TAR DNA-binding protein 43 (TDP-43) is a major component within ubiquitin-positive inclusions of a number of neurodegenerative diseases that increasingly are considered as TDP-43 proteinopathies. Identities of other inclusion proteins associated with TDP-43 aggregation remain poorly defined. In this study, we identify and quantitate 35 co-aggregating proteins in the detergent-resistant fraction of HEK-293 cells in which TDP-43 or a particularly aggregate prone variant, TDP-S6, were enriched following overexpression, using stable isotope-labeled (SILAC) internal standards and liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS). We also searched for differential post-translational modification (PTM) sites of ubiquitination. Four sites of ubiquitin conjugation to TDP-43 or TDP-S6 were confirmed by dialkylated GST-TDP-43 external reference peptides, occurring on or near RNA binding motif (RRM) 1. RRM-containing proteins co-enriched in cytoplasmic granular structures in HEK-293 cells and primary motor neurons with insoluble TDP-S6, including cytoplasmic stress granule associated proteins G3BP, PABPC1, and eIF4A1. Proteomic evidence for TDP-43 co-aggregation with paraspeckle markers RBM14, PSF and NonO was also validated by western blot and by immunocytochemistry in HEK-293 cells. An increase in peptides from methylated arginine-glycine-glycine (RGG) RNA-binding motifs of FUS/TLS and hnRNPs was found in the detergent-insoluble fraction of TDP-overexpressing cells. Finally, TDP-43 and TDP-S6 detergent-insoluble species were reduced by mutagenesis of the identified ubiquitination sites, even following oxidative or proteolytic stress. Together, these findings define some of the aggregation partners of TDP-43, and suggest that TDP-43 ubiquitination influences TDP-43 oligomerization. TDP-43 is a major protein component in ubiquitin-positive, tau- and α-synuclein-negative inclusions of frontotemporal lobar degeneration (FTLD) and amyotrophic lateral sclerosis (ALS) It is unknown if TDP-43- or TDP-S6-associated post-translational modifications (PTMs) play a role in the mechanism(s) underlying TDP-43 proteinopathy because precise identification of PTM sites and PTM involvement in recruiting interaction partners to biochemically insoluble aggregates with TDP-43 remains largely unexplored. Mechanisms of TDP-43 aggregation defined in cellular models, particularly determinants in terms of primary structure motifs and PTMs on TDP-43 or partners could provide insight into pathology in more complex tissues. PTMs generally influence protein-protein, protein-nucleic acid, and/or protein-membrane interactions by altering or augmenting the protein surfaces available for stable interactions with select PTM-sensitive or PTM-dependent partners. For example, ubiquitination of a protein can enable interactions with ubiquitin receptors facilitating aggresome formation, or with other receptors that drive protein flux through the proteasome, or at autophagosomes accumulating proteins for degradation The purpose of this study was to determine what interactions with TDP-43 or TDP-S6 occur in detergent-resistant protein aggregates to suggest aggregation-associated TDP-43 function, and to unambiguously identify associated PTMs including TDP-43 ubiquitination sites. Biochemical fractionation preceding quantitative mass spectrometry was followed by extensive validation of TDP-43 or TDP-S6 overexpression-induced cytoplasmic detergent-insoluble co-aggregate proteins. We also characterized similarly composed arsenite-induced TDP-43-positive cytoplasmic stress granules and spontaneous TDP-S6 inclusions in both HEK-293 cells and primary motor neurons using immunofluorescence colocalization. Four ubiquitination sites on TDP-43 or TDP-S6 were identified in addition to TDP-43 overexpression-induced methylation on intrinsically detergent insoluble proteins. An intriguing and unexpected finding is that the methylation and ubiquitination events that co-occur during TDP-43 or TDP-S6 overexpression occur primarily on RNA interaction motifs, suggesting that these PTMs play a role in remodeling the network of cellular RNPs during protein aggregation which may be an underlying process in neurodegenerative proteinopathy.C57BL6 timed pregnant mice (Charles Rivers) were sacrificed following ethical standards in the protocol approved by the Institutional Animal Care and Use Committee (IACUC) at Emory University.Sodium arsenite, IU-1, and MG-132 for treatment of cultured cells were respectively obtained from Sigma (St. Louis MO), R&D Systems/Tocris (Minneapolis MN), and EMD Chemicals/Calbiochem (Gibbstown NJ). All other reagents were obtained from Sigma unless otherwise noted.8) were mock transfected or transfected with HA-TDP-43 or HA-TDP-S6 constructs for 48 hours essentially as described previously Human Embryonic Kidney-293 cells (HEK-293 cells available from the American Type Culture Collection as CRL-1573) , and supplemented with 10% fetal bovine serum  and 1% penicillin-streptomycin (Cambrex). Cells were grown in a humidified 5% CO, we used mAb clone 3H8 against TDP-43 as indicated but confirmed transfection with the HA antibody on another fluorescent channel after using a triple-labeling technique that minimizes cross-reactivity of same-species antibodies and using anti-HA antibody before the pan-TDP-43 antibody. Specifically, triple staining was performed with mouse anti-HA.11 overnight followed by first Cy5-conjugated (1∶200 for 1 h), then unconjugated (1∶50 for 3 h) goat anti-mouse monovalent Fab (Jackson Immunoresearch), followed by immunochemistry as described using mouse anti-TDP-43 clone 3H8 and one of the rabbit antibodies against hnRNP A0, G3BP, PABPC1, or eIF4A1 listed above.In one experiment, −20°C methanol fixation for 2 min benefited the visualization of G3BP and TDP-43 positive stress granules with a N-terminal specific monoclonal TDP-43 antibody , but may have also decreased the signal from nuclear TDP species. For consistency with previous staining using paraformaldehyde fixation, all other visualization of stress granules by immunocytochemistry was performed with paraformaldehyde, although like the other N-terminal epitope for TDP-43, the N-terminal HA tag did not generally image with acceptable contrast or signal-to-noise in paraformaldehyde-fixed stress granules. Therefore, for many of the images presentedin vitro. Mouse anti-TDP-43  and rabbit anti-G3BP (1∶100), eIF4A (1∶100), and PABPC1 (1∶30) antibodies were incubated overnight at 4°C. Cy3- or Cy2-conjugated secondary antibodies (Jackson Immunoresearch) were incubated for 1 h at room temperature. Z-series  were acquired with an epifluorescence microscope  equipped with a cooled CCD camera . Images were deconvolved using Autoquant  and analyzed with ImageJ.Motor neurons were fixed for 15 minutes with 4 percent paraformaldehyde in PBS at 3 days Immunoblotting was performed according to standard procedures as reported previously 5′-ACATCCGATTTAATAGTGTTGG-3′, occurs in exon 3 while the reverse or 3′ primer in exon 6 of TDP-43, 5′-ACAGCACTACTTTCAATGAAGTG-3′, has its 3′ end 32 bp downstream of the TDP-S6 specific junction, which is 100% conserved in TDP-43 mRNA from the mouse TDP-S6 mRNA (European Nucleotide Archive sequence ACV52544.1) over 39 bases 5′ of the junction and 57 bases 3′ of the junction, with 951 intervening bases in the TDP-43 mRNA. Predicted amplicons for TDP-S6 and TDP-43 were 580 bp and 1531 bp. Total RNA was extracted from three treatment groups of HEK-293 cells  in biological duplicate using Trizol reagent (Invitrogen) according to manufacturer’s protocol. Superscript III one step RT-PCR with Platinum Taq (Invitrogen) was used according to manufacturer’s directions with 100 ng RNA input and cDNA synthesis for 20 min at 53°C. Twenty-five percent of RT-PCR products were visualized on 3% TAE agarose.A primer set capable of amplifying both human TDP-43 and TDP-S6 mRNA was selected from the National Center for Biotechnology Information reference sequence NM_007375.3 for TDP-43. The forward or 5′ sense primer, 13C615N4) and L-Lysine  were added  to a final concentration of 0.26 mM. Excess proline was added at 200 mg/L to block arginine to proline conversion 18 column  and eluted during a 10–30% gradient . The eluted peptides were detected by Orbitrap  target, 1,000 ms maximum ion time, resolution 60,000 FWHM) followed by five data-dependent MS/MS scans in LTQ  on a hybrid mass spectrometer . All data were converted from .RAW files to the .DTA format using ExtractMS version 2.0 (Thermo) and searched against the human reference database downloaded from the National Center for Biotechnology Information (downloaded July 2010) using the SEQUEST Sorcerer algorithm . Searching parameters included mass tolerance of precursor ions (±50 ppm) and product ion (±0.5 m/z), partial tryptic restriction, with a dynamic mass shifts for oxidized Met (+15.9949), Lys (+8.01420 for 13C615N2) and Arg (+10.00827 for 13C615N4), four maximal modification sites and two maximal missed cleavages. Only b and y ions were considered during the database match. To evaluate false discovery rate (FDR), all original protein sequences were reversed to generate a decoy database that was concatenated to the original database  corr, minimum 1.0) and ΔCn (minimum 0.05) values to reduce protein FDR to less than 1 percent. All MS/MS spectra for proteins identified by a single peptide and those modified by ubiquitin (lysine +114.0429) or methylation  were manually inspected as described previously www.matrixscience.com; May 20, 2011) against the full human database using variable modification settings for the PTMs, ±20 ppm peptide  and ±0.6 Da MS/MS tolerances. Importantly, Mascot was able to discriminate multiple site modified peptides with mixed modifications, e.g. monomethylation and dimethylation on a single peptide. The identified proteins/peptides are listed in HEK-293 cells were cultured in DMEM (deficient in L-Lysine and L-Arginine) supplemented with 2% dialyzed fetal calf serum (Invitrogen) as described 5) cells were harvested in RIPA buffer, and RIPA-insoluble proteins were solubilized in urea buffer as described above. All RIPA insoluble protein was loaded on a 10% SDS-PAGE gel, and proteins below 50 kDa were excised and digested with trypsin. Peptides were loaded and eluted off a C18 nanocolumn  during a reverse-phase LC 10–30% gradient  were monitored and