Alzheimer's disease (AD) is a progressive neurodegenerative disease that destroys memory and cognitive function. Inflammasome activation has been suggested to play a critical role in the neuroinflammatory response in AD progression, but the cell‐type expression of inflammasome proteins in the brain has not been fully characterized. In this study, we used samples from the hippocampus formation, the subiculum, and the entorhinal cortex brain from 17 donors with low‐level AD pathology and 17 intermediate AD donors to assess the expression of inflammasome proteins. We performed analysis of hippocampal thickness, β‐amyloid plaques, and hyperphosphorylated tau to ascertain the cellular pathological changes that occur between low and intermediate AD pathology. Next, we determined changes in the cells that express the inflammasome sensor proteins NOD‐like receptor proteins (NLRP) 1 and 3, and caspase‐1. In addition, we stained section with IC100, a humanized monoclonal antibody directed against the inflammasome adaptor protein apoptosis‐associated speck‐like protein containing a caspase recruitment domain (ASC), and a commercially available anti‐ASC antibody. Our results indicate that hippocampal cortical thickness did not significantly change between low and intermediate AD pathology, but there was an increase in pTau and β‐amyloid clusters in intermediate AD cases. NLRP3 was identified mainly in microglial populations, whereas NLRP1 was seen in neuronal cytoplasmic regions. There was a significant increase of ASC in neurons labeled by IC100, whereas microglia in the hippocampus and subiculum were labeled with the commercial anti‐ASC antibody. Caspase‐1 was present in the parenchyma in the CA regions where amyloid and pTau were identified. Together, our results indicate increased inflammasome protein expression in the early pathological stages of AD, that IC100 identifies neurons in early stages of AD and that ASC expression correlates with Aβ and pTau in postmortem AD brains. The Emerging evidence supports the idea that there is a link between the misfolded protein aggregates and the activation of the inflammasome of the innate immune system . The infRecent studies have implicated an important role for the NLRP3 inflammasome and ASC specks in the spread of the inflammatory response and the aggregation of misfolded proteins characteristics of neurodegenerative diseases . ImportaPrevious studies using anti‐ASC antibodies have shown that this therapeutic approach reduces pathology in several indications, including spinal cord injury , traumat22.1Informed consent was acquired for postmortem examination research according to the University of Miami, Institutional Regulatory Board (IRB) guidelines.2.2Seventeen postmortem brains from donors with intermediate AD  average age 83.41 ± 7.05 years; 10 females and 7 males) were used in this study, and 17 age‐matched non‐demented controls with age‐related neuropathological changes ; average age 84.59 ± 10.26 years; 10 females and 7 males). The neuropathological staging was based on a complete histological assessment including samples taken from 20 different brain regions and a panel of 15 immunohistochemical stains  immunostaining completed in 7 brain regions and anti‐mouse monoclonal beta‐amyloid immunostaining completed in 8 brain regions) and 7 brain regions stained with Bielschowsky Silver Technique. The diagnosis of cognitive status was provided by a clinician as noted in the patient charts  or ascertained via the Modified Telephone Interview for Cognitive Status (TICS‐M) before death for , 25 and In brief, whole brains were procured on a postmortem interval (PMI) of an average of 17.23 ± 8.72 h after the time of death. The left hemisphere was frozen, and the right hemisphere was fixed in 10% formalin (pH 7.0) for 1 month, and then it was sliced, sampled and embedded in paraffin blocks that were processed on a Leica Tissue‐Tek Processor (Leica Biosystems). Paraffin‐embedded tissue sections were then taken from the hippocampus formation, which included the entorhinal cortex, the Cornu Ammonis (CA) regions CA1–CA3, the subiculum, and the dentate gyrus (DG) and were used for immunohistochemical and histochemical staining as described below. Paraffin‐embedded tissue‐blocks were sectioned at a 20‐μm thickness with 20 retrieved serial sections using a Leica RM2245 microtome (Leica Microsystems Ltd.). Three sections based on a systematic sampling principle and a section‐sampling fraction of 1/5  were sel2.32O2) for 10 min. Sections were immersed in preheated 10 mM citric acid (VWR), pH 6.0, for 30 min and cooled in cold water or pretreated with formic acid (Sigma‐Aldrich) for 5 min. Sections were then blocked in 5% goat serum (Vector Laboratories) for 20 min before being incubated overnight at 4°C in a solution of mouse anti‐Phospho‐Tau  Antibody , mouse anti‐β‐Amyloid , rabbit anti‐NLRP3 , mouse anti‐NLRP1 , mouse anti‐ASC  human anti‐ASC  and/ Figure .2.4To identify the cellular location of the NLRP proteins, immunofluorescence (IF) triple‐labeling was performed on the intermediate AD and on the low AD samples. Primary antibodies rabbit anti‐NLRP3 (3.0 μg/ml) and mouse anti‐NLRP1 (1.0 μg/ml) were mixed in separate cocktail solutions with compatible antibodies, as follows: chicken polyclonal anti‐ionized calcium‐binding adaptor molecule 1  or rabbit polyclonal Iba‐1  as a marker for microglia and macrophages and guinea pig neuronal nuclear antigen  and a marker for neurons. Sections were pretreated as described above and blocked in 5% goat serum for 20 min before the primary antibodies were applied and incubated overnight at 4°C. Following primary antibody incubation, sections were rinsed three times in PBS, for 3 min before the secondary antibodies were added. The samples were finally soaked for 1.5 h in PBS containing secondary antibody cocktail: goat anti‐mouse IgG conjugated to Alexa Fluor 488  or goat anti‐rabbit IgG conjugated to Alexa Fluor 488 . Included in the cocktails were goat anti‐chicken IgG conjugated to Alexa Fluor 546  or goat anti‐rabbit IgG conjugated to Alexa Fluor 546  and goat anti‐guinea pig conjugated to Alexa Fluor 647 . Finally, the sections cover slipped using ProLong Gold antifade reagent (Invitrogen) and kept in the dark at 4°C until analysis.2.5Hematoxylin and eosin (H&E) staining was used to evaluate the general morphology of the brain tissue and orientation of the brain regions as described previously . For H&EMultichannel confocal triple‐labeled microphotographs were captured using a Leica SP8 spectral confocal microscope with settings appropriate for the fluorophore. Images were captured with a Leica microscope DM6000 B using a 40× objective (Leica Microsystems Ltd.) and processed in Adobe Photoshop .2.6oriens to the edge of the stratum lacunosum) using perpendicular lines with a 10‐μm step to give an average of 100 measures, in an average area of 3 mm2 per slide.Images of H&E‐stained sections were obtained using the standard virtual tissue scan  at a 40× magnification as described in . Unbiase2.72 of tissue were obtained using the extended Depth of Field (EDF) virtual tissue scan, which allowed for a series of Z‐stack images to be transformed into a single image . Three contours from each region of interest (ROI) were taken from the CA1, CA2, CA3, the subiculum, and the adjacent DG, which encompassed an average area of 3.2 mm2 per region using the Image‐Pro Premier (Media Cybernetics) program. ROIs were determined by the cellular architecture as described in  connected positive processes or Aβ clusters [>20 μm2]). In a pilot study, we confirmed that the counting profile described previously counted the correct number of labeled cells and nuclei (using an ImageJ cell counter).Cellular densities of positive‐stained cells and Aβ clusters in all contours were quantified by investigators who were blinded to case data. Tissue scans were reviewed (by RV) to ensure that counts had met the criteria to avoid duplication of counts .In this study, we used a Student's t test to compare the variables between two groups (AD and control) in all experiments. Data were presented as mean ± standard deviation (SD); significance was assumed at 33.1Experiments in this study were designed to determine the density and distribution of Aβ and pTau, and the expression of inflammatory proteins, NLRP1, NLRP3, ASC, and caspase‐1 in postmortem human brains with and without intermediate AD neuropathological changes. Neuropathological scores and demographics are shown in Table The Braak score in the low AD group ranged from 0 to II; none to low AD neuropathological change. The neuropathological score for the distribution of neurofibrillary tangles ranged from B0 to B1 with a mode of B1 . The Aβ diffuse plaque distribution score, Thal phase, and A score, ranged from A0 to A2, with a mode of A1 and the neuritic plaque density or CERAD score, ranged from C0 to C1 with a mode of C0. Causes of death were caused by the complications of cardiovascular disease (14 donors), renal failure (1 donor), cancer (1 donor), and liver failure (1 donor).p > 0.05). Additionally, the two groups were not significantly different with respect to PMI time (p > 0.05).Donors with intermediate AD had Braak Scores that ranged from III to VI; intermediate neuropathological change. The neuropathological score for the distribution of neurofibrillary tangles ranged from B2 to B3 with a mode of B2 . The Aβ diffuse plaque distribution score, Thal phase, and A score, ranged from A1 to A3, with a mode of A2 and the neuritic plaque density or CERAD score, ranged from C1 to C3 with a mode of C2. The intermediate AD group had similar complications as the low AD group such as cardiovascular disease (10 donors), renal failure (4 donors), cancer (1 donor), and liver failure (1 donor). Ages of the low AD donors were not significantly higher than that of donors with intermediate AD , CA2 , CA3  regions, and subiculum , indicating that changes in cellular populations are not related to changes in hippocampal volume.Any changes in cellular density in a CA region could result from shrinkage in the strata caused by the neuropil changes , 36. Mor3.3p > 0.05; Figure p = 0.02; Intermediate AD 54.08 ± 25.62, n = 17; low AD 22.94 ± 20.75, n = 17) and in the entorhinal cortex . Outside of the ROIs, we investigated the neuropathological scores of diffuse Aβ plaques  identified in the case assessments. The intermediate AD cases had an average Thal score of “A2” and an average CERAD  score of “C2,” whereas in the low AD group, the average Thal score was “A1” and the average CERAD was “C0.” The increase of Aβ plaques in the subiculum and the entorhinal cortex demonstrates that there are numerous regions that are prone to have a significant change in protein accumulation as the neural degeneration progresses.Pathologic change that incorporates histopathologic assessments of Aβ deposits and the staging of neurofibrillary tangles . It is i3.4p = 0.0006; Intermediate AD 64 ± 48, n = 17; low AD 6.2 ± 14, n = 17) and entorhinal cortex . In the hippocampus, there was a significant increase in pTau in the intermediate AD group in the DG , the CA2  and the CA1 region , but not in the CA3  and the subiculum . The DG , the CA3 , the CA2 , and the CA1 , the CA3 , the CA2 , the CA1 , and the subiculum . Interestingly, there were no significant differences in the number of neurons that were detected with IC100 in the EC, the region that commonly present in the early stages of AD pathology , primarily labeled microglia. To our knowledge, this is the first demonstration of ASC expression in distinct cell populations during the early stages of AD and highlights the importance of the inflammasome in the early stage of AD pathology.Recent evidence has accumulated that inflammasome‐induced cytokines and inflammasome signaling proteins released from activated microglia interact with AD‐associated proteins and exacerbate AD pathological progression and cellular damage. The expression of NLRP3 in microglia of low and intermediate AD cases has been previously reported  NLRP3 maThe ages of the cohort examined in this study were similar in the intermediate AD and low AD groups, but cognitive impairment was higher in the intermediate AD group. We cannot exclude the possibility that AD would have progressed in some low AD cases if donors had lived longer. Nevertheless, our data suggest that changes in the inflammasome protein expression in neurons and microglia accompany the neurodegeneration of AD in the central nervous system of aging individuals.The hippocampal formation cortical band did not differ in thickness between low AD and intermediate AD, indicating that neuronal death and atrophy were not evident in these cases. Two other studies examined hippocampal thickness and neuronal numbers in AD cases staged at different Braak stages V–VI , 42 and 1–42, in the extracellular space, which boosts Aβ1–42 toxicity in microglia [Protein aggregation has been connected to more than 30 proteinopathies, including many neurodegenerative diseases such as AD in which both Aβ and tau aggregates are present , 57. Recicroglia , 59, sugicroglia . In suppicroglia . Our resThe inflammasome adaptor ASC has different