study including 40 cutaneous SCC cases and 40 normal controls. The patients were recruited from the Dermatology Department of the People’s Hospital of Xinjiang Uygur Autonomous Region , and had received a diagnosis of histologically confirmed cutaneous SCC between January 2012 and February 2014. Controls were normal individuals from the Plastic Surgery Department of the hospital who reported no history of any type of cancer at the time of study recruitment. The basic characteristics for the participants included in this study are presented in Table n = 40) and adjacent tissues (n = 40) were obtained from the head or the hands/legs of the 40 cutaneous SCC patients. Normal skin samples (n = 40) were collected from the face or the hands/legs of the 40 controls. This study was approved by the ethics committee of the People’s Hospital of Xinjiang Uygur Autonomous Region. Written informed consent was also obtained from each participant enrolled in the study.To investigate the methylation status of the Genomic DNA from tissue samples was extracted using the Tissue DNA Kit (Qiagen) according to the manufacturer’s recommendations. The DNA concentration and quality were measured using the NanoDrop ND-1000 spectrophotometer . Bisulfite modification of genomic DNA was performed using the EZ DNA Methylation Kit (Zymo Research) according to the manufacturer’s protocol. Bisulfite-treated genomic DNA was amplified in a 384-well plate using HotStar Taq Polymerase in a 5-μl reaction volume (Qiagen). PCR conditions were 94 °C for 4 min followed by 45 cycles of 95 °C for 20 s, 56 °C for 20 s, and 72 °C for 60 s, with a final extension of 72 °C for 3 min. Primer sequences are given in Table The PCR products were treated according to the standard protocol (Sequenom EpiTyper Assay) by SAP treatment and T-cleavage reaction. The samples were then cleaned by Resin and were dispensed to a 384 SpectroCHIP by Nanodispenser. DNA methylation levels were determined as previously described  using MaU test or the Kruskal-Wallis H test. All P-values presented in this study were two sided, and we used P < 0.05 as the cutoff value for statistical significance. The receiver operating characteristic (ROC) curve was used to estimate the specificity, sensitivity, and accuracy of the regression test.The SPSS 17.0 statistical software  and Microsoft Excel  were used for statistical analysis. The methylation levels in cutaneous SCC patients and normal samples were compared by nonparametric Mann-Whitney SFRP1, SFRP2, SFRP4, and SFRP5 in 40 cutaneous SCC patients and 40 normal subjects. Table p > 0.05).In the present study, we investigated the methylation status of SFRP1, SFRP2, SFRP4, and SFRP5 in 40 cutaneous SCC tissues, 40 adjacent tissues, and 40 normal samples using the MassARRAY EpiTYPER system. Aberrant promoter methylation of SFRP1, SFRP2, SFRP4, and SFRP5 was detected in cutaneous SCC tissues and adjacent tissues compared with normal samples. Additionally, the frequency of SFRP promoter methylation in tumors was significantly higher than in adjacent tissues and normal samples , suggesting that hypermethylation of these SFRPs, particularly of SFRP1, could be important in the onset of cutaneous SCC.In the present study, we describe the aberrant DNA methylation of four members of the l cancer , and huml cancer . Additiol cancer , 28, 29.SFRP promoters in different pathological levels of cutaneous SCC tissue, and found the methylation rate to increase with the pathological level. ROC curve analysis showed that the SFRP1 CpG site is a potential biomarker of cutaneous SCC, and the further identification of genes that are methylated during cutaneous SCC carcinogenesis together with an improvement in the quantitative rather than the qualitative analysis of methylation will be of great value in the future molecular screening of cutaneous SCC.Aberrant hypermethylation of CpG islands in gene promoters was previously shown to be a primary mechanism in the inactivation of several tumor suppressor genes . We asseSFRP silencing in cutaneous SCC relates to its involvement in the Wnt signaling pathway. This pathway is involved in the tumorigenesis of many human cancers, including those of the colon, breast, lung, and liver, as well as melanomas [SFRPs in cervical SCC [SFRPs occurs in hepatocellular carcinoma, and that restoration of SFRP1 attenuates Wnt signaling, decreases the abnormal accumulation of β-catenin in the nucleus, and suppresses cell growth [SFRP1 and SFRP2 expression in cutaneous SCC, in particular SFRP2, exhibit very high constitutive expression in normal skin. The data provided by the Human Protein Atlas on cutaneous SCC (www.proteinatlas.org) showing that the SFRPs  exhibit very low expression in cancer tissues, except SFRP1, which was slightly high. Our results showed that the SFRPs were highly methylated in cutaneous SCC, which in accordance with the data of the Human Protein Atlas on cutaneous SCC. Nevertheless, much work remains to be done to obtain a clearer understanding of the role of SFRPs in Wnt signaling and tumor pathogenesis.The potential importance of elanomas . Chung eical SCC . Additiol growth , 33. To l growth  demonstrSFRPs  is associated with the development of cutaneous SCC. Although it is not possible to determine whether SFRPs are directly related to carcinogenesis from this study, the aberrant methylation of SFRPs may nevertheless be a useful tumor biomarker for early diagnosis. Despite the current study possessing enough statistical power, some limitations should be considered. First, we limited our investigation to only four SFRPs: SFRP1, SFRP2, SFRP4, and SFRP5. Therefore, we cannot exclude the possibility that other genes may play a role in the pathogenesis of cutaneous SCC. Second, the sample size of our study was relatively small, so our findings should be confirmed in larger case-control studies.In conclusion, our study demonstrates that promoter hypermethylation of