fragmented at precursor m/z and compared to previously identified MS/MS spectra for  two TDP-43 peptides ,  one peptide unique to TDP-S6,  an eIF4A1 peptide unique to both eIF4A1 splicing isoforms, and VFGESDELIGQK; f, V(161 or 198)VLAYEPVWAIGTGK) two triosephosphate isomerase peptides found to be constitutively present at high levels in the detergent insoluble fraction with no significant effect of TDP-S6 overexpression on quantitation in this fraction, and thus suitable for normalization. MS/MS settings were: 1.7 m/z isolation width centered at , 35% collision energy, 5,000 AGC target, 150 ms maximum ion time. Each sample was run in technical replicate.Control, 0.5 mM sodium arsenite-treated (90 min), and TDP-S6 transfected (60 h) HEK-293 (5×1010), a2 1351.61 (y14); b1 896.44 (y7), b2 767.39 (y6), b3 604.33 (y5); c1 808.43 (y7), c2 695.35 (y6), c3 921.51 (y8)], and total summed intensity for each peptide was multiplied by 150 ms/(ion inject time) to cancel out effects of AGC on MS2 fragment ion intensities, particularly in weak and multiplexed MS/MS spectra. All fragment ions used for quantification were required to be present for a positive identification and accurate quantification. Extracted ion current (XIC) intensity of the precursor ion not subject to AGC was used to quantify eIF4A1 and triosephosphate isomerase peptides. Each of the triosephosphate isomerase peptide intensities was then used to normalize each TDP or eIF4A1 peptide intensity before calculation of arsenite-treated/control or TDP-S6 transfected/control relative intensity. Finally, the two triosephosphate isomerase peptide-normalized intensities for each of the other peptides were averaged and presented as log2 ±95% confidence interval.Thermo .RAW files were analyzed manually using Qual Browser 2.0.7 (Thermo). MS/MS signal intensity was summed for the two or three most prominent fragment ions from each of the TDP peptides a-c . Consistent with previous results following sarkosyl-detergent extraction 2-transformed  ratio for proteins quantified in one or more molecular weight regions of both replicates  was calculated using IQUAN software Table S1). The quantified protein populations showed a Gaussian distribution in mock transfected cells, but an uneven or possibly bimodal distribution in the TDP-43 or TDP-S6 experiments  consistently changing more than 1.64 times the standard deviation of the mean  in the TDP-43 and/or TDP-S6 cell models relative to mock transfected HEK-293 cells, or in the TDP-43 model relative to TDP-S6 (2(TDP-43/Mock), ±0.89 log2(TDP-S6/Mock), and ±0.65 log2(TDP-S6/TDP-43). To visualize proteins significantly changing in the TDP-43 and/or TDP-S6 models, we constructed a triple SILAC map 2-transformed ratios , consistent with interactors of the TDP-43 C-terminal region that is missing in TDP-S6; some of the group 4 proteins are significantly changed by other measures in groups 1 to 3 and are not repeated, but rather are denoted above by an additional diagonal downward arrow.In the first three of four groups of changing proteins in Interestingly, nine out of the 35 proteins (25.7%) increasing significantly in TDP-43 and/or TDP-S6 insoluble fractions contain at least one RRM domain. Manual comparison of MS spectra for differences in light/heavy ratios in mock, TDP-43 and TDP-S6 models confirms the changes provided by automatic data analysis for four such proteins: PABPC1, G3BP, RBM14, and PSF  are coenriched with TDP-43 and/or TDP-S6. In addition, cytoplasmic RNA binding proteins which participate in cytoplasmic stress granules that have a role in stress-induced translational repression of housekeeping gene mRNAs  also coenriched. This raises the question if overexpressed TDP-43 or TDP-S6 localize in either paraspeckles or stress granules, which is addressed in below results sections.Other novel observations discussed here  are that TDP-43 more than TDP-S6 preferentially accumulates with the previously reported interacting 60 S and 40 S ribosomal proteins L5, S3a, L14, P0, and L3, and the nascent polypeptide chaperone complex represented by Cct7 in group 3. Group 4 proteins that significantly decrease in the comparison of TDP-43 to TDP-S6 insoluble proteome include dynein and EWS (in both groups 3 and 4), as well as RNA helicase A. The latter two proteins interact in a drug-sensitive nuclear complex 2(TDP-43/Mock)] rather than FUS (0.34) or TAF15 (0.37) (Table S1), consistent with cell type specific interactions, which may not occur in the neurons affected in either FTLD or ALS. An equally plausible alternative to the interpretation of protein-protein interaction is that TDP-43 overexpression may indirectly and differentially affect transcription, translation, or post-translational stability of these intrinsically detergent-resistant proteins that have potential overlapping function with TDP-43.Recently, TDP-43 negative, FUS-positive FTLD inclusions were found to contain EWS and TAF15 Figure S1), where categories for localization, domain content, or nucleic acid association were determined using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) The quantitative approach employed for this study following qualitative detergent insoluble protein enrichment has two important caveats that must be addressed. First, qualitatively, the aggregate proteome is not the entire detergent insoluble proteome. In fact, the makeup of the mock-transfected detergent insoluble proteome provides insight into a background level of proteins that copurify with aggregate proteins. These proteins fall into categories of possibly ordered protein complexes with nucleic acid chains (RNPs and chromatin), cytoskeletal proteins, or mitochondrial organelle contaminants  could expand or contract the total protein amount that is resistant to detergent extraction. This issue of mass balance underpins whether any quantitation as calculated is reliably indicating the specified change in protein. In the case of TDP-43 overexpression, mass balance is roughly maintained because the total protein in the detergent insoluble fraction containing aggregates does not grossly change as a percentage (about 4 percent) of total cellular protein in lysates of TDP-43 or TDP-S6 transfected vs. untransfected HEK-293 cells Identifications of 299 proteins increasing moderately or better, at least 0.5 log2-ratio units (41 percent) in either the TDP-43 or TDP-S6 aggregate proteome, were input into Ingenuity Pathway Analysis. Selected output functional annotation categories for these enriched proteins are given in 2 ratio), EIF4G1 (replicate 2∶1.60 TDP-S6/mock log2 ratio), and EIF4H (replicate 2∶0.73 TDP-S6/mock log2 ratio).In fact, for all of the functional categories in With a preponderance of proteomic evidence indicating a role for TDP-S6 in altering translation initiation complexes, causing both core components and modulators to become increasingly resistant to detergent solubilization, we asked whether TDP-S6-induced inclusion bodies contain stress granule components such as G3BP, PABPC1, and eIF4A1, and if any colocalization with full length HA tagged TDP-43 could be discerned. Immunocytochemistry indicated that TDP-S6 inclusions indeed are strongly positive for G3BP  MS/MS peak abundance ratio of 0.70±0.15; 2 ratio of 2.3±0.28), similar to a shared N-terminal peptide residing in both full length TDP-43 and TDP-S6 RRM1. In contrast, with TDP-S6 overexpression, the TDP-S6 peptide increased 60-fold, and the peptide that is specific for non-TDP-S6 splice isoforms increased to an extent similar to the levels seen with arsenite treatment. These results indicate that endogenous TDP-S6 may also participate in arsenite-induced detergent-insoluble cellular features along with TDP-43. The most likely candidate for such features is stress granules. One explanation for the significantly less robust increase in TDP-S6 than other TDP-43 isoforms with arsenite treatment could be the intrinsic low abundance of TDP-S6 relative to other isoforms; indeed, a rough comparison of relative abundance provided by the average raw signal intensity for each of the two exon junction peptides suggests a stoichiometry of 20∶3 for endogenous TDP-43:TDP-S6, even in the arsenite treated insoluble fraction. Moreover, no increase in mature TDP-S6 splicing product is evident via reverse transcriptase PCR of RNA from 1.5 h arsenite-treated HEK-293 cells relative to controls, although the mRNA for full length TDP-43 appears to decrease in abundance . We conclude that proteins coenriching in the insoluble fraction of the overexpression cell models, particularly other predominantly nuclear proteins that are not overexpressed, are likely to exist in a heterogeneous population of structures that contribute to the TDP-43 and TDP-S6 aggregate proteome, potentially partly due to indirect effects of TDP-43 overexpression. These data also highlight the heterogeneity of TDP-S6 localization, varying from mostly cytoplasmic in large aggregates . In the case of the putative PSF-TDP-S6 interaction, the relative lack of substantial colocalization in contrast to that seen for nuclear RBM14 and TDP-S6 is noted. In combination with the finding of biochemical enrichment in the detergent insoluble fraction, this observation may suggest that an indirect effect of TDP-S6 overexpression is to increase PSF association with chromatin; PSF-chromatin interaction is thought to promote dynamic changes in transcription coregulator complexes, thereby affecting gene-specific transcription rates Three paraspeckle proteins  involved in pre-mRNA splicing and transcriptional repression upper panel, and detergent insoluble heavy internal standard, lower panel). Comparison of the MS spectra for differences in light/heavy ratios of this peptide in the mock, TDP-43, and TDP-S6 mixtures in Table S3).Beyond generating and validating a list of interaction partners in an aggregate-enriched fraction of overexpressing cells to complement existing TDP-43 interactomes The significance of changes in RGG motif methylation stoichiometry in the detergent-insoluble fraction of TDP-43 and/or TDP-S6 overexpressing cells is subject to additional questions. For example, since the identified RNP proteins with increasing RGG methylation are not in the target aggregate proteome that changes with TDP-43 or TDP-S6 overexpression, this may be a response to TDP-43 overexpression that alters affinity for (possibly