isoforms in addition to the canonical ASC. These other isoforms are referred to as ASCb, ASCc, and ASCd, and they differ in amino acid composition . ASC andPrevious studies have reported inflammasome signaling proteins in neurons and microglia in brain of donors with AD , 48, 64,In this study, we expand that knowledge by comparing the cell‐specific staining characteristics of two ASC antibodies, one against the CARD of ASC and the other, IC100, against the PYD, and a panel of commercially available antibodies to identify Ab, pTau, and the inflammasome proteins NLRP1, NLRP3 and caspase‐1. Compared to a commercially available mouse ASC antibody, IC100 identified neurons in the early stages of neurodegeneration in intermediate stages of AD. IC100 expression patterns were consistent with Aβ and pTau staining in postmortem AD brains, emphasizing a spatial and temporal relationship of this sensor molecule in the pathogenesis of AD neuropathology. The reported differential patterns of IC100 neuronal immunostaining in human AD specimens without evidence for cell loss may emphasize the importance of targeting this unique ASC configurational state for future molecular imaging and therapeutic approaches to reduce neuronal vulnerability and the subsequent release of ASC specks leading to continued disease progression.Several surrogate markers are under development to assess initial signs of disease emergence, including molecular neuroimaging, blood or CSF biomarkers, and sensitive indicators of cognitive disturbances , 69, 70.5In conclusion, our findings in the brain of donors with low and intermediate AD pathology indicate that the NLRP1 inflammasome is mainly present in neurons, whereas the NLRP3 inflammasome is mainly present in microglia. Moreover, ASC is present in neurons and microglia. However, the antibody against the CARD of ASC mainly detected ASC in microglia; whereas IC100, which recognizes the PYD of ASC mainly detected neurons. Thus, our data suggest that IC100 identifies neurons in the early stages of neurodegeneration in intermediate stages of AD and that ASC expression is consistent with the levels of Aβ and pTau in postmortem AD brains.JPdRV, HMB, RWK, and WDD are co‐founders and managing members of InflamaCORE, LLC and have licensed patents on inflammasome proteins as biomarkers of injury and disease as well as on targeting inflammasome proteins for therapeutic purposes. JPdRV, HMB, RWK, and WDD are Scientific Advisory Board Members of ZyVersa Therapeutics. NHJ and RTV declare no conflicts of interest.Research study ethics was obtained from the Human Subjects Research Office, University of Miami, Miami, Florida ; Brain Endowment Bank).FIGURE S1. Protein expression in tonsil and skin tissueClick here for additional data file.FIGURE S2. Alzheimer pathology seen in hematoxylin and eosin staining in two donors with intermediate Alzheimer's disease neuropathological changesClick here for additional data file.


Selection detection analyses showed that diversifying selection influenced MHC class II β diversity, whilst diversity within MHC class II α is the result of strong purifying selection. Comparison of translated sequences between species revealed the presence of twelve trans-species polymorphisms, some of which appear to be specific to the genera Crocodylus and Caiman. Phylogenetic reconstruction clustered MHC class II α sequences into two major clades representing the families Crocodilidae and Alligatoridae. However, no further subdivision within these clades was evident and, based on the observation that most MHC class II α sequences shared the same trans-species polymorphisms, it is possible that they correspond to the same gene lineage across species. In contrast, phylogenetic analyses of MHC class II β sequences showed a mixture of subclades containing sequences from Crocodilidae and/or Alligatoridae, illustrating orthologous relationships among those genes. Interestingly, two of the subclades containing sequences from both Crocodilidae and Alligatoridae shared specific trans-species polymorphisms, suggesting that they may belong to ancient lineages pre-dating the divergence of these two families from the common ancestor 85–90 million years ago. The results presented herein provide an immunogenetic resource that may be used to further assess MHC diversity and functionality in Crocodylia.Major Histocompatibility Complex (MHC) class II genes encode for molecules that aid in the presentation of antigens to helper T cells. MHC characterisation within and between major vertebrate taxa has shed light on the evolutionary mechanisms shaping the diversity within this genomic region, though little characterisation has been performed within the Order Crocodylia. Here we investigate the extent and effect of selective pressures and trans-species polymorphism on MHC class II  MHC characterisation and comparison across major vertebrate taxa have provided valuable insights into vertebrate evolution since the MHC evolved from primitive species, such as sharks, approximately 472–584 million years ago (MYA) α and β chains, each of which is organised into two extracellular domains (α1/α2 and β1/β2 respectively), one transmembrane and one cytoplasmic tail domain α and II β genes are organised into four to six exons: exon 1 encoding the leader sequence, exons 2 and 3 encoding the two extracellular domains, and exon 4 encoding the transmembrane domain with some variable exons (exons 5 and 6) encoding for the cytoplasmic tail and the 3′-untranslated region  is expected to be more than one. Some of the polymorphism persists longer than expected among species under neutrality because i) new species generally inherit an appreciable endowment of MHC variants from their ancestors, ii) some particular sequence polymorphisms at nucleotide or amino acid level can persist after speciation and sequence divergence, and iii) new MHC variants are slow to accumulate ω close to zero, it is considered a signature of strong purifying selection MHC class II genes are polymorphic and polygenic, thus generating diversity for loading and presentation of antigens from a wide range of microorganisms β exon 3 (DAB1-DAB5 genes) in Galapagos marine iguanas Alligator sinensis) and Nile crocodile (Crocodylus niloticus), both of which showed some diversity of MHC genes at the population level α and β genes across 20 species of Crocodylia. Overall, we identified ancient trans-species polymorphisms within and between families of the Order Crocodylia, and detected a greater role of diversifying selection in the MHC class II β relative to the MHC class II α.In non-avian reptiles , studies on MHC class II genes are limited to a few taxa. One study of MHC class II α exons 2 and 3, respectively, were identified among species of the Order Crocodylia  were identified among all the amino acid sequences: two in each of the MHC class II α exons and eight in the MHC class II β exon 3  from C. rhombifer, C. moreletii and C. yacare. In addition, stop codons at aa site 31 or 48 were observed among three MHC class II α exon 3 sequences  from C. intermedius, O. tetraspis and C. crocodylus  and a single species of Alligatoridae (Meni-DB02) were identified, based on the presence of stop codons. However, other sequences from these five species displayed functional putative reading fragments with most containing conserved peptide interacting sites and cysteine bridges (C-C).In total, 11 non-functional sequences were found among the MHC class II exons studied  and S2. ocodylus . Despiteβ gene sequences among species of Crocodylia showed evidence of diversifying selection on their exon 2 with high dN/dS ratios . The sites under diversification, as identified in our study, resemble those PBR sites in humans that are polymorphic, yielding a wide variety of motif specificities for antigen binding so as to handle the immune response to any pathogen, regardless of how peculiar the pathogenic protein might be Bayesian analyses of MHC class II S ratios . Figure α sequences did not detect sites under diversifying selection in the antigen presentation region of exon 2 , which is of interest for comparisons of MHC genes between species. The data analysed herein highlight a predominant role of purifying selection acting on amino acid sites of MHC class II α, especially peptide-binding sites, consistent with the high number of synonymous substitutions and highly conserved amino acid sites involved in forming the MHC-peptide complex described in In contrast, the Bayesian analysis of MHC class II f exon 2 . Althougα exons 2 and 3 sequences clustered into two major clades corresponding to the families Crocodilidae and Alligatoridae  = 0.9 at exon 2; 0.6 at exon 3). Furthermore, phylogenetic analyses of these MHC class II α sequences, as well as those from other vertebrates, showed the Crocodylia exons clustered as a sister clade of bird DRA (Anpl-DRA).Bayesian analyses of MHC class II atoridae . Maximumodilidae -A. The eα variants in both clades. In particular, TSP1 contained an intact open reading fragment and was observed among the sequences of eight and five species of Crocodilidae and Alligatoridae, respectively , using tuatara sequences as outgroups  clustered into Clade 2; although one from M. niger is expected to be pseudogenic (containing a stop codon). The resultant topology within each clade and subclade was comprised of different species of Crocodylia, consistent with the notion that an orthologous relationship exists for a gene among related species, as described by Burri et al. Bayesian and maximum-likelihood analyses of MHC class II utgroups  and S6. utgroups . The Baymplified  and S2 amplified . For exaβ genes among major lineages within Mammalia. For instance, DRB1 sequences from different mammalian lineages clustered together, as did DOB and DQB1 sequences  and between the families (Alligatoridae and Crocodilidae) indicates that MHC class II β polymorphism may have been present before these two families diverged from the common ancestor 85–90 million years ago β genes will also permit confirmation of an ancient lineage of TSP exons as discussed above (plus differentiation between TSP and convergent evolution), particularly if the phylogenetic clustering of intron sequence data is consistent with that of exon sequence data in this study The current study has demonstrated that diversifying selection is driving and maintaining diversity of MHC class II β evolution, purifying selection appears to play a predominant role in the conservation of MHC class II α genes and their PBR. Low interspecific MHC variability, and TSPs of the MHC class II α exons, suggest that the Order Crocodylia has experienced purifying selection, whereby the slow-evolving MHC genes have been maintained by removing nonsynonymous nucleotide substitutions that are deleterious to immune protein function, consistent with that seen in birds α locus and at least two MHC class II β loci per species in the preliminary diversity analyses suggests that the α chain of the MHC molecule (II α) has maintained some conservation of protein structure necessary for interactions with different polymorphic β chains (II β). Primate species also show strong selection of MHC class II α genes (DRA), against any corrupt rearrangements or nonsilent mutants, in order to maintain their functional abilities to bind with all MHC class II DRB molecules available In contrast to mechanisms seen in MHC class II β genes appear to be more suitable markers for future diversity and disease-resistance association studies. They have more polymorphic sites than the MHC class II α (ω>1), where nonsynonymous substitutions occur at the amino acid level. As the MHC class II β gene encodes for an extracellular domain (β chain) of the MHC molecule directly involved in antigen presentation, these selected sites might have been mediated by pathogen challenges  and Alligatoridae  that diverged approximately 22 and 65 MYA, respectively α exons studied herein encode for an extracellular domain of the MHC molecule (directly involved in the presentation of antigens). A possible explanation for the sequence conservation is that these MHC class II α exons may have been influenced by a preferential retention of similar variants among species within families, as an advantageous way to preserve a specific biological function HE = 0.040–0.941) between populations of C. porosusA. mississippiensisC. latirostrisC. porosus using MHC class I markers MHC class II β exon 3 and their orthology of sequences from both Crocodilidae and Alligatoridae may suggest a greater number of gene lineages in this exon, relative to the MHC class II α exons described above. This is consistent with the varying numbers of loci that have been observed for both MHC class II α and β genes in other vertebrates α discussed above. This is because the gene copy number and divergence of MHC class II β is a key factor for the MHC protein assembly of wide motif specificities to antigen binding and subsequent immune responses to pathogens β genes have different evolution when their orthologous relationships have been masked, especially in some bird lineages, due to recent gene duplication events and frequent genetic exchange between genes within a species (recombination or gene conversion) Furthermore, numerous phylogenetic subdivisions of MHC class II α genes, those for MHC class I seem to have been subject to independent events of duplication which have led to further gene-lineage diversity in Crocodilidae than in Alligatoridae. This is not surprising given that MHC class I molecules appear to be more diverse in structure and immune function than class II counterparts Comparisons of the present results with a recent MHC class I study in the same taxa α appears to be well conserved among species of the Order Crocodylia, while MHC class II β appears to have undergone a process of diversification. In this respect, diversification selection appears to have played a larger role in the evolution of MHC class II β relative to that of MHC class II α. These findings suggest marked degrees of differential evolution between the two MHC class II chains. In addition, the MHC class II β appears to be the most informative immunogenetic resource for future studies assessing population diversity for species of Crocodylia and for association studies between MHC and disease. Those studies will help refine estimates of variation in gene copy number and content among species and their implication in disease outbreaks in farmed and wild populations of Crocodylia.From an evolutionary perspective, MHC class II Caiman (3 spp.), Melanosuchus (1 spp.), Paleosuchus (1 spp.), Alligator (2 spp.), Crocodylus (11 spp.), Mecistops (1 spp.), Osteolaemus (1 spp.)  . Most ofα exons 2 and 3 (which encode α1 and α2 domains respectively), while published primers β exon 3 (which encodes the β2 domain). The former two sets were designed using the regions conserved between the spectacled caiman MHC class II α exons 2 and 3 (AF256650), MHC class II α sequences from human  and mallard  sequences available in GenBank. Similarly, MHC class II β exon 3 primers targeted conserved regions among caiman, chicken and frog sequences. The purpose of these primers was to amplify as many MHC class II gene loci as possible across all species of Crocodylia. MHC class II specificities of those primers were verified using BLASTN search in GenBank. The search performed against the genome drafts of Alligator mississippiensis, Crocodylus porosus and Gangeticus gavialis , and 20–350 ng of genomic DNA. PCR cycling was as follows: 5 mins at 94°C, followed by 35 cycles of 94°C for 30 s, 61°C (for MHC class IIB primers) or 67°C (for MHC class II α primers) for 30 s, and 72°C for 40 s, with a final extension of 72°C for 10 mins. To enhance the efficiency of cloning, pre-cloning poly-A addition was performed as a final step by adding 0.25 U Taq polymerase to each PCR reaction and incubating at 72°C for 10 min. PCR products were gel purified using a UltraClean® GelSpin® Kit , and were subsequently cloned using a TOPO TA Cloning® Kit . Clones with positive inserts were confirmed for the expected insert size by i) PCR with the same conditions and primers and ii) cutting the inserts from the clones using the restriction enzyme EcoRI ; and then visualisation in 1.7% agarose gels. Positive clones from the PCR or restriction enzyme digestion were randomly selected and four to six clone inserts per individual were sequenced using both plasmid M13 forward and reverse primers at the Australian Genome Research Facility (AGRF). We estimated to what extent the number of positive clones per individual sequenced here provided information on the variation of these genes at the individual level, using the simulated statistical model based on the probability f for diploid genomes in the program NegativeMultinomial . This analysis showed that the number of positive clones used here accounted for up to 31.25% of total MHC variation in each individual. We considered this variation sufficient to retrieve representative variants for each species and preliminarily reconstruct the evolutionary history of these genes in Crocodylia, contrasting with MHC diversity studies where more clones with positive inserts are recommended to be analysed The three gene fragments were amplified using the same Polymerase Chain Reaction (PCR) reaction conditions in 50-µl reaction containing: 10 mM Tris–HCl, 50 mM KCl pH 8.3, 1.5 mM MgClβ exon 3 except for C. mindorensis, C. palustris and C. novaeguineae for which a single individual was used due to the sample availability. A single individual per species was used for MHC class II α exons 2 and 3 analysis because preliminary screening showed them to be highly conserved amongst the families Crocodilidae and Alligatoridae (97–100%). Also, samples from two and nine species (out of 20) characterised for the MHC class II α exons 2 and 3, respectively, generated non-MHC or waste sequences although a number of positive clones were sequenced. These species were marked as ‘NA’ in Two individuals per species were used for the amplification of MHC class II α) or DB (an abbreviation for MHC class II β) and then the identification number  a MHC class II α exon 2 dataset consisting of sequences from 18 species of Crocodylia; ii) a MHC class II α exon 3 dataset consisting of sequences from 11 species; and iii) a MHC class II β exon 3 dataset consisting of sequences from 20 species. This difference in numbers of species among datasets was the result of difficulties in retrieving those genes, as explained above. Forward and reverse nucleotide sequences were overlapped using the BioEdit Sequence Alignment Editor  to generate a consensus sequence. To assess whether the retrieved sequences show identity to target loci among closely and distantly related vertebrate taxa, basic local alignment searches were performed in BLAST (http://www.ncbi.nlm.nih.gov/). Once confirmed, nucleotide sequences were translated into amino acids based on a standard genetic code in the MEGA 5.0 program α (AF256650) and β . Alignments of nucleotide and deduced amino acid (aa) sequences were generated using MUSCLE 3.6 Three nucleotide sequence datasets were generated in the current study: Trans-species polymorphisms (TSPs) in each MHC class II dataset were identified when identical amino acid sequences were found among two or more different species ω value) performing Bayesian Inference was calculated on the following two alignment datasets: the MHC class II α alignment and MHC class II β alignment . In addition, the MHC class II β dataset from 20 species of Crocodylia was tested for selection using an input alignment that contained 18 GenBank exon 2 sequences , three GenBank sequences of exons 2 and 3 , and 72 exon 3 sequences generated in the current study.In order to assess whether diversifying selection was present in each translated amino acid site of MHC genes studied herein, an estimate of a dN/dS ratio  and the recombination rate (ρ = 4eNc), both of which are allowed to vary along the sequence alignment or amino acid positions. Two independent runs of omegaMap were conducted as follows: 5×105 Markov chain Monte Carlo (MCMC) iterations, 5×104 0000 burn-in iterations, 102 thinning iterations, codon frequency 1/61, the number of orderings equal to ten, and the ω model set to be independent. Results from both omegaMap runs that matched within an acceptable degree of error were subsequently interpreted, and graphics were created using R version 2.11.1 (http://www.r-project.org).An analysis of Bayesian Inference was used to estimate ρ) and mean number of nucleotide substitutions in each alignment dataset (θ) were estimated and subsequently compared using omegaMap. An additional test of recombination was performed on three sequence datasets of MHC class II α exon 2, MHC class II α exon 3, and MHC class II β exon 3 using RDP3 Beta 34, as the test is able to identify possible recombinant sequences from different species of Crocodylia p = 0.05, and disentangle overlapping signals plus the Bonferroni correction for multiple comparisons were used. This approach allows recombinant sequences to be identified by comparing results from different recombination detection algorithms implemented in the program, using the following criteria: the recombinant sequence is detected by at least two algorithms; has a high consensus score of more than 60; and has a recombining portion from different parental sequences.In addition to possible technical reasons that could result in recombinant MHC sequences (artefacts) as described above, there are mechanisms of evolution that could result in natural events of recombination α and β sequences among species of Crocodylia and identify TSPs with very similar nucleotide sequences from two different species, phylogenetic analyses were performed using maximum likelihood in PHYML 4 nonparametric bootstraps and 5×108 MCMC steps (sampling every 104 steps and 5×104 burn-in steps) respectively.In order to assess orthologous relationships of MHC class II i) a MHC class II α exon 2 dataset consisting of 19, 2 and 12 sequences from Crocodylia, Aves and Mammalia respectively as well as 4 sequences from Chondrichthyes, which was used as an outgroup; ii) a MHC class II α exon 3 dataset consisting of 12 sequences from Crocodylia, and the same sequences from Aves, Mammalia, and Chondrichthyes as the dataset described above; and iii) a MHC class II β exon 3 dataset consisting of 75 sequences from Crocodylia, 6 from other Reptilia, 11 from Aves, 10 from Mammalia, and a single sequence from Amphibia, which was used as an outgroup. The best-fitting model was selected for phylogenetic reconstruction as described above. The HKY model with a gamma distribution parameter  of 1.23 was used for the MHC class II α exon 2 dataset; HKY model with gamma distribution  for the MHC class II α exon 3 dataset; and the TRN model with gamma distribution  for the MHC class II β exon 3 dataset.Phylogenetic analyses described above were performed separately on the following three nucleotide sequence datasets as described in Figure S1Amino acid alignments of MHC class II α sequences within Crocodylia. Variable positions are relative to the sequence at the top. The first column contains the names of MHC sequences from two families of Crocodylia: Crocodilidae  and Alligatoridae . The second column presents the amino acid alignment in letters. Dots represent amino acid identity to the top sequence; X letters represent unknown amino acids due to single-base deletions; asterisks represent stop codons; and numbers above the alignments represent the order of amino acid positions. Sites in boxes with closed triangles indicate conserved residues of antigen N and C termini on the peptide-binding region of the MHC class II α exon 2 alignment, as described in Kaufman et al. (1994); and sites in boxes linked with a line indicate the cysteine bridge (C-C) observed in the MHC class II α exon 3 alignment. Background colours in the alignments indicate degrees of amino acid identity: 100% in blue; 80–100% in yellow; and below 80% in white. The end of the alignments shows GenBank accession numbers. Trans-species polymorphisms (TSPs) are represented by numbers immediately after each MHC sequence. The same TSP is assigned with the same sequential number.(PDF)Click here for additional data file.Figure S2Amino acid alignment of MHC class II β sequences across 20 species of Crocodylia. Variable positions are relative to the sequence at the top. The first column contains the names of MHC sequences from two families of Crocodylia: Crocodilidae (pate green colour) and Alligatoridae . The second column presents the amino acid alignment in letters. Dots represent amino acid identity to the top sequence; X letters represent unknown amino acids due to single-base deletions; asterisks represent stop codons; and numbers above the alignments represent the order of amino acid positions. Sites 24 and 80 in boxes linked with a line indicate the cysteine bridge (C-C); and sites 42–66 in the red box indicate a CD4+ binding region. Background colours in the alignments indicate degrees of amino acid identity: 100% in blue; 80–100% in yellow; and below 80% in white. The end of the alignment shows GenBank accession numbers. Trans-species polymorphisms (TSPs) are represented by numbers immediately after each MHC sequence. The same TSP is assigned with the same sequential number.(PDF)Click here for additional data file.Figure S3Amino acid alignment of MHC class II β exons 2 and 3 used for selection detection tests. The first column contains the names of MHC sequences. The second column presents the amino acid alignment in letters. Question marks represent unknown amino acids, and numbers above the alignments represent the order of amino acid positions. Sites in boxes with open triangles indicate potential peptide contact residues on the peptide binding region of the HLA-DRB1 molecule based on crystallography models , and those in boxes with closed triangles indicate conserved residues of antigen N and C termini on the peptide-binding region of the MHC class II β molecule .