Alternaria alternata and Penicillium oxalicum were applied as a pathogenic and non-pathogenic fungal species, respectively. Protein profile analysis revealed that a five protein species  possessed completely coupled interaction with non-pathogenic inducer application . However, three protein species  recorded a strong positive interaction with both fungal species. Protein 14 exhibited the maximum interaction with fungal applications, and its role in plant metabolism was studied after its identification as protein Q9M1W6. It was determined that protein Q1M1W6 was involved in guaiacyl lignin biosynthesis, and its inhibition increased the coumarin contents in tomato plants. Moreover, it was also observed that the protein Q9M1W6 takes significant part in the biosynthesis of jasmonic acid and Indole acetic acid contents, which are defense and growth factors of tomato plants. The study will help investigators to design fundamental rules of plant proteins affecting cell physiology under the influence of external fungal applications.The pattern of protein induction in tomato plants has been investigated after the applications of pathogenic and non-pathogenic fungal species. Moreover, particular roles of the most active protein against biological applications were also determined using chromatographic techniques.  Plant cell responses under the influence of pathogenic and non-pathogenic fungal species have always been an important aspect in the field of cell biology. These cell responses have also been frequently used in plant protection programs against biotic and abiotic stresses   fungal species. It will help to understand the PR proteins and their roles in cell physiological processes and ultimately plant defenses. Furthermore, it will also help to understand the nature of plant responses against fungal applications.Tomato has always been ranked in the list of widely consumed vegetables around the globe. Its dietary uses are very diverse in nature and ranged from domestic to industrial level. Its nutritional value also makes it prominent food item. All of its features have attracted the attention of researchers to improve its yield and quality. Many researchers have investigated the defense weapons of tomato under stress conditions. These studies were conducted to improve tomato yields and to augment tomato cultivation against the activity of a number of its pathogens  and a fungal inducer . Moreover, two tested fungal species were also procured from the same lab of PU, Lahore, Pakistan. Their cultures were maintained on 2% Malt Extract Agar medium and inocula (3000 spores/mL) were prepared in distilled sterilized water.In current investigation both of these cultivars were procured from Fungal Biotechnology Lab, Institute of Agricultural Sciences (IAGS), University of the Punjab (PU), Lahore, Pakistan; and treated with a fungal pathogen , Inducer Control “IC”  and Pathogen+ Inducer “P+I” . Results of Ahmad et al.  was applied in the soil. Each treatment of both tomato cultivars was replicated thrice to maintain the reliability of the results; however each replicate consisted upon 10 separate plant pots. After incubation period of 2 weeks, plant samples were analyzed for their protein profiles.Seeds of tomato cultivars were grown under greenhouse conditions to minimize adverse environmental fluctuations. Seeds were cultivated in the plastic pots and incubated at 26 ± 2°C. Plants were watered using soil drip irrigation system. At the age of 1 month plants of both cultivars got three treatments, i.e., Pathogen Control “PC”  was used to extract total protein contents of plant samples. Protein samples were dissolved in Urea solution (8 M) prior their electrophoration.Protein analysis was carried out by adopting the method of Ahmad et al. . Sodium Protein samples were elctrophorated on 12% Native Polyacrylamide Gel (Native PAGE). Second dimension of each sample was performed on same gel with the addition of SDS to get fine resolution of protein samples. Then, gel was stained using coomassie blue to record results of visible protein samples. Digital images of protein gels were captured for their detailed analyses.Protein profiles of PC, IC, and P+I of each cultivar were compared with their respective NC protein profiles, and induction index for each protein was calculated with the following formula. A matrix plot showing protein “induction index,” was plotted to evaluate the induction behavior of each protein against the both fungal species.Protein spots were identified and compared using digital software SAMESPOTS  and TOPSPOT . Important features of each species were checked from online database UniProt. Solution-state NMR spectroscopy was carried out in order to closely determine physical properties of experimentally important proteins. Data obtained through NMR was statistically analyzed and compared with online protein database using the software PSVS .The protein showing the highest affinity with tested fungal species was analyzed for its role in cell physiological processes. For this purpose, the synthesis of the protein was blocked using respective small inhibitory RNA. Total metabolites of tomato plants with inhibited synthesis of proteins were extracted and analyzed through gas chromatography mass spectrometery (GCMS) using Clarus SQ8 system of PerkinElmer, USA. Derivatization of samples was carried out by overnight incubating 50 μL plant extract in methoxymine (MOX) reagent (30 μL) at room temperature. Then, 20 μL N-trimethylsilyl N-trifluoroacetamide (MSTFA) was added to each extract sample separately and incubated for 30 min prior to loading of 3 μL sample on GCMS apparatus. Oven temperature was initiated from 70°C and raised up to 200°C with a continuous increment of 5°C/min. Then temperature was raised up to 240°C with continuous increment of 10°C/min. Mass spectrum of each eluted biochemical was