promoting) RNA binding in RNPs at a more global level outside of TDP-43 aggregates. Moreover, increased occupancy of the methylated form of RGG motifs by RNA that accumulates in response to TDP-43 overexpression could drive detergent insolubility and increase the apparent stoichiometry of the methylated vs. unmethylated forms of these proteins in the detergent insoluble fraction. Alternatively, TDP-43 has been found to extensively bind to exons of arginine methyltransferase PRMT2/HRMT1L1 mRNA Ubiquitination alters the fate of proteins, expediting degradation or changing activity and trafficking, and thereby plays central roles in neurodegeneration and cancer Table S5. TDP-S6 sequesters endogenous TDP-43 in TDP-S6 aggregates D. melanogaster, and K145 and K181 are still conserved in the closest C. elegans TDP-43 homolog.Detergent insoluble TDP-S6 on immunoblots is found in high molecular weight polymers -TDP-43 with two alkyl groups mimicking the GG remnant on lysine with regards to mass and miscleavage upon tryptic digestion . Moreover, a recent proteome-wide study in HEK293T cells found K102 and K114 as well as K160 to be ubiquitinated Figure S3). Even though deubiquitinase activity was inactivated by IAA, we noted that in WT TDP-43, there is only a faint steady state band at the expected location of monoubiquitinated (or SUMOylated) HA.TDP-43  is consistent with the existence of additional lysine residues on TDP-43 suitable for ubiquitin or ubiquitin-like modifier conjugation during stress, as already reported in global proteomic studies We asked whether the decrease in polymerization of TDP-43 with ubiquitination site mutation might correspond with a resistance to oxidative polymerization of the mutant protein in response to oxidative stress  that target RRM1 of TDP-43 during pathogenesis. If inhibition of these enzymes can be achieved, disease course may be altered. Evidence further suggests that ubiquitin dynamics on RRM1 of TDP-43 may also coordinate its participation in aggregates with oxidized polymers. This data suggests an intriguing role for ubiquitination of TDP-43 RRM1 in its participation in stress granules and paraspeckles, with potential effects on nucleation, assembly or disassembly, and thereby would respectively affect translation and transcription-coupled splicing in response to cellular conditions inducing such ubiquitination. Precedent for a role of ubiquitination of an RNA-binding protein affecting translation in neurons at dendrites with effects on learning and memory was recently published by the Kandel group This study presents significant advances in the characterization of TDP-43-associated PTMs and potential effects of TDP-43 PTMs on phenotypic changes in proteins with RRM and RGG RNA-binding domains. The four sites of direct ubiquitin conjugation to TDP-S6 at residues K102, K114, K145, and K181 are conserved with the RRM1 fold in TDP-43 homologs, consistent with a yet unappreciated role or roles in TDP-43 function. The TDP-S6 target aggregate proteome, which accumulates non-degradation-associated K63 and to a lesser extent K48 ubiquitin linkages Ubiquitin conjugate accumulation, insolubility of TDP-43 in aggregates or inclusions, and cleavage fragments of TDP-43 have been found to occur during the pathogenesis of TDP-43 proteinopathies including ALS and FTLD, as well as in diseases not previously associated, including Alzheimer disease, Machado-Joseph disease, and Parkinson disease Figure S1Protein groups in the background detergent insoluble proteome and those significantly changed in the TDP-43 and TDP-S6 target aggregate proteomes. Protein categories defined by DAVID version 6.7 were graphed as a percentage of the population of the 585 proteins identified in (TIF)Click here for additional data file.Figure S2Costaining of Nuclear RNA-binding proteins with TDP-S6. HA.TDP-S6 (red) colocalization with nuclear PSF (A), arrow, or RBM14 (B) in distinct subnuclear structures in representative cells. PSF and RBM14 staining are shown in green. Scale bars, 10 µm.(TIF)Click here for additional data file.Figure S3Phospho Ser409/Ser410 TDP-43 decreases in the insoluble fraction with ubiquitination site removal via mutation of lysine to arginine. Western blot of the same membrane for HA.TDP-43  and phospho Ser409/Ser410 of TDP-43 (right panel).(TIF)Click here for additional data file.Figure S4Quadruple TDP-43 ubiquitin site mutantis resistant to oligomerization following oxidative or proteolytic stress in HeLa cells. Detergent-fractionated HeLa cell extracts from cells transfected with equal amounts of WT or 4R TDP-43 and treated as indicated for 1 h with sodium arsenite or 6 h with MG-132 plus IU1 were immunoblotted for the HA tag. †, the expected position of monoubiquitinated TDP-43 is indicated. Western blot signal for calnexin  is provided as a loading control.(TIF)Click here for additional data file.Table S1Quantification of 585 proteins in both experimental replicates. All proteins quantified by light/heavy peptide ratio in both experimental replicates  are listed. Standard deviation across all quantified peptides of each protein is given along with the number of quantified peptides, and average signal to noise ratio of the quantified peptides for each of six light/heavy mixtures. Mean normalization factors for recentering population data are given on the darkened header row above each of the six log2(light/heavy) data columns.(XLS)Click here for additional data file.Table S2All proteins and peptides identified by LC-MS/MS of mock, TDP-43, or TDP-S6 transfected detergent insoluble fractions. Total number of spectral counts (SC), the number of unique peptides assigned on each protein, sequencing coverage (%), the mass error measured in Orbitrap (deltaMass), the SEQUEST matching scores (XCorr and deltaCn), the link to assigned spectra, and where calculated, extracted ion current intensity expressed as signal-to-noise ratio for paired light and heavy peptides in mixtures are listed. The labeled heavier K or R residues are marked .(ZIP)Click here for additional data file.Table S3Lysine methylation site peptides identified and quantified in the TDP-43 and TDP-S6 insoluble proteome of HEK-293 cells. Histone and elongation factor Tu methylation sites were identified without any quantified change due to TDP-43 or TDP-S6 overexpression. Note that H3 methylation sites are numbered on the mature histone without Met1. Ion suppression affected the four WT TDP-43 histone H3 XIC intensities in a single LC-MS/MS run relative to the comparable TDP-S6 and Mock runs. This suggests that extra caution must be taken when quantifying peptides without an internal standard.(XLS)Click here for additional data file.Table S4Identification of methylated and ubiquitinated proteins and peptides. All peptides identified by MS/MS to harbor PTMs in this study are listed with the mass error measured in Orbitrap (deltaMass), the SEQUEST matching scores (XCorr and deltaCn) and matched ion count. The labeled K or R residues are marked as follows: dimethyl-Lys (@), methyl-Lys ∧, dimethyl-Arg (#), Lys-epsilon-amino-GG .(XLS)Click here for additional data file.Table S5Comparison of pseudo-GG peptide MS/MS spectra obtained by LC-MS/MS of IAA-alkylated GST-TDP-43 and bona fide TDP-43 or TDP-S6 GG peptide spectra. Sequest matched ions are shown on MS/MS spectra for pseudo-GG peptides obtained for purified GST-TDP-43. Where available to the right, representative lysine-GG peptide spectra sequenced from the urea-solubilized detergent insoluble fraction of TDP-S6 overexpressing HEK-293 cells  are also shown to the right. The K145-GG peptide mascot spectrum and matched ions table are also inset to the right.(XLS)Click here for additional data file.


Interleukin-4 (IL4) is a secreted immunoregulatory cytokine critically involved in host protection from parasitic helminths . ReasoniMus musculus musculus and Mus musculus castaneus, which happen to differ at 5 residues (including three at positively selected sites) in and adjacent to the site 1 epitope that binds the IL4Rα subunit shared by the Type I and Type II IL4 receptors. We show that this intra-species variation affects the ability of IL4 neither to bind IL4 receptor alpha (IL4Rα) nor to signal biological responses through its Type I receptor.This analysis revealed evidence of diversifying selection at 15 residues, clustered in epitopes responsible for IL4 binding to its Type I and Type II receptors. Such a striking signature of selective pressure suggested either recurrent episodes of pathogen antagonism or ligand/receptor co-evolution. To test the latter possibility, we performed detailed functional analysis of IL4 allotypes expressed by Our results -- reminiscent of clustered positively selected sites revealing functionally important residues at host-virus interaction interfaces -- are consistent with IL4 having evolved to avoid recurrent pathogen antagonism, while maintaining the capacity to bind and signal through its cognate receptor. This work exposes what may be a general feature of evolutionary conflicts fought by pathogen antagonists at host protein-protein interaction interfaces involved in immune signaling: the emergence of receptor-binding ligand epitopes capable of buffering amino acid variation. Viruses and bacteria have evolved survival strategies based on antagonism of host immunoregulatory molecules . CytokinIn vivo administration of antibodies or recombinant cytokines that raise IL4 levels diminish helminth infection; conversely, lowering IL4 levels increases helminth infection [Interleukin-4 (IL4) is a 17 kDa monomeric glycoprotein of the Type I hematopoietin superfamily secreted by T helper 2 (Th2) cells, NK T cells, mast cells and basophils -9. Its pnfection ,12. Micenfection ,13. IL4Rnfection . This coIL4 promoter, leading to the fixation of promoter sequence variants that differentially bind the transcription factor NFAT and consequently have distinct thresholds for transcriptional triggering [As a key host molecule triggered by and required for the control of parasitic worms , IL4 mayiggering . High lePrevious studies have remarked on the rapid evolution of IL4 and IL4Rα -18. To eIL4 coding sequence from 28 eutherian mammalian lineages. The 'Model Selection tool' at the online HyphY server (see methods) identified the HKY85 model as the most appropriate using the AIC criterion (p <0.07). A maximum-likelihood