(PDF)Click here for additional data file.Figure S4Amino acid alignment of MHC class II α exons 2 and 3 used for selection detection tests. The first column contains the names of MHC sequences. The second column presents the amino acid alignment in letters. Question marks represent unknown amino acids, and numbers above the alignments represent the order of amino acid positions. Sites in boxes with open triangles indicate potential peptide contact residues on the peptide binding region of the HLA-DRA molecule based on crystallography models , and those in boxes with closed triangles indicate conserved residues of antigen N and C termini on the peptide-binding region of the MHC class II α molecule .(PDF)Click here for additional data file.Figure S5Maximum-likelihood trees of (A) MHC class II α exon 2, and (B) exon 3. Sequences of MHC class II α among different species of Crocodylia, birds and mammals are analysed using the shark Gici sequences as an outgroup. Brackets in the middle show vertebrate groups to which the MHC class II α sequences belong. Bootstrap values (BV) over 50 are provided on branches. ELW tests show that these two trees did not differ significantly from their Bayesian trees of MHC class II α exon 2 sequences described in α exon 3 sequences described in (PDF)Click here for additional data file.Figure S6Maximum-likelihood analysis of MHC class II β exon 3. Sequences of MHC class II β among different species of Crocodylia, Aves and Mammalia are analysed using the amphibian sequence as an outgroup. Brackets on the right show vertebrate groups to which the MHC class II β sequences belong. Clades were defined on the basis of their monophyletic groupings and high posterior probabilities. Bootstrap values (BV) over 50 are provided on branches, and some below 50 are selectively present.(PDF)Click here for additional data file.Figure S7Variable nucleotide sites of MHC class II β exon 3 sequences within Crocodylia. Variable nucleotide positions are relative to the MHC class II β sequence from C. rhombifer (Crrh-DB04). Dots represent identical bases to the first sequence. The first column contains the names of MHC class II β sequences. Brackets on the right show Clades 1 and 2 of the MHC sequences, as have been explained in the text. Sites highlighted in red indicate fixed differences between Clade 1 and Clade 2 sequences.(PDF)Click here for additional data file.Figure S8Distribution map of the Order Crocodylia showing the number of species per country. This map does not show the actual distribution within each country, but the detailed distribution and list of species in each country can be obtained from http://crocodilian.com/cnhc/cnhc.html. This website also contains a list of primary references supporting this distribution map.(PDF)Click here for additional data file.Table S1List of exon 3 sequences of MHC class II β across 20 species of Crocodylia investigated in the current studies .(PDF)Click here for additional data file.Table S2Summary of MHC class II β exon 3 sequences observed within a representative from each species of Crocodylia, where more than three sequences corresponding to at least two loci have been identified in this study.(PDF)Click here for additional data file.Table S3List of MHC class II α and β sequences available in GenBank used in three datasets for phylogenetic analyses of MHC class II sequences among major vertebrate classes.(PDF)Click here for additional data file.Appendix S1Characterisation of MHC class II α exons 2 and 3 within Crocodylia.(PDF)Click here for additional data file.Appendix S2Characterisation of MHC class II β exon 3 within Crocodylia.(PDF)Click here for additional data file.Appendix S3Effect of recombination at MHC class II α and β.(PDF)Click here for additional data file.Appendix S4BLASTN searches of MHC class II primers used in this study against genome drafts of Alligator mississippiensis (v0.2.1), Crocodylus porosus (v0.2) and Gangeticus gavialis (v0.2). These genome resources are available in GenBank and can be accessed with authors’ permission . Good hits were observed between the primers and putative MHC class II sequences from those species, and this is likely to suggest an unbiased amplification of the presumed targets using the current primers. All the MHC class II sequences on the genomes were annotated and are expected to be published in another manuscript .(PDF)Click here for additional data file.


P<0.05) with precipitation, but their sensitivity to precipitation (diversity change per mm precipitation increase) was different between the steppe types. The sensitivity of α diversity of different steppe community types was negatively (P<0.05) correlated with mean annual precipitation, whereas the sensitivity of β and γ diversity showed no trend along the precipitation gradient (P>0.10). (iii) The α diversity increased logarithmically, while β diversity increased exponentially, with γ diversity. Our results suggest that for local species diversity patterns, the site species pool is more important in lower precipitation areas, while local ecological processes are more important in high precipitation areas. In addition, for β diversity maintenance niche processes and diffusion processes are more important in low and high precipitation areas, respectively. Our results imply that a policy of “multiple small reserves” is better than one of a “single large reserve” for conserving species diversity of a steppe ecosystem, and indicate an urgent need to develop management strategies for climate-sensitive desert steppe ecosystem.Understanding the distribution pattern and maintenance mechanism of species diversity along environmental gradients is essential for developing biodiversity conservation strategies under environmental change. We have surveyed the species diversity at 192 vegetation sites across different steppe zones in Inner Mongolia, China. We analysed the total species diversity (γ diversity) and its composition (α diversity and β diversity) of different steppe types, and their changes along a precipitation gradient. Our results showed that (i) β diversity contributed more than α diversity to the total (γ) diversity in the Inner Mongolia grassland; the contribution of β diversity increased with precipitation, thus the species-rich (meadow steppe) grassland had greater contribution of β diversity than species-poor (desert steppe) grassland. (ii) All α, β and γ species diversity increased significantly ( Half a century ago, Whittaker first defined species diversity from three different perspectives: alpha (α) diversity, beta (β) diversity, and gamma (γ) diversity Studies on the geographical patterns of species diversity generally showed a decreasing trend of α and γ diversity with increasing latitude from tropics to poles, which was primarily driven by temperature Species evolution and diffusion, inter-specific competition, and environmental changes commonly influence the α, β and γ diversity of plant communities, but the response of species diversity pattern to these biological and environmental changes and the mechanisms for the response differ among the three species diversity measures The Inner Mongolia steppe grassland is an essential part of the Eurasian steppe All the survey sites were owned and/or managed by pastoral farmers, who gave permission to the survey. The field studies did not involve any endangered or protected species.We surveyed the grassland species diversity in the whole region of the Inner Mongolia grassland in northern China. The region stretches from latitudes 41.31°N to 50.78°N and longitudes 108.16°E to 120.39°E with elevation ranging from 532 to 1725 m above sea level . The typLeymus chinensis meadow steppe, Stipa baicalensis meadow steppe, S. grandis typical steppe, L. chinensis typical steppe, S. krylovii typical steppe, S. breviflora desert steppe, and S. klemenzii desert steppe. Nineteen to 39 sites were surveyed for each community type; the number of sites for each type was approximately determined by the relative size of its distribution area. The position of each site was located using GPS  in the surveyed ten plots at a site:iS represents the species richness in each plot.γ diversity, also called site diversity, is the total species richness at a site.β diversity, defined as the difference in species composition among the ten plots at a site, is calculated by subtracting α diversity from γ diversity:β diversity has two components, one quantifying the degree of nestedness of species richness (Nβ), i.e. the degree to which species richness differs between plots within one site from the most species-rich plot, and the other component reflecting the difference in species composition among the plots (Rβ). With maxS representing the species number in the richest plot, Nβ and Rβ are calculated as follows:γ) is the sum of the mean species richness of all the plots at the site (α), the differences in species richness due to the nestedness (Nβ) and species composition (Rβ) among the plots:Consequently, the total species richness at a site  were assessed for each grassland site. The species diversity at all of the sites for each steppe community type was averaged to represent the species diversity of the community type. The species diversity composition of three steppe vegetation types  were also aggregated in the same way to represent the species diversity at all grassland sites of a steppe vegetation type.The components of species diversity  at each vegetation site using the approach of Thornthwaite The MAP of each community type was calculated as the mean of the MAP at all the sites that belongs to the community type.R and βN) of the seven steppe community types, and of the three steppe vegetation types, was ordered according to the precipitation of their distribution areas in order to examine the species diversity composition changes across these steppe types in relation to precipitation.First, the proportions of α and β to γ diversity were used to quantify the relative contribution of these two kinds of diversity to γ diversity. The composition of γ diversity  across all 192 sites. The relationships between γ diversity and the ‘occasional species’ (species recorded in only one or two of the ten plots at a site) were also analysed. These relationships were used to interpret the mechanism of species diversity maintenance in the grasslands.Second, we used regression analysis to model relationships between γ diversity and its components  calculated for all the vegetation sites, we plotted each diversity measure against precipitation, and tested for a significant correlation between species diversity and MAP using linear regression analysis. We also did a linear regression analysis between the species diversity and precipitation for each of the seven steppe community types, and used the slope of the regression (i.e. diversity change per mm precipitation change) to represent the sensitivity of the species diversity of each community type to precipitation. A steep slope or high sensitivity means a greater effect of precipitation on community species diversity. The changes in sensitivity across seven community types along a precipitation gradient were tested by examining if the sensitivity and precipitation of these community types were significantly correlated.All statistical analyses were performed using Excel 2010 and SPSS 17.0.γ) and its components  were consistently low in desert steppe and high in meadow steppe, and in-between in the typical steppe (β diversity had a slightly greater contribution (51.83%) to γ diversity than α diversity (48.17%) in the Inner Mongolia grassland , while β nestedness diversity (Nβ) showed little change. When these steppe types were ordered according to the MAP of their distribution areas, a trend of decreasing α and increasing β with increasing MAP was shown  with increasing precipitation (α diversity to precipitation across the seven steppe community types significantly decreased (P = 0.028) with increasing precipitation , though the sensitivity of Rβ diversity showed a non-significant increasing trend (P = 0.10) (Both ncreased . However = 0.10) .γ diversity also significantly increased with precipitation  . The β diversity . The occiversity .α and β diversity to γ diversity form the basis for understanding the biodiversity components α and β diversity to γ diversity: some believe that α diversity is more important, while the others contend that β diversity is more important. A third group suggest that α and β diversity work together β diversity contributes slightly more (51.83%) than α diversity (48.17%) to γ diversity in the Inner Mongolia grassland (β diversity is greater in species-rich grassland (meadow steppe) in high precipitation areas than in species-poor grassland (desert steppe) in low precipitation areas. In other words, the contribution of β diversity has an increasing trend with precipitation   . Thus, tγ diversity and α diversity would suggest that the regional species pool was the main limiting factor. Alternatively, a saturated curve between α and γ diversity would suggest ecological processes are more important in maintaining diversity The maintenance mechanism of local species diversity has always been an important topic in ecology. Local ecological processes  α and γ diversity increased as precipitation increased   with low precipitation, the inter-specific competition is relatively weak resulting in much spare niche capacity. Niche theory indicates that every species occupies its unique corresponding niche γ diversity with α diversity  . That isiversity  in low pβ diversity reflects different degrees of species composition. The environment heterogeneity (or the niche process β diversity Nβ) represents the degree to which species richness in each plot differs from the richest plot at a site, and reflects the extent of the variation in species number within each community. It is closely related to resource heterogeneity or the niche processes i.e., desert steppe), strong winds may erode and move the soil from grass-dominant areas to areas occupied by shrub clamps to create fertile “islands”, thus increasing the environmental heterogeneity i.e., meadow steppe), Nβ diversity increased with an increasing species pool. However, since α diversity is almost saturated with respect to γ diversity  than in species-poor (desert steppe) communities suggests it more useful to apply multiple small reserves for protecting the meadow steppe grassland in relatively humid areas. Second, since species diversity provides a mechanism for maintaining ecosystem stability through compensatory interactions among species α diversity) to precipitation in desert steppe than in meadow steppe (Changes in regional precipitation patterns under global climate change will undoubtedly affect species diversity and ecosystem function and stability iversity  implies w steppe  suggests