recorded during the operation and analyzed by MZmine .P. oxalicum  had been reported from plant cell nucleus and lays its role in blue light pathway. Moreover, it also responds toward detection of chitin. A plant cell mitochondrial protein (Q9M0V0), which plays its role in electron transport chain and biotin synthesis was inversely associated with inducer application. Similarly, a DNA binding protein species 1 (Q9SN83) was also inversely associated with application of the pathogenic fungal species.A total of 14 protein species were identified from tomato plants. Analysis of these proteins on database declared an association of nine protein species  had already been proved with A. alternata in case of resistant cultivar (Table Protein species 10 (Q9FJY1) and 12 (Q9LF87) recorded their higher affinities with application of both fungal species (pathogenic and non-pathogenic). Protein 14 (Q9M1W6) exhibited the highest association with all types of fungal applications. It was always 100 percent associated with inducer application, while 50% with Protein 14 (Q9M1W6) was strictly associated with inducer application in both of the tested cultivars. However, protein species 10 and 12 were completely inducer associated in case of susceptible cultivar, but their association decreased to 50% in case of resistant cultivar. Furthermore, Q9M138 (protein 4) showed completely positive relation with all fungal applications in case of resistant cultivar Dinaar; however, it did not show any response in case of susceptible cultivar. Interestingly, there were only two proteins (2 and 4), which were associated significantly with the pathogen in resistant cultivar, and the same proteins did not respond to pathogenic application in susceptible cultivar.Production of Q9M0V0 (protein 5) was inhibited after inducer applications in susceptible cultivar. However, the same protein did not respond toward any fungal application in resistant cultivar. On the other side, protein 1 interacted negatively with pathogen application in case of resistant cultivar, while the same protein species did not respond to any fungal species in case of susceptible cultivar. It was also noticeable that the interactions of all negatively behaving proteins were partial and no protein showed 100% negative behavior with any fungal application. Furthermore, Q9M1W6 was the only protein which exhibited 100% positive interaction with pathogenic applications on susceptible cultivar Figure .Chromatogram of control plants of cultivar Dinaar exhibited more peak heights elevated than the plants with inhibited protein species. Biochemical eluting at 10.31 min of chromatographic run had increased peak height in control treatment of Dinaar cultivar. The similar trend was also observed in case of Red Tara cultivar, in which control treatment plants showed more peak heights as well as more number of peaks than the respective inhibited protein plants . Retionic acid was increased up to 4.16 and Pentadecanoic acid also showed an increase of 3.76-folds after the inhibition of the protein. Sugar contents, e.g., Fructose, Galactopyranose, Galactose, and L-altropyranose recorded significant increase in their contents . The sugar with minimum increase in its contents (0.31) after the protein inhibition was Rhamnose. Some acid contents of tomato metabolites  also showed an increase after inhibition of the protein. However, contents of Hepatonic acid, Sinapic acid, Jasmonic acid, Ferulic acid, Quinic acid, and Xylonic acid were decreased up to −3.54, −2.05, −1.76, −2.88, −2.64, and −1.58-folds, respectively. Moreover, Indole acetic acid recorded a decrease of −0.47-folds and p-Coumaric acid reduced up to −0.82-folds in the plants with inhibited protein Q9M1W6 (Table Inhibition of protein 14 (Q9M1W6) resulted in the retardation of cinnamic acid contents. The decreased cinnamic acid contents triggered a chain of organic acids with reduced quantities . Those induced organic acids boosted the quantities of downstream biochemicals in their pathways. Coniferyl alcohol was recorded to be enhanced by ferulic acid in the downstream process of coniferin and guaiacyl lignin biosynthesis. Coniferin contents were found to be increased due to enhanced coniferyl alcohol contents. However, a reduction in the quantity of guaiacyl lignin was recorded. Decreased contents of 5-Hydroxyferulic acid resulted into reduced quantities of 5-Hydroxyconiferaldehyde, which also retarded 5-Hydroxy-coniferyl alcohol in tomato plant tissues. However, it didn't induce 5-Hydroxyguiacyl alcohol  and its quantity didn't show any significant change. Decrease in sinapic acid quantities also reduced sinapyl alcohol contents in plant tissues. It was also notable that 5-Hydroxy-coniferyl alcohol was also involved in reduction of sinapyl alcohol contents. Therefore, sinapyl alcohol and its downstream biochemical syringyl lignin showed reduced quantities .A function toward chitin synthesis had already been reported for protein 4 (Q9LJB7), which clearly indicates its role against invading fungal pathogens  had not been previously characterized for its functions. However, this study concludes it as a very important protein with respect to fungal pathogens and plant protection program. However, characterization of this protein, determination of its functions and its categorization in the most suitable group need more scientific investigations to be done.Moreover, results indicate that Penicillium induced the production of protein 2 and protein 4 in resistant cultivar, which can be linked with induced systemic resistance (ISR). However, Penicillium did not elevate the production of these proteins in susceptible cultivar; rather than it inhibited the production of protein 5. It clearly indicates that mechanism of ISR differs with respect to the level of innate resistance of the cultivar. Ahmad et al.  also poiExtensive work by Mendoza-Mendoza et al.  and