phylogeny  or permit diversifying selection (M8), we found that models permitting diversifying selection fit IL4 evolution significantly better than those that disallow it (Table -4) consistent with previous reports [p > 0.5, Table When we compared the likelihood of it Table . In the  reports -18,25. WOur analysis identifies 15 codon positions in which there is significant evidence of diversifying selection   and M. castaneus (strain CAST/Ei) and discovered 5 amino acid sequence changes between them   Figure . StrikinM. musculus IL4Rα extracellular domain [To test whether naturally arising variation in site 1 residues is functionally relevant with respect to IL4Rα interactions, we expressed and purified recombinant BALB/c and CAST/Ei IL4 for biophysical and functional studies. To determine the affinity of IL4Rα for BALB/c and CAST/Ei IL4, we measured surface plasmon resonance (SPR) using a Biacore apparatus. Purified r domain  was immor domain ,13.Next, we sought to determine whether, despite sharing similar binding affinity for IL4Rα, BALB/c and CAST/Ei IL4 might differ in their ability to signal IL4-dependent biological responses. Mouse B and T cells fail to express IL13α1 and therefore express only the Type I IL4 receptor , ensurinM. musculus and M. castaneus  domain of IL4Rα ,38. The We propose instead that genetic conflict  is most consistent with such evolutionary signatures. We have found that IL4 has evolved under strong and recurrent diversifying selection focused at 15 positions (with a NEB criteria). Twelve of these fall in or near the site 1 epitope comprising the IL4Rα binding interface. Two more positively selected residues form a second cluster falling in or near the site 3 IL13Rα1-binding epitope used by the Type II IL4 receptor. From an evolutionary perspective the interaction interface of IL4 with its receptor is an ideal antagonist target as it is likely to be functionally constrained, necessitating escape from antagonism to require coordinated changes in both IL4 and its receptor. It is tempting to speculate that pathogen antagonism has specifically targeted IL4 complexed with the non-hematopoietic Type II IL4 receptor (that lacks γc), as would be the case for gut and lung resident helminths confronting Type II IL4 receptor-dependent expulsatory effector mechanisms triggered by IL4 activation of intestinal and lung epithelia ,40.A functional comparison of two intra-specific murine IL4 proteins allowed a direct evaluation of the functional consequences of variation at positively selected codon positions without the confounding changes that may occur due to epistasis over long evolutionary divergences . Our discovery that genetic variation at three such positively selected residues in murine IL4 is functionally neutral with respect to both IL4Rα binding and signaling suggests that the IL4 site 1 epitope displays a remarkable degree of evolutionary flexibility to accommodate changes in sequence to escape (inferred) antagonism by parasite-encoded proteins while maintaining interaction with its receptor.Approximately 80% of the IL4Rα binding energy for IL4 comes from interactions with a core of 2 residues Figure  and 6. CWe posit that the striking signature of diversifying selection coupled with the absence of a functional consequence on the IL4:IL4Rα interaction provides strong evidence for the existence of a pathogen antagonist that shapes IL4 evolution. A precedent for our hypothesis comes from a case study of Protein Kinase R (PKR) and its highly conserved substrate eukaryotic translation initiation factor 2 alpha (eIF2α). Pathogen mimics of eIF2α can antagonize the eIF2α:PKR interaction. A key to escape this antagonism may be the evolution of a highly flexible PKR epitope responsible for recognition of eIF2α ,37. Simihttp://www.datamonkey.org), we first identified the appropriate nucleotide substitution model, in this instance HKY85. Maximum likelihood trees were constructed and bootstrap analyses performed using the PhyML program [We used TBLASTN and BLASTN searches  using ei program ,48 and e program . Both mo program . This nuhttp://www.datamonkey.org[We tested the dataset for evidence of recombination using two programs in the HyPhy suite  (http://onkey.org): GARD aonkey.org. Neitheronkey.org. To idenBALB/c and CAST/Ei IL4 cDNAs were prepared from Th2 cells from spleen and lymph nodes of BALB/c and CAST/Ei mice as described . Total R1HIK), type I (3BPL) and type II IL4 receptor complexes (3BPN) using PyMol  on World Wide Web http://www.pymol.org).Polymorphic and positively selected residues were mapped onto the crystal structures of human free IL4  and a combination of rabbit and guinea pig complement. As determined by FACS analysis, B cell purity from BALB/c and CAST/Ei spleens was typically 85% and 66%, respectively. CD4 T cell-enriched splenocytes were prepared by complement-mediated lysis using anti-CD8 , anti-HSA , anti-MHC class II  and a combination of rabbit and guinea pig complement. As determined by FACS analysis, T cell purity from BALB/c and CAST/Ei spleens was typically >91%.B cells were distributed to 24 well plates containing graded concentrations of recombinant BALB/c or CAST/Ei IL4 and incubated at 37°C for 16 hours prior to staining with PE-conjugated anti-mouse CD23 Ab  and flow cytometric analysis.5 B cell-enriched splenocytes and 50 ng/ml of LPS (B cells) or 1 × 105 CD4 T cell-enriched splenocytes (T cells) in 200 ul RPMI 1640 medium supplemented with 10% FCS, 50 μM β-mercaptoethanol, 2 mM L-glutamine, and 100 U/ml penicillin and streptomycin. AlamarBlue  was added at 24 hr and at 48 hr the extent of its reduction was determined by comparing absorption of control and test culture media at 570 nm and 600 nm. AlamarBlue reduction (AR570) was calculated as: AR570 = A570 - A600 where A570 and A600 are sample absorbances minus a media blank.Serially diluted recombinant BALB/c or CAST/Ei IL4 was added to 96 well plates containing either 1 × 10IL2: interleukin-2; IL4: interleukin-4; IL5: interleukin-5; IL7: interleukin-7; IL13: interleukin-13; IL15: interleukin-15; IL21: interleukin-21; IL4Rα: interleukin-4 receptor alpha; IL13Rα1: interleukin-13 receptor alpha 1; Th2: T helper 2 cells; MHC; major histocompatibility complex; dN: nonsynonymous substitutions per site; dS: synonymous substitutions per site; TGFβ: Transforming growth factor beta; γc: common gamma chain; GMCSF: granulocyte macrophage colony stimulating factor; PKR: Protein kinase R; eIF2α: Eukaryotic translation initiation factor 2 alpha.MK performed all the immunological analyses and participated in the collection and analysis of the biophysical data. JAK performed sequence alignment and evolutionary analysis. LC isolated, cloned, sequenced and assembled rodent IL4 genomic DNA. YZ produced, purified and characterized recombinant IL4. SB carried out the collection and analysis of the biophysical data. TM created and analyzed the structural models. HSM participated in the study design, carried out the evolutionary analysis and co-wrote the manuscript. MB conceived of the study, and participated in its design and coordination and co-wrote the manuscript. All authors read and approved the final manuscript.IL4 polymorphisms between BALB/c and CAST/Ei.Click here for fileKinetic profiles of surface plasmon resonance depicting the binding of IL4 and IL4Rα.Click here for fileIL4 alignment from 28 eutherian mammals in .phy format.Click here for fileIL4 alignment from 16 primates in .phy format.Click here for fileStages of purification of recombinant IL4 purification from insect cell supernatant as measured by functional bioassay.Click here for fileIL4 yield and fold purification.Click here for fileMonoclonal anti-IL4 antibody BVD6 binds equivalently to recombinant BALB and CAST IL4.Click here for file


Effects of the humidity were studied at room temperature (18–20 °C) with relative humidity 33%, 75%, and 100%. Effects of the surfaces were observed at −20 °C (relative humidity 36%) to enable close monitoring with slower crystal growth. The nucleation time of ibuprofen was faster at high humidity conditions probably due to the local formation of the unfavorable ibuprofen melt/water interface. The crystal morphologies of ibuprofen were governed by the nature of the surfaces, and they could be associated with the growth kinetics by the Avrami equation. The current study demonstrated the effective control of the melt crystallization of ibuprofen through the melt/atmosphere and melt/surface interfaces.Melt crystallization of ibuprofen was studied to understand the effects of humidity and surfaces. The molecular self-assembly during the amorphous-to-crystal transformation was examined in terms of the nucleation and growth of the crystals. The crystallization was on Al, Au, and self-assembled monolayers with –CH Crystallization is a process where self-assembly is initiated at a molecular level during nucleation. The self-assembly of the molecules continues as crystals grow, obeying specific assembly rules defined by the various molecular interactions. The assembly rules are ultimately translated into the crystallographic structures. Often, molecules could form several crystallographic structures to show multiple metastable and stable phases, a phenomenon known as polymorphism . Also, tControlled crystallization of active pharmaceutical ingredients could affect their bioavailability, processability, and stability. Bioavailability is usually a function of solubility, which can be modulated by the molecular packing ,6. ProceIn the present study, melt crystallization of ibuprofen (IBU) was investigated. Melt crystallization is essentially an amorphous-to-crystal transformation governed by supercooling, defined as the difference between the melting and crystallization temperatures. During typical melt crystallization, two existing interfaces are melt/surface and melt/atmosphere. Herein, we studied the effects of various surfaces and humidity to alter these interfaces and ultimately control the molecular assembly process of IBU.Differential scanning calorimetry (DSC) was performed to confirm the temperature range that could be utilized for the crystallization of IBU. The two limiting points that defined the temperature range were taken as the glass transition temperature and the melting point of IBU . The for3 functional groups . Each result was the average of eight independent experiments. On all surfaces, the observation time of the initial nucleation was inversely proportional to RH, i.e., the nucleation time was in the order, RH 100% < 75% < 33%. Also, the nucleation time was similar for all surfaces at RH 100%, and it was relatively shorter on metal surfaces and longer on SAM surfaces  at RH 75% and 33%. Overall, we could conclude that humidity, probably through the adsorbed water molecules at the melt/atmosphere interface, acted on the IBU melts to initiate the molecular assembly and start the nucleation process. Although the exact mechanism through which the water molecules affected the metastable IBU melts is not clear at this point, it could be through the increased instability. The adsorbed water molecules on the metastable IBU melts would replace some of the existing IBU melt/air interface with the melt/water interface. The new interface is most likely less favorable since water is immiscible with IBU melt, and it is a very poor solvent of IBU (solubility 0.011 mg/mL at 25 °C and pH 7.4) [The effects of humidity on IBU melt crystallization were monitored in terms of nucleation, crystallinity, crystal phase, and morphology. First, the effect on the nucleation was summarized in  pH 7.4) ,16. Therca. 