If r2≥0.65 at p≤0.05 in any of these regressions, then the trend is regarded as statistically meaningful. Out of ten investigated time series from different scientific disciplines, five displayed statistically meaningful trends. A Microsoft Excel application (add-in) was developed which can perform statistical meaningfulness tests and which may increase the operationality of the test. The presented method for distinguishing statistically meaningful trends should be reasonably uncomplicated for researchers with basic statistics skills and may thus be useful for determining which trends are worth analysing further, for instance with respect to causal factors. The method can also be used for determining which segments of a time trend may be particularly worthwhile to focus on.Linear trend analysis of time series is standard procedure in many scientific disciplines. If the number of data is large, a trend may be statistically significant even if data are scattered far from the trend line. This study introduces and tests a quality criterion for time trends referred to as statistical meaningfulness, which is a stricter quality criterion for trends than high statistical significance. The time series is divided into intervals and interval mean values are calculated. Thereafter, r If one scientific phenomenon is represented and measured by several variables, the trends of these variables may have very low p values and may be contradictory if a large enough number of data is used. This problem may be illustrated using data associated with marine eutrophication. The trophic state of a marine (or any other) water body is defined as the level of primary production near the water surface. Primary producers are organisms which use photosynthesis to transform carbon dioxide and water into tissue and other molecules which other organisms can metabolise. In marine waters, primary producers mainly consist of various phytoplankton species. The trophic state is commonly measured by several complementary variables such as chlorophyll-a, nitrogen and phosphorus concentrations. Chlorophyll-a is a phytoplankton pigment while nitrogen and phosphorus are nutrients which individually or in combination control long-term phytoplankton productivity in most marine and estuarine waters. In many cross-systems surveys, total nitrogen, total phosphorus and chlorophyll-a have all been positively correlated in bivariate regressions with r2 = 0.003, p<0.001, n = 54,511; 2 = 0.006, p<0.001, n = 45,609; 2 = 0.0004, p = 0.010, n = 14,723; Total nitrogen, total phosphorus and chlorophyll-a in surface waters of the Baltic Proper , however, showed quite different linear trends during 1975–2007 . The totAdmittedly, the perceived or practical meaningfulness of trends may differ greatly between variables even within one specific academic discipline. The aim of this paper is to suggest a definition of a statistically meaningful trend based on previously published statistics concepts and methods and to test this definition on a group of time series from different disciplines. The idea is to establish a method which produces sensible results and which is also simple and straightforward enough to be used by scholars with either basic or advanced statistics skills. Statistical meaningfulness is intended as a complementary quality criterion together with high statistical significance as a basis and support for discussions regarding how a certain time trend should be classified, treated and reported. The Theory section will motivate the definition of a statistically meaningful trend. Details about the analysed time series and about analysis methods will also be provided. Results will be displayed in the subsequent section. The final section of this paper will discuss and conclude the findings and their practical usefulness.2 value is commonly known as the coefficient of determination and may be used for measuring the correlation between two variables, x and y. An r2 value at or near 0 means low correlation between x and y and a value near 1 indicates high correlation. The r2 value is defined in eq. 1 where2  in statistical significance tests in which a null hypothesis is rejected when the p value is low. The 95% confidence level (p≤0.05) has traditionally been used for indicating statistical significance in such tests within a wide variety of academic research fields 2 from :(2)The p2≥0.65 according to Prairie's staircase method. Moreover, regressions based on mean values over longer time-periods often have higher r2 values than those of regressions which include all data pairs Prairie's line of reasoning could also be applied on time series analysis. Using a trend equation and time as a predictor, a variable could be reconstructed with high accuracy if r2≥0.65 and p≤0.05, then the time series is statistically meaningful.If one or several regressions concerning time and values in a time series, or time and mean values from intervals into which the series has been divided, yields rThis definition uses the well-established 95% confidence level and Prairie's threshold Ten time series with linear trends at p≤0.05  from difFurthermore, an epidemiology time series on reported malaria cases in the Philippines 1990–2006 was analysed ; n = 17 Finally, economics data from equal time steps or different time steps. Whenever a time series contained one observation or mean value from each time unit , it was divided according to the equal time steps method. An example would be an even time series with seven observations (y1–y7) at the occasions x1 = 1, x2 = 2, x3 = 3, x4 = 4, x5 = 5, x6 = 6 and x7 = 7. If this series should be divided into three intervals, the mean y value from the first interval would be (y1+y2+1/3 • y3)/(2+1/3). The mean y value from the second interval would be (2/3 • y3+y4+2/3 • y5)/(2+1/3). Finally, the mean y value from the third interval would be (1/3 • y5+y6+y7)/(2+1/3). Whenever a time series contained uneven time steps, the series was instead divided into intervals according to the different time steps method. For instance, a time series with seven observations (y1–y7) at the occasions x1 = 1, x2 = 3, x3 = 4, x4 = 5, x5 = 6, x6 = 8 and x7 = 9 could be divided into three time intervals, x = 1–3, 4–6 and 7–9. The mean y values from these intervals would then be (y1+y2)/2, (y3+y4+y5)/3, and (y6+y7)/2. All time series were divided into intervals using one of the two methods 2 values were calculated and assessed and the statistical meaningfulness was tested.To determine which type of interval division is most prone to yielding mean values displaying a statistically meaningful trend according to the definition stated earlier in this section of the paper, Monte Carlo simulations were performed and adapted to producing a Gauss-like distribution shape displaying different occurrences of statistical meaningfulness indications for mean values from different interval divisions. In each simulation run, an x variable was constructed from a series of 1,000 data ranging from 1–1,000 and with an interval of 1, i. e., symbolising a time series with an equal time step of 1 time units between measurements. A y variable was constructed from x and two random variables, Rand1 and Rand2 (both ranging from 0 to 1) according to the following equation:www.mathworks.com). Trends in time series and correlations were evaluated by means of linear regression using Matlab and Microsoft Excel (office.microsoft.com). A software application for performing the statistical meaningfulness test was programmed and designed in Visual Basic using the Developer Center in Microsoft Excel.Monte Carlo simulations were performed using the software Matlab  and r2 (near 0.65) are displayed in 2 values below 0.65. Conversely, if the number of intervals is 3–6, regressions with r2 values higher than 0.65 may have p values above 0.05.Equations 1 and 2 give at hand that the number of intervals, the p value and the rThis breaking point between mean values from 6 and 7 interval divisions initially appeared to play an important role for determining which type of interval division is most prone to producing mean values which indicate a statistically meaningful trend and results from this investigation using 100,000 Monte Carlo simulation runs are displayed in 2 values in trends was also studied using the Monte Carlo simulation runs and results are displayed in 2 values were frequently attained using mean values from a small number (3–7) of intervals and that r2 values gradually decreased by an increasing number of intervals which the series were divided into. However, exceptions to this general pattern were numerous. The p value displayed an even more obscure pattern in relation to the number of intervals from which mean values and trend regressions were generated  and are thus represented just slightly above the diagonal line of 2 value yielded from interval means . Using test results from additional interval divisions (>30) in the add-in was also investigated but turned out to impose severe constraints on the possibility to test the statistical meaningfulness of very long time series .Altogether, results from the Monte Carlo simulations implied that performing a statistical meaningfulness test could in practice require computer programming skills or very much time spent on manually dividing time series into many different intervals. The authors therefore designed a Microsoft Excel add-in , i. e., 2 values and to the statistical meaningfulness definition. Interval divisions were made both on-screen in Microsoft Excel and automatically (using Matlab and the add-in), primarily to study and cross-check the statistical meaningfulness in trends but partly also to detect and correct inconsistencies in the add-in. All time series were divided into 3, 4, 5, and up to 100 intervals  and mean values for each interval were calculated. The main test results from this analysis are displayed in 2 values which were used for determining the outcome of the test are provided in tables S1 and S2  of the 20–25 interval divisions produced r2 values from interval means which were higher than corresponding r2 values from the six interval division  have the advantage that they are based on well-established scientific practice. Whether these limits also produce sensible results will be revealed by the manner and extent to which future studies which will use the method presented in this paper.The limits of the retermine  which tiTo the best of our knowledge, there are no previous descriptions in the academic literature of any attempts to establish demarcation criteria for a statistically meaningful time trend which are applicable to many different variables and scientific disciplines and that are stricter than the common requirements regarding high statistical significance. Variable-specific criteria for meaningful trends are, however, plentiful e. g. . Wu et aTo conclude, the present study has presented a method for assessing whether a time series displays a trend which is meaningful enough to analyse further. The method is based on a concept referred to as statistical meaningfulness. To test the rationale for the method, ten time series with linear trends (p<0.05) were described and analysed with respect to statistical meaningfulness and five of the time series were found to be statistically meaningful. A comparison between the temperature deviation time series in File S1A software application (Microsoft Excel 2007 add-in) which enables a rapid performance of the statistical meaningfulness test.(XLAM)Click here for additional data file.File S2Installation manual and source code for (DOC)Click here for additional data file.File S32 values from the statistical meaningfulness test (see Two tables containing p and r) regarding ten time series described in .(DOC)Click here for additional data file.