PozoPlant resistance induced by a non-pathogenic biotic inducer and by a pathogenic entity are mediated by different signaling pathways  after the application of fungal species, and its role in modulation of plant metabolism. It has been clarified from the results that the protein was involved in the regulation of lignin biosynthesis. Its inhibition significantly reduced the quantities of lignin and most of the intermediates of lignin biosynthesis pathway. Moreover, some of the intermediates, e.g., coniferyl alcohol was found to be enhanced; however, it produced the elevated quantities of coniferin and couldn't yield guaiacyl lignin. It is notable that coniferyl alcohol is the intermediate for the biosynthesis of guaiacyl lignin and coniferin. There is a need of more investigations to explore the factors which modulated higher coniferyl alcohol contents to produce increased coniferin only. It is clear from the recorded data that after induction from fungal species, the protein enhances lignin accumulation in plant cell walls, which may enhance plant defenses against the fungal pathogens  also resulted into elevated contents of coumarins and its intermediates. Coumarin contents play an important role in defining palatability of food. Enhanced coumarin contents represent the increased palatability of the food items (Blahová and Svobodová, Altogether, proteins are themselves are the most active defense weapons of the plant cells, and they may also drive the other defense responses of the plants (Zhu et al., NY, SoS, and ShS conceived the idea of this manuscript. AA, YA, SN, and WA designed this study. ZB, AA, and AI performed the experiment. NY, YA, ShS, SN, and SoS record and analyzed the data. ZB, AI, and WA wrote this manuscript. All the authors reviewed the manuscript and recommended its submission.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Investigators from the Accident Vasculaire Cérébral de nouveau-né (AVCnn) Study Group, a multicenter registry in France, examined outcomes at 7 years of age in children previously identified with neonatal arterial ischemic stroke (NAIS). Investigators from the Accident Vasculaire Cérébral de nouveau-né (AVCnn) Study Group, a multicenter registry in France, examined outcomes at 7 years of age in children previously identified with neonatal arterial ischemic stroke (NAIS). 100 patients were enrolled in this cohort, 80 patients completed at least part of the total assessment. Investigators obtained the patient's medical history, assessment of his/her developmental profile, and parental opinions on their child's medical sequelae from NAIS. Outcomes studied were presence of epilepsy, academic performance, presence and severity of cerebral palsy, presence of intellectual disability, presence of impaired spoken language, co-occurrence of deficits and parental opinion of outcomes. Impaired language was the most common problem, affecting 49% of children studied. The prevalence of the other outcomes was as follows: cerebral palsy 32%, low academic skills 28%, active epilepsy 11% and global intellectual impairment 8%. The investigators conclude that 59% of the patients in this cohort had any type of disability and that co-occurrence of disabilities is high. The investigators found a higher prevalence of speech impairment in comparison with other previously reported studies. This cohort presents a cross section of outcomes of school children presenting with NAIS in the neonatal period. [COMMENTARY. Neonatal arterial ischemic stroke (NAIS) is by definition a symptomatic arterial ischemic infarct which presents within the first 28 days of life . It is l


Cordyceps/Isaria) dominated the fungal assemblage after NP addition. In contrast, sequences attributed to the nitrogen-fixing Rhizobiales bacteria appeared vulnerable to Ag NP-mediated toxicity. This combination of physiological, biochemical and molecular studies clearly demonstrate that Ag NPs can severely disrupt the natural seasonal progression of tundra assemblages.The impact of silver nanoparticles (NPs) and microparticles (MPs) on bacterial and fungal assemblages was studied in soils collected from a low arctic site. Two different concentrations (0.066% and 6.6%) of Ag NPs and Ag MPs were tested in microcosms that were exposed to temperatures mimicking a winter to summer transition. Toxicity was monitored by differential respiration, phospholipid fatty acid analysis, polymerase chain reaction-denaturing gradient gel electrophoresis and DNA sequencing. Notwithstanding the effect of Ag MPs, nanosilver had an obvious, additional impact on the microbial community, underscoring the importance of particle size in toxicity. This impact was evidenced by levels of differential respiration in 0.066% Ag NP-treated soil that were only half that of control soils, a decrease in signature bacterial fatty acids, and changes in both richness and evenness in bacterial and fungal DNA sequence assemblages. Prominent after Ag NP-treatment were Hypocreales fungi, which increased to 70%, from only 1% of fungal sequences under control conditions. Genera within this Order known for their antioxidant properties ( Over the last 25 years, both consumers and industrialists have benefited from the technological breakthroughs associated with the manufacture of nanoparticles (NPs). Due to their antimicrobial activities, silver NPs are popular in textiles, food contact surfaces, building materials, vehicle interiors, cosmetics, paints, air conditioners, and medical applications Some argue that the consequences of NP pollution are not necessarily worrisome since NPs aggregate and will then exhibit traditional properties of their bulk, parent materials. However, the propensity for NP agglomeration depends on the environment itself with characteristics of the soil and water determining if the relatively large reactive surfaces of the NPs aggregate or sorb to organic and inorganic