75 °C–78 °C, suggesting that the obtained crystals were of the same crystal polymorph.  This was also confirmed by powder X-ray diffraction (PXRD) patterns, as the characteristic diffraction peaks were identical among the purchased powders and all the recrystallized samples on all surfaces. Representative results were shown in 3 along with the originally purchased IBU powders, and the results were the same for the IBU recrystallized under all the other conditions. Finally, the effect of humidity on the IBU crystal morphology was negligible. Again, the representative case was shown for the IBU recrystallized on SAM–CH3  connected through a rubber vacuum tube to a glass desiccator  of the controlled RH. Within a few minutes of initial crystal formation, the crystal growth appeared to complete as shown in the bottom pictures  From these results, we could conclude that the effects of humidity was largely limited to the nucleation of IBU crystals, and the crystallinity, crystal phase, and morphology of IBU were on the whole invariant with the change of relative humidity.Second, the effects of humidity on the crystallinity and crystal phase (or polymorph) of IBU were minimal . The mel SAM–CH3 . Top pic SAM–CH3  were takpictures . The morTo study the effects of the various surfaces, the melt crystallization of IBU was performed at −20 °C, rather than room temperature as was in the pervious section. This condition was chosen to make it easy to monitor the growth behavior on the various surfaces because it ensured a relatively slower crystal growth after nucleation, probably due to the combined effects of the low temperature and reduced humidity. The very low atmospheric water content also made it possible to examine the effects of surfaces with a minimal influence of humidity.  compared to 4.75 g/kg dry air at 20 °C and RH 33% ). Also, In this experiment, multiple IBU melts on the same type of surfaces were placed in the −20 °C freezer in the beginning, and each sample was taken out at a given crystallization time to microscopically observe the crystalline area out of the entire melt area. Then, the crystallization behavior was analyzed through the Avrami equation:Xc(t) is the relative crystallinity at time t, n is the Avrami exponent, and K is the rate constant. Since the Avrami equation is based on the spatial profile of molecular assembly on the crystal surfaces, the Avrami-type analysis of the crystallization kinetics provides important information on the assembly and the resulting crystal morphology [where rphology ,18.Xc. This analysis clearly revealed that the Al and Au surfaces exhibited completely different behavior from the SAM surfaces . Also, its recrystallization behavior was studied on Al, Au, and three different self-assembled monolayers (SAMs). Al crucibles  were utilized for all surfaces to make their roughness uniform. Al surface was used after successively cleaning with acetone , ethanol , and deionized water . Au surface was prepared on the cleaned Al by sputter-coating Au  using a Cressington Sputter Coater 108  [3, –OH, and –COOH functional groups  were prepared by treating the Au surfaces in 1.0 mM (ethanol) solutions of 1-decanethiol , 11-mercapto-1-undecanol , and 11-mercaptoundecanoic acid , respectively [2  before further usage.IBU was purchased from Sigma (>98%). Its thermal behavior was studied using differential scanning calorimetry . The IBU samples were then subject to the environments of controlled temperature and humidity for further observation of recrystallization. Recrystallization temperature was −70 °C, −20 °C, 0 °C, or room temperature (ca. 18–22 °C). The −70 °C freezer was a DF8514 from Ilshin Biobase , and the −20 °C and 0 °C conditions were obtained using a R-A104GDA from LG Electronics . The relative humidity for the room temperature experiments was controlled as 33%, 75%, and 100% by using saturated MgCl2(aq) , saturated NaCl(aq) , and deionized water [Crystallization of IBU was performed by first preparing IBU melt and then recrystallizing the melt at appropriate conditions. The IBU melt was prepared on the various surfaces by melting the purchased IBU powders (2–3 mg) using a hot stage . Temperature of the hot stage was increased from 30 °C to 100 °C (10 °C/min), and it was cooled to 30 °C (ed water .λ = 1.5406 Å) at 30 kV and 10 mA was used to scan the 2θ region of 5°–40° with a scanning rate of 1°/min. DSC was done again using a DSC821e (Mettler-Toledo) with a scanning rate of 10 °C/min.Morphology of the recrystallized IBU was observed with optical microscopy  in the reflectance mode under cross polarization. The crystalline nature of the recrystallized IBU was also analyzed by powder X-ray diffraction (PXRD) and DSC. PXRD was performed using a D2 Phaser diffractometer (Bruker AXS). CuKα radiation (In summary, the effects of humidity and surfaces were studied on the melt crystallization of ibuprofen to enable the controlled crystallization through melt/atmosphere and melt/surface interfaces. The humidity was effective in controlling the nucleation time. High humidity influenced the initiation of crystal formation probably through the local development of unfavorable melt/water interfaces. The humidity could control the IBU nucleation independently with minimal effects on the crystallinity, polymorphs, and crystal morphology. The examined surfaces, which could be broadly categorized as high-energy metal and functionalized SAM surfaces, affected mostly the morphology of the IBU crystals, and the crystal morphology was in agreement with the Avrami analysis of the crystal growth. Our results demonstrated that the melt/atmosphere and melt/surface interfaces could be effectively utilized to control the melt crystallization without any additional additives.


Interferon alpha (IFNα) has immune stimulatory actions implicated in its pulmonary toxicities. We describe deterioration of idiopathic pulmonary fibrosis (IPF) associated with IFNα treatment for chronic hepatitis C in a 58 year old woman culminating in a fatal suspected acute exacerbation of IPF (AE-IPF). Caution should be exercised in the use of IFNα in subjects with concomitant IPF given its known immunostimulatory effects and possible role in this suspected AE-IPF. Pulmonary toxicity is a recognised complication of interferon alpha (IFNα), thought to be related to its immunostimulatory effects. IFNα has been shown to influence the immune system along multiple pathways including augmentation of proinflammatory and profibrotic cytokines -related Child-Pugh A liver cirrhosis developed an oesophageal variceal bleed. Hepatitis C was associated with moderate inflammatory activity (Metavir score A3F4), previous hepatic decompensation with ascites and F3 oesophageal varices treated with prophylactic ligation. She had a history of tobacco-related chronic obstructive pulmonary disease (COPD). Eighteen months before admission, high-resolution computed tomography (HRCT) of the chest demonstrated lower zone predominant subpleural interstitial fibrosis with honeycombing consistent with UIP/IPF  (see Table Pseudomonas aeruginosa and non-multiresistant methicillin-resistant Staphylococcus aureus (nmMRSA). On day 6, intravenous hydrocortisone was commenced. On Day 7, bronchoalveolar lavage was performed and specimens again grew nmMRSA, however tested negative for all other pathogens including Pneumocystis jiroveci (carinii). Transthoracic echocardiogram demonstrated normal left ventricular function. On day 10, there was further deterioration in oxygenation and she required high flow oxygen via mask to achieve oxygen saturations of 90%. Pulse intravenous methylprednisolone was commenced however her respiratory status continued to deteriorate. Escalation of therapy including endotracheal intubation was thought to be futile and she died on day 14.On admission, she received intravenous octreotide, prophylactic ceftriaxone and endoscopic variceal banding. On day 3, she developed progressive hypoxaemia, requiring high flow nasal prong oxygen to achieve oxyhaemoglobin saturations of 96%. She was febrile to 38.3°C. HRCT of the chest demonstrated diffuse ground-glass change superimposed on markedly deteriorated bilateral pulmonary fibrosis with honeycomb changes  and radiologic (within 2 months) evidence of deterioration. The 6% decline in FVC was felt to be within the limits of variability, although recent data have shown that FVC decline of >5% predicts a doubling of one year mortality  and subsequent bronchoscopy (performed because of progressive hypoxia) did not reculture Pseudomonas. Furthermore, her clinical course was marked by relentlessly progressive, antibiotic-unresponsive, hypoxic respiratory failure without evidence of sepsis, features much more consistent with AE-IPF than nmMRSA pneumonia. While exclusion of infection forms part of Collard’s proposed criteria for definition of AE-IPF (Collard et al. The acute respiratory decline during the described admission was suspected to be secondary to AE-IPF. Although Given that IFNα is now part of standard therapy for chronic HCV infection and the rising incidence of UIP/IPF in Western countries (Navaratnam et al.