Structural magnetic resonance imaging brain scans were obtained from each dog. Tracer washout analysis yielded parametric maps of PiB retention in brain. In the CCD group, dogs had significant retention of [11C]PiB in the cerebellum, compared to the cerebral cortex. Retention in the cerebellum is at variance with evidence from brains of humans with AD. To confirm the lack of sensitivity, we stained two dog brains with the immunohistochemical marker 6E10, which is sensitive to the presence of both Aβ and Aβ precursor protein (AβPP). The 6E10 stain revealed intracellular material positive for Aβ or AβPP, or both, in Purkinje cells. The brains of the two groups of dogs did not have significantly different patterns of [11C]PiB binding, suggesting that the material detected with 6E10 is AβPP rather than Aβ. As the comparison with the histological images revealed no correlation between the [11C]PiB and Aβ and AβPP deposits in post-mortem brain, the marked intracellular staining implies intracellular involvement of amyloid processing in the dog brain. We conclude that PET maps of [11C]PiB retention in brain of dogs with CCD fundamentally differ from the images obtained in most humans with AD.Dogs with Canine Cognitive Dysfunction (CCD) accumulate amyloid beta (Aβ) in the brain. As the cognitive decline and neuropathology of these old dogs share features with Alzheimer’s disease (AD), the relation between Aβ and cognitive decline in animal models of cognitive decline is of interest to the understanding of AD. However, the sensitivity of the biomarker Pittsburgh Compound B (PiB) to the presence of Aβ in humans and in other mammalian species is in doubt. To test the sensitivity and assess the distribution of Aβ in dog brain, we mapped the brains of dogs with signs of CCD ( A prominent explanation of the etiology of Alzheimer’s disease (AD) is the amyloid cascade hypothesis  made non-invasive PET imaging of amyloid deposits possible. Prior to this, visualization of Aβ deposits was only possible using histological post-mortem material .n = 16) and a control group of cognitively normal dogs (n = 4). Dogs were recruited from the Small Animal University Hospital at The Department of Clinical Veterinary and Animal Sciences, University of Copenhagen or through referring veterinarians.The study population consisted of a group of dogs with a clinical diagnosis of CCD . All dogs had a clinical and neurological examination, standard hematological and chemical profiles including thyroid panel showing no evidence of systemic or neurological disease, which could mimic clinical signs of CCD. All dogs had magnetic resonance imaging (MRI) that showed no signs of intracranial lesions that might give rise to clinical signs mimicking CCD. A clinical diagnosis of CCD was established after evaluation with a validated owner questionnaire that targeted signs of CCD and was further supported by the finding of significant brain atrophy on MRI images by means of stereology PiB. Anesthesia was induced by intravenous injection of propofol 4 mg/kg. Following intubation, anesthesia was maintained by a continuous rate infusion of propofol 4–6 mg/kg/h  and the dog was placed in dorsal recumbency with the head positioned in the scanner field. Each dog was carefully positioned in a deflatable Kroeyer bag in order to minimize individual positioning variability between scans. Respiration was maintained with a ventilator , and heart rate was monitored by ECG, Oxygen saturation through a pulse oximeter and blood pressure through a pediatric blood pressure cuff placed on one of the hind extremities. One monitor  registered all parameters. The dogs received Lactated Ringer’s solution from an infusion pump (Baxter) throughout the anesthesia at a maintenance rate of 10 ml/kg/h. All dogs were fasted for at least 12 h prior to imaging to reduce anesthetic risk.PET images of the dog brains were obtained with the HRRT CPS Innovations tomograph mainly used for animal model research. Before PET, each dog was sedated with an intramuscular injection of diazepam 0.4–0.7 mg/kg and methadone 0.2–0.4 mg/kg. Two catheters were placed either in the cephalic or saphenous veins, depending on accessibility, one for the combined administration of anesthesia and maintenance fluids and one for the administration of [N-methyl-11C]2-(4′-methylaminophenyl)-6-hydroxybenzothiazole ([11C]PiB) dissolved in 10 ml of sterile isotonic saline. PET emission data were collected for 90 min preceded by a transmission scan, commencing with the injection of [11C]PiB.Each dog was injected intravenously with 84–333 MBq PiB binding between the CCD and control groups in any ROI. Neither did we find any correlation between the in vivo [11C]PiB accumulation in images obtained with PET, and the ex vivo matched measures of Aβ and AβPP staining post-mortem .We used the washout-dependent time variable Θ to identify an alternative region of reference and to calculate binding potentials. The key to the analysis is the time variable Θ, which is related to and serves as an index of the rate of washout and hence of the degree of expansion of the apparent volume of distribution of the tracer occasioned by binding. By this approach, we found areas of rapid clearance in small areas of the temporal cortex Figure , which w11C]PiB to the same degree as the deposits in the cerebellum, implying that dogs with CCD are not afflicted with a typical form of AD (Figure We did note diffuse Aβ/AβPP immunostaining of both frontal and temporal cortices with 6E10, however these deposits did not bind [D Figure . BecauseD Figure . However11C]PiB binding in the cerebellum, with few if any extracellular deposits and large amounts of intracellular Aβ or AβPP, or both, suggests that [11C]PiB binding may be used to distinguish between intracellular Aβ and AβPP deposits in the dog cerebellum. Aged dogs with CCD spontaneously exhibit diffuse Aβ deposits in the cerebral cortex that are similar to those found in early AD brains (Cummings et al., 1–42 and do not stain with Congo red and thioflavine, unlike proven cerebral amyloid angiopathy (Uchida et al., The high degree of [11C]PiB in tissue from AD patients also recognizes diffuse Aβ deposits in addition to compact Aβ deposits (Klunk et al., 11C]PiB in principle would be a tracer suitable for outlining the distribution of Aβ deposits in the aged dog with CCD with a cranial to caudal distribution. The results point to a pattern of [11C]PiB retention in the dog brain, which is occasionally seen in humans. We also found a discrepancy between the distributions of Aβ and AβPP, when we visually correlated [11C]PiB images with regionally matched images of the post-mortem histological material stained with 6E10. In a study of a cohort of 10 AD patients, one patient who met the histopathological criteria for AD had PiB-refractory PET images (Rosen et al., 1–40 and Aβ1–42, and a higher ratio of Aβ1–40 to Aβ1–42, compared to brain tissue from the nine other AD patients.The high proportion of diffuse to compact Aβ deposits in dogs with CCD theoretically should not pose a problem, because previous investigations show that [11C]PiB imaging in PS1/APP mice and post mortem histological analysis have shown diverging results of different attempts to find a correlation between the [11C]PiB images and Aβ deposits in vitro (Klunk et al., Studies of [11C]PiB retention in dogs with CCD fundamentally is different from that seen in humans with AD. The results of the study support previous studies showing that [11C]PiB is a complex tracer in animals and humans and more investigations of this radiotracer, including displacement studies are needed.This study gave evidence that the distribution of [The research in this paper was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest to authors.