materials Previously, we examined the impact of several NPs including Ag NPs on bacterial communities derived from a high arctic site Betula glandulosa), sedges, ericaceous shrubs, Labrador tea, mosses and lichens −1 dissolved organic carbon. Mean concentrations of Ag, Cu, and Mo in the soil were under the detection limit with Ag and Mo both at <2 ppm, and Cu at <5 ppm. Concentrations of other transition metals present in the soil include Mn at 15.9 ppm, Zn at 19.6 ppm, and Fe at 5392.8 ppm. These humic acid- rich soils were transported to the laboratory in insulated boxes with −20°C freezer packs, quickly composited into a single sample after removal of obvious stones and plant material including leaves and roots, while maintaining sterile technique at 4°C. The soil was then stored at −18°C until further experimentation.Soil samples were collected near the Tundra Ecological Research Station at Daring Lake  in Northwest Territories Canada, approximately 300 km from Yellowknife, the closest, permanent population center. The samples were collected under the license issued by Auora Research Institute, Inuvik, NWT, Canada (Licence no. 14514R). The region is located north of the tree line and underlain by permafrost. The mean diel temperature in winter is −35°C, with a shallow active layer melting during the spring with early summer temperatures reaching ∼15°C Ag NPs and Ag MPs were obtained in powder form from MK Nano . The manufacturer's reported sizes of 20 nm (99.9% purity) for NPs and 3 µm (99.9% purity) for MPs were independently determined by assessing the average hydrodynamic Ag NP sizes L and NPH, respectively). After thorough mixing, the soil was divided into three aliquots and sequentially packed into sealed polypropylene containers  prepared by washing with 70% ethanol, followed with a 95% ethanol rinse, and plugged with autoclaved glass wool. In an analogous procedure, containers with Ag MPs, 0.066% and 6.6% (w/w) were prepared and designated as low and high levels of Ag MPs . The concentration chosen, while higher than that which would be found under natural conditions, allowed us to determine the environmental consequences under the incubation times chosen for the study. The concentration was also selected based previous reports of NP levels that would mimic ‘pollution-type’ contamination, as well as more critically test earlier results on Arctic soils −1vs. 0.002 nm−1) to assist in determining if NP toxicity was due solely to the leaching of ionic silver. NPH then served as a further control. Two types of unamended control soils were used for comparison; neither received NP or MP additions, but both were subjected to the same mixing treatment described above. One of the control soils was heat sterilized  prior to loading in the polypropylene containers, and the other did not receive heat treatment . A further ‘respiration negative’ control was prepared by packing 125 g of autoclaved white quartz sand  into a similarly prepared polypropylene container.The uniformly mixed soil samples were divided into 6 aliquots (110 g), maintaining the temperature at 0°C by the use of a sterilized tub over a salt-ice mixture in a 4°C incubator. Two concentrations of Ag NPs, at 0.066% and 6.6% (w/w), were dispersed into two of the soil samples. To ensure thorough mixing, each soil sample was first divided into four separate aliquots and each mixed with 25% of the Ag NPs, prior to a final mixing for 15 min. For convenience these were designated as concentrations of low and high Ag NPs  was assessed using an infared CO2 sensor . The chamber gas was sampled sequentially with a gas switcher  in real time with the data captured by computer. Differential respiration was calculated automatically by the subtraction of the mean CO2 production in a particular microcosm from the autoclaved sand control. In order to use the equipment for other experiments, respiration from the microcosms was not continually monitored over the three months, but assessed on a near-continuous basis during the freeze-thaw cycling period and periodically after transfer to 15°C when the equipment was available, at least every 2–3 weeks throughout the incubation period. When not fitted to the respiration apparatus, the microcosms were placed in separate sealed plastic containers at the appropriate temperature. At the conclusion of the respiration monitoring, multiple replicates were obtained from different regions of the microcosms to ensure that results were representative of the treatment type, as described in the analytical sections.The temperature of the microcosms and control containers was monitored using sensors fitted into ports and sealed into the container tops, with humidity monitored using a downstream in-line sensor . Pumped Triplicate soil samples were retrieved from the sequential positions (≥10 cm apart) in the microcosms using a sterile spatula. Each sample, except for the autoclaved control soil, was then sub-sampled (3 g), and placed in 15 mL plastic centrifuge tubes and shipped on ice packs to the testing facility . There, fatty acid methyl esters were extracted according to standard procedure of Microbial Identification System  as described The triplicate soil samples for each of the treatment group microcosms (see 2.3) were also sub-sampled (400 mg) for DNA extraction. Ethidium monoazide bromide  was added to each of the samples and after vortexing for 5 sec, they were incubated in the dark for 5 min prior to photo activation treatment, achieved by placement of the sample tubes 20 cm away from a 500 W light  for 60 sec. EMA is a cross-linker that reduces the probability of amplifying DNA from dead or moribund microorganisms 5′-ACTCCTACGGGAGGCAGCAG) with a GC clamp et al. 5′-CGATAACGAACGAGACCT) and FR1 (5′-AICCATTCAATCGGTAIT) with a GC clamp 2, 0.2 µM each primer, 1.0 U of Taq polymerase , and 1 µL DNA template. Amplifications were started at 95°C for 