Fast as possible gait velocity, timed-up-and-go time, 180°turn duration, and steps to turn 180°were impaired in PD compared to controls (P < 0.05) and did not improve following either intervention (P > 0.05). Preferred pace gait velocity and timing of yaw rotation onset of body segments  during 180°turns were not different in PD (P > 0.05) and did not change following either intervention. No improvements in gait or turning occurred after five days of rotating treadmill training, compared to one day. The rotating treadmill is not recommended for short-term rehabilitation of impaired in-place turning in the general PD population.Since turning is often impaired in Parkinson's disease (PD) and may lead to falls, it is important to develop targeted treatment strategies for turning. We determined the effects of rotating treadmill training on turning in individuals with PD. This randomized controlled study evaluated 180°in-place turns, functional turning (timed-up-and-go), and gait velocity before and after 15 minutes of rotating treadmill training or stepping in place in 26 people with PD and 27 age-matched controls. A subset of participants with PD  Parkinson's disease (PD) is a progressive neurodegenerative disease resulting in a variety of motor symptoms. Individuals with PD frequently experience difficulty with gait and turning, with more than half reporting difficulty turning –3 which Stepping in place on the rotating treadmill has been recommended as a possible rehabilitation option for those with PD . After sImmediately after stepping in place on a rotating disk for a total of 15 minutes on one day, turning performance was improved in two people with PD on medication who also experienced freezing of gait during turns [We recruited 29 participants from the Movement Disorders Center at Washington University School of Medicine who had been diagnosed with idiopathic Parkinson's disease according to standard criteria . We alson = 3) returned for an additional five consecutive days of training and testing. Training and testing sessions were identical for the one-day and five-day portions of the study. Surgical skin pens were used to ensure consistent placement of reflective markers across days. The Movement Disorders Society Unified Parkinson's Disease Rating Scale motor subscale (MDS-UPDRS-III) was given to all participants prior to testing to assess movement impairments [All participants with and without PD completed testing on one day, and a small subset of participants with PD  to an intervention condition (rotating treadmill (Train) or stepping in place (Step)). Those in the Train condition were asked to step in place on the perimeter of a rotating disk built into the floor  as it rotated approximately 45°/sec either clockwise or counterclockwise. The direction of treadmill rotation was selected for each participant to train turns in the worse direction , where clockwise rotation trained left turns and counterclockwise rotation trained right turns. For the five-day training sessions, right turns were trained for all participants. Participants walked on the rotating treadmill for a total of 15 minutes, divided into 5-minute blocks with interspersed 5-minute rest periods . Those iTurning and walking were assessed in two separate blocks, once before (PRE) and once after (POST) the assigned intervention. In each testing block, we examined gait, functional turning while walking, and in-place turns of 180°. Gait was assessed using a 4.8 m GAITRite instrumented walkway  to determine if the interventions had any effects on gait. The GAITRite calculated gait velocity in six walking trials in each block: three at a participant's preferred pace and three as fast as possible. Functional turning ability was assessed using the timed-up-and-go (TUG) test where participants rise from a chair, walk three meters, turn 180°, walk three meters back to the chair, and sit down. Participants completed the TUG six times in each block, with instruction to turn left or right on each trial . The time to complete this task was measured using a stopwatch. To assess in-place turning, we instructed participants to stand in the middle of the room and turn 180° to the right or left, 10 times in each direction (randomized), to face the wall behind them. Kinematic data were recorded at 100 Hz during these turns using an eight-camera 3-D motion capture system . Thirty-four reflective markers were placed on each participant: four on the head , seven on the trunk , five on the pelvis , and nine on each leg . The Motion Monitor software  was used to create body segment models for the head, trunk, pelvis, and feet based on marker positions and to export segment rotation data. Custom written Matlab programs were used  to determine rotation onsets and offsets for the head, trunk, pelvis, and feet body segments, using a 5° yaw plane rotation threshold criterion. The onset of rotation of the foot used for the first step was designated as the turn onset, and the offset of rotation of the foot used for the last step was designated as the turn offset. To quantify body segment rotation sequences during turn initiation, we examined the timing of the onsets of the head (HTO), trunk (TTO), and pelvis (PTO) relative to turn onset. All onset times were expressed as a percentage of the first gait cycle of the turn. To assess overall turn performance, we also determined the number of steps used to complete each turn and turn duration. Kinematic, TUG, and gait velocity data were averaged across trials within each participant for the PRE block and for the POST block.Our primary variables of interest were functional turning ability (TUG), 180° in-place turn duration, and normalized rotation onset of the head, trunk, and pelvis relative to turn onset, to quantify timing of body segment rotations during turn initiation. Secondarily, we looked at number of steps to turn 180°. We also examined velocity during preferred pace and fast as possible gait to determine if the interventions, specifically the rotating treadmill, impacted gait. In the Train groups, we trained the worse turn direction, and the other turn direction was untrained. In order to similarly compare turn performance for the Step groups, we designated the worse turn direction and the better turn direction based on turn durations. For statistical comparisons across groups, the trained direction of the Train group was compared with the worse direction of the Step group, and the untrained direction of the Train group was compared with the better direction of the Step group. We were primarily interested in the trained direction, as turns in this direction were expected to be affected by rotating treadmill training. Separate RM-ANOVAs were run  for our primary variables of interest for the trained/worse directions. We also ran RM-ANOVAs for step number and gait velocity. Only 3 participants with PD completed the 5-day training component, so formal statistical tests were not used. However, we examined POST data from Day 1 and Day 5 for primary variables of interest, step number, and gait velocity to determine trends. Secondarily, we also evaluated variables similarly for the untrained/better directions.P = 0.503). The PD Train and Step groups had similar ages, MDS-UPDRS-III scores, and disease durations (P > 0.05). Similar ages and MDS-UPDRS-III scores were also seen across CN Train and Step groups (P > 0.05). There were no significant differences in any variables at baseline for turns in the trained/worse direction or turns in the untrained/better direction (P > 0.05). There were also no significant differences between those with left as the trained/worse turn direction and those with right as the trained/worse direction (P > 0.05), so data were combined for analysis.The PD and CN groups did not differ significantly in age (P = 0.12) or Group  = 1.40, P = 0.24), nor any significant interaction effects (P > 0.05) for preferred pace gait velocity (P = 0.06), with individuals tending to demonstrate higher preferred pace gait velocity POST intervention. For fast as possible gait velocity (P = 0.62) or Condition  = 3.28, P = 0.08), nor any significant interaction effects (P > 0.05). There was a significant effect of Group  = 4.77, P = 0.034), with PD walking slower than CN. GAITRite data for two participants  were lost due to hard drive failure, but all remaining data for these participants was included in analyses. The mean velocity data are shown for PD and controls before and after the assigned intervention in velocity . There wvelocity , there wP = 0.58) or Condition  = 3.43, P = 0.070), nor any significant interactions (P > 0.05). There was a significant Group effect  = 5.25, P = 0.026), with PD requiring more time to complete the TUG, turning to the trained/worse direction, compared to controls. Results were similar for the untrained/better direction.For TUG where the turn component was in the trained/worse direction , there wP = 0.62) or Condition  = 0.99, P = 0.33), nor any significant interactions (P > 0.05). There was a significant Group effect  = 15.95, P < 0.001), with PD turning slower than CN. For the untrained/better direction, results were similar. For 180° turn duration in the trained/worse direction , there wP = 0.15) or Condition  = 1.33, P = 0.25), nor any significant interactions (P > 0.05). There was a significant Group effect  = 13.71, P = 0.001), with PD requiring more steps to turn. Similar results were seen for the untrained/better direction. For steps to turn 180° in the trained/worse direction , there wP = 0.30), Condition  = 0.60, P = 0.62), or Group  = 1.48, P = 0.23), nor any significant interactions (P > 0.05). For body segment  rotation onsets relative to turn onset for turns in the trained/worse direction, there were no significant effects of Time  = 1.26, A small subset of the original group of participants returned for 5 consecutive days of rotating treadmill training. All three individuals who returned for five consecutive days of training were able to tolerate the training program. On average, gait velocity, TUG, turn duration, steps to turn, and body segment rotation onsets relative to turn onset were very similar following a single session of training (Day 1 POST), compared to after five sessions of training (Day 5 POST) in either the trained or untrained direction. Difficulty with turning is common in individuals with PD, and the development of therapeutic approaches that target turn deficits might reduce the occurrence of falls and serious injuries in these individuals. As a result, it is important to evaluate potential treatment strategies in individuals with PD who demonstrate a range of turning ability and might benefit from these treatment options.Contrary to our initial hypotheses, we did not see improvements in turning in those with PD following one day or five consecutive days of rotating treadmill training. For most turning variables, group effects indicated turning was impaired in those with PD ON medication, compared to controls, as has been previously reported –10. Interestingly, the body segment rotation onset patterns we observed were similar between those with PD and controls. All groups initiated turns with the head, followed by the trunk, pelvis, and foot. Controls display this top-down rotation sequence during turns while walking , 18–24, Turning and gait velocity did not systematically worsen in any intervention group from PRE to POST. Also, participants were permitted to rest as often as necessary during testing and had mandatory five-minute rests between the five-minute blocks of treadmill training. As a result, we think our results were likely not confounded by fatigue. Further, we likely tested a higher-functioning group of people with PD than some prior studies, since preferred pace gait velocity did not differ between PD and controls. Despite smaller differences in gait performance, we detected distinct impairments in turn performance compared to controls, confirming turning impairments can be present in those with relatively normal gait . This hiThe most notable difference between the present study and the previous rotating treadmill study  is the fAnother limitation of the study is that the sessions were of relatively low intensity and were few in number. It may be that more intense rotating treadmill training sessions or increased number of sessions may result in detectable changes, as previous traditional treadmill studies report improvements after completion of 10–28 training sessions of 20–30 minutes each , 31. HowFifteen minutes of rotating treadmill training alone on one day or for five consecutive days did not affect turn performance in PD. As a result, this type of training is unlikely to serve as an effective short-term rehabilitation strategy for many individuals with PD. However, future studies should determine whether rotating treadmill training may improve turning impairments with longer training paradigms or when combined with other external cues, as well as assess its effects on performance of turns while walking in addition to the in-place turning studied here.