Applying the Bruggeman-Hanai equation, the high-frequency limiting permittivity (εh) of the slurries was extracted from the dielectric spectra. The εh of the 10 vol% slurry showed abnormal size independence in the range from 100 nm to 700 nm, and the εh of the 30 vol% slurry exhibited good agreement with the previous prediction. Through analysing quantitatively the response of εh to the changing permittivity of the powders under different solids loading, it was found that the εh of the slurry with lower solids loading is more inclined to be interfered by the systematic and random errors. Furthermore, a high permittivity value was found in the BaTiO3 powders with 50 nm particle size.The dielectric nanosize dependence of BaTiO So it is very difficult to obtain the exact critical size of BaTiO3 by means of using traditional solid-state pellet technique. Recently, the dielectric evaluation of ceramic slurries as an in situ method has been of primary interest [3 powders keeps basically constant when the particle size is above 200 nm [3 powders and implies that some defects in the slurry method need to be improved. In this paper, we focused on the effect of the solids loading on the slurry method and offered some accurate and valuable information to the dielectric nanosize dependence of BaTiO3 powders.With the achievement of the particle size from several microns downward tens of nanometers, the issue about the nanosize effect of BaTiOtentions –3. Howevd 110 nm , 5. The interest , 7. Howee 200 nm . The res3 powders with seven kinds of particle sizes, 50, 100, 200, 300, 400, 500, and 700 nm, were commercially obtained from Inframat Advanced Materials, USA. The purities of all powders are higher than 99.95%, and the room-temperature density is 5.85 g/cm3. BaTiO3 slurries at two solids loadings, 10 vol% and 30 vol%, were prepared by ultrasonically mixing powders with a propylene carbonate  for 30 min. The slurries were then placed in a liquid dielectric test fixture , and the frequency dependence of the permittivity of the slurries was measured with an impedance analyzer (Agilent Tech. 4294A) from 40 Hz to 20 MHz at 25°C. BaTiO3 powders dispersed in propylene carbonate (PC) with 10 vol% and 30 vol% solids loadings, respectively. A clear relaxation behavior can be seen at near 104 Hz, which is aroused from the interfacial polarization between the BaTiO3 powders and the PC. By using Bruggeman-Hanai equation [3 powders (εp) can be calculated directly from the high-frequency limiting permittivity of the slurry (εh) in the case that the volume fraction of the powders in the slurry (φ) and the permittivity of the PC  (εm) are known accurately. So εh is a significant dielectric parameter in order to obtain the εp with small margin of error. equation (1)εh−εpεh of BaTiO3 slurries with different φ. According to the nonlinear relationship between εh and φ in . So it is reasonable that the εh of 30 vol% BaTiO3 slurry is much higher than the one of  10 vol% slurry at each particle size. Furthermore, the BaTiO3 slurries with different volume fractions display distinct particle size dependence. For the slurry with 10 vol% solids loading, εh keeps constant basically on the size range from 700 nm to 300 nm, which agrees with the results in Wada's research [εh displays a nonlinear size dependence similar with the results from solids method [and φ in , the εhresearch . For the powders 00~5000. 3 powders is supposed to decrease from 4000 to 3000 with decreasing particle size, and the permittivity of the BTiO3 slurries with different given solids loading is calculated by /εh,2 × 100%) can be found. With the volume fraction becoming diluted from 25% to 4%, the Δεh% decreases gradually from 1.90% to 0.20%. It means that the diluter the slurry is, the higher the requirement to the measurement accuracy will be. In experimental measurements, there are always both systematic and random errors, which are mixed into the original data usually. For the dilute slurry, the small Δεh% is more inclined to be interfered by the systematic and random errors and offers inaccurate information. So the solids loading of the slurry should be increased high enough in order to weaken the confused influence of the systemic error on the original data. Now, the permittivity of the BaTiOlated by . Accordiεh from 3 powders, εp. εp, which has the similar size dependence with the corresponding εh. It can be found that the εp increased obviously with the particle size decreasing from 700 nm to 500 nm, and then decreased gradually with the particle size decreasing from 500 nm to 100 nm. The result agrees with the current postulation from the pellet method. The εp dependence in fine BaTiO3 structures is driven by a combined effect of the ferroelectric core whose nonlinearity is gradually reducing, together with the increasing amount of the nonferroelectric “dead-layer” grain boundaries, when reducing the grain size down to tenths of nanometers [εp with 50 nm particle size appeared with significant high value, which was reported only in Wada's slurries method. There is not enough attention for explaining the phenomenon yet, and we will focus on it in our following research.Considering the positive effect of higher solids loading on the accuracy of the slurry method, the 3 powders. By means of comparing the dielectric data and calculation of the BaTiO3 slurries with two different solids loadings, 10 vol% and 30 vol%, the higher one was found to possess lower calculation error. Based on the finding, the conflicting nanosize dependence of the BaTiO3 powders obtained from previous slurry and pellet method was attributed to the low solid loading used in the slurry method.  The importance of the solids loading in the accuracy of the sully method was researched in order to get the accurate nanosize effect of BaTiO


Imidophosphates are phosphorus and nitrogen containing compounds that have been used as chemical fertilizers for some time. In recent years, these compounds have also been used as flame retardants in organic materials, including a variety of plastics and painting materials –3. The cIn recent years, however, numerous reports have appeared in the literature indicating that the addition of specific metal ions to imidophosphates can greatly improve their chemical stability, and this has resulted in extensive research in this area –10. The cyclo-μ-imidotriphosphate anions to protons and various divalent metal ions increased in a linear manner as the number of imino groups in the anions increased. Furthermore, the complexation reaction of the Cu2+– cyclo-P3O6(NH)3 ligand was shown to form an intramolecular bidentate complex with a Cu2+ ion as a consequence of the stereochemical adjustment of the ligand molecule to the metal ion. The stabilization of the complex resulting from this stereochemical adjustment was suggested as the basis for the complexation equilibria between the cyclic imidopolyphosphates and the different metal ions.The triphosphate anion, mentclass2pt{minimous work –24, we sH° and ΔS°) were determined from the temperature dependence of the complex stability constants, and the coordination structures of the complexes resulting from these anions were estimated. These accurate thermodynamic investigations of the complexation equilibria of the linear polyphosphate anions should provide useful information to enhance our understanding of the influence of different metal ions on the hydrolysis behaviors of imidopolyphosphates.In the current study, stability constants of ML-type complexes of the 5P3O10·6H2O, was synthesized and purified according to the literature  were prepared at about 0.2 mol·L−1 from their respective reagents with distilled water. The molalities of these stock solutions were determined by complexometric titration with EDTA using murexide (M: Ni and Cu), Eriochrome Black T , and NN diluted with K2SO4 (M: Ca) as indicator, respectively. Other reagents used in this work were analytical grade of ordinary commercial products (over 98 %).Pentasodium triphosphate hexahydrate, Naterature , 26. Eleth KHCO3 . A carborocedure , and the5P3O8(NH)2·6H2O, was synthesized by an improved hydrolysis method of trisodium cyclo-tri-μ-imidotriphosphate tetrahydrate, Na3P3O6(NH)3·4H2O, as has been reported b, and The first two and three protonation steps of the 10 [H+]) for the 3O8(NH)2 ligand for protons is greater than that of the P3O10 ligand  were also titrated against a solution of 0.04 mol·L−1 NaOH + 0.10 mol L−1 NaNO3, and the resulting titration curves are shown in Fig. S1. In spite of the differences in the initial concentrations of the divalent metal ions, there are no discernible differences between the titration curves and the log10βML values of the anions calculated with the BEST program. These results therefore effectively confirmed the dominance of normal 1:1 complexes.With regard to the log = 7.20) . Further10Κ1 values of the 10βML values of the corresponding Cu and Zn complexes are only 0.37  and 0.92 , respectively. It is likely that the specific properties of the metal ions will have a greater effect on the stabilities of the P3O10 and P3O8(NH)2 complexes with different divalent metal ions than the basicities of the ligands. It has been reported that the log10βML values of cyclo-triphosphate and cyclo-tri-μ-imidotriphosphate anions can vary significantly following the stereochemical adjustment of the ligand molecule to a metal ion  [10βML values of the P3O10 and P3O8(NH)2 complexes on the divalent metal ionic radius, rM. Both the P3O10 and P3O8(NH)2 ligands show their greatest stabilities in the corresponding Cu complexes, and also clearly show a similar rM dependence in terms of their log10βML values, despite the difference in the bridging atoms of the different ligands. Furthermore, the order of the log10βML values for the first-row transition metal ions is in accordance with the Irving–Williams order [The difference between the logtal ion) , 46. Fig92 Zn, 7.–6.55, rems order . These rH°, and the entropy, ΔS°, during the complexation reactions of a series of ligands [G°, which only reflect the stability of the complex, tend to be less significant for the estimation of different complex structures. As a consequence of enthalpy–entropy compensation, a mere comparison of the complex stabilities may not accurately reflect the coordination structures of the complexes of a ligand [3O10 and P3O8(NH)2 ligands, a van’t Hoff plot  (Table S1) was employed to evaluate the thermodynamic parameters of the complexation reactions, ΔH° and ΔS° [A comparison of the stabilities of the complexes on their own is insufficient when discussing the effects of the different functional groups and bridging atoms of a series of ligands with similar molecular structures on different complex structures. This is because a specific enthalpy–entropy compensation effect is frequently observed between changes in enthalpy, Δ ligands –55. Consa ligand . Thus, i and ΔS° .H° and TΔS° values are listed in Table H° and TΔS° values for the complexation reactions of the P3O10 and P3O8(NH)2 ligands. The slopes of the −ΔH° versus TΔS° plots have a gradient of ca. −1, which indicates a specific enthalpy–entropy compensation effect. In all of the complex formation systems of the P3O10 and P3O8(NH)2 ligands evaluated in the current study, the complexation reactions of the Ca2+, Sr2+, Ba2+–2+, Zn2+, Ni2+–2+, Zn2+, Ni2+–2+, Ba2+, Sr2+–2+, Zn2+, Ni2+–The van’t Hoff plots obtained in the current study give straight lines for all of the complexation systems . The −Δsolution , 56. In 3O10 ligand from the relaxation rates of the 31P and 1H NMR spectra, which have been corrected for the influence of the paramagnetism of the transition metal ions [2 type tetradenate complex at pH > 9. These coordination structures are in good agreement with the structures estimated from the results of the current research in the low pH region, and therefore effectively confirm the validity of the estimated coordination structures used in this study.Laurie et al.  estimatetal ions . Given t2+, Ba2+, and Sr2+–−) and imino (P–NH–P) groups of imidopolyphosphate anions [2+, Ba2+ and Sr2+ should bind to the harder oxygen atom rather than the softer nitrogen atom of the imidopolyphosphate anion. Consequently, direct coordination with the imino nitrogen atom can now been excluded. It therefore follows naturally that the metal ions must also coordinate to the two non-bridging oxygen atoms in the Ca2+, Ba2+, Sr2+–Although two possible coordination structures can be postulated for the bidentate complexes of the Cae anions , 23. The2+, Cu2+ and Zn2+, no remarkable increases in the stability constants of the complexes is suggested, based on the chelate effect or conspicuous entropic predominance in the complex formations; hence, participation of the imino nitrogen atom and the formation of bidentate complexes cannot be considered in the Ni2+, Cu2+, Zn2+–ca. 0.2–0.3 Ǻ) in the distance between the neighboring phosphate groups because of the substitution of bridging oxygen atoms by imino nitrogen atoms, and it can be estimated that the two non-bridging oxygen atoms in the P3O10 and P3O8(NH)2 ligands coordinate to one metal ion whose ionic radius is suitable for the distance between the neighboring phosphate groups, as shown in Fig. For the soft metal cations, including Ni10βML values using Schwarzenbach’s procedure, a good correlation has been found between the log10βML and log10K1 values. All of the log10βML values increase as the basicity of the anions increase because of the imino groups in the P3O8(NH)2 ligand. The specific properties of the metal ions, however, probably have a more significant effect on the stabilities of the divalent metal complexes than the basicities of the ligands.The stepwise protonation constants of 3O10 and P3O8(NH)2 ligands show the highest log10βML values, as well as a similar rM dependence for the log10βML values. In addition, the order of the log10βML values for first-row transition metal ions of the P3O10 and P3O8(NH)2 ligands is in accordance with the Irving–Williams order. These observations suggest that only the non-bridging oxygen atoms are coordinating directly to the metal ions for both of these ligands, and that the imino groups can not participate in the coordination to the metal ions.The Cu complexes of the PH° and TΔS° for the complexation reactions evaluated in the current study. In addition, in the complexation reactions of the Ca2+, Sr2+, Ba2+–2+, Zn2+, Ni2+–2+, Zn2+, Ni2+–2+, Ba2+, Sr2+–A specific enthalpy–entropy compensation effect was observed between −ΔThe thermodynamic findings concerning the complexation equilibria between the imidophosphate anion and the different metal ions studied in this work will provide useful information and benchmark values for the complexation properties, coordination properties, and hydrolysis profiles of imidophosphate derivatives such as those used in a variety of inorganic flame retardants.Supplementary material 1 (DOCX 177 kb)Supplementary material 2 (DOCX 177 kb)Supplementary material 3 (DOCX 949 kb)Below is the link to the electronic supplementary material.