10 min and followed by 35 cycles of 1 min at 95°C, 1 min at 50°C, and 1 min at 72°C , followed by final extension of 5 min at 72°C .Polymerase chain reaction denaturing gel electrophoresis (PCR-DGGE) was conducted by first amplifying bacterial 16S rRNA gene sequences from the extracted DNA samples (triplicates) using the primer pairs 338f  according to manufacturer's recommendations. Bacterial amplified DNAs were separated on 6% (w/v) polyacrylamide gels with a denaturing gradient of 40 to 60% (100% denaturant contains 7 M urea and 40% formamide). The fungal PCR products were separated on 8% (w/v) gels with denaturing gradients of 25 to 55%. Equal concentrations of amplified DNA (300 ng) were loaded onto DGGE gels and electrophoresed in 1x Tris-acetate-EDTA buffer at 60°C and 65 V for 20 h . Gels were subsequently stained with 1∶10,000 SYBR Green I  and scanned using a ChemiGenius scanner . PCR-DGGE was performed multiple times on each amplified sample  to ensure the reproducibility of the gel patterns. Scans of the stained gels were analyzed after rolling disc background subtraction using Quantity One image analysis software, version 4.6.7 .5′-TGGAGGGCAAGTCTGGTG) and SSUFungiR (5′-TCGGCATAGTTTATGGTTAAG). The amplified ∼500-bp fragments spanning the V1 to V3 hypervariable regions of the bacterial 16S rRNA genes and the amplified ∼400-bp fragments of the fungal 18S rRNA genes were generated using a one-step PCR with a total of 30 cycles, a mixture of Hot Start and HotStar high fidelity Taq polymerases, and amplicons originating and extending from the 28F for bacterial diversity and 515F for fungal diversity. Tag-encoded FLX amplicon pyrosequencing analyses utilized Roche 454 FLX instrumentation with Titanium reagents performed at the Research and Testing Laboratory  based upon RTL protocols (www.researchandtesting.com). All failed sequence reads, low quality sequence ends and tags and primers were removed post-sequencing and the read collections were depleted of any non-bacterial or non-fungal ribosome sequences and chimeras using B2C2 DNA was quantified using a Nanodrop spectrophotometer  and used for pyrosequencing. After multiple initial PCR amplifications, all subsequent pyrosequencing procedures were performed at the Research and Testing Laboratory . Tag-encoded FLX amplicon pyrosequencing (TEFAP) was performed as described The means  were used for the statistical analysis. Since the assumption that the data would be normally distributed may not always hold true, nonparameteric statistical analyses were performed. Wilcoxon Matched Pair tests were used for the comparison of the mol% fatty acid profiles obtained with the FAME analysis, as well as the community composition observed at the Order level in pyrosequencing analysis between the untreated controls and the silver-treated samples. Analyses were performed using Statistica (Release 8.0) software, with a value of ≤0.05 used to indicate a significant difference between the compared values. Pyrosequencing data were further subjected to clustering analysis using Ward's method, which calculates the total sum of the squared deviations from the mean of the cluster in order to evaluate the impact of the particles on the combined microbial communities in soil 2 was detected during ‘winter’ conditions (−18°C), but during the ‘spring’ period of 24 h cycles of −18°C to 0°C, there was a periodicity to CO2 discharge when soil temperatures approached 0°C : NPL, NPH, and MPH microcosms showed mean differential CO2 levels of 128, 55 and 60 ppm, respectively. The MPL treatment group showed the highest differential respiration at 330 ppm. At the conclusion of the respiration monitoring period there was a scattered appearance of white or beige thread-like and cottony forms resembling fungi in the MPL treatment group, which showed the highest differential respiration. In contrast, there were only a few white threads in the NPL -treated soil. This was not seen in the other microcosms, nor has it been observed in previous experiments where arctic soils were exposed to either temperature perturbations or metal exposure As expected, microcosm parameters varied according to the temperature. For example, the relative humidity of the analyzed gas ranged from means of ∼30% to ∼65% at 0°C and 15°C, respectively. No differential COched 0°C , insert. at 15°C . Three tL, NPH, MPL and MPH microcosms, respectively). Indeed, the relative abundance of many Gram positive indicators . When compared to control soil, NPL and MP treatments resulted in statistically significant reductions in the Gram positive fatty acid peak profiles (p≤0.05). Signatures for Gram negative bacteria appeared to decrease in all the treatment groups, but this was not statistically significant.The FAME profiles obtained from the microcosms showed 73 different fatty acid peaks in untreated and Ag-treated soils. Of these, 37 were relatively well represented (≥0.5 mol %). In order to more easily visualize the many fatty acids in each of the treatments and controls, they were further clustered into Gram positive, Gram negative, fungal and other groups . It musttors see  was reduL and MPL treatment groups since it doubled (12 and 11 mol% from 4.5 mol% in controls). With the knowledge that the statistical comparison of fungi fatty acids profile in different samples must be carried out with caution as there are only three fatty acids assigned to the group, no differences were observed for any treatments when compared to control (p > 0.05).The mol% reduction in many of the bacterial signature fatty acids was inversely correlated with an apparent increase in fungal fatty acid markers in all treatment groups, irrespective of silver particle size and concentration . The incvs. 