Since the sensors used in the new calibration process are already installed in the commercial incubator, no additional hardware is necessary; and the calibration necessity can be diagnosed in real time without the presence of technical professionals in the neonatal intensive care unit (NICU). Experimental tests involving the aforementioned calibration system are carried out in a commercial incubator in order to validate the proposal.Measurement and diagnostic systems based on electronic sensors have been increasingly essential in the standardization of hospital equipment. The technical standard IEC  60601-2-19 establishes requirements for neonatal incubators and specifies the calibration procedure and validation tests for such devices using sensors systems. This paper proposes a new procedure based on an inferential neural network to evaluate and calibrate a neonatal incubator. The proposal presents significant advantages over the standard calibration process,  Within this context, a neonatal incubator helps in taking care of the health of newborns . A neonaA neonatal incubator is one of the most important pieces of neonatal intensive care unit (NICU) equipment ,4. For eAs with any other electro-medical equipment, a neonatal incubator must be calibrated periodically, because its malfunction may cause serious damage to the newborn's health or even lead to the newborn's death. The technical standard IEC 60601-2-19 establishes operating specifications for neonatal incubators, so that a safe environment can be offered for newborns . Such spIn order to perform the aforementioned tests, the incubator is removed from service, and a calibration system is installed, so that temperature and humidity data are provided for a standardized calibration procedure. Considering that it is necessary to turn off the incubator to run the tests and, also, that the number of available incubators in neonatal centers is limited in most Brazilian hospitals, a maintenance strategy that minimizes the incubator down time will prove to be very useful.et al. [In this work, a literature survey is carried out by considering the published studies addressing the identification and control of the dynamics involving temperature and humidity in neonatal incubators. Zermani et al.  use geneet al. . Such coet al. [et al. [Zermani et al.  design a [et al. , the resAmer and Al-Aubidy  declaredANNs are massively-distributed parallel structures, consisting of simple processing units known as neurons, which have a natural propensity for storing experimental knowledge and making it available for use . Among tet al. [In the literature, several studies report applications of ANNs as a potential technique for identification of the dynamical behavior for temperature and humidity inside controlled environments. Although these next briefly described works are not directly related to neonatal incubators, there is some similarity with the scope of this paper. Martnez et al.  presenteet al. [et al. [i.e., temperature or relative humidity. The last model takes into account both variables as outputs at the same time. Various aspects described in the aforementioned papers may be considered in the proposed study.In another paper, Ferreira et al.  develope [et al.  in orderThe present work introduces a new method for calibrating neonatal incubators based on multilayer perceptron (MLP) neural network models, with a reduced number of sensors if compared with that used in the traditional calibration procedure. The basic idea is the use of an ANN to infer the temperature and humidity of the extra sensors positioned inside the equipment according to standard IEC 60601-2-19 by using only the sensors included in the commercial neonatal incubators. The proposed method has four significant advantages over the standard calibration process: (i) while the standard technique requires five temperature sensors and one humidity sensor, the proposed method dramatically reduces the number of sensors to one for temperature and one for humidity; (ii) the calibration process works with the incubator under operation; (iii) no hardware calibration is necessary, and the sensors used in the new process are already installed in the traditional incubator; and (iv) the necessity for calibration is diagnosed in real time, and the presence of technical experts in the NICU is not necessary.This paper is organized as follows. The next section presents a brief description of the incubator used in this research and the traditional calibration procedure for such equipment. In Section 3, a summary of the main points established by the IEC standard is presented. The theoretical referential of MLP and inferential systems is presented in Section 4. Finally, the simulations and relevant results are discussed in Section 5, while the main conclusions are given in Section 6.2.A neonatal incubator, which is represented in The arrangement is a multivariable system characterized by nonlinearities and interaction among the variables. Within this context, two variables are the most important ones: temperature and humidity, which are regulated by controlling the electric current that flows through two resistors. Temperature and humidity are measured by sensors positioned on the dome. The relative humidity sensor, SHT11, represented in To perform the standardized calibration procedure, an embedded digital system was designed. The system is composed of a data acquisition platform based on the microcontroller PIC18LF2620 and a data communication wireless link based on ZigBee protocols. The embedded system is connected to a PC  through a ZigBee radio link. This embedded system is responsible for monitoring the sensor states and sending commands to the power drivers that control temperature, humidity and oxygen levels and the air flowing inside the neonatal incubator. The main objective of the embedded system is to provide the data acquisition and the communication link with the PC.The communication link is a ZigBee network, which is a low-cost, low-powered wireless network standard . The reduced cost allows the technology to be widely used in wireless control and monitoring applications. The low-powered ZigBee devices often transmit data over long distances by transferring data through an intermediate device in a mesh configuration. ZigBee operates in industrial, science and medical radio bands. The prototype uses the ZigBee radio MRF24J40MA (Microchip), which is shown in The designed microcontrolled system is based on standard IEC 60601-2-19. This standard specifies the behavior of the temperature in specific points inside the incubator. The aforementioned points are outlined in The mechanical part of the calibration system is comprise of a rigid base made of acrylic, five supports for sensors arranged according to the standard recommendation (given in Section 3) and a control board. At points B, C, D and E, the temperature sensors, MCP9808 (Microchip), are placed. Point A integrates a temperature and humidity sensor, SHT11. The acrylic base with sensors for calibration purposes must be positioned inside the incubator during the tests and removed from the dome when the incubator is under normal operation. The sensor system that integrates the commercial incubator is maintained during the test. 3.The parameters for quality and safety in Brazilian neonatal incubators must comply with standard IEC 60601-2-19 “Particular requirements for the safety of neonatal incubator”. This standard determines the variation range of environmental variables in the neonatal incubator, such as temperature, humidity, velocity of air flow, and noise level.According to the referred IEC standard, five positions within the incubator are defined to carry out the measurements of temperature and relative humidity, as shown in Before starting the tests, verify if the environment temperature is between 21 °C and 26 °C.Adjust the incubator temperature control (set by the operator) to 11 °C over the environment temperature. The incubator must reach the temperature control at the time instant specified by the manufacturer with a tolerance of up to 20%. The incubator temperature control is measured by the incubator sensor.i.e., 32 °C and 36 °C. At each point, wait for the stabilization temperature condition (the measured incubator temperature at point A must not vary more than 1 °C within the period of one hour).Adjust the incubator temperature control to two operation points, In step number three, the average temperature measured by the sensors at points A, B, C, D and E cannot differ by more than 0.8 °C from the average temperature of the incubator within the period of one hour. Moreover, the average temperature cannot differ more than ±1.5 °C from the incubator control temperature. The incubator average temperature is obtained by means of temperatures measured in regular intervals.With the incubator temperature at 32 °C, set the temperature control reference in steady state to 36 °C and verify if the overshoot is below 2 °C and that the setting is reached in less than 15 min.The humidity value shown by the incubator sensor must not differ by more than 10% of the value measured by the sensor at position A during the whole period of the incubator functioning.ccording to standard IEC 60601-2-19, besides the correct positioning of the sensors, a set of six steps must be followed to calibrate the incubator, which are:The aforementioned procedures must be performed periodically after each maintenance procedure or when the incubator sensors are found to be uncalibrated. The accuracy of temperature and humidity measured by the designed embedded digital system (Section 2) are given by the IEC standard and listed in 4.Inferential systems (or soft sensors) represent an attractive approach to estimate the primary process variables , particuInferential systems are mathematical algorithms that have been used in a wide range of applications in industry, such as supervision, control and optimization of processes due to their advantages over some physical sensors that present measurement problems. Such systems provide faster measurements with more accuracy and reliability at a lower cost in terms of development, implementation and maintenance.et al. [According to Warne et al. , despiteThe MLP neural network architecture consists of a set of neurons arranged in layers, where a layer sends its outputs only to the neurons of the next layer. In addition, all neurons in a given layer are connected to all neurons of the next layer through adjustable parameters of the network, called synaptic weights. These connections are responsible for the MLP's ability to learn and store the knowledge extracted from the problem context. An MLP has at least one intermediate layer, called a hidden layer. If only one hidden layer is used, the MLP is able to solve problems of low complexity. Cybenko  demonstrThe synaptic weights between the MLP layers are adjusted through a process called learning or training. The supervised training process can be applied to the MLP architecture to solve mapping problems. In this learning process, the synaptic weights are adjusted based on a set of experimental input-output pairs of the problem and a cost function . A commoN pairs of vectors, {x(n), d(n)}, n = 1, 2, …, N, where x(n) ∈ ℝ(p+1) represents the input vector at discrete time n and d(n) ∈ ℝm denotes the desired vector of outputs (responses) for such an input vector.A supervised neural network requires an external source to provide information about the analyzed problem. This information is given by a set of p > 0 denotes the effective number of input variables used in the problem. The term “effective” is used here, because the input component, x0(n), is not really a variable in the usual sense, since it has a fixed value equal to −1 and is known as the threshold or (bias). Similarly, the n – th output vector at a discrete time is represented as follows:m > 0 indicates the number of output variables in the neural network. Any component of the input vector is symbolized by jx(n) ∈ ℝ, while the component of a given vector output is symbolized as kd(n) ∈ ℝ.Each input vector is represented as:n) and d(n) are related according to some unknown mathematical relationship, f(·):For a given problem, it is considered that vectors x(f (·), denoted by fˆ (·):n) generated by the neural network to be very close to the desired output d(n), even when the inputs presented to the network are different from those used in the training process. This is possible because of the generalization ability of neural networks.For this purpose, one can use a supervised neural network, such as MLP, by adjusting its synaptic weights during the training procedure to generate a mathematical model that acts as an approximation of n) represents the real behavior of such variables and y(n) correspond to the values inferred by the network.The main goal of this work is to use the supervised neural network MLP to infer the humidity and temperature values at the points specified by IEC 60601-2-19. Thus, in the learning process, vector d as inputs, which were instantaneously measured by the sensor, SHT11, available in a commercial incubator. By using measurements and a trained MLP, the system is able to estimate primary variables, which are: humidity at point A and temperature at points A, B, C, D and E, as shown in sT and sH are the measurements of temperature and humidity at the incubator's dome output, respectively, d is the transport delay of the system and, finally, m1 and m2 are the dimensions of the regressors applied