A search was conducted in the PubMed electronic databases in August 2011. In the studies analyzed, increasing the α/β ratio is associated with an increase in the strength of the correlation between isocenter BED and local control, especially in the studies with median followup of ≥24 months, for which Spearman's correlation coefficients of 0.74–0.76 were achieved for α/β of 20 Gy, 30 Gy, and 50 Gy (P =  0.007–0.008). A trend toward statistical significance was observed for the correlation of isocenter BED and the 2-year overall survival when an α/β of 20 Gy was used approached statistical significance (P = 0.073). Our results suggest that an α/β > 10 Gy may be more appropriate for the prediction of dose response in the setting of lung SBRT.We hypothesize that the correlation between the radiation dose expressed as the biologically effective dose (BED) and the clinical endpoints will correlate better as the value of the  Stereotactic body radiation therapy (SBRT), a technique which delivers an ablative dose of radiation over a short period of time, has emerged to become a major noninvasive treatment modality for early stage nonsmall cell lung cancer (NSCLC) worldwide. Excellent local control with tolerable toxicity profile has been consistently reported . In operDue to the large variation in the dose fractionation schedules used in clinical practice, dose response following SBRT was investigated and demonstrated after the radiation dose delivered is converted to the biologically effective dose (BED) after linear quadratic normalization , 4. The Despite this wide adaptation of the BED in lung SBRT, many have questioned its validity because of the potential overestimation of tumor cell kill when large doses of radiation are delivered in 1 fraction by the linear quadratic (LQ) formalism –8. To avα/β ratio, which is approximately 20 Gy for oropharyngeal cancers [α/β ratio of higher than 10 Gy may be more appropriate for NSCLC. Higher α/β ratio has been known to produce straighter curves in the high-dose region through the LQ model. Therefore, the potential overestimation of dose response in high-dose regions by the LQ model in the setting of SBRT for early stage NSCLC may be reduced by simply using an α/β ratio of higher than 10 Gy when calculating tumor BED, especially when large fractional doses are used [α/β ratio is the most appropriate for tumor BED calculation in this setting.As shown previously, NSCLC cells can possibly repopulate as fast as oropharyngeal cancer cells . It has  cancers . Therefoare used . In the α/β ratio should be most appropriate for BED calculation in the setting of SBRT for early stage NSCLC. This is assessed by investigating the strength of correlation between the tumor BED at the isocenter of the target calculated with various randomly selected α/β ratios  and the clinical endpoints of local tumor control and overall survival. A search based on PubMed electronic databases was conducted to select studies outlining the following: local control for early stage NSCLC following SBRT; toxicity following SBRT for NSCLC. The following terms were explored and used for each database search: non-small cell lung cancer, early stage, stage I, stereotactic body radiotherapy, stereotactic radiosurgery, and stereotactic ablative radiotherapy. Reference lists of relevant papers were then searched for additional publications. The tumor BED was calculated based on the linear quadratic formula with α/β ratios described above. For this study, the tumor BED is the BED at the isocenter of the target volume. Local control refers to the rate of tumor control at the primary site only for the duration of each study. It equals the number of patients with the tumor controlled locally decided by the total number of patients treated for a specific dose fractionation schedule.This systematic review was designed to explore what Scatterplots and nonparametric regression lines are generated using lowess smoothers , 14 to iA total of 24 studies reporting the clinical outcome associated with one dose fractionation scheme for which the isocenter dose can be calculated (most commonly used scheme if outcome following multiple dose fractionation schemes was reported) following SBRT delivered with photon therapy for stage I, and mostly T1, NSCLC were identified –39. TheyP = 0.033). This dose response relationship is shown in As shown in α/β ratio through the linear quadratic formula, they were correlated with the associated local control values. As shown in α/β ratio was used in the BED calculation. The isocenter BEDs calculated with α/β ratios ranging from 5 to 50 Gy were all significantly correlated with the local control. However, the Spearman's rank correlation coefficient appeared to increase more noticeably as the value of α/β ratio increased to over 10 Gy. The strength of correlation  between tumor isocenter BED and the local control also increased as the α/β ratio increased, especially when an α/β ratio of >10 Gy was used.After the isocenter BEDs were calculated with gradually increasing but randomly selected values of α/β ratios and the local control rate reported in these studies was also observed. As shown in α/β ratio is used in BED calculation. The highest correlation is observed for α/β ratios of 20, 30, and 50 Gy with correlation coefficients of 0.74–0.76 . Seven of the 24 studies reported overall survival (OS) at 2 years , 29, 39.α/β ratio has commonly been accepted to be approximately 10 Gy for tumor or “early responding” tissue. However, more studies are reporting a highly variable range of α/β ratios for various cancers based on individual tumor's rate of proliferation [α/β ratios based on specific tumor type may be important in the setting of SBRT, in which the LQ model has been criticized for overpredicting dose potency when large fractional dose, such as 20 Gy, is delivered [α/β ratio is increased to 20 Gy to account for the rapidly proliferating nature of NSCLC cells when SBRT is used to deliver large fractions over ≤5 fractions [As a tissue specific fractionation sensitivity parameter in the LQ formula, the feration , 41, 42.elivered . This isractions . On the ractions . Howeverα/β ratios. This implies the robustness of the linear-quadratic (LQ) formalism in predicting dose response and its clinical applicability in the setting of lung SBRT. The correlation between local control and the isocenter BED increased when the α/β ratio used in BED calculation increased from 5 Gy to 50 Gy . This finding supports the use of higher α/β ratios, such as 20 Gy, for the prediction of biologically effective dose response in the setting of lung SBRT. For an α/β ratio of infinity, the Spearman's correlation coefficient was 0.40 (P = 0.15) for correlation between local control and tumor BED in studies with median followup of at least 24 months. Similarly, there was no statistically significant correlation when physical dose was used to correlate with 2-year OS . This suggests that the physical dose should not be used directly for dose response estimation in the setting of lung SBRT.The most important finding of this study is that the biologically effective dose response relationship in the setting of lung SBRT appears to be very stable throughout a spectrum of  Figures  and 3. T Figures . These sculation . This coα/β ratio to be used for iso-dose effect comparison of the SBRT dose fractionation schedules and conventionally fractionated dose regimens has been estimated to be 8.2 Gy in a modeling study by Stuschke and Pöttgen [α/β ranging from 8 Gy to 14 Gy. Our study is different from the previous studies in that it further suggests that an α/β of >10 Gy may be comparatively more appropriate in the setting of lung SBRT even that spectra of α/β ratios from 5 Gy to 50 Gy may all be valid. However, this should be further validated in a large prospective study to include NSCLC patients who are treated with both conventionally fractionated radiotherapy and SBRT. This will need to be conducted to further investigate if a single α/β that would be suitable for both conventionally fractionated radiotherapy and SBRT can be defined. Furthermore, our study analyzes a relatively more homogeneous group of studies which report the clinical outcome following SBRT only. This minimizes the confounding factors, such as the delayed tumor cell repopulation associated with conventionally fractionated radiotherapy, the difference in reassortment, and reoxygenation between conventionally fractionated radiotherapy and ablative radiotherapy, as well as differences in treatment outcome related to the different technology used for radiotherapy delivery.The robustness of the LQ model in the prediction of biologically effective dose response observed in our study is also supported by other studies , 45. The Pöttgen . In anotSpearman's correlation coefficient was used to assess the relationship between the tumor BED and the clinical endpoints assuming a nonlinear monotonic function. However, the study size was not taken into account when Spearman's correlation coefficient was calculated, which is a major limitation of our study. As a result, the findings from this study can only be suggestive and need to be further validated in future studies. Also, the heterogeneous nature of the different patient populations included in different studies greatly limits the study and warrants future investigation in a study that will assess tumor BED and clinical outcome based on individual patient outcome. Another limitation is that there were only 7 studies reporting the 2-year overall survival, which may be too few to establish a correlation with a high level of confidence.α/β ratio is associated with an increasing trend in the strength of the biologically effective dose response relationship, especially when the α/β ratio is increased to ≥20 Gy. All of our findings support the previous hypothesis that the overestimation of tumor cell kill from the LQ model may be reduced by simply increasing the value of α/β [α/β ratio in the setting of SBRT for early stage NSCLC. But it does suggest that an α/β > 10 Gy may be more appropriate for the prediction of dose response in the setting of lung SBRT.Our study demonstrates that increasing the e of α/β . However