28 NPL, 30 NPH, 32 MPL, 27 MPH), some of the microcosms showed different banding patterns  showed changes in staining intensity, particularly in the NPL treatment group.When PCR-DGGE was performed after amplification of 18S rRNA sequences a large number of major and minor bands were observed (average of 30 bands in each lane). As with the 16S rRNA gene sequence amplifications, gels were identical for the two independent soil samples analyzed for each microcosm (not shown). The majority of the dominant bands  in the number of bacterial Orders after treatment with low concentrations of silver, with bacteria from NPL and MPL microcosms grouped into 7 and 10 Orders, respectively . There was a reduction in total number of Orders after treating microcosms with high concentrations of silver, with bacteria in NPectively .H and NPH microcosms, including Actinomycetales (10% and 13%), Acidobacteriales (9% and 6%), Rhizobiales (1.2% and 1.7%), Rhodospirillales (32% and 16%), and Sphingobacteriales (6% and 10%). These changes were statistically significant . Together these 5 Orders made up 65% of the assemblage in control, 58% in MPH and 47% in NPH microcosms, again suggesting at best a rather modest impact of highly concentrated silver on community richness . In contrast, more obvious changes were seen at lower silver concentrations. Relative to the untreated control, MPL bacterial assemblages showed increases in Actinomycetales (28%), Acidobacteriales (34%) and Burkholderiales (25%) accounting for 87% of the sequences, along with decreases in Rhizobiales (6%), Rhodospirillales (4%), and Sphingobacteriales (9%). Even more striking changes were seen after NPL treatment. Only three Orders, Acidobacteriales (45%), Nitrosomandales (40%), and Burkholderiales (7.4%), with only the first as relatively abundant in the untreated control , accounted for more than 92% of the assemblage. We investigated these changes at a deeper taxonomic level to better understand the community shifts. More than 200 genera could be identified in untreated controls, with only three genera dominating at ∼10% each . Soils incubated with the lower concentration of silver retained a high abundance of these genera, with the notable exception of Rhizobium . However, the genera that rose to predominance in the MPL and NPL microcosms were Burkholderia (34%) and Janthinobacterium (55%), respectively.In control soil, the most dominant bacterial Orders included Actinomycetales (18%), Acidobacteriales (14%), Rhizobiales (12%), Rhodospirillales (11%), and Sphingobacteriales (10%). These abundant Orders, were also represented in the MPL, MPH, and NPH treatment groups Helotiales decreased but remained a dominant Order, representing 46%, 27% and 24% of the total abundance, respectively. However, after NPL treatment, the number of reads in this Order fell from 75% in control to 7%. Another Order, Hypocreales, a minor contributor in the original fungal assemblage, increased 70-fold after silver NP treatment (1% in control soil vs.73% and 70% in NPL and NPH), showing almost an inverse relationship. Statistically, the NPH-treatment group showed significant changes in the fungal community compared to controls (p≤0.05).Similar analysis after pyrosequencing of the 18S rRNA sequences in duplicate treatment groups was performed to determine the relative abundance of the fungal sequences in the microcosms. When 18S rDNA gene sequences representing ≥0.5% of the total abundance were used for comparison, the number of Orders represented in each of the samples was similar (21 in controls and 17–22 in the treatment groups), but there were some differences in evenness depending on the treatment . ControlChalara, a telomomorph and a litter saprotroph H or NPL-treatment, Chalara sequences dropped to 5% and 3%, respectively (Cordyceps and Isaria (Cordyceps is the teleomorph of Isaria the anamorph) in NPL, and Cordyceps in NPH treated soil , NPL-treatment by Cordyceps (27%) and Isaria (19%) as indicated above, NPH by Cordyceps (60%), MPL soil by Chalara (43%), and MPH treated soil by Mortierella (29%) and Chalara (15%).When analyzed at the genus level, Helotiales itself was dominated by the genus ectively . As noteted soil . Indeed,L treatment group had a branch point closest to the control, with NPL and NPH-treatment groups the most distant, irrespective of microbe type.In order to compare the impact of the two concentrations of NPs and MPs on the bacterial and fungal Orders, Ward's method was used for statistical cluster analysis. A hierarchical tree  clustereL and MPL treatments). Fungal PCR-DGGE analysis supports this interpretation; there were few silver-mediated changes in richness, with the obvious exception of the appearance of a new, prominent band in the NPL microcosm. Pyrosequencing of the amplified fungal DNA was also concordant, confirming that silver addition (except for NPL) did not have a large impact on community richness. For example, the sac fungi, Helotiales, a dominant Order in the control soil, remained so in the NPH, MPH and MPL treatment groups , bacterial populations were not able to follow their normal temporal increase during ‘summer’ conditions, resulting in the apparent decrease in bacterial fatty acid signatures, as well as the marked reduction in bacterial Orders that dominated control soil.We speculate that silver particles and any associated ions inhibited bacterial division H and MPH–treatment groups appeared comparable to control soils. It is likely that many of the microbes, with the exception perhaps of some fungi, could not divide when exposed to such high silver concentrations, with the consequence that the microcosms largely retained their previous ‘summer’ DNA profiles. Since experimental protocols that are designed to assay microbial richness such as pyrosequencing do not normally allow an assessment of absolute numbers, estimation of an overall reduction in the community members may not be easily obtained. For example, the most abundant bacteria in control soil, making up 65% of the sequences, also represented the majority of Orders