to the incubator's secondary variables. At the output of the structure, iŷ is the estimation of the i-th primary variable provided by the i-th inferential system, according to The general structure of MLP inferential systems is shown in 5.The results and the methodology used are detailed in the next two subsections. In Section 5.1, the analysis of the results obtained by the neural network is presented. The results are related to the inferential values of the temperature and humidity inside the incubator. In Section 5.2, the procedural steps for the evaluation and calibration of the incubator with the inferential MLP system are presented.5.1.For the training and testing of the MLP network, 900 samples of temperature and humidity were acquired from points A, B, C, D and E and the incubator sensor, with sampling periods of 24 s. The collected data were divided into two sets: one for training, containing 750 samples and 150 samples for tests. The samples were collected by applying two PRBS (pseudo-random binary sequence) electric current signals to the incubator resistors. The amplitude limits of the PRBS electric currents are set by IEC 60601-2-19 for humidity and temperature inside the incubator. Main text paragraph.SH) and temperature (ST) values measured by the incubator sensors at the air outlet of the dome were used as input data in the network, aiming to infer the magnitudes measured by the humidity sensors at point A (AH) and temperature sensors at points A, B, C, D and E . Therefore, the IEC 60601-2-19 standardized temperature and humidity points can be determined by the inferential MLP process using only the temperature and humidity values (SH and ST) measured by the incubator sensor.The humidity , SH(n) and SH(n — 1) are used in AĤ(n).SH(n), ST(n) and ST(n — 1) to estimate humidity iTˆ(n)), where i is the reference temperature at points A, B, C, D and E. Such values are used in the training process of the network based on a backpropagation algorithm [The values of lgorithm . After tBoxplot (or box diagram) is a graphical way to represent numerical data aligned horizontally or vertically through five quantities: the smallest observation, lower quartile, median, upper quartile and largest observation . The boxaT. It can be seen that the boxplots for this variable provide results that are very close to those for variable aH.By analyzing the boxplots in −4 and 7.69 × 10−4. The results for each network are detailed in From the aforementioned results, it is clear that MLP has succeeded in inferring the humidity presented by the sensor at point A and, also, the temperatures given by the sensors positioned at all points specified by the standard. At points B, C, D and E, the network has the best performance, with the MSE ranging between 4.53 × 10−3 and the MSE for humidity is 4.55 × 10−3. Point A corresponds to the central position of the incubator, as it tends to present higher nonlinearity in the dynamics by being more susceptible to variations. This is less likely to happen at points B, C, D and E, which are located at the ends of the incubator and are less susceptible to temperature variation.The results show higher values of MSE for the temperature and humidity at point A. The temperature MSE at this point is 4.18 × 10i.e., the humidity and temperature at point A represents a variation of temperature slightly higher if compared to the other specified points. At point A, the moisture presented a relative percentage error ranging from −5% to +5% and a temperature error ranging from −7.5% to +8.0%. At other points, the variation is always within the range of −3.0% to +6.0%, showing that the difference between the desired and inferred temperatures is small. This demonstrates that the MLP achieved satisfactory performance, serving as an effective tool for evaluating the calibration of sensors in the incubator.Regarding the analysis of the aforementioned results, the calculation of the relative percentage error between the desired values and the inferred network was performed. In terms of this error, there is the same trend as the MSE, 5.2.The aforementioned inferential neural network system can be used to implement a software-based calibration system as a substitute or a complementary strategy to hardware calibration. The steps described in the previous section can be summarized as the following instructions in the form of the flowchart presented in When the software detects that the incubator control loops are not within the standard specified range through the MLP inferential sensors, a warning is automatically sent to the NICU computer and to the responsible nurse's mobile phone number, notifying that the incubator needs to be calibrated. This trigger may also occur manually, when the operator detects that the incubator is operating under a nonstandard state. After sending the alert message, the software checks if there is a newborn in the incubator. This check is performed by means of a load sensor. If the presence of a newborn is detected, an alarm signal is triggered, which persists, until the newborn is removed. Then, the software automatically sends a command that starts the calibration procedure of the temperature and humidity loops. Finally, a test is performed to check whether the temperatures at points A, B, C, D and E and, also, humidity at point A are adequate after the calibration process. Numerically, this test results in 6.The proposed neural network inferential calibration process of neonatal incubators can be used as an option other than the traditional calibration system based on hardware sensors. This inferential method based on standard IEC 60601-2-19 has shown the advantages of such a method over the hardware calibration process, such as the fact that only one temperature and one humidity sensor are used, that it is not necessary to turn off the incubator to evaluate the incubator condition, that if a more accurate calibration is necessary, it can be detected in runtime, and that during the occurrence of a process warning, alert signals can be sent directly to NICU personnel for repair. Therefore, the intelligent sensor system based on an inferential neural network can reduce the period of the evaluation and calibration of the incubator.Regarding the accuracy of the estimated values, the neural network architecture has shown small errors with respect to the actual values for humidity and temperature. Therefore, it can be stated that this technique allows for the accurate identification of the dynamic model of the incubator, which is capable of providing estimation in possible advanced risk cases, such as the temperature being out of a safe range and failures in the heater system and/or air flow in the equipment.With the use of the incubator over the years, it may be required that an MLP retraining be performed, due to natural changes in the operational conditions of this equipment. This is supposed to be the unique limitation of the proposed system. This limitation could be overcome with the implementation of a more sophisticated self-training MLP algorithm.


Bc, an approximately temperature-independent point in the measured longitudinal resistivity ρxx, which is ascribed to the direct insulator-quantum Hall (I-QH) transition, is observed. By analyzing the amplitudes of the magnetoresistivity oscillations, we are able to measure the quantum mobility μq of our device. It is found that at the direct I-QH transition, μqBc ≈ 0.37 which is considerably smaller than 1. In contrast, at Bc, ρxx is close to the Hall resistivity ρxy, i.e., the classical mobility μBc is ≈ 1. Therefore, our results suggest that different mobilities need to be introduced for the direct I-QH transition observed in multi-layered graphene. Combined with existing experimental results obtained in various material systems, our data obtained on graphene suggest that the direct I-QH transition is a universal effect in 2D.We have performed magnetotransport measurements on a multi-layer graphene flake. At the crossing magnetic field  Graphene, which is an ideal two-dimensional system , has attν > 2 QH state which is normally dubbed as the direct I-QH transition continues to attract interest [The insulator-quantum Hall (I-QH) transition -13 is a interest . The dirinterest , GaAs muinterest , GaAs twinterest -18, a deinterest ,20, GaN-interest  and on Sinterest , InAs-bainterest , and eveinterest , suggestinterest  and metainterest -29, haveinterest -33, grapinterest , reducedinterest , and fluinterest ,37, the interest , but notinterest , multi-linterest -42, makiρxx which can be ascribed to experimental evidence for the direct I-QH transition. At the crossing field Bc in which ρxx is approximately T-independent, ρxx is close to ρxy. In contrast, the product of the quantum mobility determined from the oscillations in ρxx and Bc is ≈ 0.37 which is considerably smaller than 1. Thus, our experimental results suggest that different mobilities need to be introduced when considering the direct I-QH transition in graphene-based devices.In this paper, we report magnetotransport measurements on a multi-layer graphene flake. We observe an approximately temperature-independent point in the measured longitudinal resistivity 2/Si substrate. Optical microscopy was used to locate the graphene flakes, and the thickness of multi-layer graphene is 3.5 nm, checked by atomic force microscopy. Therefore, the layer number of our graphene device is around ten according to the 3.4 Å graphene inter-layer distance [I = 20 nA in a He3 cryostat equipped with a superconducting magnet.A multi-layer graphene flake, mechanically exfoliated from natural graphite, was deposited onto a 300-nm-thick SiOdistance ,43. Ti/Adistance . Similardistance ,46. The ρxx(B) and ρxy(B) at T = 0.28 K. Features of magnetoresistivity oscillations accompanied by quantum Hall steps are observed at high fields. In order to further study these results, we analyze the positions of the extrema of the magnetoresistivity oscillations in B as well as the heights of the QH steps. Although the steps in the converted Hall conductivity ρxy are not well quantized in units of 4e2/h, they allow us to determine the Landau-level filling factor as indicated in the inset of Figure 16 m−2 following the procedure described in [Figure ribed in ,48.ρxx(B) and ρxy(B) as a function of magnetic field at various temperatures T. An approximately T-independent point in the measured ρxx at Bc = 3.1 T is observed. In the vicinity of Bc, for B <Bc, the sample behaves as a weak insulator in the sense that ρxx decreases with increasing T. For B >Bc, ρxx increases with increasing T, characteristic of a quantum Hall state. At Bc, the corresponding Landau-level filling factor is about 125 which is much bigger than 1. Therefore, we have observed evidence for a direct insulator-quantum Hall transition in our multi-layer graphene. The crossing points for B > 5.43 T can be ascribed to approximately T-independent points near half filling factors in the conventional Shubnikov-de Haas (SdH) model [We now turn to our main experimental finding. Figure H) model .m* of our device which is an important physical quantity. The amplitudes of the SdH oscillations ρxx is given by [By analyzing the amplitudes of the observed SdH oscillations at various magnetic fields and temperatures, we are able to determine the effective mass given by :ρ0, kB, h, and e are a constant, the Boltzmann constant, Plank's constant, and electron charge, respectively. When where C1 is a constant. Figure m0 to 0.07m0 where m0 is the rest mass of an electron. Interestingly, the measured effective mass is quite close to that in GaAs (0.067m0).where ρxx is close to ρxy. In this case, the classical Drude mobility is approximately the inverse of the crossing field 1/Bc. Therefore, the onset of Landau quantization is expected to take place near Bc[B at various temperatures. As shown in Figure 2/V/s. Therefore, near μqBc≈ 0.37 which is considerably smaller than 1. Our results obtained on multi-layered graphene are consistent with those obtained in GaAs-based weakly disordered systems [In our system, for the direct I-QH transition near the crossing field, e near Bc. Howevere near Bc. In orde systems ,21.T-independent suggests that Coulomb interactions do not seem to be dominant in our system.It has been shown that the elementary neutral excitations in graphene in a high magnetic field are different from those of a standard 2D system . In thisρxx is ascribed to the direct I-QH transition. Near the crossing field Bc, ρxx is close to ρxy, indicating that at Bc, the classical mobility is close to 1/Bc such that Bc is close to 1. On the other hand, μqBc≈ 0.37 which is much smaller than 1. Therefore, different mobilities must be considered for the direct I-QH transition. Together with existing experimental results obtained on various material systems, our new results obtained in a graphene-based system strongly suggest that the direct I-QH transition is a universal effect in 2D.In conclusion, we have presented magnetoresistivity measurements on a multi-layered graphene flake. An approximately temperature-independent point in 2D: Two-dimensional; 2DEGs: Two-dimensional electron gases; I-QH: Insulator-quantum Hall; SdH: Shubnikov-de Haas.The authors declare that they have no competing interests.CC and LHL performed the experiments. CC, TO, and AMM fabricated the device. NA, YO, and JPB coordinated the project. TPW and STL provided key interpretation of the data. CC and CTL drafted the paper. All the authors read and agree the final version of the paper.