in NPH and MPH treatment groups at 47% and 58%, respectively. A further example of sac fungal predominance after high silver treatment has been already mentioned. The results of the biochemical analyses of these highly contaminated soils underscores the importance of some physiological monitoring for these types of studies, with respiration assays offering a convenient and real-time assessment of the health of microcosms.Notwithstanding any differential effect on the bacterial and fungal communities, the addition of high concentrations of silver had an obvious impact on soil physiological function. Differential respiration was depressed to only ∼25% of that seen in the control soils , and preL and MPL treatment groups; fatty acid signatures showed a similar ∼35% reduction and pyrosequencing showed an identical 95% reduction for the two soils. The fatty acid signature associated with Actinomycetes, which are filamentous, rhizosphere-associating bacteria, suggested a 66–80% reduction in all treatment groups. Pyrosequencing confirmed a reduction in the sequence reads attributable to this Order in all but the MPL treatments, with decreases ranging from 18% (NPH) to more than 96% (NPL). Previously Suutari and Laakso As suggested, when bacteria were exposed to the lower silver concentration simultaneously with freeze-thaw conditions followed by a ‘summer’ period, they were unable to reach levels seen in control soil. Particularly susceptible were the Gram positive bacteria  from the NPL) to the bacterial assemblage (as opposed to its impact in nanosilver form). For example, pyrosequencing showed that Orders dominating the untreated controls (65%) similarly made up the great proportion (81%) of those after MPL treatment. Clustering analysis supported these observations and showed that NP-exposed microbial communities were different than those in control and MP-containing soil  came to completely dominate (55%) all genera in the NPL treatment group. Species in this genus are notable not only for their antifungal properties but for their heavy metal resistance http://www.uniprot.org/uniprot/A6SYR2). Pseudomonas  includes species that are well known for their resistance to silver by the intracellular accumulation of Ag NPs Of the 25 different bacterial Orders (≥1%) in control soil, less than a third were recovered after NPChalara, an anamorphic genus with saprotrophic and endotrophic species, declined in relative abundance by an order of magnitude from 75% in control soil to 7% after NPL treatment. Representatives of the Hypocreales, however, showed an inverse trend by increasing from 1% in control to >70% of the fungal sequences. One of the Hypocreales, Verticillium sp., increased in abundance from <1% in controls to 14% after NPL-treatment  the nanosilver microcosms suggesting that these fungi have mechanisms that allow them to cope with the toxic effects of these particles. Indeed, these fungi are well known for their antioxidant properties Hitherto only limited studies have examined Ag NP toxicity on fungi, with the exception of yeast cultures reatment , and thireatment . AnotherPseudomonas and Janthinobacterium, as well as the fungal genera Cordyceps, and Isaria that are known for their antioxidant properties, appeared relatively resilient. Until we understand the possible long term impacts of the perturbed microbial community, we urge all nations to exert efforts not to deliberately contaminate the Arctic with such particles.One of our goals was to investigate if concerns over the potential environmental impact of Ag NPs could simply be due to silver itself since this metal in bulk form has antimicrobial properties. Here we show that the size of the particle does matter; low concentrations of Ag NPs were more harmful than MPs, with toxicity unlikely due to ionic silver leaching since the NPs had an impact that was distinct from concentrations of MPs used to control for surface area. Further, we have shown that the addition of silver particles to soil coincident with temperature, fluctuations typical of a winter to summer transition, appears to interfere with the normal, temporal microbial changes in the arctic soil community, and with the potential to decrease soil fertility. Bacteria were generally more susceptible than fungi to these engineered NPs; likely this was due to the inability of the bacterial assemblage to recover quickly from temperature-regulated mitotic constraints in order to out-compete these eukaryotes for resources in the presence of Ag NPs. Alternatively, the arctic fungal assemblage could be more resistant. We have also shown that the plant-associating Rhizobiales was susceptible to NP toxicity but some bacterial species, including Figure S1Bacterial phylogenetic composition within the Daring Lake soil at the genus level. Samples include soil that had been incubated for 86 days without NPs or MPs treatment (CS), soil incubated with 0.066% NPs (NPL), and soil with 0.066% MPs (MPL). Sequence identity was determined after pyrosequencing of the partial 16S rRNA genes, classified into genus, and the means of duplicate, replicate samples of those with >0.5% abundance (for either treatment or control groups) presented in separate categories, with groupings of less abundant genus shown as ‘Others’.(TIF)Click here for additional data file.Figure S2Fungal phylogenetic composition within the Daring Lake soil at the genus level. Samples include soil that had been incubated for 86 days without NPs or MPs (CS), soil incubated with 0.066% NPs (NPL), and soil with 0.066% MPs (MPL). Sequence identity was determined after pyrosequencing of the partial 18S rRNA genes, classified into genus, and the means of duplicate, replicate samples of those with >0.5% abundance (for either treatment or control groups) presented in separate categories, with groupings of less abundant genus shown as ‘Others’.(TIF)Click here for additional data file.